Air Toxics Risk Assessment /W**
Reference Library
Volume 1
Technical Resource Manual
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U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Research Triangle Park, NC
EPA-453-K-04-001A
www. epa. go v/ai r/oaq ps
April 2004
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EPA-453-K-04-001A
April 2004
Air Toxics Risk Assessment Reference Library
Volume 1
Technical Resource Manual
Prepared by:
ICF Consulting
Fairfax, Virginia
Prepared for:
Nona Smoke, Project Officer
Office of Policy Analysis and Review
Contract No. EP-D-04-005
Work Assignment No. 0-2
Rachael Schwartz, Project Officer
Clean Air Marketing Division
Contract No. 68-W-03-028
Work Assignment No. 11
Bruce Moore, Project Officer
Office of Air Quality Planning and Standards
Contract No. 68-D01-052
Work Assignment No. 0-08
Work Assignment No. 0-09
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Emissions Standards Division
Research Triangle Park, NC
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Disclaimer
The information and procedures set forth here are intended as a technical resource to those
conducting air toxics risk assessments. This Technical Resource Document does not constitute
rulemaking by the Agency, and cannot be relied on to create a substantive or procedural right
enforceable by any party in litigation with the United States. As indicated by the use of non-
mandatory language such as "may" and "should," it provides recommendations and does not
impose any legally binding requirements.
The statutory provisions and EPA regulations described in this document contain legally binding
requirements. This document is not a regulation itself, nor does not it change or substitute for
those provisions and regulations. While EPA has made every effort to ensure the accuracy of the
discussion in this guidance, the obligations of the regulated community are determined by
statutes, regulations, or other legally binding requirements. In the event of a conflict between the
discussion in this document and any statute or regulation, this document would not be
controlling.
The general description provided here may not apply to a particular situation based upon the
circumstances. Interested parties are free to raise questions and objections about the substance of
this guidance and the appropriateness of the application of this guidance to a particular situation.
EPA and other decision makers retain the discretion to adopt approaches on a case-by-case basis
that differ from those described in this guidance where appropriate. EPA may take action that is
at variance with the recommendations and procedures in this document and may change them at
any time without public notice. This is a living document and may be revised periodically. EPA
welcomes public input on this document at any time.
Reference herein to any specific commercial products, process, or service by trade name,
trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement,
recommendation, or favoring by the United States Government.
April 2004 Page i
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Acknowledgments
The U.S. Environmental Protection Agency's Air Toxics Risk Assessment reference library is a
product of the EPA's Office of Air Quality, Planning, and Standards (OAQPS) in conjunction
with EPA Regions 4 and 6 and the Office of Policy Analysis and Review. The interoffice
technical working group responsible for library development includes Dr. Kenneth L. Mitchell
(Region 4), Dr. Roy L. Smith (OAQPS), Dr. Deirdre Murphy (OAQPS), and Dr. Dave Guinnup
(OAQPS). In addition to formal peer review, an opportunity for review and comment on
Volumes 1 and 2 of the library was provided to various stakeholders, including internal EPA
reviewers, state and local air agencies, and the private sector. The working group would like to
thank these many internal and external stakeholders for their assistance and helpful comments on
various aspects of these two books. (Volume 3 of the library is currently under development and
is expected in late 2004.) The library is being prepared under contract to the U.S. EPA by ICF
Consulting, Robert Hegner, Ph.D., Project Manager.
April 2004 Page ii
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Authors, Contributors, and Reviewers
Authors
Kenneth L. Mitchell, Ph.D.
U.S. EPA Region 4
Roy L. Smith, Ph.D. Deirdre Murphy, Ph.D.
U.S. EPA OAQPS U.S. EPA OAQPS
External Peer Reviewers
Doug Crawford-Brown, Ph.D., University of North Carolina at Chapel Hill
Michael Dourson, Ph.D., D.A.B.T., Toxicology Excellence for Risk Assessment
Eric Hack, M.S., Toxicology Excellence for Risk Assessment
Bruce Hope, Ph.D., Oregon Department of Environmental Quality
Howard Feldman, M.S., American Petroleum Institute
Barbara Morin, Rhode Island Department of Environmental Management
Patricia Nance, M.A.,M.Ed., Toxicology Excellence for Risk Assessment
Charles Pittinger, Ph.D., Toxicology Excellence for Risk Assessment, Exponent
Additional Contributors & Reviewers
John Ackermann, Ph.D., U.S. EPA Region 4
Carol Bellizzi, U.S. EPA Region 2
George Bollweg, U.S. EPA OAQPS
Pamela C. Campbell, ATSDR
Ruben Casso, U.S. EPA Region 6
Motria Caudill, U.S. EPA Region 5
Rich Cook, U.S. EPA, OTAQ
Paul Cort, U.S. EPA Region 9
David E. Cooper, Ph.D., U.S. EPA OSWER
Dave Crawford, U.S. EPA OSWER
Stan Durkee, U.S. EPA Office of Science Policy
Neal Fann, U.S. EPA OAQPS
Bob Fegley, U.S. EPA Office of Science Policy
Gina Ferreira, USEPA Region 2
Gerald Filbin, Ph.D., U.S. EPA OPEI
Danny France, U.S. EPA Region 4
Rick Gillam, U.S. EPA Region 4
Thomas Gillis, U.S. EPA OPEI
Barbara Glenn, Ph.D., U.S. EPA National
Center for Environmental Research
Dave Guinnup, Ph.D., U.S. EPA OAQPS
Bob Hetes, U.S. EPA National Health and
Environmental Effects Research Laboratory
James Hirtz, U.S. EPA Region 7
Ofia Hodoh, M.S., U.S. EPA Region 4
Ann Johnson, U.S. EPA OPEI
Brenda Johnson, U.S. EPA Region 4
Pauline Johnston, U.S. EPA ORIA
Stan Krivo, U.S. EPA Region 4
Deborah Luecken, U.S. EPA National Exposure
Research Laboratory
Thomas McCurdy, U.S. EPA National Exposure
Research Laboratory
Megan Mehaffey, Ph.D., U.S. EPA NERL
Latoya Miller, U.S. EPA Region 4
Erin Newman, U.S. EPA Region 5
David Lynch, U.S. EPA OPPTS
Ted Palma, M.S., U.S. EPA OAQPS
Michele Palmer, U.S. EPA Region 5
Solomon Pollard, Jr., Ph.D., U.S. EPA Region 4
Anne Pope, U.S. EPA OAQPS
Marybeth Smuts, Ph.D., U.S. EPA Region 1
Michel Stevens, U.S. EPA National Center for
Environmental Assessment
Allan Susten, Ph.D., D.A.B.T., ATSDR
Henry Topper, Ph.D., U.S. EPA OPPTS
Pam Tsai, Sc.D., D.A.B.T., U.S. EPA Region 9
Susan R. Wyatt, U.S. EPA (retired)
Jeff Yurk, M.S., U.S. EPA Region 6
April 2004
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Table of Contents
PART I BACKGROUND
Chapter 1 Introduction
1.1 Introduction 1
1.2 The Special Concerns of Urban Areas 2
1.3 Promoting Localized Assessment 4
1.4 The Risk-Based Approach 4
1.5 The Purpose of this Reference Manual 5
1.6 The Layout of this Reference Manual 6
1.7 The Relationship of this Manual to Volumes 2 and 3 9
References 10
Chapter 2 Clean Air Act Requirements and Programs to Regulate Air Toxics
2.1 Introduction 1
2.2 HAPs and their Sources: Stationary, Mobile, and Indoor Sources 2
2.2.1 Hazardous Air Pollutants (HAPs) 2
2.2.2 Stationary Sources: The Pre-1990 CAA "Risk-Only" Approach 4
2.2.3 Stationary Sources and the 1990 Clean Air Act Amendments: A "Technology First,
Then Risk" Approach 4
2.2.3.1 Step 1: The Technology-based Approach 5
2.2.3.2 Step 2: The Risk-based Approach 5
2.2.4 Mobile Sources of Air Toxics Rule 6
2.2.5 Indoor Air and Indoor Air Toxics 8
2.2.5.1 Potential Sources of Indoor Air Toxics 9
2.2.5.2 Indoor Air Toxics 9
2.2.5.3 Health Risks and Indoor Pollutants 11
2.3 Progress in Understanding and Reducing Toxic Air Pollution 12
2.3.1 Trends 12
2.3.2 NATA National Scale Assessment 14
2.4 Other Air Pollutants of Potential Concern 16
2.4.1 Criteria Air Pollutants 16
2.4.2 Chemicals on the Toxics Release Inventory 20
2.4.3 Toxic Chemicals that Persist and Which Also May Bioaccumulate 21
2.4.4 Overlaps and Differences Between Chemical "Lists" 22
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2.5 Reports to Congress on Air Toxics Issues 23
2.5.1 Air Toxics Deposition to the Great Waters 23
2.5.2 Mercury Study Report to Congress 24
2.5.3 Utility Report to Congress 25
2.5.4 Residual Risk Report to Congress 26
2.5.5 Integrated Urban Strategy Report to Congress 27
2.5.6 Other Reports 27
References 27
Chapter 3 EPA's Risk Assessment Process for Air Toxics: History and Overview
3.1 Introduction 1
3.2 A Short History of the Development of Human Health Risk Assessment and Risk Management
Approaches for Air Toxics 1
3.2.1 The 1983 National Academy of Sciences Report 1
3.2.2 The 1994 National Research Council Report 3
3.2.3 The CRARM 4
3.2.4 Development of Human Health Risk Assessment at EPA 6
3.3 Air Toxics Human Health Risk Assessment: Overview of the Process 9
3.3.1 Air Toxics Risk Assessment: What Is the Question? 10
3.3.2 Air Toxics Risk Assessment: The Process 12
3.3.2.1 Planning, Scoping, and Problem Formulation 13
3.3.2.2 Analysis Phase 14
3.3.2.3 Risk Characterization 15
3.3.3 Tiered Assessment Approaches 16
3.4 Uncertainty and Variability in Air Toxics Risk Assessment 18
3.4.1 Distinguishing Uncertainty and Variability 19
3.4.2 Sources of Uncertainty in Air Toxics Risk Assessment 20
3.4.3 Sources of Variability in Air Toxics Risk Assessment 22
3.4.4 Characterizing Uncertainty and Variability 23
3.4.5 Tiered Approach to Uncertainty and Variability 24
3.4.6 Assessment and Presentation of Uncertainty 26
References 29
Chapter 4 Air Toxics: Chemicals, Sources, and Emissions Inventories
4.1 Introduction 1
4.2 Air Toxics 1
4.2.1 Introduction to Air Toxics Chemical Lists 1
4.2.2 Hazardous Air Pollutants (HAPs) 4
4.2.3 Criteria Air Pollutants 5
4.2.4 Toxics Release Inventory (TRI) Chemicals 6
4.2.5 Toxic Chemicals That Persist and Which Also May Bioaccumulate 6
4.2.6 Other Chemicals 11
4.3 Sources of Air Toxics 11
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4.3.1 Point Sources 12
4.3.2 Nonpoint Sources 13
4.3.3 On-Road and Nonroad Mobile Sources 14
4.3.4 Sources Not Included in the NEI or TRI 15
4.3.4.1 Indoor Sources 16
4.3.4.2 Natural Sources 18
4.3.4.3 Formation of Secondary Pollutants 19
4.3.4.4 Other Sources Not Included in NEI or TRI 20
4.4 Emissions Inventories 20
4.4.1 National Emissions Inventory (NEI) 21
4.4.2 Toxics Release Inventory (TRI) 25
References 29
PART II HUMAN HEALTH RISK ASSESSMENT: INHALATION
Chapter 5 Getting Started: Planning and Scoping the Inhalation Risk Assessment
5.1 Introduction 1
5.2 Framework and Process for Air Toxics Risk Assessments 1
5.2.1 Framework for Cumulative Risk Assessment 1
5.2.2 General Framework for Residual Risk Assessment 3
5.2.3 The Air Toxics Risk Assessment Process 3
5.2.4 Overview of Inhalation Exposure Assessment 6
5.2.4.1 Exposure and Exposure Assessment: What's the Difference? 6
5.2.4.2 Components of an Exposure Assessment 7
5.3 Planning and Scoping 8
5.3.1 Why is Planning and Scoping Important? 9
5.3.2 The Planning and Scoping Process 9
5.3.2.1 What is the Concern? 9
5.3.2.2 Who Needs to be Involved? 10
5.3.2.3 What is the Scope? 12
5.3.2.4 Why is There a Problem? 13
5.3.2.5 How will Risk Managers Evaluate the Concern? 13
5.3.2.6 Lessons Learned on Planning and Scoping 13
References 15
Chapter 6 Problem Formulation: Inhalation Risk Assessment
6.1 Introduction 1
6.2 Developing the Conceptual Model 1
6.3 Developing the Analysis Plan 4
6.3.1 Identification of the Sources 5
6.3.2 Identification of the Chemicals of Potential Concern 6
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6.3.2.1 Toxicity-Weighted Screening Analysis 6
6.3.2.2 Risk-Based Screening Analysis 7
6.3.3 Identification of the Exposure Pathways/Routes 8
6.3.3.1 Characteristics of the Assessment Area 12
6.3.3.2 Scale of the Assessment Area 14
6.3.3.3 Use of Modeling versus Monitoring 14
6.3.3.4 Estimation of Exposure 17
6.3.3.5 Evaluation of Uncertainty 20
6.3.3.6 Preparation of Documentation 20
6.3.4 Identification of the Exposed Population 20
6.3.5 Identification of the Endpoints and Metrics 21
6.4 Data Quality in the Risk Assessment Process 22
References 24
Chapter 7 Quantification of Exposure: Development of the Emissions Inventory for the
Inhalation Risk Assessment
7.1 Introduction 1
7.2 Process for Developing an Emissions Inventory 1
7.2.1 Planning 2
7.2.2 Gathering Information 3
7.2.3 Estimating Emissions 3
7.2.3.1 Direct Measurement 5
7.2.3.2 Emission Estimation Models 5
7.2.3.3 Emission Factors 8
7.2.3.4 Mass Balance 9
7.2.3.5 Engineering Judgment 9
7.2.4 Compiling Data Into a Database 9
7.2.4.1 Selection of Production Rates 9
7.2.4.2 Unusual Conditions: Process Upsets, Accidental Releases, and
Maintenance 11
7.2.5 Data Augmentation 12
7.2.6 Quality Assurance/Quality Control 13
7.2.7 Documentation 14
7.2.8 Access to Data 14
7.3 Data Sources 14
7.3.1 Permit Files 15
7.3.2 Regional Inventories 15
7.3.3 Industry Profiles 16
7.3.4 AP-42 Emissions Factors 17
7.3.5 Factor Information Retrieval System 17
7.3.6 Locating and Estimating Documents 18
7.3.7 RCRAMo 18
7.3.8 Emissions and Dispersion Modeling System (EDMS) 19
7.3.9 Summary 19
References 21
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Chapter 8 Quantification of Exposure: Dispersion, Transport, and Fate of Air Toxics in the
Atmosphere
8.1 Introduction 1
8.2 Dispersion and Atmospheric Transport of Air Pollutants 1
8.2.1 General Types of Releases 2
8.2.2 Characteristics of Releases that Affect Dispersion and Transport 3
8.2.3 Physical and Meteorological Factors Affecting Air Toxics Dispersion and Transport . 7
8.3 Fate of Air Toxics in the Atmosphere 13
8.3.1 Physical Processes Removing Air Toxics 13
8.3.2 Chemical Reactions that Remove Air Toxics 15
8.3.3 Chemical Reactions that Result in the Secondary Formation of Pollutants 16
8.3.4 Overall Persistence of Air Toxics in the Atmosphere 17
References 19
Chapter 9 Assessing Air Quality: Modeling
9.1 Introduction 1
9.2 Air Quality Modeling 1
9.2.1 The Overall Structure of an Air Quality Model 1
9.2.2 Types of Models: Scientific Principles 6
9.2.3 Modeling Deposition 7
9.2.4 Screening vs. Refined Models 8
9.2.5 Specific Data Required for Modeling 9
9.2.6 Sources of Air Quality Models and Information 11
9.2.7 Examples of Air Quality Models 12
9.2.8 Emissions from Soil 18
9.3 Air Quality Modeling Examples 19
References 19
Chapter 10 Assessing Air Quality: Monitoring
10.1 Introduction 1
10.2 Air Toxics Monitoring: Recent Advances 2
10.3 Monitoring for Air Toxics Risk Assessments: Why Monitor? 4
10.4 Planning for Air Toxics Monitoring 9
10.4.1 General Planning Approach 10
10.4.2 Specific Planning Issues 14
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10.5 Implementing Air Toxics Monitoring 19
10.5.1 Locating Monitors and Selecting Sample Size 19
10.5.1.1 Locating Monitors 19
10.5.1.2 Selecting Sample Size 24
10.5.1.3 Setting Up a Monitoring/Sampling Program 25
10.5.2 Data Analysis and Reporting 28
10.5.3 The Use of Monitoring Data to Calculate Exposure Concentrations 29
10.6 Monitoring Methods, Technologies, and Costs 31
10.6.1 Ambient Air Monitoring 33
10.6.2 Sampling Costs 35
10.7 Archiving Air Toxics Monitoring Data 35
10.8 Using Air Monitoring Data to Evaluate Source Contribution 37
References 38
Chapter 11 Estimating Inhalation Exposure
11.1 Introduction 1
11.2 Estimating Inhalation Exposure Concentrations 1
11.2.1 General Approaches for Deriving Exposure Concentrations 2
11.2.2 Common Ways to Estimate Exposure Concentrations 3
11.3 Exposure Modeling 6
11.3.1 Inhalation Exposure Modeling 9
11.3.2 Microenvironment Concentration: How is it Developed? 12
11.3.3 Sources of Data for Human Activity for Inhalation (and other)
Exposure Assessments 13
11.3.4 Examples of Inhalation Exposure Models 16
11.3.5 Exposure Modeling Examples 19
11.4 Personal Monitoring 20
11.5 Exposure to a Population: Common Descriptors 22
11.6 Evaluating Uncertainty 22
11.7 Presenting the Results of an Exposure Assessment 23
References 23
Chapter 12 Inhalation Toxicity Assessment
12.1 Introduction 1
12.1.1 Hazard Identification and Dose-Response Information 1
12.1.2 Dose-Response Assessment Methods 5
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12.2 Hazard Identification 8
12.2.1 Weight of Evidence - Human Carcinogenicity 9
12.2.2 Identification of Critical Effect(s) - Non-Cancer Endpoints 11
12.3 Dose-Response Assessment for Cancer Effects 12
12.3.1 Determination of the Point of Departure (POD) 13
12.3.2 Derivation of the Human Equivalent Concentration 14
12.3.3 Extrapolation from POD to Derive Carcinogenic Potency Estimates 17
12.4 Dose-Response Assessment for Derivation of a Reference Concentration 19
12.4.1 Determination of the Point of Departure and Human Equivalent Concentration 20
12.4.2 Application of Uncertainty Factors 22
12.5 Sources of Chronic Dose-Response Values 24
12.6 Acute Exposure Reference Values 26
12.7 Evaluating Chemicals Lacking Health Reference Values 31
12.7.1 Use of Available Data Sources 31
12.7.2 Route-to-Route Extrapolation 31
12.8 Dose-Response Assessment for Mixtures 32
References 35
Chapter 13 Inhalation Risk Characterization
13.1 Introduction 1
13.2 Quantification of Cancer Risk and Noncancer Hazard 4
13.2.1 Cancer Risk Estimates 5
13.2.1.1 Characterization of Individual Pollutant Risk 5
13.2.1.2 Characterization of Cancer Risk from Exposure to Multiple
Pollutants 6
13.2.2 Noncancer Hazard Estimates 8
13.2.2.1 Characterizing Individual Pollutant Hazard for Chronic Exposures 8
13.2.2.2 Characterizing Multiple Pollutant Hazard for Chronic Exposures 9
13.2.2.3 Characterizing Hazard for Acute Exposures 11
13.2.3 Quantifying Risk From Background Sources 12
13.3 Interpretation and Presentation of Inhalation Cancer Risks and Noncancer Hazards 13
13.3.1 Presenting Risk and Hazard Estimates 17
13.3.2 Exposure Estimates and Assumptions 17
13.3.3 Toxicity Estimates and Assumptions 18
13.3.4 Assessment and Presentation of Uncertainty in Risk Characterization 19
13.3.4.1 Practical Approaches to Uncertainty Assessment 20
13.3.4.2 Presentation of Uncertainty Assessment 23
13.3.5 Additional Information 23
References 25
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PART III HUMAN HEALTH RISK ASSESSMENT: MULTIPATHWAY
Chapter 14 Overview and Getting Started: Planning and Scoping the Multipathway Risk
Assessment
14.1 Introduction 1
14.2 Overview of Multipathway Air Toxics Risk Assessment 3
14.2.1 Planning, Scoping, and Problem Formulation 3
14.2.2 Analysis 4
14.2.3 Risk Characterization 5
14.3 Overview of Multipathway Exposure Assessment 5
14.4 Planning and Scoping 9
14.4.1 Identifying the Concern 9
14.4.2 Identifying The Participants 9
14.4.3 Determining the Scope of the Risk Assessment 9
14.4.4 Describing the Problem 10
14.4.5 Determining How Risk Managers Will Evaluate the Concern 10
14.5 Tiered Multipathway Risk Assessments 10
References 11
Chapter 15 Problem Formulation: Multipathway Risk Assessment
15.1 Introduction 1
15.2 Developing the Multipathway Conceptual Model 1
15.3 Developing the Multipathway Analysis Plan 2
15.3.1 Identification of the Sources 3
15.3.2 Identification of the Chemicals of Potential Concern 3
15.3.3 Identification of the Exposure Pathways/Routes 3
15.3.3.1 Characteristics of the Assessment Area 4
15.3.3.2 Scale of the Assessment Area 5
15.3.3.3 Use of Modeling vs. Monitoring 5
15.3.3.4 Quantitation of Exposure 6
15.3.3.5 Evaluation ofUncertainty 7
15.3.3.6 Preparation of the Documentation 7
15.3.4 Identification of the Exposed Population 7
15.3.5 Identification of Endpoints and Metrics 7
15.4 Exposure Assessment Approach 7
15.4.1 Scenario Approach 8
15.4.2 Population-Based Approach 11
References 12
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Chapter 16 Quantification of Exposure: Development of the Emissions Inventory for the
Multipathway Risk Assessment
16.1 Introduction 1
16.2 Developing the Emissions Inventory 1
Chapter 17 Quantification of Exposure: Chemical and Physical Properties Affecting
Multimedia Fate and Transport
17.1 Introduction 1
17.1.1 Measures of Persistence 1
17.1.2 Metrics of Bioaccumulation 5
17.2 Chemical and Physical Properties that Affect Persistence and Bioaccumulation 8
17.3 Evaluating Persistence and Bioaccumulation in Exposure Assessments 10
References 11
Chapter 18 Quantification of Exposure: Multimedia Modeling
18.1 Introduction 1
18.2 Multimedia Fate and Transport Modeling 1
18.2.1 Basis of Multimedia Models 1
18.2.2 Multimedia Exposure Models 2
18.3 Key Parameters/Inputs for Multimedia Models 5
18.4 Examples of Multimedia Modeling 8
References 10
Chapter 19 Quantification of Exposure: Multimedia Monitoring
19.1 Introduction 1
19.2 Why Monitor? 1
19.3 Planning and Implementing Issues 1
19.4 Monitoring and Sampling Methods, Technologies and Costs 3
19.4.1 Method Selection 3
19.4.2 Available Methods 7
References 12
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Chapter 20 Exposure Metrics for Multimedia Assessment
20.1 Introduction 1
20.2 Generic Equation for Dietary Intake 3
20.3 Estimating Exposure Concentrations 4
20.4 Calculating Intake Variable Values 6
20.4.1 Consumption Rate 7
20.4.2 Exposure Frequency 10
20.4.3 Exposure Duration 10
20.4.4 Body Weight 12
20.5 Calculating Averaging Time Value 12
20.6 Combining Exposure Estimates Across Pathways 13
20.7 Exposure Models 14
References 16
Chapter 21 Ingestion Toxicity Assessment
21.1 Introduction 1
21.2 Hazard Identification 2
21.3 Predictive Approach for Cancer Effects 2
21.3.1 Determining the Point of Departure (POD) 2
21.3.2 Deriving the Human Equivalent Dose 2
21.3.3 Extrapolating from POD to Derive the Oral Cancer Slope Factor 3
21.4 Dose-response Assessment for Derivation of a Reference Dose 3
21.5 Sources of Human Health Reference Values for Risk Assessment 4
References 5
Chapter 22 Multipathway Risk Characterization
22.1 Introduction 1
22.2 Cancer Risk Estimates 2
22.2.1 Characterizing Individual Pollutant Ingestion Risk - Scenario Approach 2
22.2.2 Characterizing Risk from Exposure to Multiple Pollutants - Scenario Approach 3
22.2.3 Combining Risk Estimates across Multiple Ingestion Pathways - Scenario Approach . . 4
22.2.4 Evaluating Risk Estimates from Inhalation and Ingestion Exposures 4
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22.3 Noncancer Hazard 4
22.3.1 Characterizing Individual Pollutant Hazard - Scenario Approach 5
22.3.2 Multiple Pollutant Hazard 6
22.3.3 Evaluating Hazard Estimates From Inhalation and Ingestion Exposures 6
22.4 Interpretation and Presentation of Risks/Hazards 7
References 8
PART IV ECOLOGICAL RISK ASSESSMENT
Chapter 23 Overview and Getting Started: Problem Formulation
23.1 Introduction 1
23.2 Overview of Air Toxics Ecological Risk Assessment 4
23.2.1 Problem Formulation 6
23.2.2 Analysis 8
23.2.3 Evaluation of Ecological Effects 9
23.2.4 Ecological Risk Characterization 9
23.3 Planning and Scoping 9
23.3.1 What is the Concern? 10
23.3.2 Identifying The Participants 11
23.3.3 Determining the Scope of the Risk Assessment 12
23.3.4 Study-Specific Conceptual Model 12
23.3.4.1 Identifying Receptors of Concern 13
23.3.4.2 Identifying Assessment Endpoints and Measures of Effects 15
23.3.5 Analysis Plan and Quality Assurance Program Plan (QAPP) 16
23.4 Tiered Ecological Risk Assessments 21
References 23
Chapter 24 Analysis: Characterization of Ecological Exposure
24.1 Introduction 1
24.2 Characterization of Exposure 1
24.2.1 Quantifying Releases 3
24.2.2 Estimating Chemical Fate and Transport 3
24.2.2.1 Physical and Chemical Parameters 3
24.2.2.2 Multimedia Modeling 3
24.2.2.3 Multimedia Monitoring 4
24.2.3 Quantifying Exposure 5
24.2.3.1 Metrics of Exposure 5
24.2.3.2 Dimensions of Exposure 7
24.2.3.3 Exposure Profile 9
24.2.3.4 Evaluating Variability and Uncertainty 9
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References 10
Chapter 25 Analysis: Characterization of Ecological Effects
25.1 Introduction 1
25.2 Ecological Response Analysis 1
25.2.1 Stressor-Response Analysis 1
25.2.1.1 Ecological Effect Levels 1
25.2.1.2 Selection of TRVs for a Particular Assessment 7
25.2.1.3 Stressor-Response Curves 11
25.2.1.4 Species Sensitivity Distribution 11
25.2.2 Linking Measures of Effects to Assessment Endpoints 12
25.3 Stressor-Response Profile 16
25.4 Evaluating Variability and Uncertainty 16
References 16
Chapter 26 Ecological Risk Characterization
26.1 Introduction 1
26.2 Risk Estimation 2
26.2.1 Single-Point Exposure and Effects Comparisons 2
26.2.2 Comparisons Involving the Entire Stressor-Response Relationship 3
26.2.3 Comparisons Involving Variability 4
26.2.4 Process Models 4
26.3 Risk Description 5
26.3.1 Lines of Evidence 5
26.3.2 Significance of the Effects 6
26.4 Risk Characterization Report 7
26.5 Evaluating Variability and Uncertainty 9
References 9
PART V RISK-BASED DECISION MAKING
Chapter 27 Risk Management
27.1 Introduction 1
27.2 Role of Risk Management in Regulating Hazards 1
27.3 Types of Risk Management Decisions Related to Air Toxics 4
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27.4 Use of Risk Estimates in Decision-Making 5
27.5 Process for Making Risk Management Decisions 9
27.5.1 Define the Problem and Put it in Context 9
27.5.2 Analyze the Risks Associated with the Problem in Context 9
27.5.3 Examine Options for Addressing the Risks 11
27.5.4 Make Decisions about Which Options to Implement 12
27.5.5 Take Actions to Implement the Decisions 13
27.5.6 Conduct an Evaluation of the Action's Results 14
27.6 Information Dissemination 14
References 15
Chapter 28 Community Involvement
28.1 Introduction 1
28.2 Why is Community Involvement Important? 1
28.3 When to Involve the Community 2
28.4 How to Involve the Community 2
28.4.1 Understand Goals, Objectives, and Responsibilities for Effective Community
Involvement 4
28.4.2 Identify Community Concerns and Interest 5
28.4.3 Plan Community Involvement Strategy and Activities 5
28.4.4 Identify Possible Tools and Implement Community Involvement Activities 6
28.4.5 Provide Opportunity for Continued Public Interaction 7
28.4.6 Release of Risk Assessment and Risk Management Documents 8
References 10
Chapter 29 Risk Communication
29.1 Introduction 1
29.2 Risk Perception 2
29.3 Your Risk Communication Strategy 2
29.4 Risk Comparisons 3
29.5 Implementing Risk Communication Strategies 5
29.5.1 Presentation of Risk Results 5
29.5.2 Working with the Media 8
References 14
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PART VI SPECIAL TOPICS
Chapter 30 Public Health Assessment
30.1 Introduction 1
30.2 History of Public Health Assessment 2
30.3 Relationship of Public Health Assessment to Risk Assessment 3
30.4 What Is Public Health Assessment? 4
30.5 How Is a Public Health Assessment Conducted? 6
30.5.1 Conduct Scoping 6
30.5.2 Obtain Study Area Information 7
30.5.3 Community Involvement/Outreach/Response to Community Concerns 7
30.5.4 Exposure Evaluation 8
30.5.5 Health Effects Evaluation 9
30.5.6 Draw Public Health Conclusions 12
30.5.7 Recommend Public Health Actions 13
30.5.8 Prepare PHA Documents 13
References 14
Chapter 31 Probabilistic Risk Assessment
31.1 Introduction 1
31.2 Tiered Approach for Risk Assessment 2
31.3 Methods for Probabilistic Risk Assessment 4
31.4 Presenting Results for Probabilistic Risk Assessment 6
References 10
Chapter 32 Use of Geographic Information Systems (GIS) in Risk Assessment
32.1 Introduction 1
32.2 Selecting a GIS 2
32.3 Acquiring and Using Demographic Data 4
32.3.1 U.S. Census Data 5
32.3.2 Current and Small-Area Demographic Estimates 5
32.3.3 Public Health Applications 7
32.3.4 Data Access and Distribution 7
32.4 Cartographic Concepts 7
32.4.1 Generalization, Simplification, and Abstraction 10
32.4.2 Map Projections 10
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32.5 Using the Internet as a GIS Tool 10
32.6 Current GIS Applications at EPA 11
32.6.1 ORD/ESD 12
32.6.2 ATtlLA 12
32.6.3 ReVA 12
32.7 GPS Technology 13
References 15
GLOSSARY
APPENDICES
Appendix A Listing of all HAPs
Appendix B Guide to Federal Agencies that Oversee Air Toxics
Appendix C Recommended Dose-Response Values for HAPs
Appendix D Methodology for Identifying PB-HAP Compounds
Appendix E Overview of Air Toxics Emission Sources
Appendix F Specific HAPs Included in the National Emissions Inventory (NEI)
Appendix G Atmospheric and Meteorological Concepts Relevant to Dispersal, Transport, and
Fate of Air Toxics
Appendix H Data Quality Evaluation
Appendix I Use of Air Monitoring Data to Develop Estimates of Exposure Concentration (Data
Analysis and Reduction)
Appendix J Air Monitoring and Sampling Methods
Appendix K Equations For Estimating Concentrations of PB-HAP Compounds in Food and
Drinking Water
April 2004 Page xix
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PARTI
BACKGROUND
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Chapter 1 Introduction
Table of Contents
1.1 Introduction 1
1.2 The Special Concerns of Urban Areas 2
1.3 Promoting Localized Assessment 4
1.4 The Risk-Based Approach 4
1.5 The Purpose of this Reference Manual 5
1.6 The Layout of this Reference Manual 6
1.7 The Relationship of this Manual to Volumes 2 and 3 9
References 10
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1.1 Introduction
The mission of the United States Environmental Protection Agency (EPA) is to protect human
health and to safeguard the natural environment - air, water, and land - upon which life
depends.(1) Following this mission, the Agency has implemented a variety of laws and programs
that require and encourage the safe use and management of toxic chemicals. Many of these
programs focus on understanding the consequences of releasing chemicals to the air, land, and
water and working to reduce those releases when they pose too great a risk (see Glossary for
definition of risk in this Reference Library). This manual describes the programs and technical
tools that EPA uses to evaluate and address chemicals that are released to the air from many
different types of sources, and which have the potential to harm people and the environment.
The potential impacts of chemicals released to the air depend on a number of factors, including
the quantity of chemicals in the air, how the chemicals move and transform in the environment,
the length of time people or the environment is exposed, and the toxic nature of the chemicals.
The human health effects of exposure to air pollutants can range from no response, responses that
are relatively minor and reversible (such as mild eye irritation), responses that are more serious
and debilitating (such as aggravation of asthma) and, in some cases, fatal responses. Air
pollution also can cause negative impacts on the environment, including distress and death in
plants and animals, as well as damage to buildings and important cultural sites.
In the mid-20th century, Congress recognized the potential for air pollution to cause these kinds
of problems and responded by enacting the Clean Air Act (CAA). Since that time, this Act, as
amended, has provided the primary authority that EPA uses to develop programs for protecting
people and the environment from the harmful effects of air pollution across the United States.
A key component of the current version of the CAA (most recently amended by the 1990 CAA
Amendments) is the requirement that EPA significantly reduce emissions to the air of chemicals
that are known or suspected to cause serious health problems, such as cancer or birth defects. As
a starting point in this effort, the Act explicitly identifies 188 hazardous air pollutants
(HAPs)(a) for regulation. This group of chemicals is also commonly referred to as the HAPs,
toxic air pollutants or, simply, air toxics. (The CAA also covers another important group of
chemicals, known as criteria air pollutants; these are discussed in Chapter 2.)
Many different types of sources can release air toxics. These sources include stationary facilities
that release large quantities of HAPs to the air (known as major sources); stationary facilities
that release smaller amounts of HAPs to the air (known as area sources); on-road and nonroad
mobile sources (such as cars, trucks, and construction equipment) that release HAPs to the air;
indoor sources of air toxics (such as paint and cleaning products); and natural sources of air
toxics (such as volcanoes). Chapter 4 provides a detailed description of how EPA identifies and,
in the case of anthropogenic (manmade) sources, regulates each of the various types of sources of
air toxics.
"Since the original Act, which listed 189 chemicals, one chemical (caprolactam) has been delisted, leaving
188 HAPs. EPA is also in the process of considering proposals to delist methyl ethyl ketone (MEK and ethylene
glycol butyl ether (EGBE)). EPA has the authority to add and delete chemicals from the original list based on
specified criteria [CAA Section 112(b)(3)].
April 2004 Page 1-1
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1.2 The Special Concerns of Urban Areas
In urban areas, toxic air pollutants are of particular concern because people and sources of
emissions are concentrated in the same geographic area. Since most people live in urban areas,
this proximity leads to the potential for large numbers of people to be exposed to numerous air
pollutants. While some of these urban chemical exposures tend to be fairly similar across the
country (e.g., ambient air concentrations of benzene from petroleum use tend to be similar across
the lower 48 states), studies also indicate that the concentrations of air toxics in many urban (and
some nonurban) areas can vary significantly from one location to the next (e.g., concentrations in
areas with petroleum refineries may be higher than in areas that do not have petroleum
refineries). The sources of urban emissions tend to be relatively small in size but large in
number, such as gas stations or mobile sources. In addition, these emissions are typically found
at ground level where people are more likely to be exposed to them.
Urban air toxics also have a potential to elevate health risks among particular urban sub-
populations, including children, the elderly, and persons with existing illnesses. In addition, the
prevalence of minority and low-income communities in urban industrial and commercial areas,
where concentrations of air toxics may be greatest, increases the likelihood of elevated exposures
among these subpopulations.
Considering the large number of people potentially at risk from air toxics exposures, Congress
directed in the 1990 CAA amendments that elevated outdoor (also called ambient)
concentrations of air toxics in large urban areas be substantially reduced. In response to this
mandate, EPA developed an Integrated Urban Air Toxics Strategy. This Urban Strategy,
which was published in the Federal Register on July 19, 1999,(2) has since become EPA's Air
Toxics Strategy (The Strategy) and is part of the overall national effort to reduce air toxics.
The Strategy attempts to address all the significant stationary, mobile, and indoor sources
necessary to achieve protection of public health and the environment. The specific goals of the
Strategy are to:
• Attain a 75 percent reduction in incidence of cancer attributable to exposure to HAPs emitted
by stationary sources;
• Attain a substantial reduction in public health risks posed by HAP emissions from area
sources; and
• Address disproportionate impacts of air toxics hazards across urban areas.
The Strategy identifies four main areas of action to help achieve these goals:
• Develop regulations addressing sources of air toxics at the national and local levels.
Pursuant to this effort, the Agency will continue its work to develop rules that require
reductions in air toxics emissions from stationary facilities (such as manufacturing plants,
electric power plants, gas stations, and dry cleaners), as well as from cars, trucks, and other
mobile sources and their fuels. EPA has historically developed and implemented many such
standards over the years, and the Strategy indicates the need for additional standards to
reduce risks in urban areas.
April 2004 Page 1-2
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Initiate local and community-based projects to address specific multi-media pollutants
(e.g., mercury) and cumulative risks within urban areas. The CAA requires EPA to
"encourage and support area-wide strategies developed by the state or local air pollution
control agencies" to address air toxics in urban areas. EPA is developing tools (such as this
Reference Library) and is working with communities to assess and reduce risks at the
community level.
The Strategy also recognizes the need to T . , , ,, , , „
°J ° In risk assessment, the term receptor
generally refers to an individual person or
ecological component that is potentially
exposed to a stressor (air toxic). In
modeling, the term sometime refers to the
location where impacts are predicted.
assess the risks from exposures to indoor air
toxics and to develop non-regulatory,
voluntary programs to address those risks.
The Strategy also points out that air pollutants
may move into other environmental media
such as soil and water resulting in multimedia N ^
(i.e., more than just air) concerns. EPA is
engaged in a number of activities that recognize the ability of many air toxics to deposit out
of the air and bioaccumulate in biota consumed by humans and ecological receptors (e.g.,
deposition of mercury in watersheds, with subsequent uptake by fish).
Conduct air toxics assessments to identify areas of concern, prioritize efforts to reduce
risks, and track progress. The Strategy identifies a variety of national-level assessment
activities that will help EPA identify urban areas of particular concern, characterize the risks
that air toxics pose, and track the progress toward meeting overall air toxics program goals.
EPA is implementing the National Air Toxics Assessment (NATA) to address this goal.
NAT A includes:
- Expanding air toxics monitoring;
- Improving and periodically updating emissions inventories;
- Assessing national- and local-scale air quality by using multimedia and exposure
modeling;
- Continuing to research the exposures to, and health effects of, toxic chemicals in ambient
and indoor air; and
- Using and improving exposure and assessment tools.
These activities will help EPA and other stakeholders03' better understand air toxics risks, as
well as risk reductions associated with emissions control standards and other initiatives
aimed at reducing emissions. A particularly high-profile aspect of NATA has been the
national-scale assessment of 1996 emissions that produced predictions of county-level
estimates of air toxics concentrations and calculated risks for a subset of HAPs that EPA
believes pose most of the urban area risk. For additional information this particular analysis,
see EPA's The National-Scale Air Toxics Assessment.^ The national scale assessment of
1999 emissions is currently being performed and will be released in 2004 (see Chapter 2).
This reference manual uses the term "stakeholder" broadly to include all parties with a potential interest in
a given air toxics risk assessment, including regulators, the regulated community, community partners, and individual
members of the public.
April 2004 Page 1-3
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• Perform education and outreach. Given the scientific complexity inherent in air toxics
issues, EPA recognizes that the success of the overall air toxics program depends on the
public's understanding of the nature of air toxics risks and the activities that can help reduce
those risks. To further this understanding, EPA will support education and outreach efforts at
the national level and through its state, local, and tribal (S/L/T) partners (e.g., government,
industry, community). This reference manual, for example, is an outgrowth of this
educational/outreach effort.
For additional information on the Integrated Urban Strategy see EPA's Air Toxics Strategy:
Overview^.
1.3 Promoting Localized Assessment
While substantial reductions have been achieved through federal standards, EPA is evaluating the
need for additional emissions controls at the national level. However, since the mix of sources
and pollutants in specific geographic areas can be quite variable, one element of an effective
approach for reducing any remaining unacceptable risks is to understand the cumulative impacts
at the local level, target the problem areas, and tailor risk reduction strategies to the local
circumstances in those areas.
To encourage reductions of air toxics emissions at the local community level, EPA Headquarters
and Regional Offices are working collaboratively with S/L/T and community partners. This team
effort has focused on education/information exchanges, identification and assessment of
pollution prevention and control options, and promotion of voluntary measures and innovative
solutions to assess and address community air pollution problems.
While EPA has the authority to issue standards to address certain air toxics risks, in many cases
these risks may be more appropriately and more effectively addressed at the S/L/T level, rather
than at the federal level. Specifically, S/L/T air agencies may wish to address issues that are of
concern on a state-wide, area-wide, community-wide, or individual neighborhood basis, and for
areas in the immediate vicinities of specific air toxics sources. Some S/L/T governments are
already addressing some of these issues; others are just beginning to develop their own programs.
1.4 The Risk-Based Approach
While there are several methodologies to assess potential health impacts of air toxics on
populations at the local level, the risk-based approach is perhaps the most effective.
The methodology described here, called risk assessment, is the process for evaluating:
• The sources of air toxics released to the environment;
• How the released chemicals move and change in the environment;
• Who may be exposed to the chemicals and at what levels;
• How exposures may occur;
• The toxic effects of the chemicals in question and how potent; and
• How likely it is that the potentially exposed people will experience harm because of the
exposures.
April 2004 Page 1-4
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This manual also discusses the ecological risk assessment process, which assesses the impact of
air toxics on ecological receptors such as aquatic organisms and terrestrial mammals.
This kind of information can be extremely helpful to decision makers as they try to balance the
competing concerns of protecting pub lie health, fostering economic development, and evaluating
issues of fairness and equity, among others. Specifically, risk assessment can provide:
• A predictive estimate of the potential health risks posed by air toxics, which may help
determine the need for action;
• A basis for determining the levels of chemicals that can be released to the air without posing
unacceptable risks to public health and the environment;
• A basis for comparing potential health impacts of various pollution reduction alternatives;
• A consistent process for evaluating and documenting threats to public health and the
environment from toxic air pollution; and
• A basis for comparing risks from various exposure scenarios (e.g., the risk from breathing
contaminated air compared to the risk from eating contaminated food).
Performing an air toxics risk assessment is often challenging. Risk assessments can be resource
and time-intensive, depending on the specific questions being asked and the level of detail
needed for informed decision making. Risk assessments usually require input from a number of
scientists and engineers with a variety of skills (e.g., chemistry, toxicology, statistics, modeling,
meteorology, monitoring). Decision makers may also need to acquire new skills in order to
understand and use the risk assessment results. Finally, although they are based on science, risk
assessments often rely on the best judgment of the analysts in the face of various uncertainties.
There has not been, up to this point, a unified and comprehensive reference manual on the
methods and tools that are currently available to perform air toxics risk assessments per se. This
document is EPA's attempt to fill that void.
1.5 The Purpose of this Reference Manual
The primary purpose of this reference manual (Volume 1) is to provide, in one single place,
descriptions of the major methods and technical tools that are commonly used to perform air
toxics risk assessments. Specifically, the manual attempts to cover all the common basic
technical approaches that are used to evaluate: how people in a particular place (e.g., a city or
neighborhood) may be exposed; what chemicals they may be exposed to and at what levels; how
toxic those chemicals are; and how likely it is that the exposures may result in adverse health
outcomes. Topics include uncertainty and variability, basic toxicology and dose-response
relationships, air toxics monitoring and modeling, emissions inventory development, and risk
characterization. This manual also discusses approaches for using the results of a risk
assessment in the risk management decision-making process. Links to more detailed references
on each subject are presented, along with EPA contacts. Additionally, EPA's Fate, Exposure,
and Risk Analysis (FERA) web site (www.epa.gov/ttn/fera) provides up-to-date tools for air
toxics risk assessment, including computer models, databases, and other information used by
EPA and others for air pollutant human exposure modeling, multimedia modeling, and risk.
To provide readers with a broad perspective on the potential impacts of air toxics (in addition to
information on the risk assessment process), this manual also includes a discussion of a
April 2004 Page 1-5
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complementary process called a public health assessment (PHA). One of the objectives of a
PHA is to evaluate whether existing cases of illness in a community may possibly have resulted
from past exposures to particular toxins (based on epidemiological principles). This process is
routinely carried out at Superfund sites by the Agency for Toxic Substances and Disease Registry
(ATSDR) in addition to EPA's Superfund risk assessment process. PHAs often involve the use
of capabilities beyond those required for risk assessment, including medical skills. S/L/T air
agencies generally will not perform such assessments themselves; however, because questions
about current or past illnesses and deaths in communities often arise during the risk assessment
process, information about the PHA process is offered to help S/L/T air agencies and other
stakeholders understand the rudiments of the process and whom to contact for more information
and help.
1.6 The Layout of this Reference Manual
This reference manual is divided into six Parts, each of which are divided further into three or
more chapters. Chapters are numbered consecutively. A number of Appendices provide more
detailed reference materials.
• Part I (Background) provides a general introduction to air toxics risk assessment and is
divided into four chapters.
- Chapter 1 (this chapter) provides an introduction to the manual.
- Chapter 2 begins with an overview of the CAA as well as major regulations, programs,
and initiatives that relate to air toxics risk reduction.
- Chapter 3 provides an overview of risk assessment and the risk-based decision making
framework, including an introduction to tiered approaches to risk assessment.
- Chapter 4 identifies the set of chemical pollutants that are the focus of this manual and
describes the general categories of air toxics sources and the primary emissions
inventories (which contain information on the nature and magnitude of emissions
released from various sources).
• Part II (Human Health Risk Assessment: Inhalation) provides a discussion of the
methods and tools used to evaluate risks to human health via the inhalation pathway. It is
divided into nine chapters.
- Chapter 5 provides an overview of the inhalation risk assessment process, discusses the
initial planning and scoping process that needs to be completed before the risk assessment
begins, and describes the exposure assessment, which will usually comprise the bulk of
the effort for most air toxics risk assessments.
- Chapter 6 describes the problem formulation phase which results in the development of
the conceptual model and analysis plan for the risk assessment.
- Chapter 7 describes how to develop an emissions inventory for the risk assessment.
- Chapter 8 discusses the factors that affect the movement and, in some cases, chemical
transformation of chemicals in the atmosphere following release (i.e., the fate and
transport of chemicals in the atmosphere).
- Chapter 9 provides an overview of the use of computer modeling to predict the
movement, fate, and transport of air toxics in the atmosphere. It also describes the major
computer models that are commonly used for this purpose.
- Chapter 10 provides an overview of monitoring methods that are commonly used to
measure ambient concentrations of air toxics in the atmosphere.
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- Chapter 11 provides information for estimating exposure concentrations for inhalation
analyses, including exposure modeling.
- Chapter 12 provides an overview of toxicity assessment for air toxics.
- Chapter 13 provides information for completing the risk characterization, including
uncertainty analysis and how to present the results of the risk assessment.
• Part III (Human Health Risk Assessment: Multipathway) provides a discussion of the
methods and tools used to evaluate risks to human health when air toxics that are highly
persistent or bio accumulative are present in emissions. The focus of the multipathway risk
assessment is to evaluate the potential exposures associated with ingesting soil, food, and
water that has become contaminated with these chemicals after deposition from the
atmosphere to surfaces, such as soils and surface waters. This Part is divided into nine
chapters.
- Chapter 14 provides an overview of the multipathway risk assessment process, discusses
the initial planning and scoping process that needs to be completed before the risk
assessment begins, and describes the multipathway exposure assessment.
- Chapter 15 describes problem formulation for the multipathway risk assessment.
- Chapter 16 describes how to develop an emissions inventory for the multipathway risk
assessment.
- Chapter 17 discusses the factors that affect the movement and, in some cases, chemical
transformation of air toxics in soil, water, sediment, and biota.
- Chapter 18 provides an overview of the computer modeling used to predict the
movement, fate, and transport of toxics in soil, water, sediment, and biota and describes
the major multimedia computer models commonly used by risk assessors.
- Chapter 19 provides an overview of monitoring methods used to measure ambient
concentrations of air toxics in soil, water, sediment, and biota.
- Chapter 20 provides a summary of the process and assumptions used to estimate chemical
intake rates - the key measure of exposure used to assess ingestion risks - including
exposure modeling.
- Chapter 21 provides an overview of the toxicity assessment for air toxics that are
persistent and which may also have a high potential to bioaccumulate in food chains.
- Chapter 22 provides information on how to complete the risk characterization for the
multipathway risk assessment, including uncertainty analysis and how to present the
results of the risk assessment.
• Part IV (Ecological Risk Assessment) provides an overview of the methods and tools used
to evaluate risks to ecological receptors (e.g., birds, mammals, plants, and ecological
communities) due to exposure to air toxics. This Part is divided into four chapters.
- Chapter 23 provides an overview of the ecological risk assessment process and discusses
the initial planning and scoping process that needs to be completed before the risk
assessment begins.
- Chapter 24 provides information on characterizing exposure for the ecological risk
assessment.
- Chapter 25 provides information on characterizing ecological effects, including
development of the stressor-response profile.
- Chapter 26 provides information on how to complete the risk characterization for the
ecological risk assessment, including the analysis of uncertainty, and how to present the
results of the ecological risk assessment.
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Part V (Risk-Based Decision Making) discusses the process by which the information from
the risk assessment can be used to inform risk management decisions and two important
aspects of that process. This Part is divided into three chapters.
- Chapter 27 provides an overview of the risk management process, including the types of
decisions that may need to be made and how the risk assessment informs the decision-
making process.
- Chapter 28 provides an overview of the importance of stakeholder involvement in the risk
assessment and management process and provides information for developing and
implementing a stakeholder involvement plan.
- Chapter 29 provides information for developing and implementing a risk communication
strategy for helping members of the community and the media understand the risk
assessment results and how they are being used in the decision-making process.
Part VI (Special Topics) provides an overview of three tools or procedures that may be used
as part of performing or reporting a risk assessment.
- Chapter 30 provides an overview of the process by which public health agencies may
evaluate the public health implications posed by the emissions from air toxic sources in a
community. The public health assessment, if performed, is a complementary process to
risk assessment.
- Chapter 31 discusses probabilistic risk assessment, which is aimed at describing risks as a
distribution (or range) of potential outcomes.
- Chapter 32 provides an overview of the use of Geographical Information System (GIS)
tools in the process of conducting risk assessments and reporting results.
The Glossary defines key terms and acronyms.
Appendix A provides a listing of all HAPs along with their status as a Toxics Release
Inventory (TRI) chemical, a Section 112(k) high priority urban toxic, and a Mobile Source
Air Toxic.
Appendix B provides a guide to the agencies and organizations that oversee air toxics
regulations.
Appendix C provides recommended dose-response values for cancer and noncancer effects
for all HAPs.
Appendix D presents the decision process by which the persistent, bioaccumulative HAP
compounds (PB-HAPs) were selected.
Appendix E provides an overview of all CAA designated air toxics Source Categories,
including the most common HAPs in emissions, typical industries, and applicable maximum
achievable control technology (MACT) standards.
Appendix F provides a list of all of the specific pollutants and compound groups included in
the 1999 National Emissions Inventory (NEI) along with their Chemical Abstract Services
(CAS) numbers.
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• Appendix G provides an overview of meteorology as it relates to the movement of air toxics
in the atmosphere. This appendix also provides information on sources of meteorological
data for modeling air toxics dispersal and transport.
• Appendix H discusses the process of evaluating and reducing a monitoring data set (e.g., air,
water, soil sample results) into a grouping of data that are useable for exposure evaluation.
• Appendix I provides a general overview of how a reduced monitoring data set (developed by
the methods in Appendix H) maybe used to estimate exposure concentrations.
• Appendix J provides an overview of available air toxics monitoring methods.
• Appendix K provides the equations for calculating the concentrations of PB-HAPs in non-air
media (e.g., soil, food, water).
1.7 The Relationship of this Manual to Volumes 2 and 3
This manual is the first volume of a three-volume set. Volume 1: Technical Resource Manual
discusses the overall air toxics risk assessment process and the basic technical tools needed to
perform these analyses. The manual addresses both human health and ecological analyses. It
also provides a basic overview of the process of managing and communicating risk assessment
results. Other evaluations (such as the public health assessment process) are described to give
risk assessors, risk managers, and other stakeholders a more holistic understanding of the many
issues that may come into play when evaluating the potential impact of air toxics on human
health and the environment.
Volume 2: Facility-Specific Assessment builds on the technical tools described in Volume 1 by
providing an example set of tools and procedures that maybe used for source-specific or
facility-specific risk assessments, including tiered approaches to source- or facility-specific risk
analysis.
Volume 3: Community-Level Assessment builds on the information presented in Volume 1 to
describe to communities how they can evaluate and reduce air toxics risks at the local level. The
volume will include information on screening level and more detailed analytical approaches, how
to balance the need for assessment versus the need for action, and how to identify and prioritize
risk reduction options and measure success. Since community concerns and issues are often not
related solely to air toxics, the document will also present readily available information on
additional multimedia risk factors that may affect communities and strategies to reduce those
risks. The document will provide additional, focused information on stakeholder involvement,
communicating information in a community-based setting, and resources and methodologies that
may play a role in the overall process. Note that EPA's Office of Pollution Prevention and
Toxics has also developed a "Community Air Screening How To Manual" that will be available
in 2004 and will be discussed in Volume 3 (Volume 3 will be available in late 2004).
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References
1. U.S. Environmental Protection Agency. Agency Mission Statement. Updated June 11, 2002.
Available at: http://www.epa.gov/history/org/origins/mission.htm. (Last accessed March
2004).
2. U.S. Environmental Protection Agency. 1999. National Air Toxics Program: The
Integrated Urban Strategy. Notice. Federal Register 64:38705. July 19, 1999. Available
at: http://www.access.gpo.gov/su_docs/fedreg/a990719c.html (the PDF file is indexed at:
http://frwebgate. access, gpo.gov/cgi-bin/getdoc.cgi?dbname=1999_register&docid=99-17774-
filed.pdf).
3. U.S. Environmental Protection Agency. Technology Transfer Network National Air Toxics
Assessment. The National-Scale Air Toxics Assessment. Updated September 18, 2002.
Available at: http://www.epa.gov/ttn/atw/nata/index.html. (Last accessed March 2004).
4. U.S. Environmental Protection Agency. Technology Transfer Network Air Toxics Web site.
Air Toxics Strategy: Overview. Updated February 10, 2004. Available at:
http://www.epa.gov/ttn/atw/urban/urbanpg.html (Last accessed March 2004).
April 2004 Page 1-10
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Chapter 2 Clean Air Act Requirements and
Programs to Regulate Air Toxics
Table of Contents
2. 1 Introduction
2.2 HAPs and their Sources: Stationary, Mobile, and Indoor Sources ....................... 2
2.2.1 Hazardous Air Pollutants (HAPs) .......................................... 2
2.2.2 Stationary Sources: The Pre-1990 CAA "Risk-Only" Approach .................. 4
2.2.3 Stationary Sources and the 1 990 Clean Air Act Amendments: A "Technology First,
Then Risk" Approach [[[ 4
2.2.3.1 Step 1: The Technology-based Approach ............................. 5
2.2.3.2 Step 2: The Risk-based Approach ................................... 5
2.2.4 Mobile Sources of Air Toxics Rule ......................................... 6
2.2.5 Indoor Air and Indoor Air Toxics .......................................... £
2.2.5.1 Potential Sources of Indoor Air Toxics ............................... 9
2.2.5.2 Indoor Air Toxics ................................................ 9
2.2.5.3 Health Risks and Indoor Pollutants ................................. ii
2.3 Progress in Understanding and Reducing Toxic Air Pollution ......................... 1_2
2.3.1 Trends [[[ 12
2.3.2 NATA National Scale Assessment ........................................ 1_4
2.4 Other Air Pollutants of Potential Concern ......................................... \6_
2.4.1 Criteria Air Pollutants .................................................. 16
2.4.2 Chemicals on the Toxics Release Inventory ................................. \9_
2 A3 Toxic Chemicals that Persist and Which Also May Bioaccumulate ............... 20
2.4.4 Overlaps and Differences Between Chemical "Lists" ......................... 22
2.5 Reports to Congress on Air Toxics Issues ......................................... 22
2.5.1 Air Toxics Deposition to the Great Waters .................................. 23_
2.5.2 Mercury Study Report to Congress ........................................ 23_
2.5.3 Utility Report to Congress ............................................... 24
2.5.4 Residual Risk Report to Congress ......................................... 25
2.5.5 Integrated Urban Strategy Report to Congress ............................... 26
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2.1 Introduction
In a general sense, an air pollutant is any substance
introduced into the air by human activities (currently,
approximately 75,000 industrial chemicals are produced or
imported into the United States,(a) and science knows many
millions more). Some air pollutants may take the form of
solid particles, liquid droplets, or gases. Many different types
of air pollutants can injure health and/or harm the
environment (see Common Air Pollutants box).
In early versions of the Clean Air Act (CAA), Congress
identified six criteria air pollutants for regulation. In addition
to these pollutants, the 1990 CAA Amendments focused
EPA's efforts on another group of pollutants, the 188
Hazardous Air Pollutants (HAPs).(b) Additionally, EPA has
identified 21 mobile source air toxics, 20 of which are also
HAPs and the other one is "diesel particulate matter and
diesel exhaust organic gases" (see Chapter 4).
Common Air Pollutants
acid aerosols
asbestos
carbon monoxide (CO)
carbonyl compounds
ground level ozone
metals
nitrogen oxides (NOX)
particulate matter (PM)
propellants
radon
refrigerants
semivolatile organic compounds
sulfur dioxide (SO2)
.volatile organic compounds
The group of six criteria air pollutants occur
commonly throughout the U.S. and are derived
from numerous and diverse mobile and stationary
sources. EPA has set National Ambient Air
Quality Standards (NAAQS) for these pollutants
based on health and welfare-related criteria (see
Section 2.4.1 and http://www.epa.gov/ttn/naaqs/).
No such national ambient air quality standards
currently exist for HAPs, although regulatory
programs are in place to address emissions of
HAPs. In addition, air pollutants from indoor
sources are of concern (with many of the
chemicals emitted indoors overlapping with the
criteria and HAP lists). EPA, however does not
currently regulate indoor air.
The CAA is the primary federal law that regulates
air emissions of HAPs. The Act applies to a
number of different types of sources; these include
small and large stationary facilities such as
factories and neighborhood dry cleaners, as well
as mobile sources such as cars and trucks. The
original CAA was passed in 1963 and has been
A Note on Terminology
The terms "air toxics" and "toxic air pollutants"
are often used interchangeably with "hazardous
air pollutants" (which is a Clean Air Act phrase
specific to the 188 pollutants that are the focal
point of section 112 of the Act - see
http://www.epa.gOV/ttn/atw/l 88polls.html). For
the purposes of this reference library, however,
the term "air toxics" is used in the more general
sense to refer generally to any air pollutant (other
than criteria pollutants) that has the potential to
cause adverse impacts to human health or the
environment.
Criteria air pollutants are six common air
pollutants determined to be hazardous to human
health and for which EPA has established
National Ambient Air Quality Standards
(NAAQS). The six criteria air pollutants are
carbon monoxide, lead, nitrogen dioxide, ozone,
, sulfur dioxide, and particulate matter.
aTSCA Chemical Substance Inventory, http://www.epa.gov/opptintr/newchems/invntory.htm
CAA section 112(b)(l) lists 189 HAPs, but since the original Act, one chemical (caprolactam) has been
Page 2-1
delisted, leaving 188 HAPs (61 FR 30816, June 18, 1996).
April 2004
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amended since that time on a number of occasions, most recently in 1990. Congress intended the
1990 amendments to resolve unaddressed or insufficiently addressed air pollution problems such
as acid rain, ground-level ozone, and stratospheric ozone depletion. The 1990 amendments also
dramatically affected how EPA was to approach the issue of air toxics. For example, previous
versions of the Act required EPA itself to identify pollutants as HAPs one-by-one and to set
health-based standards for each. Given the problems that arose in working to implement this
approach, Congress restructured the approach for air toxics in the 1990 amendments. The
discussion below describes this current approach.
Specifically, this chapter provides an overview of the CAA requirements that are specific to
HAPs, with emphasis on stationary sources, mobile sources, and indoor sources of HAPs.
The chapter also provides insight into other aspects of air quality that play a role in understanding
the air toxics problem. The chapter concludes with a brief description of some of the important
studies EPA was required to perform under the Act to better understand the nature of the air
toxics problem. The full text of the Act can be accessed at http://www.epa. gov/oar/caa. EPA has
also developed a plain English guide to the Act that can be accessed at
http://www.epa.gov/oar/oaqps/peg_caa/pegcaain.html.
2.2 HAPs and their Sources: Stationary, Mobile, and Indoor Sources
2.2.1 Hazardous Air Pollutants (HAPs)
Hazardous air pollutants (HAPs) are those 188
listed pollutants and groups of pollutants(c) that
EPA knows or suspects cause cancer or other
serious human health effects, such as reproductive
effects or birth defects, or adverse environmental
effects (Appendix A presents the full list).(1)
Examples of HAPs include benzene, which is
found in gasoline; perchloroethlyene, which is
emitted by most dry cleaning facilities; methylene
chloride, which is used as a solvent and paint
stripper by a number of industries; dioxin;
asbestos; toluene; and compounds of metals such
as cadmium, mercury, chromium, and lead.
Congress has given EPA the authority to add and
subtract chemicals from that list, following
established criteria [CAA Section 112(b)(3)].
According to summary data compiled by EPA, an estimated 5.1 million tons of HAPs were
released from stationary and mobile sources in the U.S. in 1999.
People exposed to HAPs at sufficient concentrations and for a sufficient duration of time may
have an increased chance of developing cancer or experiencing other serious health effects.
These health effects can include damage to the immune system, as well as neurological,
Major Source - Any source or group of
stationary sources located within a
contiguous area and under common control
that emits or has the potential to emit
considering controls, in the aggregate, 10
tons per year (tpy) or more of any hazardous
air pollutant or 25 tpy or more of any
combination of hazardous air pollutants
[CAA section 112(a)(l)].
Area Source - any stationary source of
hazardous air pollutants that is not a major
source ... not including] motor vehicles or
nonroad vehicles subject to regulation under
title II [CAA section 112(a)(2)].
CAA section 112(b)(l) lists 189 HAPs, but since the original Act, one chemical (caprolactam) has been
delisted, leaving 188 HAPs (61 FR 30816, June 18, 1996)
April 2004
Page 2-2
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reproductive (e.g., reduced fertility), developmental, respiratory, and other health effects. In
addition to exposure from breathing air toxics, some HAPs such as mercury compounds can
deposit onto soils or surface waters, where they can be taken up by plants and animals (see
Chapter 4). Like humans, ecological systems may experience adverse health problems if exposed
to sufficient quantities of HAPs over time (ecological risk assessment is discussed in Part IV of
this reference manual).
People may be exposed to HAPs in many ways, including:
• Breathing contaminated air;
• Eating contaminated food products, such as fish from contaminated waters; meat, milk, or
eggs from animals that fed on contaminated plants; and fruits and vegetables grown in
contaminated soil on which HAPs have been deposited;
• Drinking water contaminated by HAPs;
• Ingesting contaminated soil. Young children are especially vulnerable because they often
ingest soil from their hands or from objects they place in their mouths; and
• Touching (making skin contact with) contaminated soil, dust, or water (for example, during
recreational use of contaminated water bodies).
Anthropogenic sources of HAPs include stationary sources (e.g., factories, refineries, power
plants), mobile sources (e.g., cars, trucks, buses), and indoor sources (e.g., some building
materials and cleaning solvents). Some HAPs are also released from natural sources such as
volcanoes.
The Urban Air Toxics
In 1999, EPA identified a group of 33 HAPs (the Urban Air Toxics) as those most important to
health risks in urban areas (see Section 1.1).
acetaldehyde
acrolein
acrylonitrile
arsenic comounds
benzene
beryllium compounds
1,3-butadiene
cadmium compounds
carbon tetrachloride
chloroform
chromium compounds
coke oven emissions
dioxin
1, 2-dibromoethane
propylene dichloride
1, 3-dichloropropene
ethylene dichloride(a)
ethyene oxide
formaldehyde
hexachlorobenzene
hydrazine
lead compounds
(a) also represented as 1,2-dichloroethane
^ also represented as dichloromethane
(c) also represented as perchloroethylene
manganese compounds
mercury compounds
methylene chloride(b)
nickel compounds
polychlorinated biphenyls (PCBs)
polycyclic organic mater (POM)
quinoline
1, 1,2, 2-tetrachlorethane
tetrachloroethylene(c)
trichloroethylene
vinyl chloride
April 2004
Page 2-3
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2.2.2 Stationary Sources: The Pre-1990 CAA "Risk-Only" Approach
Prior to 1990, the CAA directed EPA to regulate toxic air pollutants from stationary sources
based on the risks each pollutant posed to human health. Specifically, the Act directed EPA to:
• Identify all pollutants that caused "serious and irreversible illness or death," and
• Develop standards to reduce emissions of these pollutants to levels that provided an "ample
margin of safety" for the public.
In other words, EPA was tasked with identifying the chemicals to be considered HAPs and
setting standards for chemical emissions that would not only be "safe," but would be safe with an
"ample margin" to the public. (A discussion of what the term "ample margin of safety" means is
presented in Chapter 27. A discussion as how to interpret risk levels such as "one in a million" is
provided in Chapter 13.) EPA turned to a method called "risk assessment" in performing this
task because it provided the tools necessary to evaluate the potential risks posed by hazardous
chemicals released to the air.(d)
While attempting to understand and control air toxics during the 1970s and 1980s, EPA became
involved in many legal, scientific, and policy debates over which pollutants to regulate and how
stringently to regulate them. Much of the debate focused on what kinds of risk assessment
methods to use, what assumptions in the process were appropriate, the amount of data needed to
justify regulation, questions about the costs to industry and benefits to human health and the
environment, and decisions about "how safe is safe" (see additional discussion in Chapter 3).
While EPA and the scientific community gained valuable knowledge about risk assessment
methods during this time, the chemical-by-chemical regulatory approach - an approach based
solely on risk - proved difficult. In fact, between 1970 and 1990 EPA regulated only seven
pollutants (asbestos, benzene, beryllium, inorganic arsenic, mercury, radionuclides, and vinyl
chloride) in this manner. Standards for sources of HAPs, known as the National Emissions
Standards for Hazardous Air Pollutants or NESHAPs, cut annual air toxics emissions by an
estimated 125,000 tons. However, the process did not work quickly enough to address pressing
air pollution concerns.
2.2.3 Stationary Sources and the 1990 Clean Air Act Amendments: A "Technology First,
Then Risk" Approach
Realizing the shortcomings of the "chemical-by-chemical" risk-based decision framework for
stationary sources and acknowledging the gaps in scientific and analytical information, Congress
adopted anew strategy in 1990. Specifically, Congress revised section 112 of the Act to mandate
a more practical, phased approach to reducing emissions of toxic air pollutants.
People have been assessing risk in various ways for thousands of years, so in one sense, "risk assessment"
is an ancient practice. However, methods to quantitatively assess risk for specific applications are a more recent
development. As noted above, the methods necessary to assess the risks posed by air toxics are an even more recent
development and are the subject of this discussion.
April 2004 Page 2-4
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2.2.3.1 Step 1: The Technology-based Approach
This new approach has two components. In the first phase, EPA identifies categories of
stationary sources that emit large amounts of HAPs and then develops pollution reduction
regulations - called Maximum Achievable Control Technology or MACT standard - for those
sources.(e) The MACT standards adopted by EPA are technology-based (not risk-based), which
means EPA requires emission reductions based on an evaluation of the emission reductions that
the best-performing similar sources are already achieving.
Specifically, when developing a MACT standard for a particular source category, EPA looks at
the level of emissions already being achieved by the best-performing similar sources through
clean processes, control devices, work practices, or other methods. The CAA specifies baselines
(often referred to as the "MACT floors") for the new standards. At a minimum, a MACT
standard must achieve, throughout the industry, a level of emissions control that is at least
equivalent to the MACT floor. EPA can establish a more stringent standard after considering
cost, non-air quality and environmental impacts, and energy requirements (section 112(d)(2) of
the CAA).
The MACT floors specified in the CAA are different for existing sources and new sources. For
existing sources, the MACT floor must equal the average emissions limitations achieved by the
best-performing 12 percent of sources in that source category, if there are 30 or more existing
sources. If there are fewer than 30 existing sources, then the MACT floor must equal the average
emissions limitation achieved by the best-performing five sources in the category. For new
sources, the MACT floor must equal the level of emissions control achieved in practice by the
best-controlled similar source.
EPA has issued MACT standards for a variety of industrial source categories, including chemical
plants, oil refineries, aerospace manufacturers, and steel mills, and smaller sources, such as dry
cleaners, commercial sterilizers, secondary lead smelters, and chromium electroplating facilities.
EPA has also issued standards pursuant to section 129 of the Clean Air Act to control emissions
of certain toxic pollutants from solid waste combustion facilities. A comprehensive list of final
MACT rules and regulations for the MACT program can be found at http://www.epa.gov/ttn/atw/
mactfiiLhtml. EPA's proposed timetable for finalizing the remaining standards is available at
http ://www. epa. gov/ttn/atw/mactprop .html. When fully implemented, all of these standards will
reduce air toxics emissions by several million tons per year - more than 10 times the reductions
achieved prior to 1990.
2.2.3.2 Step 2: The Risk-based Approach
In the second phase of the process, EPA reviews the technology-based MACT standards to
ensure that these standards have adequately reduced risk within an "ample margin of safety." In
this second assessment, the Agency must adopt additional standards to address any significant
risks remaining (also called residual risks) after the first phase implementation of the
technology-based standards (section 112(f)(2)(A) of the CAA). This time lag between the
MACT standards are also considered NESHAPs.
April 2004 Page 2-5
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technology and risk-based phases allows EPA to evaluate the best way to use risk assessment as a
tool for assessing residual risks (see Chapter 3).
Within eight years after promulgation of MACT standards for each category or subcategory of
sources, EPA must promulgate standards for such category or subcategory if the MACT standard
for the category or subcategory does not protect public health with an ample margin of safety or
to prevent, taking into consideration costs, energy, safety, and other relevant factors, an adverse
environmental effect (section 112(f)(2)(A)). In 1999, EPA reported to Congress on its residual
risk assessment framework and included a discussion of its methods, data, and tools.(2)
EPA has begun to assess residual risk for several source categories, including coke ovens, dry
cleaning, gasoline distribution Stage I, commercial ethylene oxide sterilizers, halogenated solvent
cleaning, industrial cooling towers, and magnetic tape manufacturing.
2.2.4 Mobile Sources of Air Toxics Rule
Mobile sources is a term used to describe a wide variety of vehicles, engines, and equipment that
generate air pollution and that move, or can be moved, from place to place. Mobile sources
pollute the air through combustion and fuel evaporation. These emissions contribute greatly to
air pollution nationwide and are the primary cause of air pollution in many urban areas. EPA has
identified 21 mobile source air toxics (MSATs) (see box below). Twenty of these are also listed
as HAPs in CAA section 112(b); the remaining one (diesel particulate matter and diesel exhaust
organic gases) is a mixture that includes many HAPs.(3) The two major divisions or types of
mobile sources include:
• On-road (highway) sources include vehicles used on roads for transportation of passengers
or freight. These include passenger cars, light-duty trucks (pickup trucks, minivans,
passenger vans, and sport-utility vehicles), heavy-duty vehicles, and motorcycles. On-road
vehicles may be fueled with gasoline, diesel fuel, or alternative fuels such as alcohol or
natural gas.
• Nonroad (off-road) sources include vehicles, engines, and equipment used for construction,
agriculture, transportation, recreation, lawn and garden care, and many other purposes. These
include equipment and vehicles fueled with diesel fuel, gasoline, propane, or natural gas.
Mobile sources include boats, aircraft, and locomotives. Not all mobile sources are
"self-propelled." They can include portable generators, air compressors, chainsaws,
trimmers, and shredders.
EPA uses an integrated approach (including regulations) to reduce pollution from mobile
sources. From better engine design to better transit options, EPA's approach addresses:
• Vehicles, engines, and equipment;
• The fuels they use; and
• The people who operate them.
April 2004 Page 2-6
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Mobile Source Air Toxics Listed in 2001 Rule<3)
• acetaldehyde • dioxin/furans(b) • naphthalene
• acrolein • ethylbenzene • nickel compounds(a)
• arsenic compounds*3' • formaldehyde • polycyclic organic
• benzene • n-hexane matter (POM)(C)
• 1,3-butadiene • lead compounds00 • styrene
• chromium compounds(a) • manganese compounds(a) • toluene
• diesel particulate matter and diesel • mercury compounds^' • xylene
exhaust organic gases (DPM + DEOG) • methyl tertiary butyl
ether (MTBE)
(a) Although the different metal compounds may differ in their toxicity, the on-road mobile source inventory
contains emissions estimates for total metal compounds (i.e., the sum of all forms).
^ This entry refers to two large groups of chlorinated compounds. In assessing their cancer risks, their
quantitative potencies are usually derived from that of the most toxic, 2,3,7,8-tetrachlorodibenzodioxin.
(c) Polycyclic organic matter includes organic compounds with more than one benzene ring, and which have a
boiling point greater than or equal to 100 degrees Celsius. A group of seven polynuclear aromatic hydrocarbons,
which have been identified by EPA as probable human carcinogens (benz(a)anthracene, benzo(b)fluoranthene,
benzo(k)fluoranthene, benzo(a)pyrene, chrysene, 7,12-dimethylbenz(a)anthracene, and indeno(l,2,3-cd)pyrene)
. are used here as surrogates for the larger group of POM compounds.
^v^_ _^r
This approach includes national engine and fuel standards, as well as state requirements (e.g.,
engine maintenance, traffic flow/roadway design) established to enable attainment of the
NAAQS for the criteria pollutants. The approach also involves extensive collaboration among
EPA, state local and tribal (S/L/T) governments, transportation planners, individual citizens, and
vehicle, engine, and fuel manufacturers and has been responsible for greatly reducing mobile
source air pollution during the last 30 years.
In addition to achieving air toxics emissions reductions as a result of actions aimed at reductions
in criteria pollutants, the 1990 CAA Amendments contain provisions specific to air toxics.
These amendments direct EPA to address emissions of air toxics from motor vehicles and their
fuels. Specifically, section 202(1) of the Clean Air Act instructs EPA to:
• Study the need for and feasibility of controlling emissions of toxic air pollutants associated
with motor vehicles and their fuels. This section identifies benzene, 1,3-butadiene, and
formaldehyde for particular consideration. EPA completed this study in 1993 and updated it
in 1999.
• Set standards for HAPs from motor vehicles, their fuels, or both. Those standards are to be
promulgated under section 202(a) or section 21 l(c) of the Act and must address at least
benzene and formaldehyde. EPA is to base these standards on available technology, taking
into account existing standards; costs, noise, energy, and safety factors; and lead time. EPA
promulgated a rulemaking in accordance with CAA section 202(1) on March 29, 2001 (66 FR
17230).
April 2004 Page 2-7
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Rulemakings and Voluntary Efforts to Reduce
MSATs and other Air Pollutants
Tier 2 gasoline/sulfur rulemaking
flittp ://www. epa. gov/otaq/tr2home.htm')
Reducing nonroad diesel emissions
flittp ://www. epa. gov/nonroad/)
Voluntary diesel retrofit program
flittp ://www. epa. gov/otaq/retrofif)
Best Workplaces for Commuters
flittp ://www. commuterchoice. gov)
Clean School Bus USA
(http://www.epa.gov/cleanschoolbus.
It All Adds Up to Cleaner Air
flittp ://www. italladdsup. gov)
The many vehicle and fuel changes in the
last 25 years have greatly reduced air
toxics emissions from highway vehicles.
For example, the removal of lead from
gasoline has essentially eliminated on-
road mobile source emissions of this
highly toxic substance in the United
States. In addition, results of recent
modeling indicate that current and
planned programs will reduce emissions
of mobile source air toxics by about one
million tons (about 35 percent) between
1996 and 2007; on-highway emissions of
benzene, formaldehyde, 1,3-butadiene,
and acetaldehyde by 67 to 76 percent
between 1990 and 2020; and on-highway
diesel particulate matter by 94 percent between 1990 and 2020.(4) New cars using reformulated
gasolines are capable of emitting more than 90 percent less air toxics on a per-mile basis than the
uncontrolled models of 1970; new trucks and buses are designed to emit less than half the air
toxics of their 1970 counterparts. Overall air toxics emissions will continue to decrease as older
vehicles leave the fleets and as new regulatory programs take effect. However, the number of
vehicles on the road and the number of miles they travel is continuing to grow. Without
additional controls, growth in vehicle travel will offset progress in reducing air toxics.
2.2.5 Indoor Air and Indoor Air Toxics
Indoor pollution sources that release gases or particles into the air are the primary cause of indoor
air quality problems in homes and other buildings. Inadequate ventilation can increase indoor
pollutant levels by not bringing in enough outdoor air to dilute emissions from indoor sources
and by not carrying indoor air pollutants out of the building. High temperature and humidity
levels can also increase concentrations of some pollutants.
The importance of indoor air exposures to the total risk from air toxics is a relatively new
finding. The contribution of indoor sources was not really recognized until the early 1980s when
EPA performed the Total Exposure Assessment Methodology (TEAM) studies, which showed
that the indoor concentrations of some air toxics can be significantly higher than outdoor
concentrations. Since that time, numerous studies have confirmed that finding. In addition, the
fact that Americans spend about 90 percent of their times indoors makes these exposures even
more important
April 2004
Page 2-1
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2.2.5.1 Potential Sources of Indoor Air Toxics
Sources of Indoor Air Toxics
There are many potential sources
of indoor air toxics in any home or
building. These sources include
combustion sources such as oil,
gas, kerosene, coal, wood, and
tobacco products; building
materials and furnishings as
diverse as deteriorated, asbestos-
containing insulation, and
cabinetry or furniture made of
certain pressed wood products;
products for household cleaning
and maintenance (e.g., pesticides),
personal care, or hobbies; and
outdoor sources such as radon and
other air pollution that penetrate
into the indoor space.
The relative importance of any single source depends on how much of a given pollutant it emits
and how hazardous those emissions are. In some cases, factors such as the age of the source and
whether it is properly maintained are significant. For example, an improperly adjusted gas stove
can emit significantly more carbon monoxide
than one that is properly adjusted. /
Indoor air can
become
contaminated
from numerous
sources.
Indoor air can
have significantly
higher
concentrations of
air toxics than
outdoor air.
EPA currently
does not regulate
indoor sources of
air toxics.
Disinfectants
Pesbcides
Cleaners
Solvents
Aeiosois
Clues
Garten Monoxide
Some sources, such as building materials,
furnishings, and household products like air
fresheners, release pollutants more or less
continuously (usually at a decreasing rate
with age). Other sources, related to activities
carried out in the home, release pollutants
intermittently. These include smoking, the use
of unvented or malfunctioning stoves,
furnaces, or space heaters, the use of solvents
in cleaning and hobby activities, the use of
paint strippers in redecorating activities, and
the use of cleaning products and pesticides in
housekeeping. High pollutant concentrations
can remain in the air for long periods after
some of these activities.
2.2.5.2 Indoor Air Toxics
Although EPA does not regulate indoor air
pollution levels, it does take a proactive
approach. The Agency provides a broad
range of information about indoor air-related
How Does Outdoor Air Enter a House?
Outdoor air enters and leaves a house by:
infiltration, natural ventilation, and mechanical
ventilation. In a process known as infiltration,
outdoor air flows into the house through
openings, joints, and cracks in walls, floors, and
ceilings, and around windows and doors. In
natural ventilation, air moves through opened
windows and doors. Air movement associated
with infiltration and natural ventilation is caused
by air temperature differences between indoors
and outdoors and by wind. Finally, there are a
number of mechanical ventilation devices, from
outdoor-vented fans that intermittently remove
air from a single room, such as bathrooms and
kitchens, to air handling systems that use fans
and duct work to continuously remove indoor air
and distribute filtered and conditioned outdoor air
to strategic points throughout the house. The rate
at which outdoor air replaces indoor air is
described as the air exchange rate. When there is
little infiltration, natural ventilation, or
mechanical ventilation, the air exchange rate is
I low, and pollutant levels can increase.
April 2004
Page 2-9
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risks, as well as the steps to reduce them, through the use of public awareness campaigns,
guidance document dissemination, training course delivery, the operation of several linked
hotlines and clearinghouses, and other outreach efforts. Useful resources on indoor air quality
from the Agency are also available online.(5)(6) EPA's activities to reduce exposures to indoor air
toxics are many and include publishing guidelines about radon testing and result interpretation;
persuading parents and caregivers of young children not to smoke indoors; and providing
information to homeowners, school administrators, and office managers on the proper use of
products and materials indoors, including appropriate maintenance and ventilation.
In 2001, EPA issued the Healthy Buildings, Healthy People (HBHP) report, a vision for indoor
environmental quality in the 21st century.(7) The report covers three general areas: (1) why
human health indoors deserves the scrutiny, concern, and action of policy makers; (2) a vision
statement of EPA's vision, goals, broad strategies, and guiding principles to address indoor air
quality issues; and (3) potential actions that EPA or others may pursue. The report also provides
an overview of current indoor environmental program priorities in various offices within EPA
and examines the roles of the Agency s partners in indoor environmental protection, including
Federal, S/L/T organizations, and stakeholders.
EPA's objective is to realize major human health gains over the next 50 years by upgrading
indoor environments. The Agency has set five goals and strategies to accomplish this objective:
• Achieve major health gains and improve professional education;
• Foster a revolution in the design of new and renovated buildings;
• Stimulate nationwide action to enhance health in existing structures;
• Create and use innovative products, materials, and technologies; and
• Promote health-conscious individual behavior and consumer awareness.
In addition to providing information on actions and strategies that can be taken to protect people
indoors, EPA's vision acknowledges the important role individuals play in protecting their own
health and the health of those around them.
EPA's specific goals to reduce the health risks from indoor air for 2005 include:
• 700,000 homes with high radon levels will be mitigated and 1 million homes with radon-
resistant construction techniques will be constructed;
• The proportion of households in which children ages six and under are regularly exposed to
smoking will be reduced from 27 percent in 1994 to 15 percent;
• Five percent of office buildings will be managed with indoor air quality practices consistent
with EPA's Building Air Quality guidance;(8)
• Fifteen percent of the nation's schools will adopt good indoor air quality practices consistent
with EPA's Indoor Air Quality Tools for Schools guidance;(9)
• One million children with asthma will have reduced exposure to indoor asthma triggers; and
• 200,000 low-income adults with asthma and 2.5 million people with asthma overall, will
have reduced exposures to indoor asthma triggers.
Additional information on EPA's indoor air programs can be found EPA's Indoor Air Toxics
web site.(5)
April 2004 Page 2-10
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2.2.5.3 Health Risks and Indoor Pollutants
The health risks from a few indoor air toxics (e.g., radon, environmental tobacco smoke,
benzene, lead, and asbestos) are well known and have been the subject of risk assessments both
within and outside EPA. EPA's best estimate of annual lung cancer deaths from radon is
currently about 21,000 (with an uncertainty range of 8,000 to 45,000). Environmental tobacco
smoke is estimated to cause an additional 3,000 lung cancer deaths in non-smokers each year.
EPA estimates that environmental tobacco smoke may also significantly aggravate symptoms of
asthma for 200,000 children and may affect as many as 1,000,000 children to some extent. A
California report estimates that environmental tobacco smoke causes 9,700 to 18,600 cases of
low birth weight in infants each year and 35,000 to 62,000 cardiovascular deaths among non-
smokers.(10)
To prioritize activities for other chemicals typically
found in indoor air, EPA's Office of Radiation and
Indoor Air (ORIA) is sponsoring a screening-level,
risk-based analysis, which is currently in draft form and
being revised. Some of the chemicals that maybe of
concern in indoor air, based on the draft ranking, are
provided in the box to the right. However, it should be
noted that the final results of this analysis may be
significantly different. It should also be noted that,
because monitoring data were only available for 112
chemicals and only 59 chemicals could be ranked, many
chemicals found indoors might rank higher, given more
complete information.
Both acute and chronic cancer and noncancer health
effects were addressed in the analysis, which focused on
inhalation exposure only. Ten monitoring studies ^ ^
provided 213 concentration records for 112 air toxics
including metals, aldehydes, volatile organic compounds (VOCs), and semivolatile organic
compounds (SVOCs). Studied microenvironments included office buildings, residences, and
schools. The general methodology used in the analysis echoed that used by the stationary source
program to choose a list of urban HAPs for the Integrated Urban Air Toxics Strategy (64 FR
38706).
The study also estimated the indoor source contribution to indoor concentrations by subtracting
associated outdoor concentrations from indoor concentrations. The listed pollutants were found
to have large indoor source components. Note, however, that four of the listed pollutants (i.e.,
heptachlor, aldrin, dieldrin, and chlordane) are pesticides that are no longer in use but may
continue to be of concern due to their persistence in the environment and the presence of unused
and uncollected stocks/1!)
Some Pollutants of Potential
Concern Indoors
Formaldehyde
Heptachlor
1,4-Dichlorobenzene
Aldrin
Chloroform
Dieldrin
Benzene
Chlordane
Tetrachloroethylene
Acetaldehyde
Trichloroethylene
Dichlorvos
Methylene chloride
Lindane
April 2004
Page 2-11
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2.3 Progress in Understanding and Reducing Toxic Air Pollution
National Air Toxics Emissions
5.U
7.0
6.0 -
5.0
4.0 -
3.0 -
2.0 -
1.0 -
n n
1999
Year
While monitoring data is critical to understanding
and reducing toxic air pollution, EPA and S/L/T
governments do not currently maintain as
extensive a nationwide monitoring network for
outdoor concentrations of air toxics as they do for
many of the other pollutants (such as ozone and
particulate matter). And, while EPA and S/L/T
regulatory agencies do collect monitoring data for
a number of toxic air pollutants, both the
chemicals monitored and the geographic coverage
of the monitors vary among individual S/L/T
partners. EPA is working with these regulatory
partners to build upon the existing monitoring
sites to create a national outdoor monitoring network for a number of toxic air pollutants. The
Agency's goal is to improve the scientific and technical competency of existing outdoor air
monitoring networks in order to be more responsive to the public and the scientific and health
communities; in this way, EPA can accommodate future needs in the face of scarce resources.
2.3.1 Trends
Monitoring data that are available can help air pollution control agencies track local trends in
toxic air pollutants around the country. EPA began a pilot city monitoring project in 2001 with
the intention to help answer several important national network design questions (e.g., sampling
and analysis precision, sources of variability, and minimum quantitation levels). Based on the
results of this year-long study and an analysis of historical monitoring data, the Agency is
establishing a network of 22-city National Air Toxics Trends Sites (NATTS) that will help
develop national trends for several pollutants of concern. For the latest information on national
air toxics monitoring, see www.epa.gov/ttn/amtic/airtxfil.html.
As shown in this pie chart, based on 1999
estimates (the most recent year of available data
in the National Emissions Inventory (NEI) for air
toxics), the emissions of HAPs are relatively
equally divided between four types of sources: on
road, non road, major, and area/other sources.
However, this distribution varies from city to city.
National Air Toxics Emissions, 1989
6.1 M Tnnc
Qiraad £7%)
Malar u!6-*j
Based on the data in the NEI, estimates of
nationwide outdoor air toxics emissions have
dropped approximately 29 percent between
baseline (1990-1993) and 1999. Thirty-three of
these air toxics (the Urban Air Toxics), which are considered to pose the greatest threat to public
health in most urban areas, have similarly dropped 31 percent. Although changes in how EPA
compiled the national inventory over time may account for some differences, EPA and S/L/T
regulations, as well as voluntary reductions by industry have also achieved large reductions in air
toxic emissions.
April 2004
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National Air Toxics Trends Stations (NAATS) Sites
.05*
January 2003 Startup
January 2004 Startup
Pilot Programs
Providence, RI
Roxbury, MA
New York, NY
Washington, DC
Decatur (Atlanta), GA
Hazard, KY**
Detroit, MI
Deer Park (Houston), TX
St. Louis, MO
Bountiful, UT
Grand Junction, CO**
San Jose, CA
Seattle, WA
Chittenden County, VT**
Rochester, NY
Tampa, FL
Chesterfield, SC**
Chicago, IL
Mayville, WI
Harrison County, TX**
Phoenix, AZ
La Grande, OR**
Barcelona/San Juan, PR
Providence, RI
Keeney Knob, WV
Tampa, FL
Detroit, MI
Rio Rancho, NM
Cedar Rapids, IA
San Jacinto, CA
Grand Junction, CO
Seattle, WA
** rural site
Source: EPA's Latest Findings on National Air Quality^
Trends for individual air toxics vary from
pollutant to pollutant. Benzene, the most
widely monitored toxic air pollutant, is emitted
from cars, trucks, oil refineries, and chemical
processes. The graph at right shows
measurements of benzene taken from 95 urban
monitoring sites around the country. These
urban areas generally have higher levels of
benzene than other areas of the country. These
site measurements show, on average, a 47
percent drop in benzene levels from 1994 to
2000 (see adjacent graph). During this period,
Ambient Benzene, Annual Average Urban
Concentrations, Nationwide, 1994-2000
98 97 98
1994-00:47% decrease
00
April 2004
Page 2-13
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EPA phased in new (so-called "tier 1") car emission standards, implemented the federal
reformulated gasoline program in several parts of the country, and required reductions in
emissions of benzene and other HAPs from oil refineries and chemical manufacturers. EPA
estimates that, nationwide, benzene emissions from all sources dropped 20 percent from 1990 to
1996.
2.3.2 NATA National Scale Assessment
As part of its National Air Toxics Assessment (NATA)(f) activities, EPA has developed a
national-scale risk characterization for 33 toxic air pollutants (Exhibit 2-1), based on 1996
emissions data. This set of pollutants is similar to the list of 33 Urban Air Toxics except that
diesel particulate matter is included and dioxin is not. EPA used computer modeling of the 1996
NEI air toxics data as the basis for developing health risk estimates. The goal of the
national-scale assessment risk characterization is to identify those air toxics which may be of
potential concern in terms of contribution to population risk. The results are being used to,
among other things, set priorities for the collection of additional air toxics data (e.g., emissions
data and ambient monitoring data). EPA plans to update the national scale assessment every
three years.
A number of important limitations and uncertainties are associated with the national scale
assessment (see Summary of Limitations, Variability, and Uncertainty in the 1996 National-Scale
Air Toxics Assessment box). Nonetheless, the results provide important information for priority
setting. For example, the following map shows the distribution of relative predicted cancer risk
attributed to exposures to outdoor sources of air toxics across the continental United States as
estimated by the national-scale assessment. The highest ranking 20 percent of counties in terms
of risk (622 counties) contain almost three-fourths of the U.S. population. Three air toxics
(chromium, benzene, and formaldehyde) appear to pose the greatest nationwide carcinogenic
risk. This map does not include the potential risk from diesel exhaust emissions because the
existing health data were not deemed sufficient to develop a numerical estimate of cancer risk for
this pollutant. However, exposure to diesel exhaust is widespread, and EPA has concluded that
diesel exhaust is a likely human carcinogen and ranks it with the other substances that the
national-scale assessment suggests pose the greatest relative risk. One toxic air pollutant,
acrolein, is estimated to pose the highest potential nationwide for chronic adverse effects other
than cancer. For more information about NATA activities, see www.epa.gov/ttn/atw/nata.
This technical assessment represents an important step toward characterizing air toxics
nationwide. It is designed to help identify general patterns in air toxics exposure and risk across
the country, but is not recommended as a tool to characterize or compare risk at local levels (e.g.,
to compare risks from one part of a city to another). More localized assessments, including
monitoring and modeling, provide a more appropriate way to accurately characterize local-scale
risk.
NATA is EPA's ongoing comprehensive evaluation of air toxics in the U.S. These activities include
expansion of air toxics monitoring, improving and periodically updating emission inventories, improving national-
and local-scale modeling, continuing research on health effects and exposures to both ambient and indoor air, and
improving assessment tools (http://www.epa.gov/ttn/atw/nata/index.html).
April 2004 Page 2-14
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Exhibit 2-1. The 33 Pollutants Included in the National-Scale Air Toxics Assessment
acetaldehyde
acrolein
acrylonitrile
arsenic compounds
benzene
beryllium compounds
1,3 -butadiene
cadmium compounds
carbon tetrachloride
chloroform
chromium compounds
coke oven emissions
1 ,3-dichloropropene
diesel particulate matter
ethylene dibromide
ethylene dichloride
ethylene oxide
formaldehyde
hexachlorobenzene
hydrazine
lead compounds
manganese compounds
mercury compounds
methylene chloride
nickel compounds
perchlorothylene
polychlorinated biphenyls (PCBs)
polycyclic organic matter (POM)(a)
propylene dichloride
quinoline
1 , 1 ,2,2-tetrachloroethane
trichloroethylene
vinyl chloride
(a)Also represented as 7-PAH
EPA plans eventually to include all 188 HAPs in the NAT A national-scale assessment
Source: http://www.epa.gov/ttn/atw/nata/34poll.html
1996 Estimated County Median Cancer Risk
All Carcinogens — United States Counties
Saeram*
Upper—Bound Lifetime Cumulative Cancer Risk
Highest In U.S. ^^_ 190 In a million
95 I I 54- In a million
90 I i « In o million
Percent! le 75 32 In a million
50 26 In a million
25 23 In a million
Lowest In U.S. I 1 0 In o million
Cancer
Risk
Source: U.S. EPA / QAQPS
Nafional-Scale Afr Toxics Assessment
April 2004
Page 2-IS
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Summary of Limitations, Variability, and Uncertainty in the
1996 National-Scale Air Toxics Assessment*3'
• Limitations. The NATA results provide macro-level data on emissions, ambient air
concentrations, exposures, and risks across broad geographic areas (such as counties, states and the
nation) at a moment in time. As such, they help the EPA identify specific air toxics compounds,
and specific source sectors such as stationary sources or mobile sources, which generally produce
the highest exposures and risks in the country. But the results are also based on assumptions and
methods that limit the range of questions that can be answered reliably. The data cannot be used to
identify exposures and risks for specific individuals, or even to identify exposures and risks in
small geographic regions such as a specific census tract. Also, these data are not appropriate for
determining impacts close to particular facilities. These limitations, or caveats, must always be
kept in mind when interpreting the results, and the results should be used only to address questions
for which the assessment methods are suited.
• Variability. Emissions, air concentrations, exposures and risks are not the same throughout the
U.S., and are not the same for every person. Some geographic areas have higher concentrations
than others; there are some periods of time when the concentration is higher at a given location
than at other times. Some individuals have an exposure and/or risk below the national average,
while others have an exposure and/or risk above the national average. It is necessary, therefore, to
have some idea of how the ambient air toxics concentrations, exposures, and risks vary throughout
the U.S. Such a process is called a variability analysis.
• Uncertainty. EPA seeks to protect health with reasonable confidence. Scientific estimates of air
concentrations, exposures, and risks, however, always involve simplifying assumptions that make
the assessment possible given available information and resources. These assumptions introduce
uncertainties into the results, since there is never complete confidence that the assumptions are
entirely correct. It is necessary to understand the size of these uncertainties, the level of
confidence that can be placed in any statement related to the assessment, and how this confidence
affects the ability to make reasoned decisions. Such a process is called an uncertainty analysis.
(a)More detailed discussion of specific limitations, variability, and uncertainty associated with the 1996 national-
scale assessment is provided in three individual pages accessed by links from
http://www.epa.gov/ttn/atw/nata/natsalim2.html.
2.4 Other Air Pollutants of Potential Concern
As previously noted, there are many other air pollutants that may be harmful to public health and
the environment and, for some of these chemicals, other programs may already be in place to
help control them. This section discusses several groups of air pollutants, some of which overlap
with the list of 188 HAPs.
2.4.1 Criteria Air Pollutants
Pursuant to the CAA, EPA has set standards, also known as National Ambient Air Quality
Standards (NAAQS), for six criteria pollutants (Exhibit 2-2). The Clean Air Act requires
these standards to be set at levels that protect public health with an adequate margin of safety and
without consideration of cost. These standards serve two important purposes: first, they provide
information to the public about whether the air in their community is healthful; and second, they
April 2004 Page 2-16
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present state and local governments with the targets they must meet to achieve clean air. EPA
requires that each state containing areas that do not attain the standards develop a written plan for
cleaning the air in those areas. The plans developed are called state implementation plans (SIPs).
Through these plans, the states outline efforts that they will make to try to correct the levels of air
pollution and bring their areas back into attainment.
Exhibit 2-2. National Ambient Air Quality Standards (NAAQS)
Pollutant
Standard Value*
Standard Type
9 ppm (10mg/m3)
35 ppm (40 mg/m3)
Primary
Primary
Carbon Monoxide (CO)
8-hour Average
1 -hour Average
Nitrogen Dioxide (NO2)
Annual Arithmetic Mean
Ozone (O3)
1 -hour Average
8-hour Average
Lead (Pb)
Quarterly Average
Particulate (PM10) Particles with diameters of 10 micrometers or less
Annual Arithmetic Mean 50 |-ig/m3 Primary & Secondary
24-hour Average 150 |-ig/m3 Primary & Secondary
Particulate (PM2 5) Particles with diameters of 2.5 micrometers or less
0.053 ppm (100 |-ig/m3) Primary & Secondary
0.12 ppm (235 |-ig/m3) Primary & Secondary
0.08 ppm (157|_ig/m3) Primary & Secondary
1.5 |J,g/nf
Primary & Secondary
Annual Arithmetic Mean
24-hour Average
Sulfur Dioxide (SO2)
Annual Arithmetic Mean
24-hour Average
3-hour Average
15 |J,g/m3
65 |-ig/m3
0.030 ppm (80 l-ig/m3)
0.140 ppm (365 |-ig/m3)
0.500 ppm (1300 |J,g/m3)
Primary & Secondary
Primary & Secondary
Primary
Primary
Secondary
* Parenthetical value is an approximately equivalent concentration
April 2004
Page 2-17
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Four of these pollutants (CO, Pb, NO2, and SO2) result primarily through direct emissions from a
variety of sources. PM results from direct emissions, but is also commonly formed from
emissions of nitrogen oxides (NOX), sulfur oxides (SOX), ammonia, organic compounds, and
other gases in the atmosphere. Sources of fine particles (PM25) include many types of
combustion activities (e.g., motor vehicles, power plants, wood burning) and certain industrial
processes. Ozone is not directly emitted from sources, but is formed when NOX and VOCs react
in the presence of sunlight.
Exposure to the criteria pollutants is associated with numerous effects on human health,
including increased respiratory symptoms, hospitalization for heart or lung diseases, and even
premature death. The CAA established two types of NAAQS for the criteria pollutants:
• Primary standards are designed to establish limits to protect public health, including the
health of sensitive populations such as asthmatics, children, and the elderly.
• Secondary standards set limits to protect public welfare, including protection against
visibility impairment and adverse effects on crops, vegetation, and building materials.
Air Quality Index
Many of the health effects associated with
the criteria pollutants can happen within a
few hours or days after breathing polluted
air. Thus, EPA has developed an index,
called the Air Quality Index or AQI, for
reporting daily air quality. The AQI can be
thought of as a yardstick that runs from 0 to
500. The higher the AQI value, the greater
the level of air pollution and the greater the
health danger. For example, an AQI value
of 50 represents good air quality and little
potential to affect public health, while an
AQI value over 300 represents hazardous
air quality. Most States now provide this
information to their citizens on either their
own website or through the EPA's AirNow
website (http://www.epa. gov/airnow/
where/).
Despite the progress made in the last 30 years, millions of people live in counties in which
monitoring data show unhealthy air for one or more of the six criteria pollutants. EPA's most
recent evaluation of air pollution trends for these six pollutants can be found at http://www.
epa. gov/airtrends/. General information on the criteria pollutants can be found at
http://www.epa.gov/air/urbanair/6poll.html.
Air Quality Index
(AQI) Values
0 to 50
51 to 100
101 to 150
151 to 200
201 to 300
301 to 500
Levels of Health
Concern
Good
Moderate
Unhealthy for
sensitive groups
Unhealthy
Very Unhealthy
Hazardous
Colors
Green
Yellow
Orange
Red
Purple
Maroon
April 2004
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2.4.2 Chemicals on the Toxics Release Inventory
In 1984, a cloud of methyl isocyanate released from an accident at a pesticide plant in Bhopal,
India, killed thousands of people. Shortly thereafter, there was a serious chemical release at a
sister plant in West Virginia. These incidents underscored the needs of industrial workers and
communities for more complete information on hazardous materials. Public interest and
environmental organizations around the country increased demands for information on toxic
chemicals being released "beyond the fence line" - outside of the facility. In response, Congress
enacted the Emergency Planning and Community Right-to-Know Act (EPCRA) in 1986. Shortly
thereafter, the CAA Amendments of 1990 required EPA to publish regulations and guidance for
chemical accident prevention at facilities using extremely hazardous substances (see box below).
SX
Risk Management Planning: Accidental Release Prevention
The CAA Amendments of 1990 required EPA to publish regulations and guidance for chemical
accident prevention at facilities using extremely hazardous substances. The Risk Management
Program Rule was written to implement section 112(r) of these amendments. The rule, which built
upon existing industry codes and standards, requires companies of all sizes that use certain flammable
and toxic substances to develop a Risk Management Program, which includes a(n):
• Hazard assessment that details the potential effects of an accidental release, an accident history of
the last five years, and an evaluation of worst-case and alternative accidental releases;
• Prevention program that includes safety precautions and maintenance, monitoring, and employee
training measures; and
• Emergency response program that spells out emergency health care, employee training measures,
and procedures for informing the public and response agencies (e.g., the fire department) should an
accident occur.
A summary of each facility's risk management program (known as a "Risk Management Plan" or
"RMP") was to be submitted to EPA by 1999 and must be revised and resubmitted every five years.
The List of Regulated Substances under section 112(r) of the Clean Air Act is found in 40 CFR Part
68 and lists the regulated substances, including their synonyms, and threshold quantities (in pounds) to
help facilities assess if they are subject to the RMP rule or the general duty clause (see
http://www.access.gpo.gov/nara/cfr/cfrhtml_00/Title_40/40cfr68_00.html). Note that pursuant to
section 112(r), threshold quantities for RMPs, are of awow«fc sfora/ on sr'fe and not emissions.
Additional information on the Risk Management Program can be found at:
http://vosemite.epa.gov/oswer/ceppoweb.nsf/content/RMPS.htm
EPCRA's primary purpose is to inform communities and citizens of chemical hazards in their
areas. Sections 311 and 312 of EPCRA require businesses to report the locations and quantities
of chemicals stored on-site as a means of helping communities prepare for chemical spills and
similar emergencies. EPCRA section 313 requires EPA and the states to annually collect data on
releases and transfers of listed toxic chemicals from certain industrial facilities, and make the
data available to the public in the Toxics Release Inventory (TRI). In 1990, Congress passed the
Pollution Prevention Act which required that additional data on waste management and source
reduction activities also be reported in the TRI. One of the goals of the TRI is to empower
citizens, through information, to hold companies and local governments accountable for the
management of toxic chemicals.
April 2004 Page 2-19
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The TRI program has expanded significantly since its inception in 1987. The Agency has issued
rules to roughly double the number of chemicals that the TRI includes to over 650. The TRI has
added seven new industry sectors, expanding coverage significantly beyond manufacturing
industries. Most recently, the Agency has reduced the reporting thresholds for certain persistent,
bioaccumulative, and toxic (PBT) chemicals (discussed in Chapter 4) in order to provide
additional information to the public on these chemicals. A full list of the TRI chemicals, along
with information on accessing the database and health and environmental effects information,
can be found at http://www.epa.gov/tri/.
2.4.3 Toxic Chemicals that Persist and Which Also May Bioaccumulate
Toxic chemicals that persist and which also may bioaccumulate are compounds that can build up
in the food chain to levels that are harmful to human and ecosystem health. Such chemicals,
commonly called PBT chemicals, may be associated with a range of adverse human health
effects, including effects on the nervous system, reproductive and developmental problems,
cancer, and genetic impacts. EPA's challenge in reducing risks from these chemicals stems from
the pollutant's ability to transfer easily between air, water, and land; to linger for generations in
people and the environment; and in some cases to travel long distances. A number of "lists" of
these chemicals have been developed through international and EPA efforts (see Chapter 4).
Over the years, much work has been done to reduce the risk associated with these chemicals.
However, the nation still finds PBT chemicals in the air, water, land, and, as a result, food. For
example, the total number of advisories for eating contaminated fish in the United States
increased by 93 percent from 1993 to 2002.(13) Although there are advisories for a total of 39
chemical contaminants, most advisories involve five primary contaminants: mercury, PCBs,
dioxins, DDT, and chlordane. Almost 75 percent of the advisories have been issued at least in
part because of mercury contamination. The 2,800 advisories issued in 2002 represent
approximately 33 percent of the nation's total lake acreage and over 15 percent of the nation's
total river miles.
Until the late 1990s, EPA actions to reduce emissions of toxic chemicals that persist and which
also may bioaccumulate have been separate regulatory activities aimed at pollutant releases to
individual environmental media (air, water, or land). In 1998, EPA developed a PBT Strategy
to better coordinate these actions and to assure, for example, that regulations removing a
pollutant from the air do not inadvertently result in transferring it to the land or water
(http://www.epa.gov/opptintr/pbt/). The main goals of the strategy are to:
Develop and implement national action
plans to reduce priority PBT pollutants,
utilizing the full range of EPA tools;
Continue to screen and select more
priority PBT pollutants for action;
Prevent new PBTs from entering the
marketplace; and
Measure progress of these actions
against the Government Performance
and Results Act (GPRA) goals and
national commitments.
Uiannetta
April 2004
Page 2-20
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The Agency-wide strategy enables EPA to harness all of its tools - voluntary, regulatory,
international, enforcement, compliance, and research - and direct them at a set of priority
pollutants of common concern to all EPA program offices. Implementing the strategy will
require time and the coordination of many EPA offices as well as other stakeholders, such as
industry, other governmental groups, and the international community.
International Transport of Air Pollutants
There is the potential for toxic chemicals that persist and which also may bioaccumulate to be
transported from long distances to contaminate distant regions of the globe. An investigation by EPA
Region 5 has shown the possibility of long-range transport of certain of these chemicals (identified in
an international treaty as "persistent organic pollutants," or POPs - see Chapter 4) which were used in
Central America prior to the 1980s to impact the Great Lakes. This is due to several phenomena. The
semi-volatility of many POPs, allows them to be volatilized from warmer regions of the globe and
redeposited in cooler regions in higher latitudes. Additionally, meteorological patterns during certain
times of year can transport air masses and pollutants from the Central American region though the
central U.S. into the northern states. Air masses from Central America have an unobstructed path to
the Great Lakes (e.g. no physical barriers such as mountain ranges). Satellite photos show the
transport of smoke from Central American fires in May of 1998 up through the Great Lakes Region.
This figure illustrates the mean wind flow at
1500 meters of altitude during the months of
June, July and August from 1985 to 1996.
Although these patterns can be disrupted by
climatological events such as El Nino, it is
clear that POPs released in the southern
areas of this hemisphere can impact areas of
the U.S. Studies have shown that long range
transport from many regions of the globe is
a significant source of POP chemicals to the \
Great Lakes and that mitigation efforts are
going to be needed both in the U.S. and
globally to address potential sources. The
study of Central American sources has
shown that this region is a potential
contributor to POPs contamination in the
Great Lakes, due to the fact that these
chemicals degrade very slowly, and there still exist areas of high contamination and stockpiles of
these chemicals that are no longer in use in Cental America.
For more information on International Issues & U.S. Air Quality, see EPA's Air Trends website at
http ://www. epa. gov/airtrends/international .html
April 2004
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2.4.4 Overlaps and Differences Between Chemical "Lists"
The various lists of chemicals discussed above (e.g., HAPs, criteria air pollutants, TRI
chemicals) do not always treat groups of chemicals (or chemical precursors/reaction products) in
the same manner. Some examples of the ways in which these lists overlap or differ include:
• "Glycol ethers" are defined differently for the TRI and as HAPs (see box below);
• Ozone is formed by the interaction of NOX, VOCs, and sunlight. Some of the HAPs are
VOCs that may contribute to ozone formation;
• "Particulate matter" that is regulated as a criteria pollutant can be comprised of any number
of individual chemicals and may contain various HAPs.
Glycol Ethers in the TRI and as HAPs
The TRI includes certain glycol ethers R-(OCH2CH2)n -OR' where:
n= 1,2, or 3
R = alkyl C7 or less; phenyl or alkyl substituted phenyl
R' = H, or alkyl C7 or less
OR' consisting of carboxylic acid ester, sulfate, phosphate, nitrate, or sulfonate.
The list of HAPs includes mono- and di- ethers of ethylene glycol, diethylene glycol,
and triethylene glycol R-(OCH2CH2)n -OR where:
n= 1,2, or 3
R = alkyl or aryl groups
R' = R, H, or groups which, when removed, yield glycol ethers with the structure: R-
(OCH2CH)n-OH.
Polymers (surfactant alcohol ethoxylates and their derivatives)are excluded from the
, glycol category.
It is important to keep these overlaps and differences in mind since they can have important
legal, policy, and other practical implications when studying air toxics impact or developing risk
reduction alternatives for a particular location. The reader should also remember that the
differences among chemical "lists" are based mostly on legal and regulatory considerations, not
necessarily on toxicologic properties.
2.5 Reports to Congress on Air Toxics Issues
The CAA requires EPA to study and produce reports on several specific topics relevant to our
understanding of air toxics and the risks they pose to human health. These studies have been
critical to our understanding of important air toxics sources and how certain chemicals move
through and impact our environment. A synopsis of several of these studies is presented below.
Links to all of the various reports can be found at http://www.epa.gov/ttn/oarpg/t3rc.html.
April 2004
Page 2-22
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2.5.1 Air Toxics Deposition to the Great Waters
Pursuant to section 112(m) of the CAA, EPA, in conjunction with the National Oceanic and
Atmospheric Administration (NOAA), has issued three reports to Congress on the deposition of
air toxics and the resulting effects on the Great Lakes, Chesapeake Bay, Lake Champlain, and
certain other coastal waters, collectively known as the Great Waters. In addition to EPA and
NOAA, other international, national, regional, and local organizations also contribute to the body
of science relevant to the Great Waters program and are engaged in activities that seek to reduce
sources and quantities of pollution to the Great Waters. These activities focus on 15 pollutants
of concern, including certain pesticides, metal compounds, chlorinated organic compounds, and
nitrogen compounds. These pollutants enter the air in a variety of ways, including direct emission
from industries and natural sources, and "re-emission" from soil and water. The Agency selected
pollutants of concern due to their persistence, potential to bioaccumulate, and/or potential for
adverse impacts to the Great Waters. Some of these pollutants are also likely endocrine
disrupters, meaning they may interfere with the action of hormones in wildlife and humans.
EPA will work to increase public awareness of risks of exposure to Great Waters pollutants as
well as continue to support the development of modeling tools that address the transport and fate
of pollutants in ecosystems and characterize risk, including research to clarify mechanisms of
mercury methylation so as to better predict and manage ecosystems at risk. The most recent
Great Waters Report to Congress is available at http://www.epa.gov/airprogm/oar/oaqps/
grSwater/.
2.5.2 Mercury Study Report to Congress
Mercury compounds are one of the 188 HAPs. They are of concern because they persist in the
environment, and bioaccumulate in food, and are associated with serious health and
environmental effects, including neurological impacts in infants. Coal-fired electric utility plants
are the largest air emission sources of mercury in the U.S. (responsible for approximately
40 percent of 1999 emissions). Resultant mercury concentrations in air are usually low and of
little direct concern. However, when mercury enters surface waters, biological processes
transform it to a highly toxic form that accumulates in fish, which can result in large exposures to
fish consumers (including people). (See following graphic.)
EPA prepared the 1997 Mercury Study as a Report to Congress pursuant to the requirements of
section 112(n)(l)(B) of the CAA to provide an assessment of the magnitude of U.S. mercury
emissions by source, the health and environmental implications of those emissions, and the
availability and cost of control technologies. As the state-of-the-science for mercury is
continuously and rapidly evolving, this Report represents a "snapshot" of our understanding of
mercury. This Report does not quantify the risk from mercury exposure because of scientific
uncertainty in a number of important areas. The Report identifies areas where further research is
needed to provide a quantitative risk assessment. The full Report can be accessed at
http ://www. epa. gov/ttn/atw/112nmerc/mercury.html.
April 2004 Page 2-23
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Mercury Cycling in the Environment
2.5.3 Utility Report to Congress
Section 112(n)(l)(A) of the 1990 CAA Amendments required EPA to conduct a study of the
public health impacts of emissions of air toxics from electric utilities that burn fossil fuel. Utility
emissions include 67 HAPs, including arsenic compounds, nickel compounds, chromium
compounds, radionuclides, and mercury compounds. EPA has presented the results of these
studies in two key documents, a 1998 Report to Congress and a 1999 analysis of emissions
reduction options. The key findings of the report to Congress include:
• Air Toxics Emissions of Concern. The report indicates that, although uncertainties in the
analysis exist, on balance, mercury from coal-fired utilities is the hazardous air pollutant of
greatest potential public health concern. Three other air toxics are identified, for which there
are some potential concerns and uncertainties that may need further study: dioxins, arsenic,
and nickel.
• Risk Assessment of Exposure Pathways Other Than Inhalation. The assessment
determined that exposures due to non-inhalation routes (i.e., dermal, ingestion) are by far the
most important routes of exposure for mercury and dioxins. For arsenic and radionuclides,
both inhalation and ingestion appear to be important exposure routes. However, there are
uncertainties and limitations in the data that indicate a need for further evaluation to more
fully characterize the public health impacts of these pollutant emissions from utilities.
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• Inhalation Exposure Assessment. The modeling assessment suggests that a substantial
fraction of the utility emissions are dispersed well beyond the local area due to the nature of
the emissions (mostly fine particulate substances) and the height of the tall stacks.
Assessment of inhalation exposure for the 67 air toxics emitted by utilities indicate that the
cancer risk from inhalation exposure is estimated to be less than one in a million for the
majority of utility plants, with a few plants perhaps with slightly greater risks. Further
research and evaluation may be needed to more comprehensively assess the inhalation cancer
risks.
• Mercury. The results of the investigation indicate that mercury from coal-fired utilities is
the air pollutant of greatest potential concern to public health from utilities. Coal-fired
utilities are estimated to emit about one-third (52 tons) of U.S. anthropogenic (manmade)
mercury emissions per year. The risk assessment indicates that ingestion of contaminated
fish is the most important route of exposure to mercury. The modeling assessment, in
conjunction with available scientific data, provides evidence for a plausible link between
emissions of mercury from utilities and the methylmercury found in soil, water, air, and fish.
Consequently, mercury emissions from coal-fired utilities may contribute to the potential
exposures to mercury through consumption of contaminated fish. However, there remain
uncertainties about the extent of impacts directly attributable to mercury emissions from
utilities.
• Alternative Control Strategies. There are numerous potential alternative control
technologies and strategies for air toxics control, although the feasibility and effectiveness of
potential control technologies vary.
2.5.4 Residual Risk Report to Congress
The Residual Risk Report to Congress responds to section 112(f)(l) of the Clean Air Act, which
requires EPA to investigate and report to Congress on a variety of topics pertaining to the
assessment of residual risks associated with air toxics emissions from stationary sources
remaining after the implementation of technology based standards per section 112(d) (i.e.,
MACT standards).®
While the main purpose of the Report is to describe the methods and the framework that EPA
will use to make residual risk determinations, the Report also discusses, in general terms, the
available methods of reducing residual risks - including pollution prevention, add-on controls,
and voluntary approaches - and factors relevant to costs of these methods; the current state of
knowledge regarding health effects of air toxics on humans; and EPA's current methods for
collecting and assessing health effects data.
EAs touched on in Section 2.2.3.2, section 112(f) of the CAA requires the Agency to consider the need for
additional standards following regulation under section 112(d) to protect public health and the environment. Section
112(f) of the CAA specifies that such residual risk standards "provide an ample margin of safety to protect public
health." Section 112(f) also requires EPA to determine whether residual risk standards are necessary to prevent "an
adverse environmental effect" taking into consideration "costs, energy, safety, and other relevant factors" in deciding
what level is protective.
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While developed in response to Clean Air Act provisions particular to "residual risk," the report
describes methodologies intended for EPA's use more broadly in assessing risk from toxic air
pollutants. The Report does not specify a particular method for conducting risk assessments,
stressing that EPA has the flexibility to use current techniques along with new methods as they
are developed. The full report is available at http://www.epa.gov/ttncaaal/t3/reports/
risk_rep.pdf.
Specifically, the Residual Risk Report to Congress^ identifies two objectives for residual risk
activities:
• Assess any risks remaining after MACT standard compliance; and
• Set standards for the identified source categories, if additional HAP emission reductions are
necessary to provide an ample margin of safety to protect public health or, taking into
account cost, energy, safety, and other relevant factors, to prevent an adverse environmental
effect.
2.5.5 Integrated Urban Strategy Report to Congress
The Strategy addresses the need to reduce emissions of air toxics in urban areas and looks
collectively at large and small industrial and commercial operations, as well as mobile sources of
pollution. The Strategy also includes plans for improving current understanding of the health
risks posed by toxics in urban areas. This Report to Congress provides the following: a more
detailed examination of the methodologies used for selecting the 33 initial urban air toxics
identified in the Strategy; a summary of recent risk assessments conducted in several urban areas;
and a detailed discussion of research needs to achieve the goals outlined in the Strategy. These
needs were identified in the following areas: exposure assessment, health effects, dose-response
assessment, risk assessment, risk characterization, and risk management. The report is available
at http://www.epa. gov/ttnatwO 1 /urban/natprpt.pdf.
2.5.6 Other Reports
Finally, EPA prepared two other reports that were called for in the Clean Air Act (http://www.
epa.gov/ttn/atw/112npg.html).
First, section 112(n)(5) of the CAA required EPA to assess the public health hazards associated
with emissions of hydrogen sulfide from oil and gas extraction. This report, Hydrogen Sulfide
Air Emissions Associated with the Extraction of Oil and Natural Gas (EPA-453/R-93-045), is
available from the National Technical Information Services (NTIS) as publication number
PB94-131224.
Second, section 112(n)(6) of the CAA required EPA to assess the public health hazards
associated with emissions of hydrofluoric acid in areas that do not have comprehensive health
and safety regulations addressing hydrofluoric acid. The Hydrogen Fluoride Study: Report to
Congress (EPA 550-R-93-001) was published in September 1993 and is available from NTIS as
publication number PB 94-121308.
April 2004 Page 2-26
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References
1. U.S. Environmental Protection Agency. 2004. Technology Transfer Network Air Toxics
Website The Original List of Hazardous Air Pollutants. Updated January 9, 2004. Available
at: http://www.epa.gov/ttn/atw/188polls.html (Last accessed March 2004).
2. U.S. Environmental Protection Agency. 1999. Residual Risk Report to Congress. Office of
Air Quality Planning and Standards, Research Triangle Park, NC. March 1999.
EPA/453/R99/001. Available at http://www.epa.gov/ttnatwOI/risk/risk rep.pdf.
3. U.S. Environmental Protection Agency. 2001. Final Rule to Control Emissions of
Hazardous Air Pollutants from Mobile Sources. Final Rule. Federal Register 66:17230,
March 29, 2001. Available at http://www.epa.gov/otaq/regs/toxics/toxicfrm.pdf.
4. U.S. Environmental Protection Agency. 2000. Technical Support Document: Control of
Emissions of Hazardous Air Pollutants from Motor Vehicles and Motor Vehicle Fuels.
Office of Transportation and Air Quality, December 2000. EPA/420/ROO/023. Available at:
http ://www. epa. gov/otaq/toxics .htm.
5. U.S. Environmental Protection Agency. 2004. Air - Indoor Air Quality (IAQ). Indoor Air
Quality. Updated March 2, 2004. Available at http ://www. epa. gov/iaq/. (Last accessed
March 2004).
6. U.S. Environmental Protection Agency. 2004. Indoor Air. Publications list. Updated
February 17, 2004. Available at:http://www.epa.gov/iaq/pubs/index.html. (Last accessed
March 2004).
7. U.S. Environmental Protection Agency. 2001. Healthy Buildings, Healthy People: A Vision
for the 21st Century. Office of Air and Radiation, Washington, D.C. EPA/402/KO1/003.
Available at http://www.epa.gov/iaq/hbhp/index.html.
8. U.S. Environmental Protection Agency. 1991. Building Air Quality: A Guide for Building
Owners and Facility Managers. Office of Air and Radiation, Washington, D.C.
EPA/402/F91/102. Available at http://www.epa.gov/iaq/largebldgs/baqtoc.html.
9. U.S. Environmental Protection Agency. 2003. Indoor Air Quality Tools for Schools
Communication Guide. Office of Air and Radiation, Washington, D.C. EPA/402/K02/008.
Available at http://www.epa.gov/iaq/schools/images/communication_guide.pdf.
10. National Cancer Institute. 1999. Health Effects of Exposure to Environmental Tobacco
Smoke: The Report of the California Environmental Protection Agency. Smoking and
Tobacco Control Monograph No.10. Bethesda, MD: National Cancer Institute, National
Institutes of Health, U.S. Department of Health and Human Services. NIH Publication No.
99-4645.
11. Johnston PK, Hadwen G, McCarthy J, Girman GR. 2002. A screening-level ranking of toxic
chemicals at levels typically found in indoor air. In: Levin H, ed., Proceedings: Indoor Air
2002, 9th International Conference on Indoor Air Quality and Climate, Monterey, CA, June
30-July 5, 2002. Vol. 4, pp. 930-935.
April 2004 Page 2-27
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12. U.S. Environmental Protection Agency. 2003. Latest Findings on National Air Quality; 2002
Status and Trends. Office of Air Quality Planning and Standards, Research Triangle Park,
North Carolina. EPA 4547 K-03-001. Available at:
http://www.epa.gov/air/airtrends/2002_airtrends_final.pdf
13. U.S. Environmental Protection Agency. 2003. Updated Listing of National Fish and Wildlife
Advisories. Office of Water, Washington, B.C. June 4, 2003. Available at:
http://www.epa.gov/waterscience/fish/.
April 2004 Page 2-28
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Chapter 3 EPA's Risk Assessment Process for Air
Toxics: History and Overview
Table of Contents
3.1 Introduction
3.2 A Short History of the Development of Human Health Risk Assessment and Risk Management
Approaches for Air Toxics [[[ 1
3.2.1 The 1983 National Academy of Sciences Report .............................. 1
3.2.2 The 1994 National Research Council Report ................................. 3
3.2.3 The CRARM [[[ 4
3.2.4 Development of Human Health Risk Assessment at EPA ........................ 6
3.3 Air Toxics Human Health Risk Assessment: Overview of the Process ................... 9
3.3.1 Air Toxics Risk Assessment: What Is the Question? .......................... K)
3.3.2 Air Toxics Risk Assessment: The Process .................................. 12
3.3.2.1 Planning, Scoping, and Problem Formulation ......................... 1_3
3.3.2.2 Analysis Phase ................................................. 14
3.3.2.3 Risk Characterization ............................................ 1_5
3.3.3 Tiered Assessment Approaches ........................................... 16.
3.4 Uncertainty and Variability in Air Toxics Risk Assessment ........................... 1_8
3.4.1 Distinguishing Uncertainty and Variability .................................. \9_
3.4.2 Sources of Uncertainty in Air Toxics Risk Assessment ........................ 20
3.4.3 Sources of Variability in Air Toxics Risk Assessment ......................... 22
3.4.4 Characterizing Uncertainty and Variability .................................. 23_
3.4.5 Tiered Approach to Uncertainty and Variability .............................. 24
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3.1 Introduction
This chapter provides the historical backdrop to the air toxics risk assessment process that is in
use at EPA today. It examines the overall framework of the risk assessment process and how the
various elements of the process relate to one another, including resource and timing
considerations. Subsequent chapters of this reference manual describe each of the specific
elements of the risk assessment process in detail.
3.2 A Short History of the Development of Human Health Risk Assessment and Risk
Management Approaches for Air Toxics
Risk assessment is not new. However, only recently have some attempted to formalize the
process into a coherent framework. This section briefly describes the chronology and important
events in the development of those risk assessment methodologies outlined in this document.
3.2.1 The 1983 National Academy of Sciences Report
In the 1980s, the emerging practice of federal-level risk assessment spurred Congress to
commission a report from the National Research Council (NRC) of the National Academy of
Sciences (NAS) on how the
process was being used. The
result was the landmark 1983
study entitled Risk Assessment in
the Federal Government:
Managing the Process^ The
document is often referred to as
"The Red Book" because of its
distinctive red cover. The Red
Book acknowledged that
regulatory agencies have differing
statutory obligations that require
some flexibility in both the risk
assessment and risk management
processes. The Red Book also
clarified what risk assessment and
risk management are by giving them the definitions that are still commonly used today (see
Exhibit 3-1):
• "We use risk assessment to mean the characterization of the potential adverse health effects
of human exposures to environmental hazards" (p. 18).
• "The Committee uses the term risk management to describe the process of evaluating
alternative regulatory actions and selecting among them" (p. 18).
Purpose of the 1983 NRC Report
Assess the merits of separating the
analytic functions of developing risk
assessments from the regulatory
functions of making policy decisions.
Consider the feasibility of designating
a single organization to do risk
assessments for all regulatory
agencies.
Consider the feasibility of developing
uniform risk assessment guidelines for use by all
regulatory agencies.
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Exhibit 3-1. Risk Assessment and Risk Management Paradigm
RESEARCH
Laboratory and
field observations
Information on
Field measurements
Characterization
of populations
H
ns
ethods
1
Research n
from risk a
1
errts
n
Toxicity assessr
Hazard identif
Dose-response
eeds identified
ssessment process
Exposure asses
Emissions char
RISK ASSESSMENT
>| Risk characterization |
RISK MANAGEMENT
Development of
regulatory options
Evaluation of the public
health, economic, social,
and political consequences
of regulatory options
Regulatory decisions
and actions
Source: Adapted from the 1983 "Red Book"
The Red Book did not recommend "bright
line analysis" because it gives too much
weight to risk numbers that are, by their very
nature, uncertain. The NRC also made two
important recommendations regarding the
risk assessment and risk management
processes used by federal agencies:
• First, the scientific finding and policy
judgments embodied in risk assessments
should be explicitly distinguished from
the political, economic, and technical
considerations that influence the design
and choice of regulatory strategies.
• Second, uniform guidelines should be developed for use by federal regulatory agencies in the
risk assessment process.
The Red Book had a significant impact on risk assessment and management processes
throughout the federal government, and it continues to be an influential reference at EPA. For
example, in response to its recommendations, EPA established the Risk Assessment Council
(RAC) and began publishing Agency-wide risk assessment guidelines (see Section 3.1.4 below).
(Note that the recommendation to develop uniform risk assessment guidelines for use by all
regulatory agencies did not happen - each agency is still free to develop their own approaches
and guidelines.)
Bright Line Analysis
"Bright line analysis" is the process of
comparing a risk assessment result (the estimated
numerical value of risk) to a preestablished
acceptable level of risk (the "bright line") and
making risk management decisions solely on
whether the estimated risk is above or below the
acceptable level. The NRC emphasized that risk
assessment results are only one component of the
risk management decision process and that
assessment results should not be the only
information risk managers consider.
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3.2.2 The 1994 National Research Council Report
Recognizing the growing
importance of quantitative risk
assessment in the regulatory
process, Congress in section
112(o) of the Clean Air Act
(CAA) amendments required EPA
to enter into a contract with the
NRC to evaluate the risk
assessment methods EPA was
using at the time. The NRC's
1994 report, Science and
Judgment in Risk Assessment,^
was prepared by the NRC's
Committee on Risk Assessment of
Hazardous Air Pollutants in the
Board on Environmental Studies
and Toxicology. In a sense, the
"Blue Book" was a follow-up to the
scientific methods.
Purpose of the 1994 NRC Report
Congress asked the NRC to answer the
following questions:
IENCE
and
UDGMENT
Given that quantitative risk assessment is
essential for EPA's implementation of
the CAA, is EPA conducting risk
assessments in the best possible manner?
Has EPA developed mechanisms for
keeping its risk assessment procedures
current in the face of new developments in science?
Are adequate risk-related data being collected to permit
EPA to carry out its mandates?
What, if anything, should be done to improve EPA's
development and use of risk assessments?
1983 Red Book, but with a specific emphasis on EPA's
The NRC committee observed that several themes were common to all elements of the risk
assessment process and noted that these themes were usually the focal points for criticisms of
individual risk assessments:
• The use of default assumptions;
• Available data;
• Uncertainty and variability;
• Assessment of multiple chemical exposures, multiple routes of exposure, the potential for
multiple adverse effects; and
• Steps taken to validate the methodologies used throughout the risk assessment process.
In the Blue Book, the NRC updated the risk assessment/risk management paradigm and
presented several recommendations for increasing the effectiveness and accuracy of EPA's risk
assessment and risk management process, particularly as it pertained to air toxics:
• EPA should generally retain its conservative, default-based approach to risk assessment for
screening analysis in standard-setting.
• EPA should use iterative approaches that incorporate improvements in both the models and
data used in each successive iteration of analysis. For example, EPA should start with
relatively inexpensive screening techniques and move to a more resource-intensive level of
data-gathering, model construction, and model application as the particular situation
warrants. This method avoids costly case-by-case evaluations of individual chemicals at
every facility in every source category.
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• EPA should explicitly identify each use of a default option in a risk assessment, should
clearly state the scientific and policy basis for each default option, and should consider
attempting to give greater formality to its criteria for departure from default options.
• EPA should establish regulatory priorities based on initial assessments of each chemical's
possible impact on human health and welfare.
• EPA should present not only point estimates of risk, but also the sources and magnitudes of
uncertainty associated with these estimates.
EPA has progressively worked to adopt the report's recommendations as it transitions the
Agency into the risk-based phase of the CAA legislative strategy for HAPs.
3.2.3 The CRARM
Purpose of the 1997 White Book
Investigate "the policy implications
and appropriate uses of risk
assessment and risk management in
regulatory programs under various
Federal laws to prevent cancer and
other chronic health effects which
may result from exposure to
hazardous substances."
Section 303 of the 1990 CAA
Amendments mandated the
formation of a Presidential
Commission on Risk Assessment
and Risk Management (CRARM)
in response to unresolved
questions about EPA's approach
to assessing public health risks
remaining after implementation of
the maximum achievable control
technology (MACT) program (i.e.,
technology based control).
CRARM released its report, Risk
Assessment and Risk Management in Regulatory Decision-Making, or the White Book, in two
volumes in 1997. Volume I focuses on the framework for environmental health risk
management. Volume n addresses a variety of technical issues related to risk assessment and
risk management, including a common metric for assessment of cancer and other effects,
management of residual risks from air toxics, comparative risk, decision criteria, uncertainty
analysis, and recommendations to specific agencies.(3)
The CRARM developed a risk management framework that fosters an integrated approach to
addressing complex, real-world issues that affect multiple environmental media and involve
exposures to mixtures of chemicals (Exhibit 3-2). Note that risk assessment (here "risk") is one
of several steps in risk management. The framework aims to encourage integrated approaches to
environmental risk management.
April 2004
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Exhibit 3-2. The CRARM Framework for Risk Management
The central element of the framework is encouraging stakeholder participation throughout the six
stages of risk management. In addition, the framework intends to be iterative - if appropriate,
risk assessors can redefine and reassess the risk problem as they develop new data. Another key
principle of the framework is that risk management should explicitly consider the
comprehensive, real-world context of a risk problem and not limit the context to one that
considers only one type of risk associated with a single chemical in a single environmental
medium. The CRARM made several additional recommendations:
• Conduct Comparative Risk Assessment. Federal agencies should try a comparative risk
analysis approach on an experimental or demonstration basis to seek consensus on priorities
for managing environmental risks. The results of such efforts should influence agency
resource allocation.
• Harmonize Cancer and Non-Cancer Methodologies. Assessment techniques for
carcinogens and non-carcinogens should be harmonized. This would aid in risk
communication, risk management decisions, and comparative risk assessment.
• Devise Realistic Exposure Scenarios. Risk management decisions should be based on
realistic exposure scenarios, rather than on the hypothetical maximum exposed individual
(MEI). Distributions of the varied exposures within a population should be evaluated with
April 2004
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explicit attention to specific segments of the population (e.g., individuals with unusually high
exposures, infants, children, pregnant women, low-income groups, and minority communities
with exposures influenced by social or cultural practices).
• Place Cost-Benefit Analysis in its Appropriate Context. Economic analysis is a relevant
consideration in risk management decisions, but should not be the overriding factor in a
decision. Explicit descriptions of assumptions, data sources, sources of uncertainty, and costs
across society should be presented in parallel with descriptions associated with risk
assessments.
• Ensure Interagency Consistency. Agencies should coordinate their risk assessment
methods and assumptions unless there is a specific statutory requirement that allows for
different choices. Scientific disagreements should be explained.
• Conduct Tiered Residual Risk Assessments. EPA should implement a tiered approach to
managing residual risks after implementation of the CAA's technology-based (MACT)
standards.
Similar to the recommendations outlined in the Blue Book, EPA has continued to modify its risk
assessment guidelines and approaches in response to these recommendations. Other documents,
such as the National Research Council's 1996 document entitled Understanding Risk:
Information Decisions in a Democratic Society,^ also play a role in informing the continued
development of the risk assessment and risk management process.(a)
3.2.4 Development of Human Health Risk Assessment at EPA
EPA has conducted human health risk
assessments since its inception in 1970. EPA
built on this early experience while
confronting potential hazards associated with
pesticide use. For example, after considering
available human and non-human toxicity data,
EPA restricted domestic use of DDT and other
pesticides, in part due to their cancer risks.
EPA acknowledged that such risk-based
regulations needed an appropriate scientific
basis and began collecting cancer toxicity
information on pesticides through
administrative hearings and testimony.
Summary documents from these hearings became known as the "Cancer Principles." Criticism
of these documents, which many inadvertently perceived to be formal Agency cancer risk
assessment policy, led the Agency to develop interim guidelines in 1976. Three years later, the
Fundamental References for
Air Toxics Risk Assessment
(1) Air Toxics Risk Assessment Reference
Library, three volumes
(2) The NAS Red and Blue Books
(3) CRARM White Book
(4) EPA Guidelines for Risk Assessment Series
(Full citations are at the end of this chapter.)
8l Understanding Risk "...illustrates that making risks understandable to the public involves more than
translating scientific knowledge. The volume also draws conclusions about what society should expect from risk
characterization and offers guidelines and principles for informing the wide variety of risk decisions that face our
increasingly technological society." (See http://books.nap.edu/catalog/5138.html.)
April 2004
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Interagency Regulatory Liaison Group (a conglomeration of several federal agencies, including
EPA) published additional cancer risk assessment guidelines. Concurrently, EPA used cancer
risk assessment techniques in its toxic chemicals regulation under the 1976 Toxic Substances
Control Act. By the end of EPA's first decade in existence, the Agency used risk assessment
techniques to develop water quality criteria protective of human health.
Throughout the 1980s, EPA increasingly utilized risk assessment to evaluate the potential for
chemicals to cause non-cancer health effects in addition to cancer risks. During the 1980s, the
Agency used cancer risk assessment techniques in the development of national emission
standards for air toxics such as vinyl chloride and benzene.
As EPA increased its use of risk assessment throughout the 1980s, the Agency's inconsistent
approach to risk assessment became apparent, largely due to a lack of standard guidance on the
topic. To correct this problem, the Agency undertook administrative reforms and published
several key guidelines and other policy documents.
First, the Agency published Risk Assessment and Management: Framework for Decision
Making.^ EPA intended this reference manual to conform EPA practices with NRC Red Book
recommendations and to help the Agency make better and more rapid decisions about
environmental toxic chemical problems.
Next, in 1986, EPA established the Risk
Assessment Council (RAC) to oversee
virtually all aspects of the Agency's risk
assessment process. EPA appointed
Senior Agency officials with experience
and responsibilities in the area of science
policy and risk assessment to the RAC.
This group established EPA's
fundamental policies for conducting risk
assessments and evaluating risk
information. These officials also oversaw
the activities of the Risk Assessment
Forum.
Subsequently, EPA began publishing an
influential series of Agency-wide
guidelines in the Federal Register
identifying the recommended methods for
assessing human health risks from
environmental pollution. EPA did not
intend for these guidelines, which cover
both cancer risks and non-cancer hazards,
to be static, and the Agency has revised the guidelines as new information and methods become
available (for example, EPA began a process in 1996 to revise and update its guidelines for
carcinogenicity).
EPA Risk Assessment Forum
The Risk Assessment Forum is a standing committee
of senior EPA scientists established to promote
Agency-wide consensus on difficult and
controversial risk assessment issues and to ensure
that this consensus is incorporated into appropriate
Agency risk assessment guidance. To fulfill this
purpose, the Forum assembles Agency risk
assessment experts in a formal process to study and
report on issues from an Agency-wide scientific
perspective. Major Forum guidance documents are
developed in accordance with the Agency's
regulatory and policy development process and
become Agency policy upon approval by the
Administrator or the Deputy Administrator. Risk
Assessment Forum products include: risk assessment
guidelines, technical panel reports on special risk
assessment issues, and peer consultation and peer
review workshops addressing controversial risk
assessment topics
(http ://cfpub. epa. gov/ncea/raf/index. cfin).
April 2004
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EPA established the Science Policy Council (SPC) in 1993 with a broader mission and as a
replacement for the RAC; specifically, the SPC aims to integrate policies that guide Agency
decision-makers in their use of scientific and technical information. To accomplish this goal, the
SPC works to implement and ensure the success of selected initiatives that external advisory
bodies (such as the National Research Council and the Science Advisory Board, as well as others
such as the Congress, industry and environmental groups, and Agency staff), recommend. In this
way, the SPC provides guidance for selected EPA regulatory and enforcement policies and
decisions. The 1995 Guidance for Risk Characterization was an important part of the SPC's risk
characterization program. Standing groups such as the Risk Assessment Forum, a Steering
Committee, and interim working groups continue to support the SPC. For more information on
the SPC, see http://www.epa.gov/osp/spc/2about.htm.
S \
EPA Human Health Risk Assessment Guidelines"
Carcinogenicity
• 1999 Draft Revised Guidelines for Carcinogen Risk Assessment15
• 1986 Guidelines for Carcinogen Risk Assessment
Chemical mixtures
• 2000 Supplementary Guidance for Conducting Health Risk Assessment of Chemical Mixtures
• 1986 Guidelines for the Health Risk Assessment of Chemical Mixtures
Developmental toxicity
• 1991 Guidelines for Developmental Toxicity Risk Assessment
Exposure assessment
• 1992 Guidelines for Exposure Assessment
Mutagenicity
• 1986 Guidelines for Mutagenicity Risk Assessment
Neurotoxicity
• 1998 Guidelines for Neurotoxicity Risk Assessment
Probabilistic analysis
• 1997 Guiding Principles for Monte Carlo Analysis
Reproductive toxicity
• 1996 Guidelines for Reproductive Toxicity Risk Assessment
Risk characterization
• 2000 Handbook for Risk Characterization
• 1997 Guidance on Cumulative Risk Assessment. Part 1, Planning and Scoping
• 1995 Guidance for Risk Characterization
(a) A current list is available at http://cfpub.epa.gov/ncea/raf/recordisplay.cfm?deid=55907.
(b) These guidelines are interim final drafts. Check above website for a final version.
X /
Another important group within EPA with a risk assessment focus is the National Center for
Environmental Assessment (NCEA). NCEA is a major component of the EPA's Office of
Research and Development and acts as EPA's national resource center for human health and
ecological risk assessment. NCEA conducts risk assessments, carries out research to improve the
state-of-the-science of risk assessment, and provides guidance and support to risk assessors.
Many of the critical Agency documents on risk assessment science and policy, as well as risk
related databases such as the Integrated Risk Information System (IRIS), can be accessed through
the NCEA website (www.epa.gov/ncea).
April 2004 Page 3 -I
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EPA's use and development of human health risk
assessment continued to grow through the 1980s
and 1990s with establishment of the IRIS toxicity
database, the Agency's repository of chemical-
specific toxicity data. IRIS is a critical resource
for risk assessors because the database contains
toxicity information that reflects a consensus
among EPA program offices about a chemical's
toxic properties.
EPA's Office of Solid Waste and Emergency
Response's Superfund Program also has
developed a series of very detailed guidance
documents to help risk assessors understand the
actual nuts-and-bolts of performing human and
ecological risk assessments under the Superfund
program. These "how to" documents are called
the Risk Assessment Guidance for Superfund
series, or the RAGS series for short. RAGS
provides in-depth discussions and guidance for
risk assessors to use in their day-to-day work and
is an important reference for those working in the
field of risk assessment.(b) A full set of RAGS documents is available online.(6)
Risk Assessor. The individual or team of
individuals who organizes and analyzes air
toxics data, develops exposure and risk
calculations, and prepares the human health
risk assessment reports. Risk assessors for
air toxics can be industry, EPA, an S/L/T air
agency, or contractor personnel. The larger
risk assessment team will often be made up
of people with a variety of expertise,
including health scientists, monitoring or
modeling personnel, and laboratory analysts.
Risk Manager. The individual or group of
individuals who serve as the primary decision
maker(s) for an area subject to the risk
analysis process. The risk managers may
base their decisions about the need for risk
reduction on a variety of data, including the
results of the risk assessment, economic
considerations, technical feasibility of risk
reduction options, community acceptance,
and a number of other factors.
3.3 Air Toxics Human Health Risk Assessment: Overview of the Process
The reports and guidance documents discussed above tend to distill the risk assessment process
down to the following five questions:
• Who is exposed to environmental pollutants?
• What pollutants are they exposed to?
• How are they exposed?
• How toxic are the chemicals they are exposed to?
• What is the likelihood that harm will occur because of the exposures?
The role of the risk assessor is to answer these questions. The main product of the risk
assessment is a set of qualitative and quantitative statements about the likelihood that people will
experience adverse health outcomes because of the exposures. The statements also should
discuss how certain the assessor is about these statements. Risk managers then use the risk
assessment results and other relevant information (including the cost or technical feasibility of
resolving a problem) to decide what (if anything) should be done to reduce risk.
Although the information provided in RAGS is primarily geared towards Superfund sites, some of these
procedures are generally relevant and compatible to risk assessments developed by other Program Offices, including
the Office of Air and Radiation. As such, the information provided in RAGS was taken into consideration in the
development of this reference library.
April 2004
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The following sections briefly describe the overall risk assessment process for releases of air
toxics to the ambient air. Subsequent chapters of this reference manual revisit each of these
subjects in detail and provide contacts and references for more information.
3.3.1 Air Toxics Risk Assessment: What Is the Question?
The overall purpose of a human health air toxics risk assessment is to attempt to understand
public health risks potentially associated with exposures to particular pollutants emitted into the
air from sources of interest. Exhibit 3-3 presents a simple illustration of the overall real-world
process that is investigated through the use of risk assessment.
As Exhibit 3-3 illustrates, air toxics risk assessments usually focuses, at a minimum, on the
inhalation of contaminated air. However, for a small subset of air toxics (discussed in
Chapter 4), the risk assessment also may need to address ingestion of or dermal contact with
soils, water, or food that have become contaminated with chemicals that have deposited out of
the air. (Dermal exposures are included here for completeness, but usually they are less of a risk
factor for air toxics than ingestion or inhalation exposures.)
The following simple mathematical formula describes the basis for human health risk
assessment. Specifically, the likelihood that injury or disease may occur from exposure to air
toxics can be described as a function of two separate, but related, things - an estimate of
exposure to a chemical and an estimate of the toxic properties of the chemical:
Potential for Injury or Disease (i.e., the "Risk")
= / (metric of exposure, metric of toxicity)(c) (Equation 3-1)
Two key principles emerge from this formula and Exhibit 3-3:
• There is no risk if there is no exposure. If a person has no chance of coming in contact
with an air toxic, the risk posed to that person is zero.
• The level of risk associated with an exposure depends on the toxic properties of the
chemical. These properties determine whether the exposure is of great or little concern.
Some chemicals can cause severe health effects (even death) when a person receives
exposure even to extremely small quantities at a single point in time. Conversely, other
chemicals cause essentially no effect even after repeated exposure to high levels over long
periods of time.
The general Equation 3-1 is important to understand and keep in mind since the exact equations
used to develop risk estimates are derived from it. In other words, the risk equations that will be
detailed in later chapters all include both a estimate of exposure and an estimate of toxicity.
The symbol "/' means "is a function of
April 2004 Page 3-10
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Exhibit 3-3. Generic Conceptual Model of How Air Toxics Releases May Result in Injury or Disease
TAB GET ^- 0,;nHs *
OfiCAH/TISSUE " / \ ^,
^- - ,<&ta CL|M "
T ', \J *
a 9!R1H OtftCTf
I
INTAKE/UPTAKE
Starting at the upper left hand side of this diagram, air toxics are released from one or more sources (e.g.,
factories, cars/trucks, small businesses, forest fires) to the air and begin to disperse by the wind away from the
point of release. Once released, the chemical may remain airborne; convert into a different substance; and/or
deposit out of the air onto soils, water, or plants. People may be exposed to air toxics by breathing
contaminated air (inhalation) or through ingestion of chemicals that can accumulate in soils, sediments, and
foods (the latter process is called bioaccumulation). People also can be exposed to deposited chemicals via
skin (dermal) contact, however, this tends to be a less important risk factor than ingestion or inhalation.
Inhalation, ingestion, and dermal absorption are called the routes of exposure.
This description of what happens to an air toxic once it is released into the air is called fate and transport
analysis. "Transport" evaluates how an air toxic physically moves (i.e., is transported) through the
environment. "Fate" describes what ultimately happens to the chemical after it is released to the air (i.e., what
is the "fate" of the chemical in the environment). The results of a fate and transport analysis is an estimate of
the concentration of the air toxic in the air, soil, water, and/or food at the point where it is contacted by a
person. The exposure assessment is the process of evaluating how human contact with the contaminated
media occurs.
In the case of an air pathway analysis, the metric representing the inhalation exposure is called the exposure
concentration (EC). For example, if benzene is released from a factory and blows into a nearby neighborhood
where people breath it, the EC is the concentration of benzene in the air that they breath.
Once an exposure occurs, the air toxics can enter the body and exert an effect at the point of entry (the "portal
of entry") or move via the bloodstream to other target organs or tissues. The action of a pollutant on a target
organ can result in a variety of harmful effects, including cancer, respiratory effects, birth defects, and
reproductive and neurological disorders. An overall risk assessment process evaluates what people are
exposed to, how the exposure occurs, and, when combined with information about the toxic properties of the
chemicals in question, estimates the likelihood that the exposure will result in injury or disease.
April 2004
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Air toxics risk assessments commonly look at two types of exposures and their associated toxic
outcomes:
• Repeated or extended exposure to relatively low concentrations of air toxics over long
periods of time (chronic exposures) that may result in chronic health effects (e.g., diseases
like cancer or recurring respiratory ailments); and
• Infrequent exposure to relatively high concentrations of air toxics over short periods of time
(acute exposures) that may result in the expression of either near term acute health effects
(which can range from mild effects, such as reversible eye irritation, to extreme effects, such
as loss of consciousness or sudden death), or long term effects (chronic effects).
3.3.2 Air Toxics Risk Assessment: The Process
The illustration and narrative overview in the previous section (Exhibit 3-3) describes what may
happen when toxic chemicals are released to the air and how those releases can result in adverse
health outcomes in people. This picture and narrative description comprise a conceptual model
of how releases of air toxics may pose risks to people. It is a conceptual model because it
provides a picture (or "model") of our "concept" of what may happen in the real world when
toxic chemicals are released to the air. The conceptual model provides a starting point for
estimating risks posed by those releases. However, in addition to a conceptual model (in this
case, a simple picture), there is a need for a defined process to quantify relationships among the
conceptual model components in order to generate numeric risk estimates. Exhibit 3-4 outlines
the major steps in the process that EPA uses to perform a risk assessment:
• Planning, scoping, and problem formulation;
• Analysis, which includes exposure assessment and toxicity assessment; and
• Risk characterization.
With the addition of an explicit planning and scoping step (which should always be done for any
systematic investigation), Exhibit 3-4 encompasses the same features as espoused by the National
Academies in the Red and Blue books described previously. The National Academies' process
has been redrawn in Exhibit 3-4 to better clarify how the risk assessment is actually done in the
air toxics arena.
It is useful to think of this figure as a "roadmap" to how air toxics risk assessments are
performed. The roadmap breaks air toxics risk assessment down into four manageable elements,
each of which are described briefly below and in detail in subsequent chapters. Note, however,
that all of these steps are inter-related and usually require refinement throughout the risk
assessment process. A helpful starting place is to think of these as "separate steps."
April 2004 Page 3-12
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Exhibit 3-4. The General Air Toxics Risk Assessment Process
Planning and Scoping
Problem Formulation
a.
in
1
re
ill
ft c
,2 o
« 2
-
1 Exposure Assessment 1
Who is exposed?
How does exposure occur?
What chemicals are they exposed to?
What concentrations are they exposed to?
1 Toxicity Assessment
Is a chemical
toxic?
What is the
relationship
between the
exposure to a
chemical and
the response
that results?
l^^^l
1 !
- \ \rr v : : .,
"^ | Risk Characterization | "*"'"
What is the likelihood that the exposure will result in
an adverse health effect?
How sure are we regarding our answers?
3.3.2.1 Planning, Scoping, and Problem Formulation
Any human health risk assessment should begin with planning and scoping. Properly planning
and scoping the risk assessment at the beginning of the project is critical to the success of the
overall effort. Good planning and scoping clearly articulates the assessment questions; states the
quantity and quality of data needed to answer those questions; provides in-depth discussion of
how assessors will do the analysis; outlines timing and resource considerations, as well as
product and documentation requirements; and identifies who will participate in the overall
process from start to finish and what their roles will be. Poor planning and scoping will almost
certainly lead to an assessment that does not answer the correct questions, does not provide a
supportable basis for risk management decision-making, and wastes significant amounts of time,
resources, and good will. The planning and scoping process needs to recognize, to the extent
possible, important data gaps and uncertainties and the measures needed to address these
problems. Where the extent of data gaps and their potential impacts on the risk assessment are
not fully understood, the planning process may be iterative, with decision points specified during
the analytical phase (see below) that are contingent on the results of data gathering efforts or
sensitivity/uncertainty analyses.
April 2004
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During problem formulation, the planning and scoping team generally makes initial decisions
about the scope of the risk assessment (e.g., size of the study area, what emission sources and
chemicals are to be considered); the appropriate level of detail and documentation; trade-offs
between depth and breadth in the analysis; quality assurance and quality control requirements;
analytical approaches to be used (modeling vs. monitoring); and the staff and monetary resources
to commit. Problem formulation results in two important products: the conceptual model and
the analysis plan.
• The study-specific conceptual model is similar to the generic conceptual model (Exhibit
3-3); however, for an actual assessment the conceptual model explicitly identifies the
physical boundaries of the study area; the potential emission sources and air toxics they are
emitting that the risk assessment will consider; the location and composition of potentially
exposed populations; the fate/transport mechanisms by which those populations may be
exposed; the routes of exposures that may be occurring; and the expected health outcomes to
be evaluated. The study-specific conceptual model is developed as both a picture and a
written description of how air toxics emissions may be affecting the study area. As the
assessment moves forward, the assessment team members will use the model as a guide, but
they also routinely refine the model as they learn more about the study area. For example, the
initial study-specific conceptual model may include a deposition element. If subsequent
modeling or monitoring suggests this fate and transport mechanism is unimportant, the
assessors will revise the conceptual model.
• The analysis plan will guide the remainder of the assessment. It lays out in detail how the
elements of the conceptual model are going to be studied. In developing the analysis plan, it
is important to include provisions for tiered or iterative analyses, as discussed in Sections
3.2.3 and 3.3.5.
3.3.2.2 Analysis Phase
The analysis phase is the process in which analysts apply risk assessment approaches to evaluate
the problem at hand. It consists of two main components: exposure assessment and toxicity
assessment.
An exposure assessment is conducted to characterize the potentially exposed population, the
chemicals of potential concern, identify
exposure pathways and routes of exposure,
and estimate the exposure. This includes
estimating or measuring concentrations of
air toxics in the environment and evaluating
how nearby populations interact with the
contaminated media.
In the exposure assessment, the risk
assessment team will refine the initial
conceptual model by providing detailed
information about the study area (e.g.,
physical description, meteorology, source
locations and detailed characteristics,
population demographics and locations, the
What is "Study-Specific?"
Air toxics risk assessments can be designed to
evaluate a wide range of air toxics release
scenarios. For example, a risk assessment might
look at the impact of one emission point at a
factory on a nearby population or it might look at
the combined impact of hundreds of sources on a
large urban area.
This reference manual uses the term "study-
specific" to mean the specific geographic area and
populations under study, along with the emission
sources included in the scope of the study.
April 2004
Page 3-14
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exposure pathways under study). The exposure assessment also is the analytic step in which the
magnitude, frequency, and duration of human exposures are quantified. For example, one of the
main outcomes of an air toxics exposure assessment is an estimate of the concentration of air
toxics in the air at the point where human contact occurs (the EC). Assessors usually estimate
this value with either a computer program (a model) or by physically taking samples of air and
measuring air toxics concentrations in a laboratory (a monitor). When there are concerns about
exposure pathways other than inhalation, assessors may use different models or monitoring
strategies to estimate or measure concentrations of air toxics in soil, water, or foods.
The toxicity assessment component of the risk assessment process considers: (1) the types of
adverse health effects associated with exposure to the chemicals in question, and (2) the
relationship between the amount of exposure and resulting response. Toxicity assessment for air
toxics generally consists of two steps:
• Hazard identification is the process of determining whether exposure to a chemical can
cause an adverse health effect (e.g., cancer, birth defect, etc.), as well as the nature and
strength of the evidence of causation and circumstances in which these effects occur (e.g.,
inhalation/ingestion, repeated exposure over a long period/single exposure over a short
period, etc,).
• Dose-response assessment is the process of quantitatively characterizing the relationship
between the dose of the contaminant and the incidence of adverse health effects in the
exposed population. As information on dose at the site in the body where the response
occurs is rarely available, various factors and models are used to predict the dose metric from
estimates of exposure (the inhalation exposure concentration or oral intake). From this
quantitative dose-response relationship, toxicity values are derived for use in risk
characterization.(d) Most toxicity assessments are based on studies in which toxicologists
expose animals to chemicals in a laboratory and extrapolate the results to humans. For some
chemicals, information from actual human exposures is available (usually from workplace
exposure studies).
Although air toxics risk assessors need to understand the underlying scientific basis and
uncertainties associated with toxicity values, they will usually rely on toxicity values already
developed and available in the literature. A list of default screening level toxicity values that
EPA recommends for the 188 HAPs is in Appendix C. The most up-to-date list is at
http ://www. epa. gov/ttn/atw/toxsource/summary.html.
3.3.2.3 Risk Characterization
The risk characterization summarizes and combines outputs of the exposure and toxicity
assessments to characterize risk, both in quantitative (numerical) expressions and qualitative
(descriptive) statements. Chemical-specific exposure-response information is mathematically
combined with modeled or monitored contaminant levels and other information regarding how
exposure occurs to give numbers that represent the likelihood that the exposure may cause an
Toxicity values are numerical expressions of the relationship between a given level of exposure to an air
toxic and adverse health impacts. The two most common toxicity values for inhalation exposures are the upper-
bound inhalation unit risk estimates (lURs) for cancer effects and reference concentrations (RfCs) for non-cancer
effects (which include uncertainty factors). Chapter 12 provides a more detailed discussion of toxicity values.
April 2004 Page 3-15
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adverse health outcome. Per the Agency's Policy for Risk Characterization^ this likelihood is
evaluated both with regard to a "central tendency" of exposure estimates and "high end"
estimates. The risk characterization also includes a thorough uncertainty analysis for each step
of the entire risk assessment process in order to provide the risk manager with an understanding
of which elements of the assessment are most uncertain, the magnitude and direction of the effect
(higher or lower) that the various uncertainties have on the risk estimates and in some cases, a
quantitative analysis of uncertainty. Often the uncertainty analysis is a narrative that reflects the
assessor's best professional judgment. Other analyses, however, may require a more quantitative
approach to evaluating uncertainty.
The product of the risk assessment is a written report that provides all of the analyses performed
to assess exposure, identify toxicity values, characterize risk, and assess and present uncertainty.
It is critical that the risk assessment only provide the factual basis of why the assessment was
done, how it was done, what the answers are, and the uncertainties associated with those answers.
That is not to say that the risk assessment should not provide an analysis of differing scientific
opinions on any number of the elements of the risk assessment. It does, however, preclude the
assessment from discussing items more appropriately considered under risk management (e.g.,
cost or technical feasibility of mitigation alternatives). The presentation also must be clear and
provide enough details so future readers will find the overall assessment process, including
critical assumptions, to be fully transparent.
3.3.3 Tiered Assessment Approaches
Various EPA guidance documents and the Air Program's Residual Risk Report to Congress have
recommended tiered approaches to risk assessments/8' A tiered approach is a process for a
systematic, informed progression from a relatively simple to a more complex risk assessment
approach. Essentially, the approach begins with an analysis that includes few study-specific data
and many conservative assumptions. This process generally results in a very conservative answer
(and is likely to be fairly uncertain), but may demonstrate, with relatively little effort, that the
sources being assessed pose insignificant risk. If such an approach indicates that the risk appears
to be relatively high, assessors pursue a higher tier of analysis to determine if the risk is a realistic
concern or an artifact of the lower tier's conservative assumptions. The higher level of analysis
reflects increasing complexity and, in many cases, will require more time and resources. Higher
tiers also reflect increasing characterization of variability and/or uncertainty in the risk estimate,
which may be important for making risk management decisions.
Exhibit 3-5 illustrates a generalized representation of the tiered risk assessment concept. Central
to the concept of the tiered approach is an iterative process of evaluation, deliberation, data
collection, work planning, and communication aimed at deciding:
• Whether or not the risk assessment, in its current state, is sufficient to support the risk
management decision(s); and
• If the assessment is determined to be insufficient, whether or not progression to a higher tier
of complexity (or refinement of the current tier) would provide a sufficient benefit to warrant
the additional effort.
April 2004 Page 3-16
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Exhibit 3-5. Generalized Representation of the Tiered Risk Assessment Concept
E 53
QJ !H
o m
Z5 >i
O ±=!
tn —
QJ -D
o: .ss
o :=
O ™
Tier 3: High Complexity
Complex exposure assessment
Detailed site-specific modeling
High cost
Decision-making cycle: Evaluating the
adequacy of the risk assessment and the
value of additional complexity/lev el of effort
Tier 2: Moderate Complexity
Exposure = residential air levels
More detailed modeling
Moderate cost
QJ
Decision-making cycle: Evaluating the
adequacy of the risk assessment and the
value of additional complexity/lev el of effort
ro
-
E O
Tier 1: Screening Level
Exposure = max off site levels
Simple modeling
Low cost
The deliberation cycle also provides an opportunity to evaluate the direction and goals of the
assessment as new information becomes available. It may include evaluations of both scientific
and policy information.
This representation, which provides an example of a tiered assessment process consistent with
that described in the Residual Risk Report to Congress,(S) depicts three tiers of analysis. Each
successive tier represents more complete characterization of variability and/or uncertainty as well
as a corresponding increase in complexity and resource requirements.
• Tier 1 is represented as a relatively simple, screening-level analysis using conservative
exposure assumptions (e.g., receptors are located in the area with the highest estimated
concentrations) and relatively simple modeling (e.g., a model that requires few inputs, most
of which can be "generic," yet conservative).
• Tier 2 is represented as an intermediate-level analysis using more realistic exposure
assumptions (e.g., use of actual receptor locations) and more detailed modeling (e.g., a model
that requires additional site-specific inputs).
• Tier 3 is represented as an advanced analysis using probabilistic techniques such as Monte
Carlo analysis (see Part VII of this reference manual for a discussion of these techniques) and
more detailed and/or intensive modeling.
April 2004
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This representation does not imply that there is a clear distinction between Tiers 1, 2, and 3. For
example, a series of refinements in a Tier 1 analysis might be indistinguishable from a Tier 2
analysis, or a Tier 2 analysis could incorporate probabilistic techniques.
This representation also notes the decision-making cycle that occurs between each tier. In this
cycle, the existing risk assessment results are evaluated to determine whether they are sufficient
for the risk management decision, and if not, what refinements to the risk assessment are needed
(including moving up to the next tier).
While the tiered risk assessment concept usually contains three tiers of complexity (as in Exhibit
3-5), these three tiers are best thought of as points along a spectrum of increasing complexity and
detail in the risk assessment. The important focus is the specific ways in which a given risk
assessment is refined in successive iterations, rather than whether or not it would be considered
Tier 1, 2, or 3.
3.4 Uncertainty and Variability in Air Toxics Risk Assessment
Risk assessment is based on a series of questions that the assessor asks about available scientific
information that is relevant to human health and/or ecological risk. Each question calls for
analysis and interpretation of the studies, selection of the concepts and data that are most
scientifically reliable and most relevant to the problem at hand, and conclusions regarding the
question presented. For example, in the exposure assessment, through the use of modeling
and/or monitoring, the risk assessor asks what is known about the principal environmental fate
and transport of contaminants and the patterns and magnitudes of human or ecosystem
exposures. The toxicity assessment asks what is known about the ability of an air toxic to cause
cancer or other adverse health effects in humans, laboratory animals, or wildlife species and what
is known about the biological mechanisms and dose-response relationships underlying any
effects observed in the laboratory or in epidemiology studies. The risk characterization integrates
information from the preceding components of the risk assessment and synthesizes an overall
conclusion about estimated risk that is complete, informative, and useful for risk managers/7'
Air toxics risk assessments make use of many different kinds of scientific concepts and data
(e.g., exposure, toxicity, epidemiology, ecology), all of which are used to characterize the
estimated risk in a particular environmental context. Informed use of scientific information from
many different sources is a central feature of the risk assessment process. Highly accurate
information is often not available for many aspects of a risk assessment. However, since
scientific uncertainty is inherent in the risk assessment process, and risk managers often must
make decisions using assessments that are not as definitive in all important areas as would be
desirable, it is important that the most current and complete information that is available be used
to support decision making. Risk assessors and decision makers must understand that it may be
necessary to revise risk estimates and to alter decisions in light of new information.
Risk assessments also incorporate a variety of professional judgements (e.g., which models to
use, where to locate monitors, which toxicity studies to use as the basis of developing dose-
response values). Risk managers therefore need to understand the strengths and the limitations of
each assessment and to communicate this information to all participants and the public.
April 2004 Page 3-18
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This section provides an overview of uncertainty and variability, two critically important
characteristics of risk assessment that need to be understood and described at some level in every
air toxics risk assessment. It describes several sources of uncertainty and variability in air toxics
risk assessments, discusses approaches for describing and analyzing uncertainty and variability,
and describes how uncertainty and variability are often addressed at different tiers of the risk
assessment process.
A full discussion of this subject, including quantitative techniques for uncertainty analysis, is
beyond the scope of this reference manual. Risk assessment is an evolving discipline, and
improvements in scientific understanding and techniques will continue to provide new avenues
and insights into uncertainty and variability analysis. Because this manual is intended as an
introduction to risk assessment approaches and tools, our discussion focuses on relatively
simplistic, deterministic risk assessment techniques (i.e., Tier 1 approaches to risk
characterization that lead to single value estimates of risk). Readers are encouraged to consult
the references at the end of this Chapter for additional information about uncertainty analysis in
the risk assessment process.
3.4.1 Distinguishing Uncertainty and Variability
Variability refers to true heterogeneity or diversity. For example, among a local community that
is exposed to an air toxic originating from the same source, and with all people breathing the
same contaminant concentration in ambient air, the risks from inhalation of the contaminated air
will still vary among the people in the population. This may be due to differences in exposure
(i.e., different people have different exposure frequencies and exposure durations), as well as
differences in response (e.g., differences in metabolic processes of chemical uptake into target
organs). Differences among individuals in a population are referred to as inter-individual
variability, while differences for one individual over time (e.g., change in sensitivity to air toxics
with aging, illness) are referred to as intra-individual variability.
Uncertainty occurs because of a lack of knowledge. For example, we can be very certain that
different people are exposed to contaminated air for different time periods, but we may be
uncertain about how much variability there is in these exposure durations among the people in
the population. Data may not be available concerning the amount of time specific people spend
indoors at home, outdoors near home, or in other "microenvironments."
Uncertainty can often be reduced by collecting more and better data, while variability is an
inherent property of the population being evaluated. Variability can be better characterized with
more data, but it cannot be reduced or eliminated. Often, however, it is difficult to distinguish
between uncertainty and variability in a risk assessment, particularly if available data are limited.
For that reason, in many cases variability can be treated as a type of uncertainty in the risk
assessment.
Uncertainty is an inherent characteristic of each step of the risk assessment process. Assessing
uncertainty in risk assessment is an involved process because of the complex nature of the risk
assessment process itself (i.e., risk assessment is a combination of a variety of data gathering and
analytical processes, each with their own associated uncertainties). Specifically, risk assessment
requires the integration of the following:
April 2004 Page 3-19
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• Information on emissions of air toxics into the environment;
• Information on the fate and transport of air toxics, in a variety of different and variable
environments, by processes that are often poorly understood or too complex to quantify
completely;
• Information on the potential for adverse health effects in humans and/or ecosystems, often
extrapolated from surrogate animal studies; and
• Information on the likelihood of adverse effects in a human population that is highly variable
genetically, as well as factors such as age, activity level, lifestyle, and underlying disease.
Uncertainty, when applied to the process of risk assessment, is defined as "a lack of knowledge
about specific factors, parameters, or models."(9) Such uncertainties affect the confidence of any
risk estimates that were developed for individuals exposed to the substances in question/10' It is
important to keep in mind that many parameter values (e.g., emissions rates) maybe both
uncertain and variable. Also, the presence of uncertainty in risk assessment does not imply that
the results of the risk assessment are wrong, but rather that the risks cannot be estimated beyond
a certain degree of confidence.
The relatively simple, deterministic (i.e., single value estimate) approach outlined in this
reference manual generally relies on a combination of point values - some which may be set at
protective (i.e., high end) levels and some which may be set at typical (i.e., central tendency)
levels. The result is a point estimate of exposure, and risk that falls at some percentile within the
full distributions of exposure and risk. The degree of conservatism in high end risk estimates
depends on the combination of input values selected.0!)
One of the key purposes of the uncertainty analysis is to provide an understanding of where the
estimate of exposure, dose, or risk is likely to fall within the range of possible values. Often this
is expressed as a subjective confidence interval (one based on incomplete data supplemented by
professional judgment) within which there is a high probability that the estimate will fall. A
related analysis, termed "sensitivity analysis" or "analysis of uncertainty importance," is often
performed to identify the relative contribution of the uncertainty in a given parameter value (e.g.,
emission rate, ingestion rate) or model component to the total uncertainty in the exposure or risk
estimate. This is often used either to identify which parameter values should be varied to provide
high-end vs. central-tendency risk estimates, or to identify parameter values where additional
data collection (or modeling effort) can increase the confidence in the resulting risk estimate.
3.4.2 Sources of Uncertainty in Air Toxics Risk Assessment
Although other taxonomies are sometimes used, sources of uncertainty in risk assessment are
often divided into four categories (variability is sometimes included as a fifth category).(12)
• Scenario uncertainty occurs when information to fully define exposure and/or risk is
missing or incomplete. This may include descriptive errors regarding the magnitude and
extent of chemical exposure or toxicity, temporal and spatial aggregation errors, incomplete
analysis (i.e., missing exposure pathways), and potential mis-specification of the exposed
population or exposure scenario.
• Model uncertainty is associated with all models used in all phases of a risk assessment,
including (1) animal models used as surrogates for evaluating human carcinogenicity, (2)
April 2004 Page 3-20
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dose-response models, (3) computer models used to predict the fate and transport of
chemicals in the environment, and (4) models used to estimate exposures for populations of
concern. Model uncertainty also is sometimes referred to as specification uncertainty.
Computer models are simplifications of reality that use mathematical approximations to
describe the most important processes governing the modeled relationships, while excluding
what are believed to be less important processes, or processes that are too complex to be
easily approximated. The risk assessor needs to consider the potential importance, in
consultation with the modeler, of the level of detail and comprehensiveness of the models
being used, because specific processes may have important impacts on uncertainty in some
instances and not in others. A similar problem can occur when a model that is applicable
under average conditions is used for a case in which conditions differ from the average. In
tiered analyses, resource considerations and the level of precision required to support
decision making may enter into considerations of model selection. Model uncertainty may be
particularly important in multipathway analyses, because the modeling effort is much more
complex (as compared to inhalation analyses). In addition to air quality modeling,
multipathway analyses involve analysis of the transfer of air toxics from the air to other
media (e.g., soil, sediment, water); the subsequent movement of the air toxics between these
media (e.g., soil runoff to surface water); uptake and metabolism by biota; and subsequent
ingestion by humans and wildlife. Uncertainties are associated with all of these analytical
steps.
Model uncertainty is often difficult to deal with quantitatively. It is rarely possible to directly
evaluate the merits of competing models, either due to resource constraints, or because direct
comparisons are inherently complex (e.g., the models may take different input parameters,
and produce outputs that are not directly comparable). Statistical methods (Bayesian
analyses) can sometimes be used to combine the results of different models, but these
approaches are often complex, and generalizability to specific cases is hard to predict. Thus,
model selection tends to be based primarily on profession judgement and cost/complexity
considerations.
• Parameter Uncertainty refers to the limitations in the modelers' ability to estimate precise
values for certain parameters (variables) in the chosen models. It is a generic term that in
common usage can refer either to variability or uncertainty, and generally indicates a situation
where a given variable may take a range of values, rather than a single point estimate.
Parameter uncertainty is generally addressed in risk assessment through gathering additional
data, sensitivity analysis, or probabilistic modeling (discussed in Section 3.3.4).
• Decision-rule uncertainty is a type of uncertainty associated with policy and other choices
made during the risk assessment. For example, the number of chemicals of potential concern
(COPC) evaluated at a given tier of assessment may be reduced through use of a
toxicity-weighted or risk-based screening analysis. In this example, the decision rule could
be something like "Calculate the toxicity weighted emission for each chemical in the
emissions inventory, rank the scores from highest to lowest and, starting with the highest
score and working down, select as COPCs those chemicals that contribute to 99 percent of
the cumulative toxicity weighted sum." This type of judgment introduces uncertainties about
the contribution of the omitted air toxics to overall exposure or risk. As another example,
risk managers may decide to select as chemicals for risk reduction efforts (i.e., the Chemicals
April 2004 Page 3-21
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of Concern or COCs) only those COPCs that, individually, pose a risk above some specified
level (e.g., one per million general population lifetime cancer risks). In this case, the decision
rule would be "COCs are those COPCs which have a risk, on an individual chemical basis, of
one in one million or greater." For any given risk assessment, some or all of these practices
maybe questioned, either on technical grounds (e.g., a risk number has been generated, but it
is highly uncertain) or for policy reasons. The risk assessor needs to be sensitive these
considerations when planning, conducting, and reporting the results of the risk assessment.
3.4.3 Sources of Variability in Air Toxics Risk Assessment
As noted previously, variability refers to true heterogeneity or diversity that occurs within a
population or sample. Factors that lead to variability in exposure and risk include variability in
contaminant concentrations in an environmental medium (e.g., air, water, soil) and differences in
other exposure parameters such as ingestion rates and exposure frequencies.
Temporal and spatial variability in contaminant concentrations is often a very important aspect to
consider in air toxics risk assessments. Spatial variability arises from many factors, including the
release forms, physical and chemical dilution and transformation processes, and physical
characteristics of the source or surrounding environment. Ecological receptors and humans may
exhibit spatial variability in their contact with an exposure medium. Likewise, temporal
variability can result from a variety of factors. For example, a source may only emit a chemical
at specific times during the year (e.g., during the processing of a batch of product).
Meteorological changes between seasons also can cause variable exposure (even though source
emissions remain relatively constant). Because variability is an intrinsic property of the
quantities being evaluated, it cannot be reduced by data gathering or refinements in models.
However, understanding and/or analysis of variability are still important, especially during
problem formulation. For example, it may be thought that certain air toxic emission source
characteristics or potentially exposed populations are very heterogeneous and that a more robust
description of the numbers and types of people at different risk levels is necessary to meet risk
management decision goals
Confusion often arises about whether data are describing variability or uncertainty. For example,
consider a group of 10,000 office workers who spend part of the time indoors at home and part of
the time indoors at work. To assess the fraction of time spent indoors at a home or the office, a
randomly chosen group of 100 office workers are asked to fill out a survey (resources preclude
surveying all 10,000 people). Once we have our data, we draw a frequency diagram of the
number of workers who spend specified amounts of time indoors at home and at the office. The
picture we get clearly shows that different people spend different amounts of time inside at home
and at the office - there is variability in the parameter for this population.
However, is our picture of variability correct (i.e., how certain are we that we have a good picture
of the true variability of all 10,000 people)? Since we did not survey every possible worker and
because some of the workers may have given incorrect responses, we have to admit to ourselves
that there is probably some amount of uncertainty as to whether our frequency diagram is an
accurate representation of variability in full worker population. In other words, we have
developed an expression of variability that we think is uncertain. But only having a sense that
our picture of variability may not be an accurate representation may not be enough (knowing just
how uncertain our estimate of variability is may be important in our risk assessment).
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Fortunately we have a variety of methods to look at the uncertainty in just one parameter (e.g.,
how variable is time spent indoors versus outdoors) and in the combination of parameters to
provide estimates of exposure and risk. We can, for example, look at our data to see if patterns
of time use vary for different subgroups of workers, or we can look for "outliers" (individuals
with unusual patterns of indoor/outdoor time use). Alternatively, we could gather data from a
larger sample of workers. Any of these would decrease the level of uncertainty, in worker
behavior, by providing more accurate representations of the variability of time usage for more
clearly defined categories of workers. The newly developed worker categories would then be
included in the exposure modeling.
3.4.4 Characterizing Uncertainty and Variability
Ideally, one would like to carry through the risk assessment, in a quantitative fashion, the
uncertainty associated with each element in order to characterize the overall uncertainty
associated with the final risk estimates. However, this is not always possible (because data are
extremely limited) and, in some cases, may not be necessary (when all reasonable modeling
assumptions and parameter values lead to the same recommendation). Nevertheless, it is always
a good idea to provide some level of uncertainty analysis (be it qualitative, semi-quantitative, or
quantitative). For example, one important use of uncertainty characterization can be to identify
areas where a moderate amount of additional data collection might significantly improve the risk
assessment, and hence the decision on the need for risk reduction or the risk reduction strategy to
be used.
• Qualitative characterization. In a qualitative uncertainty analysis, a description of the
uncertainties in each of the major elements of the risk analysis is provided, often with a
statement of the estimated magnitude of the uncertainty (e.g., small, medium, large) and the
impact the uncertainty might have on the risk element (e.g., the uncertainty is large and risk
estimate is likely underestimated due to this element).
• Quantitative characterization. When appropriate, quantitative approaches to the
uncertainty analysis are used to better characterize the uncertainty associated with the risk
assessment. In this case, the first step is usually to characterize the probability distributions
for key input parameter values (either using measured or assumed distributions). The second
step would be to propagate parameter value uncertainties through the analysis using analytic
(e.g., first-order Taylor series approximation) or numerical (e.g., Monte Carlo simulation)
methods, as appropriate. Analytic methods might be feasible if there are a few parameters
with known distributions and linear relationships. Numerical methods (e.g., Monte Carlo
simulation) can be suitable for more complex relationships. "Two-dimensional" Monte
Carlo analyses may be used where separate estimates of uncertainty and variability are
available for some or all variables. Specific approaches are likely to be highly variable
depending on the nature of the assessments being performed. Examples of approaches
applied to a variety of assessments are provided in the reference list at the end of this chapter
in Exhibit 3-8 (Hope, 1999; Moore et al, 1999; Smith, 1994).
• Both qualitative and quantitative uncertainty characterization is subject to scope-related
limitations and uncertainty. For example, ecological risk assessments that are limited to
primary effects evaluation for organisms or populations are uncertain with regard to
secondary effects for communities or ecosystems. Similarly, human health assessments that
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are restricted to the HAPs may ignore exposures and potential effects from other chemicals in
the same emissions. Such uncertainties persist regardless of the assessment's refinement
level (Tier). Their communication provides important contextual information for decision
making.
Guidance developed by the National Council on Radiation Protection and Measurements03'
provides useful insights as to when to perform a quantitative uncertainty analysis in
environmental risk assessments (Exhibit 3-6).
Exhibit 3-6. When to Perform a Quantitative Uncertainty Analysis
Quantitative uncertainty analysis is NOT recommended when:
• Conservative, screening-level calculations indicate that the risk from potential exposure is clearly
below regulatory or other risk levels of concern;
• The cost of an action to reduce exposure is low; and/or
• Data for characterizing the nature and extent of contamination or exposure are inadequate to
permit even a bounding estimate (an upper and lower estimate of the expected value).
Quantitative uncertainty analysis IS recommended when:
• An erroneous result in the exposure or risk estimate may lead to large or unacceptable
consequences;
• Whenever a realistic rather than a conservative estimate is needed; and/or
• When it is important to identify those assessment components for which additional information
will likely lead to improved confidence in the estimate of exposure or risk.
Source: NCRP. 1996.'
3.4.5 Tiered Approach to Uncertainty and Variability
Building on the approach outlined in Exhibit 3-6, the following description provides one possible
tiered approach to deciding when and how to perform an uncertainty analysis.(14)
Single-Value Estimates of High-End and Central Tendency Risk. This approach starts with
simple risk estimates using both representative and more conservative scenarios, models, and
input values, using point estimates to represent each of the major parameters. This
"deterministic" approach, which is described extensively in this document, may provide
sufficient information for the risk management question being addressed. For example, if risks
for a suitably defined high-end receptor are below levels of concern, then no additional
uncertainty analysis (or risk analysis) maybe needed to support a risk management decision. It is
important to recall, however, that using single values for inputs, essentially ignores uncertainty
and variability - information that may be very important for risk managers and the public.
Despite some limitations, single-value estimates or point estimates are an important tool in the
risk assessment process. Single-value estimates are particularly useful as a screening tool to
identify situations in which even highly conservative assumptions about exposure and other
model parameters indicate low risk. (Note that EPA risk assessors are directed to provide, in
Agency risk assessments, information about the range of exposures derived from exposure
April 2004 Page 3-24
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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 .(7))
Qualitative Evaluation of Model and Scenario Sensitivity. Where the single-value high-end
and central tendency point estimates do not provide sufficient information to make a risk
management decision, qualitative analyses can be conducted to determine the range of values
within which the risk estimate is likely to fall and the major factors that contribute to uncertainty.
The sensitivity of the high-end and central tendency estimates to the plausible range of values for
various parameters can usually be evaluated by conducting a manageable number of case studies
using different parameter values and observing the resulting changes in risks. If scenario or
model specification turns out to strongly affect risk estimates, a more refined analysis (see below)
may be necessary. These may include Bayesian or decision-tree models.
Quantitative Sensitivity Analysis of High-End or Central Tendency Estimates. The risk
assessor may want to evaluate the sensitivity of the point estimates of risks to variability and
uncertainty in model input parameters. This may be done through sensitivity analysis or through
the use of more detailed probabilistic methods (see Chapter 31). If sensitivity analyses are used,
care must be taken to ensure that the combinations of parameter values that have the greatest
impact on risks are identified.
Full Quantitative Characterization of Uncertainty and Uncertainty Importance. For many
risk assessments, the systematic sensitivity analyses can provide sufficient information to provide
reasonable confidence in the risk estimate. If they do not, the next step is explicit probability
modeling, which is described in Chapter 31. Using such approaches, uncertainty and variability
distributions can be defined for the major parameter values used in the derivation of the risk
estimates. This approach is referred to as parameter uncertainty analysis and includes the
following steps:(15)
• Define the assessment endpoint (i.e., the specific measure being evaluated). Examples
would include an estimate of exposure concentration, hazard index, or a quantitative estimate
of individual cancer risk.
• List all potentially important uncertain parameters. Include additional parameters, if
necessary, to represent uncertainty in the assessment approach itself.
• Specify the maximum conceivable range of possibly applicable values for each
parameter with respect to the endpoint being assessed.
• For this range, specify a probability distribution for the parameter. The probability
distribution quantitatively expresses the state of knowledge about alternative values for the
parameter (i.e., defines the probability that the true value of the parameter is located in
various sub-intervals of the indicated range). These may include statistical distributions (e.g.,
"normal" or other distributions derived from data) or simpler approximations (triangular
distributions defined by high, medium, and low values).
April 2004 Page 3-25
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• Determine and account for dependencies that are suspected to exist among parameters.
For example intake rate may not be independent of age or body weight.
• Using either analytical or numerical procedures, propagate the uncertainty in the
model parameters to produce a probability distribution for the assessment endpoint.
This results in the development of a probability distribution function (PDF) representing the
state of knowledge for the endpoint.
• Derive quantitative statements of uncertainty in terms of a probability or confidence
interval about the assessment endpoint.
• Identify parameters according to their relative contribution to the overall uncertainty
in the prediction of the value of the assessment endpoint.
• Present and interpret the results of the analysis.
A full quantitative characterization of uncertainty requires a number of assumptions, including:
• The most important sources of uncertainty and variability are identified;
• The assumed probability distributions are correct; and
• The assumed dependence structure for different sources of uncertainty or variability is
correct.
A comprehensive quantitative analysis may be a daunting task, particularly if a large number of
sources, chemicals, receptors, exposure pathways, and endpoints, are of concern. Furthermore,
the difficulty in justifying a large number of distributional assumptions (often based on
professional judgement) needed for an uncertainty analysis might make such an analysis in itself
unreliable.
In practice, the number of "tiers" available to the risk assessor may be limited. Often the
practical choice is between using simple "screening" models (e.g., SCREEN3), and highly
refined, fully parameterized modeling packages (e.g., ISCST3). In such cases, it may be easier
to do a highly refined analysis with the state-of-the art models than to incrementally improve on
the screening methods.
3.4.6 Assessment and Presentation of Uncertainty
The assessment and presentation of uncertainty is a very important component of the risk
characterization. Based on the amount of information about sources and emissions and the
degree of uncertainty associated with estimates of risk, decision-makers will weigh the
importance of the risk estimates in the eventual decision. As noted previously, when the
uncertainty analysis is qualitative in nature, a description of the uncertainties in each of the major
elements of the risk analysis is usually described, often with a statement of the estimated
magnitude of the uncertainty (e.g., small, medium, large) and the impact the uncertainty might
have on the risk element (e.g., the uncertainty is large and risk estimate is likely underestimated).
Important uncertainties to discuss include, but are not limited to:
April 2004 Page 3-26
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• Scope issues such as the choice of air toxics, receptors, or endpoints that are evaluated in the
assessment and the choice of air quality or multimedia models used to characterize exposure;
• Data quality issues, such as the quality of available sampling, emissions inventory, or toxicity
data;
• Uncertainties inherent in the toxicity values for each substance used to characterize risk; and
• Uncertainties that are incorporated in the risk assessment when exposures to several
substances across multiple pathways are summed.
When the analysis is more quantitative in nature, the description of uncertainty generally is
separated into two parts:
• The first part is a summary of the values used to estimate exposure and risk (including model
inputs), the range of these values, the midpoint or other descriptive values, and the value used
to estimate exposure.
• The second part is a narrative discussion that identifies which variables or assumptions used
in the risk assessment have the greatest potential to affect the overall uncertainty in the
exposure assessment.
Chapter 13 provides additional discussion of how to assess and present uncertainty in an air
toxics risk assessment. Exhibit 3-7 provides additional references on uncertainty analysis.
/- ~x
Example of a Six-step Process for Producing a Quantitative Uncertainty Estimate
Finkel (1990)(12) presents another example of a quantitative uncertainty analysis process:
1. Define the measure of risk (such as deaths, life-years lost, maximum individual risk [MIR], or
population above an "unacceptable" level of risk). More than one measure of risk may result from
a particular risk assessment; however, the uncertainty may be quantified or reached individually.
2. Specify "risk equations" that present mathematical relationships that express the risk measure in
terms of its components. This step is used to identify the important variables in the risk estimation
process.
3. Generate an uncertainty distribution for each variable or equation component. These uncertainty
distributions maybe generated by using analogy, statistical inference techniques, expert opinion, or
a combination of these.
4. Combine the individual distributions into a composite uncertainty distribution.
5. Re-calibrate the uncertainty distributions. Inferential analysis could be used to "tighten" or
"broaden" particular distributions to account for dependencies among the variables and to truncate
the distributions to exclude extreme values.
6. Summarize the output clearly, highlighting the important risk management implications. Address
specific critical factors, including (1) the implication of supporting a point estimate produced
without considering uncertainty; (2) balance the costs of under- or over-estimating risks; and (3)
unresolved scientific controversies, and their implications for research.
April 2004 Page 3-27
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Exhibit 3-7. Additional References on Uncertainty Analysis
Burmaster, D.E. and Anderson, P.D. 1994. Principles of good practice for the use of Monte Carlo
techniques in human health and ecological risk assessments. Risk Analysis 14: 477-481.
Cullen, A.C. andFrey, H.C. 1999. Probabilistic Techniques in Exposure Assessment. New York:
Plenum Press.
Fayerweather, W.E., Collins, J.J., Schnatter, A.R., Hearne, F.T., Menning, R.A., and Reyner, D.P.
1999. Quantifying uncertainty in a risk assessment using human data. Risk Analysis 19: 1077-1090
Finkel, A.M. and Evans, J.S. 1987. Evaluating the benefits of uncertainty reduction in environmental
health risk management. Journal of the Air Pollution Control Association. 37: 1164-1171.
Frey, H.C. 1992. Quantitative analysis of uncertainty and variability in environmental policy making.
Pittsburgh: Carnegie Mellon University.
Hattis, D. and Burmaster, D.E. 1994. Assessment of variability and uncertainty distributions for
practical risk assessments. Risk Analysis 14: 713-730.
Hope, B. K. 1999. Assessment of risk to terrestrial receptors using uncertainty analysis - A case
study. Human and Ecological Risk Assessment 5(1): 145-170.
Moore, D.R.J., Sample, B.E., Suter, G.W., Parkhurst, B.R., and Teed, R.S. 1999. A probabilistic risk
assessment of the effects of methylmercury and PCBs on mink and kingfishers along East Fork Poplar
Creek, Oak Ridge, Tennessee, USA. Environmental Toxicology and Chemistry 18: 2941-2953.
National Research Council (NRC). 1991. Human Exposure Assessment for Airborne Pollutants.
Washington DC: National Academy Press.
Roberts, S.M. 1999. Practical issues in the use of probabilistic risk assessment and its applications to
hazardous waste sites. Human and Ecological Risk Assessment. 5(4): 729-868. Special Issue.
Smith, R.L.. 1994. Use of Monte Carlo simulation for human exposure assessment at a Superfund
site. Risk Analysis 14(4): 433-439.
U.S. Environmental Protection Agency. 1985. Methodology for Characterization of Uncertainty in
Exposure Assessments. Washington DC, EPA-600/8-85-009).
April 2004 Page 3-28
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References
1. National Research Council (NRC). 1983. Risk Assessment in the Federal Government:
Managing the Process (The "Red Book"). National Academy Press, Washington, B.C.
2. National Research Council (NRC). 1994. Science and Judgment in Risk Assessment (The
"Blue Book"). National Academy Press, Washington, B.C.
3. Commission on Risk Assessment and Risk Management (CRARM). 1996. Risk Assessment
and Risk Management in Regulatory Decision-Making (The "White Book"). Braft Report,
Washington, B.C.
CRARM. 1997. Framework for Environmental Health Risk Management. Final Report,
Volume 1, Washington, B.C.
CRARM. 1997. Risk Assessment and Risk Management in Regulatory Decision-Making.
Final Report, Volume 2, Washington, B.C.
4. National Research Council (NRC). 1996. Understanding Risk: Informing Decisions in a
Democratic Society. National Academy Press, Washington, B.C.
5. U.S. Environmental Protection Agency. 1984. Risk Assessment and Management:
Framework for Decision Making. Office of Policy, Planning and Evaluation, Washington,
B.C. EPA/600/985/002.
6. U.S. Environmental Protection Agency. Superfund Risk Assessment. Updated January 29,
2004. Available at: http://www.epa.gov/superfund/programs/risk/tooltrad.htm#gdhh. (Last
accessed March 2004).
7. U.S. Environmental Protection Agency. 1995. Policy for Risk Characterization at the U.S.
Environmental Protection Agency. Science Policy Council, Washington, B.C., March 1995.
Available at: http://64.2.134.196/committees/aqph/rcpolicy.pdf.
8. U.S. Environmental Protection Agency. 1999. Residual Risk Report to Congress. Office of
Air Quality Planning and Standards, Research Triangle Park, NC. March 1999.
EPA/453/R99/001. Available at: http://www.epa.gov/ttnatwO 1 /risk/risk rep.pdf.
9. U.S. Environmental Protection Agency. 1997. Guiding Principles for Monte Carlo Analysis.
Risk Assessment Forum, Washington, BC. March 1997. EPA/630/R97/001.
10. U.S. Environmental Protection Agency. 1988. National Emission Standards for Hazardous
Air Pollutants. Federal Register 53(145):28496-28056, Proposed Rule and Notice of Public
Hearing. July 28, 1988.
11. Hattis, B.B. and B.E. Burmaster. 1994. Assessment of variability and uncertainty
distributions for practical risk analyses. Risk Analysis 14(5):713-730.
12. Finkel, A.M. 1990. Confronting Uncertainty in Risk Management: A Guide for Decision-
Makers. Center for Risk Management, Resources for the Future. Washington, BC.
April 2004 Page 3-29
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13. National Council on Radiation Protection and Measurements. 1996. A Guide for Uncertainty
Analysis in Dose and Risk Assessments Related to Environmental Contamination. Bethesda,
MD, May 1996. NCRP Commentary No. 14.
14. U.S. Environmental Protection Agency. 1997. Policy for Use of Probabilistic Analysis in
Risk Assessment. Office of the Administrator, Washington, DC. May 15, 1997.
15. International Atomic Energy Agency. 1989. Evaluating the Reliability of Predictions Made
Using Environmental Transfer Models. Vienna, Austria. IAEA Safety Series 100.
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Chapter 4 Air Toxics: Chemicals, Sources, and
Emissions Inventories
Table of Contents
4.1 Introduction j_
4.2 Air Toxics j_
4.2.1 Introduction to Air Toxics Chemical Lists 1_
4.2.2 Hazardous Air Pollutants (HAPs) 4
4.2.3 Criteria Air Pollutants 5.
4.2.4 Toxics Release Inventory (TRI) Chemicals 6.
4.2.5 Toxic Chemicals That Persist and Which Also May Bioaccumulate 6.
4.2.6 Other Chemicals jj.
4.3 Sources of Air Toxics 11
4.3.1 Point Sources 12.
4.3.2 Nonpoint Sources 13
4.3.3 On-Road and Nonroad Mobile Sources 14
4.3.4 Sources Not Included in the NEI or TRI 1_5
4.3.4.1 Indoor Sources 15
4.3.4.2 Natural Sources 18.
4.3.4.3 Formation of Secondary Pollutants 19
4.3.4.4 Other Sources Not Included in NEI or TRI 20.
4.4 Emissions Inventories 20
4.4.1 National Emissions Inventory (NEI) 21
4.4.2 Toxics Release Inventory (TRI) 25
References 29
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4.1 Introduction
This chapter identifies the set of chemicals broadly, and most
commonly, considered "air toxics." This section also describes
the general categories of air toxics sources that emit these
chemicals as well as the primary places where air toxics
emissions information (e.g., databases that contain information
on the location and nature of emissions released from various
types of sources) used in air toxics risk assessments can be
found. Section 4.2 discusses air toxics; Section 4.3 describes air
toxics sources; and Section 4.4 describes air toxics emissions
data sources.
The exhaustive lists of air
toxics discussed in this
section do not include all of
the hazardous chemicals of
public health concern. Note
also that other forms of air
pollution (e.g., odors) are
not addressed in this
Reference Library.
4.2 Air Toxics
Chapter 2 of this Volume introduced Hazardous Air Pollutants (HAPs), criteria air pollutants,
Toxic Release Inventory (TRI) chemicals, and persistent, bioaccumulative, and toxic (PBT)
chemicals and discussed the relationships among these various groupings. This section will
revisit each of these groups to provide more detailed information related to the chemicals on
each of those lists. A thorough understanding of the different types of chemicals that may be of
interest for an assessment, as well as the nuances of the various ways chemicals are written into
those lists, will be important for the risk assessment team to comprehend before the assessment
begins in earnest.
The term "air toxics" is a generic term that could conceivably encompass literally anything in the
air that poses harm to people or the environment. This Volume uses the term "air toxics" in this
general sense. Thus, while the focus of most air toxics risk assessments will be on the 188
chemicals and chemical compounds listed as HAPs in the Clean Air Act (CAA) section 112(b),
some assessment teams may wish to have a broader focus. The use of the term "air toxics" in
this general sense is meant to provide for this flexibility. Ultimately, the scope of any
assessment must clearly identify the chemicals that will be evaluated and the reason for their
inclusion or exclusion in the evaluation.
4.2.1 Introduction to Air Toxics Chemical Lists
The various lists that are the focus of this volume were all derived directly from the Clean Air
Act, the Emergency Planning and Community Right to Know Act, or a specific EPA initiative
(e.g., the PBT initiative list of chemicals). It is important to understand that there is not always
consistency among these various lists in either the naming of chemicals or the meaning of the
names. For example, as noted in Chapter 2, "glycol ethers" are defined differently for the TRI
and as HAPs (see box in Section 2.4.4).
Lists of toxic chemicals commonly provide the chemical identity by both a name and a unique
identifying number, called a Chemical Abstracts Registry Number.(a) However, most
aCAS (Chemical Abstracts Service) is a division of the American Chemical Society. A CAS Registry
Number (CAS number or CASRN) is assigned in sequential order to unique, new substances identified by CAS
scientists for inclusion in the CAS REGISTRY database. Each CAS Registry Number is a unique numeric
identifier; designates only one substance; and has no chemical significance. A CAS Registry Number is a numeric
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chemicals have multiple synonyms (sometime dozens). Fortunately, every unique chemical has
only one unique CAS number and one can always refer to this unique number to identify the
compound in question. For example, toluene and methylbenzene are synonyms for the same
compound (which is normally referred to as toluene). However, there is only one CAS number
for the compound: 108-88-3. No matter where one is in the world or what name is attached to a
chemical, there is unanimity of identity through the CAS numbering system.
When there is any question about what a particular chemical name means, it is always advisable
to try to pinpoint the identity through use of the CAS number. For example, a risk assessment
team may ask for air sampling analysis for the HAP acetaldehyde (CAS number 75-07-0);
however, when they receive the analytical lab report, acetaldehyde is not reported. A quick scan
of the CAS numbers reported by the lab lists the CAS number 75-07-0 next to the name
"ethanal." Ethanal is a synonym for acetaldehyde and, hence, has the same CAS number.
EPA's Handbook for Air Toxics Emission Inventory Development includes a list (Appendix C)
of synonyms and CAS numbers for HAPs that is helpful in overcoming the nomenclature
obstacle/1' (Note, however, that there are nuances even beyond this simplistic description. For
example, some chemicals have one CAS number for their pure form and a different CAS number
for a technical grade. A knowledgeable chemist can usually identify and clarify these issues.)
Some of the entries on chemical lists are for large groups of compounds and not just one single
substance. For example, one of the HAPs is listed in the CAA as "polychlorinated biphenyls
(aroclors)" and is most commonly referred to as PCBs. This listing is not for one single
substance but, rather, for any one or a mixture of any of the 209 possible chemicals that are
themselves PCBs. As another example, the pesticide "2,4-D" is written into the list of HAPs as
"2,4-D (salts and esters)." This listing includes any possible salt of 2,4-D and any possible ester
of 2,4-D. In our earlier lead example, the lead compound listing includes any compound known
to exist in or be emitted to the environment that contains a lead molecule as part of the
compound's molecular structure (a potentially huge number of possibilities). Another important
group of chemicals is called "POM" for polycyclic organic matter. This includes organic
compounds with more than one benzene ring, and which have a boiling point greater than or
equal to 100° C (e.g., polycyclic aromatic hydrocarbons (PAHs) such as benzo(a)pyrene).
In reality, most risk assessments will deal with a relatively small number of chemicals because
either the sources in a given place are releasing only a limited number of chemicals or the ability
to model or monitor the numerous chemicals present is limited by the available inventories or
monitoring/analytical methods, respectively.
In the initial stages of the assessment, risk assessors often sort the chemicals of interest into
groups that, generally, have similar physical and/or chemical properties. This is a helpful thing
to do as a way of making some educated guesses about how chemicals are likely to behave in the
environment. The groupings also help an assessment team to plan for the types of sampling and
analysis methods that will be needed, because the sampling and analytical methods tend to be
broken out along these same lines. In general, all air toxics can be broadly categorized into three
main groups, organic chemicals, inorganic chemicals, and organometallic compounds as follows:
identifier that can contain up to nine digits, sometimes divided by hyphens into three parts. See
http://www.cas.org/faq.html for more information.
April 2004 Page 4-2
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Organic Chemicals
Organic chemical compounds are composed of carbon in combination with other elements such
as hydrogen, oxygen, nitrogen, phosphorous, chlorine, and sulfur (not including carbonic acid or
ammonium carbonate). Organic compounds can generally be split into two different groups,
based on their propensity to evaporate. The following such groupings are commonly employed
by analytical chemistry laboratories for purposes of sample analysis.
• Volatile Organic Compounds (VOCs). These are organic chemicals that have a high vapor
pressure and tend to have low water solubility.(b) Simply put, VOCs have a high propensity
to evaporate and remain airborne. Many VOCs are human-made chemicals that are used and
produced in the manufacture of paints, pharmaceuticals, and refrigerants, as industrial
solvents, such as trichloroethylene, or produced as by-products, such as chloroform produced
by chlorination in water treatment. VOCs are often also components of petroleum fuels (e.g.,
benzene), hydraulic fluids, paint thinners, and dry cleaning agents.(c)
A subgroup of VOCs is termed Carbonyl Compounds and includes chemicals such as
formaldehyde and acetaldehyde. While such chemicals are themselves VOCs due to their
high vapor pressure, they are often grouped as a separate class from the VOCs because of the
special sampling and analytical methods necessary to measure them in air.
• Semivolatile Organic Compounds (SVOCs). SVOCs are organic chemicals that have a
lower vapor pressure than VOCs and, thus, have a lower propensity to evaporate from the
liquid or solid form. Once airborne, they also tend to more readily condense out of the gas
phase. Examples of SVOCs include most organic pesticides (e.g., chlordane), and certain
components of petroleum, such as polycyclic aromatic hydrocarbons. Note that the
demarcation between SVOCs and VOCs is not exact. For example, the two separate air
sampling and analytical methods for VOCs and SVOCs will both usually detect naphthalene
when present, indicating that this chemical is on the lower end of the VOC scale of volatility
and on the higher end of the SVOC scale of volatility. In general, as chemicals increase in
molecular weight and/or polarity, they become more SVOC-like.
Inorganic Chemicals
This group includes all substances that do not contain carbon and includes a wide array of
substances such as:
• Metals (e.g., mercury, lead, and cadmium) and their various salts (e.g., mercury chloride);
• Halogens (e.g, chlorine and bromine);
• Inorganic bases (e.g., ammonia); and
• Inorganic acids (e.g., hydrogen chloride, sulfuric acid).
The regulatory definition of VOC does not identify vapor pressure as a consideration. See 40 CFR
51.100(s).
"VOC" refers to volatile organic compounds that contribute to ozone formation as defined by 40 CFR
50.100(s) as ozone precursors. VOC is a subset of VOCs. VOC emissions inventory information is sometimes used
to derive estimates for specific chemicals; when this is done, the VOC number is said to have been speciated.
April 2004 Page 4-3
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Organometallic Compounds
This group is comprised of compounds that are both organic and metallic in nature. The alkyl
lead compounds that were added to gasoline to enhance its properties can be used for illustration.
"Alkyl" refers to the organic portion of a compound which is attached to the inorganic metal
lead. The result is a so-called "organometallic" material, a hybrid of both metallic and organic.
(Note that salts, such as sodium benzoate, are usually classified as an organic chemical, rather
than an organometallic compound.)
An understanding of the general characteristics of organic chemicals, inorganic chemicals and
organometallic compounds will aid in planning a risk assessment and developing an appropriate
analysis strategy. For example, most VOCs tend to remain airborne and also do not tend to
bioaccumulate to the same extent as some of the non-volatile chemicals. Thus, if an assessment
were being planned to evaluate the impact of a source from which only VOCs were released, it
becomes less likely that a multipathway risk analysis will be necessary (since VOCs do not tend
to migrate into soil or water and do not tend to bioaccumulate as strongly in living tissue).
In addition, the sampling and analytical methods available to test for chemicals in environmental
media are generally broken out along the same chemical groupings noted above. Thus, if one
were interested in testing for airborne chlordane (an SVOC), a VOC monitoring method would
not be used. Detailed information on available monitoring methods and the chemicals for which
they have been validated is provided in Chapter 10.
In air toxics studies, both individual substances and mixtures of substances are of interest.
Particulate matter (PM), for example, is almost never comprised of just one substance; instead,
PM is usually made up of numerous individual substances (sometimes in the hundreds). Both
the physical and chemical nature of a mixture will influence the fate and transport of the
chemicals in the environment as well as the potential for the mixture to cause harm. For
example, a toxic chemical adsorbed onto the surface of a relatively large particle (> 10 microns
in diameter) will usually be trapped in the upper portion of the respiratory system and either
coughed/sneezed out of the body or swallowed. The same chemical adsorbed onto a very small
particle (< 2.5 microns in diameter) has a much higher likelihood of being inhaled into the deep
lung. As we will see in later chapters, both the route of exposure (in this example, ingestion or
inhalation) as well as the toxic properties of the chemical in question are important determinants
of potential harm.
4.2.2 Hazardous Air Pollutants (HAPs)
The HAPs are a group of 188 specific chemicals and chemical compounds and are identified in
Section 112(b) of the CAA. The Agency provides additional information on the HAPs online.(2)
HAPs are pollutants known to cause or suspected of causing cancer or other serious human
health effects or ecosystem damage. They include individual organic and inorganic compounds
and pollutant groups closely related by chemical structure (e.g., arsenic compounds, cyanide
compounds, glycol ethers, polycyclic organic matter) or emission sources (e.g., coke oven
emissions). EPA may add or remove pollutants from the HAP list as new information becomes
available. A full list of the HAPs is provided in Appendix A.
When people talk about "air toxics risk assessment," they generally mean assessments of risks
associated with one or more of the HAPs. This is largely because of the CAA listing of 188
April 2004 Page 4-4
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HAPs and its requirement under Section 112(f)(2) (Residual Risk) that EPA assess the risks
associated with HAPs that remain after the application of the Maximum Achievable Control
Technology (MACT) standards (Section 112(d) of the Act). However, given that this is a
relatively short list of chemicals, many communities may want to go beyond this list when
assessing risk. It is for this reason, that assessors and other stakeholders must clearly identify
why they are conducting an "air toxics" risk assessment and what they want to include in that
assessment.
In its Integrated Urban Air Toxics Strategy, EPA identified a subset of 33 HAPs as those posing
the greatest risk in urban areas (see Section 2.2.1). These 33 HAPs were selected based on a
number of factors, including toxicity-weighted emissions, monitoring data, past air quality
modeling analysis, and a review of existing risk assessment literature.
The national-scale assessment for 1996 (see Section 2.3.2) focused on 32 of these 33 Urban
HAPs (dioxin was omitted) and also includes diesel particulate matter, which is used as a
surrogate measure of diesel exhaust. EPA recently concluded that diesel exhaust is likely to be
carcinogenic to humans by inhalation at environmental levels of exposure. Diesel exhaust is
addressed in several regulatory actions and diesel particulate matter plus diesel organic gases are
listed by EPA as a mobile source air toxic (see Section 4.3.3 below).
4.2.3 Criteria Air Pollutants
The "criteria air pollutants" are six substances regulated pursuant to Title I of the CAA, for
which "criteria documents" are developed by the Agency prior to national standard setting
decisions. There are already national ambient air quality standards (NAAQS) in place for each
of these pollutants as well as established regulatory programs and activities in place to meet
those standards. However, they are discussed here because there is some crossover between the
realm of HAPs and criteria pollutants. The more important crossover issues are discussed
below.
• Particulate matter. NAAQS have been established for particles with an aerodynamic
diameter less than or equal to 10 microns (called PM10) and particulate matter with an
aerodynamic diameter less than or equal to 2.5 microns (called PM25). As noted above,
however, PM can be made up of as little as one or a few, or many hundreds of individual
chemicals. In many cases (and depending on the source of the PM), any number of
specifically listed HAPs maybe a part of the PM mix. It is for this reason that risk assessors
may opt to evaluate the composition of PM and to include the identified chemicals in risk
calculations.
For example, it is possible to collect samples of PM10 for purposes of determining the types
and amounts of individual substances contained in the particles. The risks posed by those
individual chemicals may then be estimated for the inhalation route of exposure. Because
particles with diameters greater than 10 microns are not generally respirable, analysts usually
select a PM10 monitor to capture samples for risk assessment purposes rather than a total
suspended particulate (TSP) sampler, because TSP would capture larger particles that do not
penetrate very far into the respiratory tract (thus leading to an overestimate in inhalation risk
associated with the specific pollutants studied). Note that this would not be true for particle-
bound chemicals that exert their toxic effects on the nasal passages.
April 2004 Page 4-5
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• Ozone and other criteria pollutants. Certain other criteria pollutants are not specifically
listed as HAPs, but HAPs may lead to their formation or they may lead to HAP formation.
For example, ozone is produced by the interaction of certain VOCs, oxides of nitrogen
(called NOX), and sunlight. As noted previously, many of the HAPs are VOCs and may play
a role in ozone formation. In contrast, sulfur dioxide is a criteria pollutant that can be
transformed in the environment into sulfuric acid which, in turn, may become part of a listed
HAP (e.g., cadmium sulfate). In general, the criteria pollutants ozone, nitrogen dioxide,
sulfur dioxide, carbon monoxide are not usually considered in air toxics risk assessments.
4.2.4 Toxics Release Inventory (TRI) Chemicals
Data on TRI chemicals are reported pursuant to Section 313 of the Emergency Planning and
Community Right-To-Know Act (EPCRA) of 1986 and Section 6607 of the Pollution Prevention
Act of 1990 (PPA). EPCRA and the PPA are intended to inform communities and citizens about
chemical hazards in their areas. EPA and states are required to collect data annually on releases
(to each environmental medium) and waste management methods (e.g., recycling) of certain
toxic chemicals from industrial facilities, and to make the data available to the public in the
TRI.(3) EPCRA Section 313(d) permits EPA to list or delist chemicals based on certain criteria.
In a 1994 rulemaking, EPA added 286 chemical categories to the TRI chemical list. The TRI
chemicals are listed in 40 CFR Section 372.65, and information about the 667 currently-listed
TRI chemicals is provided online .(4)
The current TRI chemical list contains 582 individually listed chemicals and 30 chemical
categories (including three delimited categories containing 58 chemicals), for a total of 612
separate chemicals. If the members of the three delimited categories are counted as separate
chemicals then the total number of chemicals and chemical categories is 667 (i.e., 582 + 27 +
58). The TRI list of toxic chemicals includes most (180) of the HAPs. Similar to the HAPs, the
TRI chemicals include VOCs, SVOCs, inorganic compounds, and organometallic compounds.
The utility of the TRI for air toxics risk assessment is two fold. First, it provides a broader
perspective of industrial emissions than the HAP list because it includes information on air
releases of many hundreds of additional chemicals. Second, accessing TRI information is
extremely quick and easy. Using the TRI Explorer search engine (http ://www. epa. gov/tri/
tridata/index.htm). one may quickly identify the location of emissions sources and the identity
and quantity of chemicals released to the air. The data is also updated annually (as opposed to
the National Emissions Inventory (NEI), a nationwide inventory of emissions developed by
EPA, which is only updated triennially). However, other characteristics of the TRI data may
limit their use for risk assessments (see Section 4.4.2).
4.2.5 Toxic Chemicals That Persist and Which Also May Bioaccumulate
Some toxic compounds have the ability to persist in the environment for long periods of time
and may also have the ability to build up in the food chain to levels that are harmful to human
health and the environment. For example, releases of metals from a source may deposit out of
the air onto the ground where they remain in surface soils for long periods of time. Children
playing in the area may ingest this contaminated dirt through hand-to-mouth behaviors. The
chemicals in the dirt may also be taken up into plants through the roots and accumulate in
foraging animals.
April 2004 Page 4-6
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EPA's challenge in reducing risks from this category of toxic air pollutants stems from this
ability to transfer from air, to sediments, water, land, and food; to linger for long periods of time
in the environment; and for some substances, their ability to travel long distances. Many of
these chemicals (e.g., DDT) have been banned for use in the U.S. As such, there should be no
active air emissions of these chemicals (although releases into the air are still possible, e.g., by
resuspension of previously contaminated soil). However some, such as mercury, are still in use
today. A number of lists of these persistent and bioaccumulative chemicals have been developed
through international and internal EPA efforts (see Exhibit 4-1). A number of the HAPs appear
on one or more of these lists.
Exposure to persistent and bioaccumulative air toxics through a pathway other than inhalation of
contaminated air is termed an indirect exposure pathway because contact with the chemical
occurs in a medium that is not the original medium to which the chemical was released (i.e., air).
In contrast, a direct exposure pathway is one in which contact occurs with the chemical in the
medium to which it was originally released. When exposure of a person to a chemical (or
chemicals) occurs through more than one pathway, a multipathway analysis may be considered.
In air toxics risk assessment, the inhalation pathway is commonly assessed (i.e., the release of a
chemical to air and human exposure through breathing that air). However, indirect exposure
pathways are usually assessed for a limited set of chemicals released to the air. EPA has
identified a preliminary set of HAPs for which indirect exposure pathway analyses should
generally be conducted for situations involving significant emissions of these chemicals in a
study area. This new list of chemicals is termed Persistent Bioaccumulative HAP Compounds
(PB-HAP Compounds) (Exhibit 4-2); however, all of the PB-HAP compounds occur on one or
more of EPA's existing lists of PBT chemicals. The designation "PB-HAP" was developed to
distinguish this list from the existing lists of PBT chemicals (Exhibit 4-1) and specifically to
clarify that chemicals on this new list are:
• HAPs;
• Relatively persistent in the environment; and
• For some chemicals, have a strong propensity to bioaccumulate and/or biomagnify.(d)
This preliminary list of PB-HAPs was derived primarily on the basis of human health concerns.
It does not consider direct contact by plants or inhalation by animals. Additional HAPs may be
identified as EPA gains more familiarity with ecological risk assessments for air toxics.
Appendix D describes the process by which EPA identified the list of PB-HAPs.
Bio magnification is the process whereby certain substances transfer up the food chain and increase in
concentration. Chemicals that biomagnify tend to accumulates to higher concentration levels with each successive
food chain level. Biomagnification is a particular concern for ecological risk assessment.
April 2004 Page 4-7
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Exhibit 4-1. "Lists" of Toxic Chemicals that Persist and Which Also May Bioaccumulate
LRTAP chemicals - The United States signed protocols on Persistent Organic Pollutants (POPs) and
heavy metals pursuant to the Convention on Long-Range Transboundary Air Pollution (LRTAP) in
June 1998 at a ministerial meeting in Aarhus, Denmark. Sixteen POPs and three metals are regulated
(http ://www. epa. gov/opp fead I/in ternational/lrtap2pg. htm):
aldrin
cadmium
chlordane
dieldrin
endrin
hexabromobiphenyl
kepone (chlordecone)
mirex
toxaphene
hexachlorobenzene
heptachlor
lead
mercury
polychlorinated biphenyls (PCBs)
dichlorodiphenyltrichloroethane (DDT)
lindanedioxins (polychlorinated dibenzo-p-dioxins)
furans (polychlorinated dibenzofurans)
hexachlorobenzene
polycyclic aromatic hydrocarbons
PBT Chemicals - EPA has identified the following priority persistent, bioaccumulative, and toxic
(PBT) chemicals and has developed the PBT program to address the cross-media issues associated with
these chemicals (http://www.epa.gov/opptintr/pbt/):
aldrin/dieldrin
mercury and its compounds
benzo(a)pyrene
mirex
chlordane
octachlorostyrene
DDT
dichlorodiphenyldichloroethane (ODD)
dichlorodiphenyldichloroethylene (DDE)
PCBs
hexachlorobenzene
dioxins and furans
alky 1-lead
toxaphene
Great Lakes Priority Substances. In keeping with the obligations of the Great Lakes Water Quality
Agreement, Canada and the United States on April 7, 1997, signed the "Great Lakes Binational Toxics
Strategy: Canada-United States Strategy for the Virtual Elimination of Persistent Toxic Substances in
the Great Lakes" (http://www.epa.gov/glnpo/p2/bns.html). This Strategy seeks percentage reductions
in targeted persistent toxic substances so as to protect and ensure the health and integrity of the Great
Lakes ecosystem. The list of "Level 1" substances is identical to EPA's priority PBT pollutants.
Great Waters Pollutants of Concern. The 1990 Clean Air Act Amendments established research and
reporting requirements related to the deposition of hazardous air pollutants to the Great Lakes, Lake
Champlain, Chesapeake Bay, and certain other "Great Waters." The Program has identified the
following pollutants of concern (http://www.epa.gov/airprogm/oar/oaqps/gr8water/index.html):
cadmium and cadmium compounds
chlordane
DDT/DDE
dieldrin
hexachlorobenzene
a-hexachlorocyclohexane
lindane (y-hexachlorocyclohexane)
lead and lead compounds
mercury and mercury compounds
PCBs
polycyclic organic matter
tetrachlorodibenzo-p-dioxin (dioxins)
tetrachlorodibenzofuran (furans)
toxaphene
nitrogen compounds
April 2004
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Exhibit 4-1 (continued)
TRI PBT chemicals. EPA has published two final rules that lowered the Toxics Release Inventory
(TRI) reporting thresholds for certain persistent bioaccumulative and toxic (PBT) chemicals and added
certain other PBT chemicals to the TRI list of toxic chemicals (http ://www. epa. gov/tri/lawsandregs
/pbt/pbtrule.htm). The following PBT chemicals are subject to reporting at lowered thresholds:
dioxin and dioxin-like compounds
lead compounds
mercury compounds
polycyclic aromatic compounds
aldrin
benzo(g,h,i)perylene
chlordane
heptachlor
hexachlorobenzene
isodrin
lead
mercury
methoxychlor
octachlorostyrene
pendimethalin
pentachlorobenzene
PCBs
tetrabromobisphenol A
toxaphene
trifluralin
Waste Minimization Priority Chemicals. EPA's National Waste Minimization Partnership Program
focuses on reducing or eliminating the generation of hazardous waste containing any of 30 Waste
Minimization Priority Chemicals (WMPCs). This list replaces the list of 53 chemicals EPA identified
in 1998 (Notice of Availability: Draft RCRA Waste Minimization Persistent, Bioaccumulative and
Toxic (PBT) Chemical List, Federal Register 63(216): 60332-60343, November 9, 1998). Twenty six
of the chemicals in the current list were also in the draft list published in 1998. The remaining four
chemicals on the current list were added in response to comments and new information EPA received
from the public regarding the Agency's methodology for selecting the 53 chemicals in the draft list
(http://www.epa.gov/epaoswer/hazwaste/minimize/chemlist.htm).
1,2,4-trichlorobenzene
1,2,4,5-tetrachlorobenzene
2,4,5-trichlorophenol
4-bromophenyl phenyl ether
acenaphthene
acenaphthylene
anthracene
benzo(g,h,i)perylene
dibenzofuran
dioxins/furans
endosulfan, alpha and endosulfan, beta
fluorene
heptachlor and heptachlor epoxide
hexachlorobenzene
hexachlorobutadiene
hexachlorocyclohexane, gamma-
hexachloroethane
methoxychlor
naphthalene
PAH group (as defined in TRI)
pendimethalin
pentachlorobenzene
pentachloronitrobenzene
p entachlorophenol
phenanthrene
pyrene
trifluralin
cadmium and cadmium compounds
lead and lead compounds
mercury and mercury compounds
April 2004
Page 4-9
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Exhibit 4-2. PB-HAP Compounds
PB-HAP Compound
Cadmium compounds
Chlordane
Chlorinated dibenzodioxins and furans
DDE
Heptachlor
Hexachlorobenzene
Hexachlorocyclohexane (all isomers)
Lead compounds
Mercury compounds
Methoxychlor
Polychlorinated biphenyls
Polycyclic organic matter
Toxaphene
Trifluralin
Pollution
Prevention
Priority PBTs
X
X(a)
X
X
X(0
X
X
X(d)
X
Great Waters
Pollutants of
Concern
X
X
X
X
X
X
X
X
X
X
X
TRI PBT
Chemicals
X
X(b)
X
X
X
X
X
X
X(e)
X
X
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4.2.6 Other Chemicals
The chemicals included in the various lists of _, „„,,„, •• T.
., . The HPV Challenge Program
air toxics described above - HAPs, criteria
pollutants, TRI chemicals, and toxic
chemicals that persist and which also may
bioaccumulate - do not represent all of the
chemicals potentially emitted to air in a
given place. EPA is required to maintain an
inventory, known as the "Toxic Substances
Control Act (TSCA) Inventory," of each
chemical substance which may be legally
manufactured, processed, or imported in the
_ , _ _ . . . . \ http://www.epa.gov/chemrtk/rtkfacts.htm.
U.S. The TSCA inventory currently contains —
EPA, in partnership with industry and environmental
groups, recently created a voluntary chemical testing
effort, the high production volume (HPV) Challenge
Program. This program was developed to make
publicly available a complete set of baseline health and
environmental effects data on HPV chemicals (those
manufactured in, or imported into, the United States in
amounts equal to or exceeding 1 million pounds per
year). Information on HPV chemicals is available at
over 75,000 chemicals (see: "enforcement
programs" at http://www.epa.gov/compliance/civil/programs/tsca/). At best, we have the
capability to assess only a few hundred in detail. As noted previously, this does not imply that
risk assessments are always missing important information. To the contrary, the actual number
of chemicals used in significant amounts and released to air are relatively small compared to the
number of chemicals known. Nevertheless, it is important to keep in mind that the ability to
evaluate air toxics releases is limited by current technology, the lack of toxicity information for
all but a relatively small number of chemicals and, in some cases, costs (e.g., a single sample for
certain analytes such as dioxin can cost upwards of $1,000 per sample, making multiple
sampling events cost prohibitive).
4.3 Sources of Air Toxics
Many anthropogenic and natural activities are sources of air pollutants. Examples of human
activities that result in the release of air toxics include:
• Fuel combustion activities in power plants, factories, automobiles, and homes;
• Biomass burning and other agricultural activities;
• Use of consumer products, such as pesticides and cleaning agents;
• Commercial activities, such as dry cleaning; and
• Industrial activities, such as petroleum refining, chemical manufacture, and metal plating.
Sources of air toxics can be categorized in various ways - whether they occur indoors or out,
whether they are stationary or mobile, by the amount of chemicals they release, or by other
approaches. For the purposes of this discussion, air toxics have been placed into several major
groupings that track EPA's programs and emissions inventories. Note that some differences in
terminology exist between the CAA and the NEI (Exhibit 4-3).
• Point sources;
• Nonpoint sources;
• On-road mobile sources;
• Nonroad mobile sources;
• Indoor sources;
• Natural sources; and
• Exempt sources.
April 2004 Page 4-11
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The first four categories are groupings of emission sources of HAPs and criteria air pollutants in
EPA's National Emissions Inventory (NEI). The NEI is a nationwide inventory of emissions
that has been developed by EPA with input from numerous state, local, and tribal (S/L/T) air
agencies. The NEI is discussed in more detail as a source of quantitative emissions release data
in Section 4.4.1 below. For detailed information on NEI, refer to EPA's main NEI web page.(5)
NEI summaries were posted in October 2003.
Exhibit 4-3. Terminology Related to Groupings of Source Types
Source Type
Point source - Major
Point source - Area
Nonpoint source
Mobile source - On-road
Mobile source - Nonroad
Indoor
Natural
Exempt
How Defined in CAA
Point source - Major
Point source - Area
Nonpoint source
Mobile source - On-road
Mobile source - Nonroad
Not defined
Not defined
Not defined
How Reported in NEI
Point source
Point source if location coordinates reported
Area source if coordinates not reported
Area
Modeled
Modeled or estimated
Not reported
Not reported
Not reported
4.3.1 Point Sources
Point sources of air toxics are stationary sources (i.e., sources that remain in one place) that can
be located on a map. A large facility that houses an industrial process is an example of a point
source - the facility and its emission release points (e.g., stacks, vents, fugitive emissions from
valves) are stationary, and the emission rates of air toxics can be characterized, either through
direct measurements, such as stack monitoring, or indirect methods, such as engineering
estimates based on throughput, process information, and other data. The CAA divides point
sources into two main categories primarily on the basis of annual emissions rates:
• Major sources are defined in Section 112(a)(l) as "any source or group of stationary sources
located within a contiguous area and under common control that emits or has the potential to
emit, considering controls, in the aggregate, 10 tons per year (tpy) or more of any hazardous
air pollutant or 25 tpy or more of any combination of hazardous air pollutants."
• Area sources are defined in Section 112(a)(2) as "any stationary source of hazardous air
pollutants that is not a major source. For purposes of this section, the term 'area source'
shall not include motor vehicles or nonroad vehicles subject to regulation under Title II."
Examples of area sources include dry cleaners, gas stations, chrome electroplaters, and print
shops. Though emissions from individual area sources may be relatively insignificant in
human health terms, collectively their emissions can be quite significant, particularly where
large numbers of sources are located in heavily populated areas. Note that sources that are
classified as "area sources" pursuant to the CAA may be reported in the NEI as "point
sources" if they can be located on a map.
April 2004
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Many sources of HAPs are subject to National Emission Standards for Hazardous Air
Pollutants (NESHAPs) pursuant to Section 112 of the CAA. This Section of the CAA directs
EPA to issue regulations listing categories and subcategories (commonly referred to collectively
as source categories) of major sources and area sources of HAPs and to develop standards for
each listed category and subcategory.(6) EPA periodically updates the list of source categories
(see Appendix E).(7)
Physical Forms of Emissions
Gas Emissions that are distinguished from solid and liquid states
Fume Tiny particles trapped in vapor in a gas stream
Mist Liquid particles measuring 40 to 500 micrometers that are formed by
condensation of vapor
Particulate Matter (and Fine liquid or solid particles
Aerosols)
Air pollutants can be found in all three physical phases: solid, liquid, or gaseous. The distinct
chemical and physical attributes of each phase contribute to the pollutant's transport and fate. For
example, as reported in the Mercury Study Report to Congress,^ elemental mercury vapor is not
thought to be susceptible to any major process of direct deposition to the earth's surface due to its
relatively high vapor pressure and low water solubility. Therefore, it is carried by the wind and
subsequently dispersed throughout the atmosphere. However, divalent mercury, in either vapor or
particulate phase, is thought to be subject to much faster atmospheric removal, and is expected to be
deposited near its source. For further details on fate and transport analysis, see Chapter 8.
As noted in Chapter 2, EPA regulates stationary sources in a two-phase process. First, EPA
issues technology-based MACT standards that require sources to meet specific emissions limits.
The emission limits are typically expressed as maximum emission rates, or minimum percent
emission reductions, for specific pollutants from specific processes. In the second phase, EPA
applies a risk-based approach to assess how well MACT emissions limits reduce health and
environmental risks. Based on these residual risk assessments, EPA may implement additional
standards to address any significant remaining, or residual, health or environmental risks (see
Chapter 2 for a more detailed discussion of the MACT and residual risk programs).
Area sources maybe subject to either MACT or Generally Available Control Technology
(GACT) standards. GACT standards are generally less stringent than MACT standards. Area
sources subject to MACT standards include Commercial Sterilizers using Ethylene Oxide,
Chromium Electroplaters and Anodizers, Halogenated Solvents Users, and Asbestos Processors.
4.3.2 Nonpoint Sources
The term nonpoint source refers to smaller and more diffuse sources within a relatively small
geographic area. In the context of EPA's NEI, nonpoint sources of air toxics are stationary
sources for which emissions estimates are provided as an aggregate amount of emissions for all
similar sources within a specific local geographic area, such as counties or cities, rather than on a
facility- or source-specific basis. Emission estimates for nonpoint sources are generated using
"top-down" methods, when detailed information at the local level is lacking. Instead, the total
emissions over a large geographic area (e.g., n tons in the northeastern states) are allocated to the
April 2004 Page 4-13
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local level (e.g., x percent is assigned to locality 1, y percent is assigned to locality 2, and so on).
Note that for the purposes of this discussion, the nonpoint source category includes only
stationary sources and does not include mobile sources.
Source-specific information maybe available for some (but not all) of the specific facilities
within a certain nonpoint source type. Area sources may be reported as either point or nonpoint
sources in the NEI. If a state or local agency reports an area source emission as a point source,
then the NEI retains the area source emission as a point source. The NEI does not aggregate
point area sources as nonpoint sources, and EPA has taken steps to avoid "double-counting"
of emissions in the point and nonpoint source inventories.
To compile nonpoint estimates for a category, the EPA first estimates county level emissions for
nonpoint source categories. Then EPA replaces nonpoint EPA generated estimates with state
and local agency and tribal estimates. If a state or local agency or tribe includes point source
estimates for an EPA generated nonpoint source category, EPA removes the nonpoint estimate
that it had generated and the point source inventory contains the S/L/T estimate. For example, in
the Denver area, the State of Colorado inventories dry cleaners and service stations as point
sources. The NEI contains point sources estimates for these two categories in the six county area
of Denver and the NEI does not contain nonpoint estimates for these two categories. Dry
cleaners and service station emissions are contained in the NEI nonpoint inventory for the other
fifty counties on Colorado.
A variety of sources are categorized as nonpoint sources in the NEI, including some small
industrial/commercial processes (e.g., small dry cleaning facilities, hospital sterilization
facilities, and dental offices). Additional nonpoint sources that contribute to air pollution are
agricultural activities, residential trash and yard-waste burning, wood stoves and fireplaces,
releases from spills and other accidents, and volatilization and resuspension of pollutants from
contaminated sites. Examples of agricultural activities contributing to air pollution are biomass
burning (e.g., for land clearing) and the application of fertilizers and pesticides. The open
burning of forests (including wildfires) are also categorized as nonpoint sources. (Note that
forest fires are generally considered for the purposes of the NEI to be an anthropogenic source of
air toxics because they are assumed to be directly or indirectly, for purposes of the NEI, caused
by man.)
Some nonpoint sources emit HAPs and are subject to NESHAPs pursuant to Section 112 of the
CAA (see Section 4.3.1 above for more information on NESHAPs). These nonpoint sources are
area sources in that they emit less than 10 tpy of a single air toxic or less than 25 tpy of a mixture
of air toxics. For example, facilities that perform perchloroethylene dry cleaning belong to a
source category that is subject to NESHAPs.
4.3.3 On-Road and Nonroad Mobile Sources
Mobile sources pollute the air with fuel combustion products and evaporated fuel. These sources
contribute greatly to air pollution nationwide and are the primary cause of air pollution in many
urban areas. Section 202(1) of the CAA gives EPA the authority to regulate air toxics from
motor vehicles. Based on 1996 National Toxics Inventory data (the NTI is the former name of
the air toxics portion of the current NEI), mobile sources contributed 2.3 million tpy or about
half of all air toxics emissions in the U.S. Mobile sources emit hundreds of air pollutants - for
example, exhaust and evaporative emissions from mobile sources contain more than 700
April 2004 Page 4-14
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compounds. EPA's Final Rule, Control of Emissions of Hazardous Air Pollutants from Mobile
Sources, commonly known as the "Mobile Source Air Toxics" (MSAT) rule,(9) identified 21
compounds as HAPs emitted by mobile sources (see Chapter 2). All of these compounds except
diesel particulate matter and diesel exhaust organic gases (DPM + DEOG) are included on the
CAA Section 112 HAPs list. Although some mobile source air toxics are TRI chemicals, mobile
sources are not generally subject to TRI reporting. Other mobile source regulations address
emissions of criteria pollutants and their precursors, including carbon monoxide (CO), nitrogen
dioxide (NO2), particulate matter (PM), volatile organic compounds (VOCs), and sulfur dioxide
(SO2). These criteria air pollutant control programs for mobile sources have and will continue to
result in substantial reduction of HAP releases.
Mobile sources include a wide variety of vehicles, engines, and equipment that generate air
pollution and that move, or can be moved, from place to place. In the NEI, EPA divides mobile
sources into two broad categories. On-road mobile sources include motorized vehicles that are
normally operated on public roadways for transportation of passengers or freight. This includes
passenger cars, motorcycles, minivans, sport-utility vehicles, light-duty trucks, heavy-duty
trucks, and buses. Nonroad mobile sources, (sometimes also called "off-road") include aircraft,
commercial marine vessels (CMVs), locomotives, and other nonroad engines and equipment.
The other nonroad engines and equipment included in NEI comprise a diverse list of portable
equipment, such as lawn and garden equipment; construction equipment; engines used in
recreational activities; and portable industrial, commercial, and agricultural engines.
EPA's National Air Pollutant Trends Report, 1900-1998(10) indicates that about 60 percent of
mobile source air toxics emissions in the U.S. are from on-road sources, and 40 percent of
mobile source air toxics emissions are from nonroad sources. The emissions distribution
between on- and off-road sources emitting criteria pollutants depends on the chemical. CO
comprises the majority of criteria pollutants emitted, with over 100 million tons per year emitted
in the U.S. Releases of CO are primarily the result of mobile sources - like HAPs, these
emissions are split approximately 60/40 between on-road and off-road sources. (The use of CO
as a monitoring surrogate for mobile source emissions is discussed in Section 4.4.1.)
Within the two broader categories of mobile sources, EPA further distinguishes on-road and
nonroad sources by size, weight, use, horsepower and/or fuel type. For example, categories of
on-road vehicles include light-duty gasoline vehicles (i.e., passenger cars), light-duty gasoline
trucks, heavy-duty gasoline vehicles, and diesel vehicles. Examples of nonroad sources include
nonroad gasoline engines and vehicles, (e.g., recreational off-road vehicles, construction
equipment, lawn and garden equipment, and recreational marine vessels that use gasoline),
nonroad diesel engines and vehicles (including the vehicles and equipment listed above, except
those that use diesel fuel), aircraft, non-recreational marine vessels, and locomotives. An
additional category covers all nonroad sources that use liquified petroleum gas or compressed
natural gas.
4.3.4 Sources Not Included in the NEI or TRI
In addition to the four primary categories used in compiling the NEI, five other sources of air
toxics which are not captured by either the NEI or TRI are described below: Indoor sources,
natural sources, secondary formation of air toxics, exempt sources, and international transport.
April 2004 Page 4-15
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4.3.4.1 Indoor Sources
Indoor pollution sources that release gases or particles into the air are the primary cause of
indoor air quality problems in homes (Exhibit 4-4). Inadequate ventilation can increase indoor
pollutant levels by not bringing in enough outdoor air to dilute emissions from indoor sources
and by not carrying indoor air pollutants out of the home. High temperature and humidity levels
indoors can increase the uptake of some pollutants, thereby magnifying negative health effects.
There are many sources of indoor air pollution in any home. These include combustion sources
such as oil, gas, kerosene, coal, wood, and tobacco products; building materials and furnishings
as diverse as deteriorated, asbestos-containing insulation, wet or damp carpet, and cabinetry or
furniture made of certain pressed wood products; products for household cleaning and
maintenance, personal care, or hobbies; central heating and cooling systems and humidification
devices; and outdoor sources such as radon, pesticides, and outdoor air pollution.
The relative importance of any single source depends on how much of a given pollutant it emits
and how hazardous those emissions are. In some cases, factors such as how old the source is and
whether it is properly maintained are significant. For example, an improperly adjusted gas stove
can emit significantly more carbon monoxide than one that is properly adjusted.
Some sources, such as building materials, furnishings, and household products like air
fresheners, release pollutants more or less continuously. Other sources, related to activities
carried out in the home, release pollutants intermittently. These include smoking, the use of
unvented or malfunctioning stoves, furnaces, or space heaters, the use of solvents in cleaning and
hobby activities, the use of paint strippers in redecorating activities, and the use of cleaning
products and pesticides in housekeeping. High pollutant concentrations can remain in the air for
long periods after some of these activities.
In addition to the same indoor air problems as single-family homes, apartments can have indoor
air problems similar to those in offices, which are caused by sources such as contaminated
ventilation systems, improperly placed outdoor air intakes, or maintenance activities.
One particularly important indoor air toxics problem actually results from an outdoor natural
source. In fact, radon gas, a HAP, is one of the leading causes of lung cancer in the U.S. The
most common source of indoor radon is uranium in the soil or rock on which homes are built
(thus, a natural source becomes an indoor air quality problem). As uranium naturally breaks
down, it releases radon as a colorless, odorless, radioactive gas. Radon gas enters homes
through dirt floors, cracks in concrete walls and floors, floor drains, and sumps. When radon
becomes trapped in buildings and indoor concentrations build up, exposure to radon becomes a
concern.
Sometimes radon enters the home through well water. In a small number of homes, the building
materials can give off radon, too. However, building materials alone rarely cause radon levels of
concern (see http://www.epa.gov/radon/risk_assessment.html for more information on radon
risks). Exhibit 4-5 shows EPA's map of radon zones in the U.S.
April 2004 Page 4-16
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Exhibit 4-4. Major Indoor Air Pollutants and their Sources
Major Indoor Air Pollutants
Radon (Rn)
Environmental Tobacco Smoke
(includes carbon monoxide,
nitrogen dioxide, and respirable
particles)
Biologicals (e.g., pollen, mold,
animal dander, and fungi)
Carbon Monoxide
Nitrogen Dioxide (NO2)
Volatile Organic Compounds
(such as xylene)
Respirable Particles
Formaldehyde
Pesticides
Asbestos
Lead
Sources
Earth and rock beneath home; well water; building materials
Cigarette, pipe, and cigar smoking
Wet or moist walls, ceilings, carpets, and furniture; poorly
maintained humidifiers, dehumidifiers, and air conditioners;
bedding; household pets
Unvented kerosene and gas space heaters; leaking chimneys and
furnaces; back-drafting from furnaces, gas water heaters,
woodstoves, and fireplaces; gas stoves. Automobile exhaust from
attached garages
Kerosene heaters, unvented gas stoves and heaters. Environmental
tobacco smoke
Paints, paint strippers, and other solvents; wood preservatives;
aerosol sprays; cleansers and disinfectants; moth repellents and air
fresheners; stored fuels and automotive products; hobby supplies;
dry-cleaned clothing
Fireplaces, wood stoves, and kerosene heaters. Environmental
tobacco smoke
Pressed wood products (hardwood plywood wall paneling, particle
board, fiberboard) and furniture made with these pressed wood
products. Urea- formaldehyde foam insulation (UFFI). Combustion
sources and environmental tobacco smoke. Durable press drapes,
other textiles, and glues
Products used to kill household pests (insecticides, termiticides,
and disinfectants). Also, products used on lawns and gardens that
drift or are tracked inside the house
Deteriorating, damaged, or disturbed insulation, fireproofing,
acoustical materials, and floor tiles
Lead-based paint, contaminated soil, dust, and drinking water
Source: U.S. Environmental Protection Agency and the United States Consumer Product Safety
Commission. 1995. Office of Radiation and Indoor Air (6604J) EPA/402/K/93/007, April 1995.
Available at: http://www.epa.gov/iaq/pubs/insidest.html.
April 2004
Page 4-17
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Exhibit 4-5. EPA Map of Radon Zones
\T^
** Zor
Guam - Preliminary
Zone Designation
Zone designation for Puerto Rico is under development.
The purpose cf this map is to assist National, Stale, and local organizations to target Iheir
resources and to implement radon-rs-sistant building codes. Thrs map is not intended Co be used
to determine if a home in a giver ?nne should be tested for radon Homes *ith elevated V:vhrr.
of radon nave been found in all three zones All homes should be tested regardless '
geographic location.
IMPORTANT: Consult the EPA Map of Radon Zones document (EPA-402-R-93-071) before using this map. This document
contains information on radon potential variations within counties EPA also recommends that this map he supplemented
mith any available local data in order to further understand and predict the radon potential of a specific area
Zone 1 counties have a predicted average indoor radon screening level greater than 4 pCi/L (pico
curies p er liter)
Zone 2 counties have a predicted average indoor radon screening level between 2 and 4 pCi/L
Zone 3 counties have a predicted average indoor radon screening level less than 2 pCi/L
4.3.4.2 Natural Sources
Natural processes are significant sources of some air pollutants, including VOCs, NOX, O3, PM
and other pollutants (Exhibit 4-6). Examples of natural sources of air pollutants that are not
covered by the four main categories described above include natural processes occurring in
vegetation and soils (e.g., emissions from trees), in marine ecosystems, as a result of geological
activity in the form of geysers or volcanoes, as a result of meteorological activity such as
lightning, and from fauna, such as ruminants and termites. Sources associated with biological
activity are called biogenic sources.
Natural pollutants contribute significantly to air pollution. For example, biogenic emission
estimates for the United States were 28.2 million tons of VOC and 1.53 million tons of NOX in
1997.00)
April 2004
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Exhibit 4-6. Categories of Natural Sources
Category
Geological
Bio genie
Marine
Examples of Emissions
• Sulphuric, hydrofluoric and hydrochloric acids
• Radon
• Nitrogen oxides
• Ammonia
• Methane
• VOCs
• Dimethyl sulfide, ammonia, chlorides, sulfates,
alkyl halides, nitrous oxides
Sources
• Volcanic gases
• Radioactive decay of rock
• Soils, lightning
• Animals wastes
• Animal wastes, plant decay
• Vegetation
• Sea spray released by
breaking waves
Source: International Fertilizer Industry Association. 2001. Food and Agriculture Organization of the
United Nations. Global estimates of gaseous emissions ofNH3, NO and N2O from
agricultural land. ISBN 92-5-104698-1. Available at:
www.fao.org/DOCREP/004/Y2780E/v2780e01.htm.
4.3.4.3 Formation of Secondary Pollutants
Some air pollutants, in addition to being directly emitted to the atmosphere by identifiable
sources, are generated in the atmosphere by the chemical transformation of precursor compounds
(a process called secondary formation). For example, under some meteorological conditions,
up to 90 percent of ambient formaldehyde originates from secondary formation from a variety of
precursor compounds in the presence of light (i.e., via a photochemical reaction). Some of the
precursor compounds include isoprene (an organic compound released from trees), isobutene,
and propene. The secondary formation of pollutants like formaldehyde and acetaldehyde is a
complex process but can be estimated by some photochemical models (e.g., UAM-Tox, a special
version of the Urban Airshed Model (UAM)). Other available models also address secondary
formation but in a much more limited way (see Chapter 9 for a more detailed discussion of air
models).
The NEI and other emission inventories generally do not include estimates of pollutants formed
through secondary formation - only the initially emitted species are included. Because the
formation of secondary pollutants depends on the meteorological conditions and the presence or
absence of other compounds and/or light, a model that incorporates chemical transformation
algorithms is required to estimate how much secondary product is formed from precursor
compounds once they enter the atmosphere. EPA has in some instances developed estimates of
secondarily formed chemicals to better inform the assessment of exposure of people to toxic air
pollutants. For example, for the 1996 NAT A, National-scale Air Toxics Assessment, risk
characterization exercise, EPA developed a special inventory of precursor compounds to
supplement the NTI, which was used in conjunction with the Assessment System for Population
Exposure Nationwide (ASPEN) model to calculate ambient concentrations (see
http://www.epa.gov/ttn/atw/nata/). Formation of secondary pollutants is discussed in greater
detail in Chapter 8.
April 2004
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4.3.4.4 Other Sources Not Included in NEI or TRI
Many air toxics sources, usually relatively small ones, may not be covered or are exempt from
various emissions control, reporting, and other requirements, and in some cases the number or
stringency of requirements is tiered according to source size or other criteria. For example, air
pollution regulations for municipal waste combustors (MWCs) promulgated pursuant to Section
129 of the CAA include separate rules for large MWCs (i.e., with capacities greater than 250
tons per day) and small MWCs (i.e., with capacities between 35 and 250 tons per day).
However, there are no rules for MWCs with capacities less than 35 tons per day.
Other miscellaneous sources of air pollution T , „ , A. „ .
., .,.,,., International Transport ol Air Toxics
(e.g., agricultural and residential burning) are
As noted earlier in Chapter 2 and Section 4.2.5,
certain air toxics may be transported over long
distances, sometimes across international borders.
International sources may be an important
contributor to local pollutant levels in some study
areas.
controlled primarily by other S/L/T
requirements. However, EPA conducts
research, provides information, and pursues
other non-regulatory means of addressing
some of these pollution sources. For
example, EPA, in conjunction with the
Consumer Product Safety Commission and "* '
the American Lung Association, has
published a guide for reducing pollution from residential wood combustion, including design
information for less-polluting stoves and fireplaces.(11) Some local areas have ordinances that
require new fireplace and wood stove installations to comply with the certification program, and
others have ordinances that prohibit the use of a wood stove or fireplace on days that are
conducive to the concentration of wood smoke emissions.
Ultimately, there is no single comprehensive source of information on all sources of air toxics in
a given area. The NEI and TRI are good places to start an investigation of what is being released
in a study area, but as noted above, in any given place, there are probably a number of air toxics
sources that are not accounted for in these inventories. Nonregulated sources, natural sources,
and material moving into a study area from distant sources all have an impact on overall air
quality. Assessors need to clearly understand what these limitations are as they move into the
planning and scoping stage of the risk assessment (see Chapter 6). (A description of how EPA
addressed background concentrations for the NATA national-scale assessment is provided at
http ://www. epa. gov/ttn/atw/nata/natsa2 .html.)
4.4 Emissions Inventories
As mentioned previously, information on releases of air toxics is primarily compiled and
maintained in emissions inventories. The primary emission inventory for HAPs and criteria
pollutants is EPA's NEI. EPA's TRI is a second inventory that has some utility for planning
and scoping an air toxics risk assessment, but is of limited use for risk assessment because of the
nature of the way the data are reported. In addition to the NEI and the TRI, S/L/T air agency
permit files and, in some instances, S/L/T inventories that have been developed, but not
submitted to the NEI, can also provide information on the location, identity, magnitude, and
source characteristics of air toxics releases.
The best inventory data are collected near the ground, literally at the source. For example, an
urban scale study might opt to do a "drive by" or "windshield" verification of the number and
April 2004 Page 4-20
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location of dry cleaners and gas stations in the study area rather than rely on an aggregate
county-level estimate. Ultimately, the needs of the assessment (e.g., screening level or more
refined) will determine the level of accuracy needed in the emissions inventory. This section
will describe the NEI and the TRI. Other potential sources of air toxics data are described in
Chapter 7. The process of developing an emissions inventory is also described in Chapter 7.
4.4.1 National Emissions Inventory (NEI)
EPA's Office of Air and Radiation compiles and maintains the National Emissions Inventory
(NEI) that includes quantitative data on anthropogenic emissions of criteria pollutants and HAPs
and characteristics of the sources of these air toxics.(5) It includes point, non-point, and mobile
sources for all 50 states, Washington, B.C., and U.S. territories.
Previously, emissions of criteria pollutants and HAPs were tracked separately by EPA in
databases that preceded the NEI. Criteria pollutant emissions data for 1985 through 1998 are
available in the National Emission Trends (NET) database. Hazardous air pollutant (HAP)
emissions data are available for 1993 and 1996 in the National Toxics Inventory (NTI) database.
For 1999 (the most recent year for which data are available), criteria and HAP emissions data
have been prepared separately but in a more integrated fashion. The final version of both the
criteria and HAP inventories (for 1999) are available at http://www.epa.gov/ttn/chief/net/
1999inventory.html. Note that the data collection and processing requirements for this
undertaking are significant. As such, EPA plans to update the NEI every three years.
The NEI inventories are developed by EPA's Emission Factors and Inventories Group with input
from S/L/T agencies, industry, and a number of EPA offices. In some cases, if a S/L/T agency
does not submit data, EPA may use data from an earlier year and "grow" the emissions (e.g., for
criteria stationary sources) or use only data available from other sources (e.g., HAP collected by
EPA as part of the development of emission standards, or data submitted by sources under the
Toxics Release Inventory program). Separate inventory documentation files have been prepared
for each part of NEI (i.e., for criteria pollutants and HAPs, and for point, nonpoint, and mobile
sources). These detailed documentation files are available online for criteria pollutants(12) and
HAPs.(13) The reader should refer to these documentation files for detailed information on NEI.
Summaries of data sources for the components of the current version of NEI are also provided
below.
An important fact to keep in mind about the NEI is that it includes data on HAPs from both
small and large stationary sources and both on- and off-road mobile sources. Equally important,
it is much more likely to include the data necessary for modeling (although many of the data
fields needed for modeling are not "mandatory," and thus states are not required to provide this
information to the NEI). Information such as stack height, emission rate, and temperature are
critical to developing reasonably accurate estimates of human exposure in the areas surrounding
a source. It is for this reason that the NEI can be of more use than other databases, for example,
for getting a better handle on realistic exposure and risk estimates in an actual study.
NEI for HAPs - Point Sources. For the NEI for HAP emissions from point sources, S/L/T
agencies are asked to supply HAP emission inventory data to EPA. If they do not provide HAP
emission inventory data to EPA, then EPA prepares default emission inventory data (this has
been done for the 1993, 1996, and 1999 inventory years). As discussed previously, EPA uses a
variety of methods to develop data and fill in gaps, where necessary (for point sources of HAPs,
April 2004 Page 4-21
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EPA uses S/L/T data, EPA estimates for MACT and source categories, and TRI data; all the TRI
facilities are in the NEI). This is one reason why the NEI provides, for some sources, data that
may not accurately reflect actual emissions in any given place. Depending on a study's specific
data quality objectives, closer inspection and verification of emissions estimates maybe
necessary.
The target area for the NEI includes every state and territory in the United States and every
county within a State. There are no boundary limitations pertaining to traditional criteria
pollutant nonattainment areas or to designated urban areas. If a facility was included in a S/L/T
database, it is included in the NEI regardless of where in the state it was located. The pollutants
inventoried included all 188 HAPs identified in Section 112(b) of the CAA. Some S/L/T
agencies collect information on more than just these HAPs, but only the 188 are included in the
HAP NEI. In addition to numerous specific chemical species and compounds, the list of 188
HAPs includes several compound groups (e.g., individual metals and their compounds,
polycyclic organic matter [POM], and glycol ethers); the NEI includes emission estimates for the
individual compounds within these groups wherever possible. Appendix F lists all of the
specific pollutants and compound groups included in the 1999 NEI along with their Chemical
Abstract Services (CAS) numbers (for individual compounds).
NEI for Criteria Pollutants - Point Sources. For the NEI for criteria emissions from point
sources, EPA solicits point source data from S/L/T governments. EPA uses S/L/T point source
data preferentially, except for NOX and SCh emissions from utilities. For utilities, EPA uses NOX
and SCh emissions that facilities report to the Emissions Tracking System/Continuous Emissions
Monitoring (ETS/CEM) Scorecard database. Some other criteria pollutant emissions data in the
most recent version of NEI have been supplemented by EPA based on submissions to other
emissions databases. In addition, emissions of ammonia (NH3) (which is not a criteria pollutant,
but is a precursor for PM) have been added to NEI based on reports submitted by S/L/T offices,
TRI data, and (for locations where reports were not submitted) also based on EPA estimation
methods.
Nonpoint Sources (Both HAPs and Criteria Pollutants). Much of the nonpoint source data in
NEI for HAPs was initially compiled as a national-level inventory. National-level emission
estimates are spatially allocated to the county-level using a number of allocation factors, such as
population and employment within certain industries. For example, aggregate amounts of dry
cleaner emissions for a county might be estimated from the number of people living within a
county. For HAPs, EPA uses MACT data and S/L/T data, where available.
When S/L/T- or locality-specific emissions data are available, those data are substituted for data
that had been allocated from national emission estimates. EPA prepares emissions for several
area source categories for the NEI each year using the most current activity and emission factor
data available. Emissions for other area source categories for which methodologies were not
prepared in a given year are extrapolated (and assumed to increase some percentage each year)
from the most recent S/L/T inventory submitted previously to EPA. For example, if an
inventory was submitted in the past 3 years to EPA for the 1996 base year, the 1999 NEI
emissions are extrapolated from the 1996 inventory. In some cases, criteria air emissions may
also be extrapolated from other inventories (e.g., the 1985 National Air Pollutant Assessment
Program inventories). A more detailed discussion of emissions estimation routines for source
categories with national-level emission estimates are described in the documents referenced
above.
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EPA uses an emissions estimation model known as the Biogenic Emissions Inventory System
(BEIS) to predict emissions of VOC andNOx from forests, crop lands, and fertilized lands.
Emission rates are dependent on several meteorological factors. VOC emissions are dependent
on temperature and sunlight, and NOX emissions from fertilized soils are dependent on
temperature and soil moisture. The BEIS model is used to predict emissions that are included in
the NEI inventory for criteria pollutants. (Keep in mind that VOCs, as a group, are inventoried,
but not speciated, to help evaluate an area's potential for ozone production. Non-speciated VOC
data are of limited use for performing air toxics risk assessments.)(e)
On-road Mobile Sources. In the final Version (V 3.0) of the 1999 NEI, EPA used the most
recent version of the MOBILE6 (Version 6.2) model to calculate emission factors for criteria
pollutants and 36 HAPs. On-road emissions inventories for CO, NOX , VOC, PM10, PM2 5, SO2,
NH3, and the 36 HAPs are calculated by multiplying an appropriate emission factor in grams
emitted per mile by the corresponding vehicle miles traveled (VMT) in millions of miles, and
then converting the product to units of tons of emissions. Emission estimates include
calculations by month, county, road type, and vehicle type, with VOC broken down by exhaust
and evaporative emissions and PM10 and PM2 5 broken down by exhaust, brake wear, and tire
wear emissions. The MOBILE6 model used is the publicly available version from EPA's Office
of Transportation Air Quality's (OTAQ) Website (http://www.epa.gov/otaq/m6.htm). This
model incorporates both MOBILE6.0, which is used to estimate emission factors of VOC, CO,
and NOX , and MOBILE6.1, which is used to calculate emission factors of PM10, PM25, SO2 and
NH3 and MOBTOX, which is used to calculate certain HAPs. The particulate and SO2 emission
factors were previously calculated using EPA's PARTS model.
Nonroad Mobile Sources. To develop this component of the NEI, data were compiled on
criteria and HAP emissions data for aircraft, commercial marine vessels, and locomotives. HAP
emissions for other nonroad engines operating in the United States were estimated using the
latest nonroad model. S/L/T data are used when provided. In this effort, national emission
estimates were often developed for each of the above types of nonroad sources and allocated to
counties based on available Geographic Information System (GIS) data. For some pollutants
associated with the nonroad category, county-level (instead of national) data were used to
estimate emissions. The methodologies used to estimate emissions and the procedures used to
spatially allocate them to the county level vary by source category and pollutant. For some
pollutants and categories, the NONROAD model was utilized to estimate emissions (see
http://www.epa.gov/otaq/nonrdmdl.htm).
Concurrent with the development of the national emission estimates, S/L/T agencies developed
and provided to EPA emissions inventory data for their areas based on local knowledge and
activity information. These S/L/T agency data replaced the national emission estimates when
the pollutant, source type, and emission type matched with the national estimates. Submitted
S/L/T data that did not match the nationally-derived data were retained along with the national
estimates. S/L/T data were used as provided and not adjusted to better match the national data.
Some S/L/T inventories did not provide estimates for all of the pollutants included in the
"Volatile Organic Compound means any organic compound which participates in atmospheric
photochemical reactions; or which is measured by a reference method, an equivalent method, an alternative method,
or which is determined by procedures specified under any subpart (40 CFR Part 60).
April 2004 Page 4-23
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nationally-derived emission estimates; in these cases, the submitted S/L/T data were used and
the national estimates were included only for the missing pollutants.
Although the current NEI data files represent a valuable source of emissions data, there are
numerous uncertainties associated with the current versions of these inventories that should be
considered when using the data in a risk assessment. Sources of uncertainty include the
following:
• The emission data included in NEI are of variable, and in some cases, undocumented
derivation. Many of the emission estimates were submitted by the sources of the emissions
to S/L/T air agencies, and then to EPA, without full explanations of how the emissions were
estimated.
• Not all sources are accounted for. In some S/L/T data sets, very small sources have been
reported, while in others only the largest sources in certain types of industry are included.
• Not all S/L/T agencies have submitted data. Specifically, for the NEI for criteria pollutants,
35 out of 50 states submitted data to EPA for the 1999 version of NEI. For the other states,
EPA extrapolated the affected portions of the inventory from an earlier year. This omits
sources that came online in the target year and erroneously include sources that have shut
down. For more information on which S/L/T governments submitted data and for which
states the inventory is extrapolated, the user can refer to the documentation for the respective
inventory sector and the respective pollutant type (see website addresses above). Some of
the states for which 1999 data were not available when these inventory versions were
compiled have now provided EPA with their data, and EPA is working to incorporate this
data into the next versions. For HAPs, 46 states have participated in the development of the
1999 NEI (with some revisions from states still under way).
• Duplicate facilities maybe present, but most of the duplicates have been removed. Facility
identification (ID) codes are a potential source of confusion. The NEI Unique Facility ID is
the ID for the entire facility, while the state IDs are usually for individual processes;
therefore an NEI Unique Facility ID can have multiple state facility IDs.
• The primary source of uncertainty associated with the inventory is the methodology used to
generate the emission estimates. The emission estimation methodology is often poorly
documented in the NEI Input Format - this data field is not mandatory. Data in the 1999 NEI
for HAPs are made using different estimation methods. Future versions of the NEI will
include a data quality rating to each emissions record, which should help characterize the
quality of the emissions estimate.
Emissions data in the NEI are submitted to EPA according to the NEI Input Format (NIF)
Shell (see http://www.epa. gov/ttn/chief/nif/index.html). This format consists of data fields
grouped into tables that provide the basic structure of NEI. The NIF shell consists of eight tables
for point sources, five tables for area sources, three tables for mobile sources, and two tables for
biogenic sources. EPA has developed data element descriptions and data element validation
rules to enforce mandatory data fields and relationships between the various tables and records
of the NIF. As the NEI has evolved (and continues to be improved and developed), the NIF shell
has evolved as well. Version 3.0 of the NIF shell was released in May 2003 and updated in
November 2003.
April 2004 Page 4-24
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In June 2002, EPA promulgated the final Consolidated Emissions Reporting Rule,(14) which
simplifies and consolidates emission inventory reporting requirements (for criteria air pollutants
only) to a single location within the Code of Federal Regulations (CFR), establishes new
reporting requirements related to PM2 5 and regional haze, and establishes new requirements for
the statewide reporting of area source and mobile source emissions. Many state and local
agencies asked EPA to take this action to consolidate reporting requirements; improve reporting
efficiency; provide flexibility for data gathering and reporting; and better explain to program
managers and the public the need for a consistent inventory program. Consolidated reporting
should increase the efficiency of the emission inventory program and provide more consistent
and uniform data.
In conjunction with the NIF shell, EPA has developed an automated software program to help
NIF users perform quality assurance/quality control (QA/QC) checks on their files to ensure
correct format specification. This software, available for download from the NIF shell web
page, separates QA/QC checks into format and content. Format checks ensure that the submitted
information includes the minimum data elements required for Emission Factor and Inventory
Group (EFIG) to accept the submitted data. Content checks are provided for the user as a way to
highlight possible errors in the submitted data. The latest version of the software allows the user
to choose whether to perform QA/QC checks on the data for format, the minimum standards
required to put the data in the database, or the more resource intensive content or reasonableness
checks. When checking for content, the format is also checked as the format must be correct in
order for content checks to be performed at all.
4.4.2 Toxics Release Inventory (TRI)
The Toxics Release Inventory (TRI) is a publicly available EPA database that contains
information about releases and other waste management activities reported annually by certain
covered industry groups as well as federal facilities for over 650 toxic chemicals (see
http ://www. epa. gov/tri/). This inventory was established under the Emergency Planning and
Community Right-to-Know Act of 1986 (EPCRA) and expanded by the Pollution Prevention
Act of 1990.
TRI reporting is required only for facilities that meet all of the following three criteria:
• They have ten or more full-time employees or the equivalent (i.e., a total of 20,000 hours or
greater; see 40 CFR 372.3);
• They are included in specified industrial sectors (see Exhibit 4-7); and
• They exceed any one reporting threshold for manufacturing, processing, or otherwise using a
TRI chemical (see Exhibit 4-8).
If a facility meets these criteria, then it must report releases to environmental media as well as
waste management data. In 2001 (the latest year for which data are publicly available), air
emissions of toxic chemicals totaled 1.7 billion pounds (over a quarter of all releases of TRI
chemicals to the environment).
April 2004 Page 4-25
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Exhibit 4-7. Standard Industrial Classification (SIC) Codes in TRI Reporting
Original Industries
SIC Code
20
21
22
23
24
25
26
27
28
29
Industry Group
Food
Tobacco
Textiles
Apparel
Lumber and Wood
Furniture
Paper
Printing and Publishing
Chemicals
Petroleum and Coal
SIC Code
30
31
32
33
34
35
36
37
38
39
Industry Group
Rubber and Plastics
Leather
Stone, Clay, and Glass
Primary Metal
Fabricated Metals
Machinery (excluding electrical)
Electrical and Electronic Equipment
Transportation Equipment
Instruments
Miscellaneous Manufacturing
New Industries Reporting to TRI as of the 1998 Reporting Year
SIC Code
10
12
4911,4931,
and 493 9
4953
5169
5171
7389
Industry Group
Metal mining (except for SIC codes 1011,1081, and 1094)
Coal mining (except for 1241 and extraction activities)
Limited to electrical utilities that combust coal and/or oil for distribution in
commerce (SIC codes 4911, 4931, and 4939)
Limited to hazardous waste treatment and disposal facilities regulated under the
Resource Conservation and Recovery Act (RCRA) Subtitle C
Chemicals and allied products wholesale distributors
Petroleum bulk plants and terminals
Solvent recovery services primarily engaged on a contract or fee basis
Source: U.S. Environmental Protection Agency. 2004. Toxic Release Inventory (TRI) Program.
Standard Industrial Classification (SIC) Codes in TRI Reporting. Updated March 2, 2004.
Available at: http://www.epa.gov/tri/report/siccode.htm. (Last accessed April 2004.)
April 2004
Page 4-26
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Exhibit 4-8. Thresholds for Reporting to the TRI
EPCRA Section 313 non-PBT chemicals (Section 372.25). A facility meeting the
SIC code (or
Federal facility) and employee criteria must file a TRI report for a non-PBT Section 3 13 chemical if
the facility:
• Manufactured (including imported) more than 25,000 pounds
• Processed more than 25,000 pounds per year; or
• Otherwise used more than 10,000 pounds per year.
oer year; or
EPCRA Section 313 PBT chemicals (40 CFR372.28). If a facility manufactures, processes, or
otherwise uses any chemicals that are listed as persistent, bioaccumulative, and toxic
(PBT), the
threshold quantity is one of the following (per Section 313 chemical or category per year):
Type of Chemical
Highly persistent and bioaccumulative
compounds
Dioxin and dioxin-like compounds
Other persistent and bioaccumulative
compounds (lead and lead compounds)
Reporting Threshold by Activity
Manufacture
10 pounds
0.1 grams
100 pounds
Process
10 pounds
0.1 grams
100 pounds
Otherwise Used
10 pounds
0.1 grams
100 pounds
Activity thresholds are calculated independently of each other based on cumulative quantities per
Section 313 chemical over the reporting year.
Current list of Section 313 PBT Chemicals
• aldrin
• benzo(g,h,i)perylene
• chlordane
• dioxin and dioxin-like compounds
• heptachlor
• hexachlorobenzene
• isodrin
• lead
• lead compounds
• mercury
• mercury compounds
• methoxychlor
• octachlorostyrene
• pendimethalin
• pentachlorobenzene
• polychlorinated biphenyl
• polycyclic aromatic compounds
• tetrabromobisphenol A
• toxaphene
• trifluralin
April 2004
Page 4-27
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Note in Exhibit 4-7 that additional industries have been added to the TRI over time. Thus, some
industries were not required to report in the past and, as such, no records will exist for these
facilities in the historical TRI files. The list of covered chemicals has also grown over time.
Thus, the ability to track trends for more recently added industries and chemicals is more limited
than for industries and chemicals that have been covered throughout the history of the TRI.
Industrial sectors subject to TRI reporting are identified by Standard Industrial Classification
(SIC) codes. SIC codes are numerical codes developed by the U.S. government as a means of
consistently classifying the primary business of business establishments. A full list of the
industry groups that are required to report can be found at http://www.epa.gov/tri/report/
siccode.htm.
Although most of the existing emissions data in the TRI system are organized according to SIC
codes, EPA has proposed regulations that would result in the use of the North American Industry
Classification System (NAICS) rather than SIC codes (see http://www.census.gov/epcd/www/
naics.html). Rather than classifying industries on the basis of several different economic
concepts (as the SIC structure does), NAICS classifies establishments according to similarities in
the processes used to produce goods and services. The TRI program issued a proposed rule to
implement the NAICS system classification on March 21, 2003. (See 66 Fed. Reg. 13872.) It is
expected that the use of NAICS in the TRI system will allow EPA to more accurately
characterize the current state of the national economy (including new and emerging industries
not adequately covered by SIC codes). The existing SIC structure will not be updated in the
future because the Office of Management and Budget has adopted NAICS as the United States'
new industry classification system. In addition, using NAICS for TRI reporting purposes will
enable more efficient database integration and will promote public access to commonly defined
data from disparate sources. This change will not affect the universe of facilities that is currently
required to report to TRI.
EPCRA requires only that facilities report their releases of the listed chemicals. There are no
additional control or mitigation actions required. The information collected through the TRI
program is made public, however, and pressure from local citizen groups has been an incentive
to many industries to reduce the quantity of pollutants they release.
While the TRI data have utility for the scoping out of an air toxics risk assessment project, they
have several limitations that assessors must understand. Importantly for risk assessors, the TRI
program requires only that one single annual value representing total releases to the air
(segregated only by stack releases and fugitive releases) be reported by the individual affected
facilities. So while annual average emissions may be useful in screening-level assessments for
chronic exposures, it may be difficult to assess acute noncancer hazard associated with short-
term, peak emission levels. Source-specific information within the facility is not routinely
reported through the TRI. Likewise, no information is reported on release parameters critical to
air dispersion modeling (e.g., location of release on the facility property, release rates, stack
height, stack diameter, release temperature). (See Chapter 9, for more information on modeling
parameters used in air quality and exposure modeling.)
As discussed in Section 4.2, the list of TRI pollutants is organized differently than the list of
HAPs in CAA Section 112, causing some complications in interpreting emission data. It is
difficult to correctly relate some of the SIC codes (under which TRI emissions are grouped) to
specific air emission processes. Because quantities are only reported if a statutory threshold is
April 2004 Page 4-28
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met, a facility may report emissions for one year but not the next, even though the facility is still
in operation. Similarly, individual pollutants may not be reported consistently from year to year
due to the thresholds that apply to individual pollutants (e.g., a facility may report releases of 10
pollutants one year and releases of only five pollutants the next year because the others dropped
below the reporting threshold).
Furthermore, for some facilities, it is possible that, for a variety of releases, the data included for
a facility's emissions in the TRI do not match the same data reported to the NEI, indicating a
potential problem with either or both data sets. The risk assessor should apply care and
discretion when using TRI information to estimate exposures and risk from individual facilities.
Ultimately, the TRI provides information about the location, identity, and amount of air toxics
emissions in a community. However, due to the nature of the way the data are developed and
reported, TRI data should generally be considered a source of limited information about a
facility and should not be used in risk assessments involving modeling (as noted above, S/L/T
and NEI data are more likely to be useful for modeling). For robust analysis, it should generally
be considered a starting point, not an end.
References
1. United States Environmental Protection Agency. 1998. Handbook for Air Toxics Emission
Inventory Development, Volume 1: Stationary Sources (Appendix C). Office of Air Quality
Planning and Standards, Research Triangle Park, NC, November 1998. EPA/454/B98/002.
Available at: http://www.epa.gov/ttn/chief/eidocs/airtoxic.pdf.
2. U.S. Environmental Protection Agency. 2003. Technology Transfer Network
Air Toxics Website. The Original List of Hazardous Air Pollutants. Updated January 9,
2004. Available at: http://www.epa.gov/ttn/atw/188polls.html. (Last accessed March 2004.)
3. U.S. Environmental Protection Agency. 2001. The Emergency Planning and Community
Right-to-Know Act: Section 313 Release and Other Waste Management Reporting
Requirements. Washington, D.C. EPA/260/KO1/001. Available at:
http://www.epa. gov/tri/guide_docs/2001 /brochure2000 .pdf.
4. U.S. Environmental Protection Agency. 2001. Emergency Planning and Community Right-
to-Know Section 313; List of Toxic Chemicals. Office of Environmental Information.
Washington, DC, March 2001. EPA/ 260/B01/001. Available at:
http://www.epa. gov/tri/chemical/chemlist2001 .pdf.
5. U.S. Environmental Protection Agency. 2004. Technology Transfer Network Clearinghouse
for Inventories & Emission Factors. National Emissions Inventories for the U.S. Updated
February 4, 2004. Available at: http://www.epa.gov/ttn/chief/net/. (Last accessed March
2004.)
6. U.S. Environmental Protection Agency. 1992. Notice Initial Source Category List. Federal
Register 57:31576, July 16, 1992.
7. U.S. Environmental Protection Agency. 2002. National Emission Standards for Hazardous
Air Pollutants: Revision of Source Category List Under Section 112 of the Clean Air Act.
Federal Register 67:6521, February 12, 2002.
April 2004 Page 4-29
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8. U.S. Environmental Protection Agency. 1997. Mercury Study Report to Congress. Office of
Air Quality Planning and Standards. Washington D.C. EPA/452/R97/0003. Available at:
http ://www. epa. gov/ttn/atw/112nmerc/mercury.html.
9. U.S. Environmental Protection Agency. 2001. Control of Emissions of Hazardous Air
Pollutants From Mobile Sources. Final Rule. Federal Register 66:17230, March 29, 2001.
Available at: http://www.epa.gov/fedrgstr/EPA-AIR/2001 /March/Dav-29/a37.htm.
10. U.S. Environmental Protection Agency. 2000. National Air Pollutant Emission Trends:
1900-1998. Office of Air Quality Planning and Standards, Research Triangle Park, NC.
EPA/454/ROO/002. Available at: (http://www.epa.gov/ttn/chief/trends/trends98/index.htmn.
11. U.S. Environmental Protection Agency, Consumer Product Safety Commission (CPSC), and
American Lung Association. 1998. What You Should Know About Combustion Appliances
and Indoor Air Pollution. CPSC Document #452. Available at: http://www.cpsc.gov/cpscpub
/pubs/452.html. (Last accessed March 2004.)
12. U.S. Environmental Protection Agency. 2004. Technology Transfer Network
Air Toxics Website. Area Source Standards. Updated January 15, 2004. Available at:
ftp://ftp.epa.gov/EmisInventory/finalnei99ver2/criteria/documentation/. (Last accessed
March 2004.)
13. U.S. Environmental Protection Agency. 2003. Documentation for the Final 1999 Nonpoint
Area Source National Emission Inventory for Hazardous Air Pollutants (Version 3).
Emissions, Monitoring and Analysis Division, Research Triangle Park, NC, August 2003.
Available at: ftp://ftp.epa.gov/EmisInventory/finalnei99ver3/haps/documentation/.
14. U.S. Environmental Protection Agency. 2002. Consolidated Emissions Reporting. Final
Rule. Federal Register 61:39602, June 10, 2002. Available at:
http://www.epa.gov/ttn/chief/cerr/index.html.
April 2004 Page 4-30
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PART II
HUMAN HEALTH RISK ASSESSMENT:
INHALATION
-------
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Chapter 5 Getting Started: Planning and Scoping
the Inhalation Risk Assessment
Table of Contents
5.1 Introduction
5.2 Framework and Process for Air Toxics Risk Assessments ............................. 1
5.2.1 Framework for Cumulative Risk Assessment ................................. 1
5.2.2 General Framework for Residual Risk Assessment ............................ 3.
5.2.3 The Air Toxics Risk Assessment Process .................................... 3_
5.2.4 Overview of Inhalation Exposure Assessment ................................ 6
5.2.4.1 Exposure and Exposure Assessment: What's the Difference? ............. 6
5.2.4.2 Components of an Exposure Assessment .............................. 7
5.3 Planning and Scoping [[[ £
5.3.1 Why is Planning and Scoping Important? .................................... 9
5.3.2 The Planning and Scoping Process ......................................... 9
5.3.2.1 What is the Concern? ............................................. 9
5.3.2.2 Who Needs to be Involved? ....................................... 10
5.3.2.3 What is the Scope? .............................................. 12
5.3.2.4 Why is There a Problem? ......................................... 13.
5.3.2.5 How will Risk Managers Evaluate the Concern? ....................... 1_3
5.3.2.6 Lessons Learned on Planning and Scoping ........................... 1_3
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in the
the
5.1 Introduction
The background discussion in Part I of this manual introduced the general air toxics risk
assessment process (see Exhibit 3-4). Part II describes the tools and approaches risk assessors
use to evaluate human health risks associated with inhalation exposures to air toxics. Section 5.2
below describes the framework used for air toxics risk assessment, including its three phases: (1)
planning, scoping, and problem formulation; (2) analysis (which includes exposure assessment
and toxicity assessment); and (3) risk characterization. Part II includes nine chapters that
describe these three phases in detail.
• The remainder of the current chapter describes planning and scoping (Section 5.3).
• Chapter 6 describes problem formulation.
• Because exposure assessment is generally the most labor and financially-intensive step in
analysis phase, and because it involves a variety of related (but heterogeneous activities),
discussion of exposure assessment includes five chapters:
- Chapter 7 describes how to characterize sources and quantify emissions;
- Chapter 8 explores the fate and transport of air toxics in the atmosphere;
- Chapter 9 discusses air quality modeling;
- Chapter 10 discusses monitoring; and
- Chapter 11 discusses quantifying exposure, including exposure modeling.
• Chapter 12 describes the remainder of the analysis phase, toxicity assessment.
• Chapter 13 describes the risk characterization phase for inhalation assessments.
5.2 Framework and Process for Air Toxics Risk Assessments
The original risk assessment framework
developed in 1983 by the NRC (see Chapter 3) /" ~ ~ _. . .
, , ,-,,, , . \ Cumulative Risk Assessment
has been refined based on the nsk assessment
experience gained by EPA and other agencies.
Two descriptions of this refined framework are
particularly useful for air toxics risk
assessments: EPA's framework for cumulative
risk assessment, and EPA's general framework
for assessing residual risks.
An analysis, characterization, and possible
quantification of the combined risks to health or
the environment from simultaneous exposure to
multiple agents or stressors.
5.2.1 Framework for Cumulative Risk Assessment
EPA's Framework for Cumulative Risk Assessment^ describes three main phases to a risk
assessment: (1) planning, scoping, and problem formulation; (2) analysis; and (3) risk
characterization (Exhibit 5-1).
April 2004 Page 5-1
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Exhibit 5-1. Three-Phase Framework for Cumulative Risk Assessment
Source: EPA Frames
Planning, Scoping, and
Problem Formulation
i
Analysis
i
Interpretation and Risk
Characterization
orkfor Cumulative Risk Assessment^
In the planning, scoping, and problem formulation phase, a team of risk managers, risk
assessors, and other stakeholders identify the problem to be assessed and establish the goals,
breadth, depth, and focus of the assessment. The end products of this phase are a conceptual
model and an analysis plan. The conceptual model establishes the air toxics, exposure
pathways, and health and ecological effects to be evaluated. The analysis plan lays out how
the elements of the conceptual model are going to be studied.
The analysis phase (the elements of which are described by the analysis plan) is primarily an
analytic process in which risk experts apply risk assessment approaches to evaluate the
problem at hand. Specifically, the analysis plan specifies how data, modeling, or
assumptions will be obtained, performed, or defined for all aspects of the exposure
evaluation. Additionally, the analysis plan specifies the strategy for obtaining and
considering hazard and dose-response information for these stressors and the method for
combining the exposure information with the hazard and dose-response information to
generate risk estimates. As the risk analysis is refined, it may be appropriate to revisit and
refine the exposure, hazard, and dose-response information in an iterative fashion.
The risk characterization phase integrates and interprets the results of the analysis phase
and addresses the problem(s) formulated in the planning, scoping, and problem formulation
phase. It describes the qualitative and/or quantitative risk assessment results and lists the
important assumptions, limitations, and uncertainties associated with those results; and
discusses the ultimate use of the analytic-deliberative outcomes.
April 2004
Page 5-2
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5.2.2 General Framework for Residual Risk Assessment
EPA's Residual Risk Report to Congress^ outlines a general framework for assessing residual
risks to implement the requirements of CAA sections 112(f)(2) through (6). Those sections
require EPA to promulgate standards beyond MACT when necessary to provide "an ample
margin of safety to protect public health" and to "prevent, considering costs, energy, safety, and
other relevant factors, an adverse environmental effect." EPA developed the general framework
using knowledge gained from past risk assessments and guidance gained from reports such as the
NRC and CRARM reports (see Chapter 3). The framework calls for an iterative, tiered
assessments of the risks to humans and ecological receptors through inhalation and, where
appropriate, non-inhalation exposures to HAPs.
As shown in Exhibit 5-2, each human health and ecological risk assessment is organized into
three phases: (1) the problem formulation phase, in which the context and scope of the
assessments are specified (this phase also includes planning and scoping activities); (2) the
analysis phase, in which the toxicity of HAPs and exposures to humans or ecological receptors
are evaluated; and (3) the risk characterization phase, in which the toxicity and exposure analyses
are integrated to determine the level of risk that may exist. The problem formulation and
analysis phases of the human health and ecological risk assessments will partially "overlap" in
that some pathway of concern for humans (e.g., consumption of contaminated fish) may also be
pathways of concern for ecological receptors (e.g., fish-eating wildlife). Consequently, exposure
analyses for some air toxics may be designed to provide information for both ecological and
human health assessments.
In both human health and ecological risk assessments, there is essentially a continuum of
possible levels of analysis from the most basic screening approach to a highly refined, detailed
assessment. The screening level or tier of analysis is designed, through the use of simplifying
assumptions and conservative inputs, to identify for no further action or analysis, exposure
pathways and air toxics for which risks are unlikely to be of concern. Screening tier analyses are
designed to be relatively simple, inexpensive, and quick, using existing data, defined decision
criteria, and models with simplifying conservative assumptions as inputs. More refined levels of
analysis include the refinement of aspects of the analysis that are thought to influence risk most
or may contain the greatest uncertainty. They may also allow a more quantitative analysis of
uncertainty and variability. Refined analysis requires more effort, but produces results that are
hopefully less uncertain and less conservative (i.e., less likely to overestimate risk).
5.2.3 The Air Toxics Risk Assessment Process
Building on the Cumulative and Residual Risk frameworks discussed above, the human health
portions of this reference manual describe the risk assessment process for air toxics in three
general phases (Exhibit 5-3; the process for ecological risk assessment is provided in Part IV).
[Note that Exhibit 5-3 is consistent with both the Cumulative and Residual Risk frameworks
discussed above. The benefit of Exhibit 5-3 is that it helps to better visualize the detailed
elements that are usually performed in an air toxics risk assessment.]
April 2004 Page 5-3
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Exhibit 5-2. General Framework for Residual Risk Assessment
Planning and Scoping
T
Human Health Risk Assessment Ecological Risk Assessment
^B
T
Risk Manac
ement Decision
Source: Modified from EPA's Residual Risk Report to Congress('
The planning, scoping, and problem formulation phase is divided into two general steps:
planning and scoping, and problem formulation. These two steps consist of the activities
described above in the cumulative risk assessment framework. The end products of this
phase are a conceptual model and an analysis plan. As shown in the Exhibit 5-3, planning,
scoping, and problem formulation encompass the entire risk assessment process because
stakeholders aim to understand and state the problem they want to study using the risk
assessment process and plan how they are going to study the problem before the risk
assessment is performed. They also must recognize that they may need to refine the problem
statement and study methodology as new information is gained during the assessment.
April 2004
Page 5-4
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Exhibit 5-3. The Detailed Air Toxics Risk Assessment Process
Problem Formulation
Planning and Scoping
D.
W
I
a
«
.
IS
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^3 S
ll
•
Exposure Assessment
SOU ROE IDENTIFICATION
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FATE AND TRANSPORT AMAIVBIB
^^HP
Metrics of
Exposuie
^±fei&
CHEMICAL
CONCENTRATIONS
Air. Soil.Vaster, fcod
(monitor/rnodel)
To xi city As s ess merit
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\7
Risk Characterization
\Z
EXPOSURE
information
DOSE/RESPONSE
information
I Quantitative and Qualitative Expressions of Risk/Uncertainty [
• The analysis phase is divided into two general steps: exposure assessment and toxicity
assessment (the general process for ecological risk assessments is described in Part IV).
Exposure assessment is a relatively complex process involving source identification;
development of an emissions inventory; fate and transport analysis (through modeling and/or
monitoring) to estimate chemical concentrations in air (and soil, food, and water for
multimedia assessments); and combining information on chemical concentrations with
population characteristics to obtain one or more metric(s) of exposure. Toxicity assessment
includes hazard identification and dose-response assessment.
• The risk characterization phase integrates the information from the exposure assessment
and the toxicity assessment to provide both quantitative and qualitative expressions of risk.
The risk characterization also includes a thorough discussion of uncertainty associated with
each of the major elements of the risk assessment.
The remainder of Parts I, II, and III of this Volume will rely on the general approach outlined in
Exhibit 5-3 as a roadmap for describing the air toxics risk assessment process.
April 2004
Page 5-5
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Risk Assessment: Is it a Linear Process?
It maybe useful to think of the risk assessment process as a set of steps that proceed in a linear
fashion. But it does not always work out that way. For example, through good planning, scoping, and
problem formulation (e.g., a thorough identification of sources and chemicals while developing the
conceptual model), much of the preliminary exposure assessment work may be accomplished. A prior
basic knowledge and discussion of toxic and chemical/physical properties of the chemicals of
potential concern (COPCs) (information often developed during the toxicity and exposure
assessments, respectively) may help the risk assessment team rule out certain pathways for
consideration during the planning, scoping, and problem formulation phase. Of course, a good
analysis plan will include mechanisms to confirm and document all these decisions, but the fact still
remains that the risk assessment process is actually a combination of a variety of steps, many of which
may occur simultaneously.
\ /•
5.2.4 Overview of Inhalation Exposure Assessment
Because exposure assessment is generally the most multifaceted and time-consuming part of an
air toxics risk assessment, it cannot be discussed in a single chapter. This subsection provides an
overview of exposure assessment and identifies where each step of the process is described in
more detail in subsequent chapters (i.e., Chapters 6 through 11). EPA's Guidelines for Exposure
Assessment^ is the key reference document for the exposure assessment portion of the risk
assessment, and air toxics risk assessors may want to obtain and become familiar with its
contents.
Exposure assessment helps identify and evaluate a population receiving exposure to a toxic
agent, and describe its composition and size, as well as the type, magnitude, frequency, route and
duration of exposure. In other words, an exposure assessment is that part of the risk assessment
that identifies:
• Who is potentially exposed to toxic chemicals;
• What toxics they may be exposed to; and
• How they may be exposed to those chemicals (amount, pattern, and route).
5.2.4.1 Exposure and Exposure Assessment: What's the Difference?
Exposure assessment is the overall process of evaluating who receives exposure to toxic
chemicals, what those chemicals are, and how the exposure occurs. Exposure, on the other hand,
(according to EPA definition(1)) represents contact with a chemical at the visible external
boundary of a person, including skin and openings into the body such as mouth, punctures in the
skin, and nostrils. This definition of exposure does not describe the contact of a chemical with
the actual exchange boundaries in the body where absorption into the bloodstream can take place,
such as the linings of the lung or digestive tract. (One exception to this is chemical contact with
skin or punctures in the skin; in this case, the location of the exposure and the exchange
boundary are one in the same.) Other than dermal exposure, chemicals must be physically taken
into the body by ingestion or inhalation (a process called intake) before they can contact an
exchange boundary and be taken into the bloodstream (a process called uptake).
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The term route of exposure is used to describe the different ways a chemical enters the body.
The three main routes of exposure are inhalation, ingestion, and absorbing a chemical through
the skin (dermal). For inhalation risk assessments, we are only concerned with the inhalation
route of exposure. The dermal and ingestion routes of exposure are generally only relevant to
chemicals that persist and which also may bioaccumulate (e.g., the persistent, bioaccumulative
HAP (PB-HAP) compounds). Discussion of these routes of exposure is reserved for Part III.
Some chemicals can cause harm in the part of the body where individuals take them in (e.g., in
the respiratory system for inhaled chemicals or in the digestive tract for ingested chemicals).
This is called a portal of entry effect because the adverse effect occurs at the place (i.e., the
"portal") where the chemical enters the body. Other chemicals have to be taken into and
distributed by the circulatory system to cause a harmful effect at a point distant from their portal
of entry into the body. Such effects are called systemic effects because they have the potential to
act at points throughout the system. As a chemical moves through the body, it may be
metabolized (possibly to a more toxic entity); stored in the body; and/or eliminated in urine,
feces, sweat, nails/hair, or exhaled breath.
5.2.4.2 Components of an Exposure Assessment
The nature and complexity of the components within the exposure assessment are often functions
of the particular risk management question (or other purpose) to be addressed. Simple screening
analyses that rely on conservative default assumptions may be sufficient to rule out the need for
further analyses or action. On the other hand, a more detailed exposure analysis may be needed
to determine the necessity for emission controls, particularly when the application of those
controls is associated with large economic consequences. Indeed, the exposure assessment raises
and addresses many of the risk assessment's difficult and critical policy questions. As illustrated
in Exhibit 5-4, the exposure assessment includes the following steps:
• Characterization of the exposure setting, including the physical environment, scale of the
study area, important sources and chemicals, and potentially exposed populations and
population characteristics (e.g., demographics). Most of this information is collected and
organized during the problem formulation portion of the risk assessment (see Chapter 6).
• Identification of exposure pathways, including sources and mechanism of release, exposure
points and routes of exposure, and transport media. Again, most of this information is
collected and organized during problem formulation (see Chapter 6).
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Exhibit 5-4. Exposure Assessment is the Most Time-Consuming Part of Risk Assessment
Problem F ormu lati on
Planning and Scoping
• Quantification of exposure, including an evaluation of uncertainty and preparation of
documentation. Quantification of exposure includes three general steps which are discussed
in several subsequent chapters.
- Characterization of emissions is discussed in Chapter 7.
- Evaluation of chemical fate and transport is discussed in three chapters. Chapter 8
discusses dispersal, transport, and fate of air toxics in the atmosphere. Chapter 9
discusses air quality modeling. Chapter 10 discusses air toxics monitoring.
- Estimation of exposure concentrations (EC) is discussed in Chapter 11, along with
exposure modeling, evaluation of uncertainty, and preparation of documentation.
5.3 Planning and Scoping
Planning and scoping is the first step in an air toxics risk assessment (good planning and scoping
is important for any scientific study). It is both a deliberate and deliberative process that
identifies the problems to be assessed; identifies stakeholders in the risk assessment process;
establishes the bounds (i.e., the scope) of the analysis, including elements to be included or
excluded from the analysis; develops a description of the potential interrelationship between air
pollutants and receptors; and articulates the overall analysis plan for the assessment. This section
provides an overview of how to plan for and scope an air toxics risk assessment. The discussion
focuses on four key elements of planning and scoping:
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• Why is planning and scoping important?
• What is the process?
• Who should be involved?
• What are the key products?
More detailed discussions of the planning and scoping process can be found in the EPA guidance
documents Guidance on Cumulative Risk Assessment, Framework for Cumulative Risk
Assessment(5), and Risk Assessment Guidance for Superfund (RAGS): Volume I ^ (Chapter 2 of
this RAGS document discusses the role of the risk assessor in planning and scoping).
5.3.1 Why is Planning and Scoping Important?
Planning and scoping may be the most important step in the risk assessment process. Without
adequate planning, most risk assessments will not succeed in providing the type of information
that risk management needs to make a well-founded decision. Thorough planning and scoping is
commonly conducted before any substantive work is done on the risk assessment. Planning and
scoping is important for developing a common understanding of why the risk assessment is being
conducted, the scope of the assessment, the quantity and quality of data needed to answer the
assessment questions, and how risk managers will use the results. This step is also a focal point
for stakeholder involvement in the risk assessment process. The specific goals of planning and
scoping include:
• The approaches, including a review of the risk dimensions and technical elements that may
be evaluated in the assessment;
• The relationships among potential assessment end points and risk management options;
• An analysis plan and a conceptual model (articulated in the problem formulation phase - see
Chapter 6);
• The resources (for example, data or models) required or available;
• The identity of those involved and their roles (for example, technical, legal, or stakeholder
advisors); and
• The schedule to be followed (including provision for timely and adequate internal, and
independent, external peer review).
5.3.2 The Planning and Scoping Process
The five essential steps in the planning and scoping process include (1) identifying the concern;
(2) identifying who needs to be involved; (3) determining the scope of the risk assessment; (4)
describing why there may be a problem (i.e., describing the presumed interrelationship among
sources of risk, humans receiving the exposure, and potential health effects); and (5) determining
how risk managers will evaluate the concern. Each is described in a separate subsection below.
5.3.2.1 What is the Concern?
Most risk assessments are conducted because of a regulatory requirement, a community need or
concern, or some other reason. The specific concerns and the resources available to address
those concerns will largely shape the risk assessment scope and methods. For example, a simple,
screening-level risk assessment may be adequate to support a typical pollution permitting process
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while a detailed analysis may be necessary to respond to a particular community concern (e.g.,
are children in a nearby school exposed to harmful levels of air toxics from all sources in the
community?).
At the end of this first step, risk assessors usually identify the full breadth of the concerns of the
participating stakeholders and clearly articulate which of those concerns will be the focus of the
risk assessment and why. For example, in a community-level multisource analysis, some
community stakeholders may be concerned about nuisance odor while others are concerned about
potential cancer health risks from airborne pollutants. At the end of this step, all stakeholders
should be clear that the risk assessment cannot address the odor issue but, rather, will focus on
the cancer concern. This is also the time to identify other resources or means for attempting to
address the non-risk related odor issue.
Stakeholders often identify a wide range of concerns in the risk assessment process that risk
assessment methods may be unable to address. It is always important to acknowledge the
legitimacy of stakeholder concerns and to work to clarify the limitations of the risk assessment
process - especially when assessors are working to respond to community concerns. At the same
time, risk assessors often assist in identifying the proper path for responding to non-risk related
issues. Proceeding in this manner will help create an attitude of trust, foster buy-in of the risk
assessment process and results, and avoid creating false expectations.
5.3.2.2 Who Needs to be Involved?
The key participants in the planning and scoping process include, at minimum, the risk managers
who will use the results of the risk assessment and the risk assessment technical team who will
perform the analysis.
• Risk managers are the persons or groups with the authority to make the decisions about the
acceptability of risk and how an unacceptable risk maybe mitigated, avoided, or reduced.
For regulatory requirements (e.g., permitting, compliance), the risk manager usually is a
government agency such as EPA or a S/L/T authority. For voluntary efforts, the risk
manager(s) generally will include members of the potentially affected or interested parties
(e.g., industry representatives, community leaders, local government).
• The risk assessment technical team includes those experts who will perform the activities
involved in the risk assessment, including environmental scientists, modelers, chemists,
toxicologists, ecologists, and engineers.
These individuals need to understand the goals of the risk assessment, how the results will be
used, the amount and quality of information necessary to make key decisions, and the
uncertainties associated with the inputs, risk assessment methods, and resulting risk estimates.
The specific concerns from step one may generate the need for a diverse set of individuals or
groups with an interest in having the assessment done ("interested or affected parties").(7) Each
group may have a unique set of questions, concerns, and fears. It is important to design the risk
assessment to address as many of these issues as possible within available time and resources.
Planning and scoping begins with a dialogue among these individuals and groups; consequently,
the initial planning and scoping team may need to expand over time to include additional
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Examples of Possible Interested or Affected Parties
State governments
Tribal governments
Local governments
Community groups
Grassroots organizations
Environmental groups
Consumer rights groups
Religious groups
Civil rights groups
Affected industry
Civic organizations
Business owners
Trade associations
Labor unions
Public health groups
Academic institutions
Impacted citizens
Other federal agencies
participants, including public officials,
citizens, and industry representatives. In
many cases, technical experts who live in
the affected communities can be effective
participants because they have both the
trust of the local community and the
technical skills to explain complex issues.
A strong community involvement effort
early in the process can help identify these
concerns (see Part V of this Volume).
One tool helpful in translating general goals
into specific metrics is an objectives
hierarchy, which is a hierarchic list starting with the overall goal of a project and moving down in
levels to (component) purposes or outcomes, outputs and specific activities (see
http://www.iac.wur.nl/ppme/content.php?ID=353&IDsub=338). A discussion of this is found in
EPA's Planning for Ecological Risk Assessment: Developing Management Objectives (Section
3.4.2) at http://www.epa.gov/NCEA/raf/pdfs/eco_objectives-sab_6-01 .pdf.
It is beneficial if planning and scoping participants understand the following six questions before
the risk assessment begins:
• What is the goal of the risk assessment and how will the results be used? A risk
assessment might be conducted to compare the costs of various emissions control options
versus the benefits in terms of reduced risks. Some conduct risk assessments primarily for
informational purposes - for example, how much do individual pollution sources contribute
to total risks within a given community? Risk management goals may be risk-related (e.g.,
reducing risks from exposure to air toxics; reducing the incidence of a specific adverse effect
such as cancer); economic (e.g., reducing risks without causing job loss or raising taxes); or
related to public policy (e.g., protecting children and other sensitive populations). Generally,
each risk assessment is designed to provide information that will support the identified goals.
• What information will the risk assessors collect and what analyses will they perform on
those data? The risk assessors develop the scope of the risk assessment during planning and
scoping. For example, participants may select a limited number of chemicals from all those
released in an area to be analyzed throughout the risk assessment process (the chemicals of
potential concern or COPC), or the assessment may focus on only a limited number of
exposure pathways that maybe most important. Stakeholders should understand exactly
what the risk assessment is (and by extension, what it is not) going to evaluate.
• What are the major concerns of the local community? Significant concerns that the risk
assessment does not address can result in "show stoppers" that complicate or delay the risk
management decision. Clarifying what the risk assessment is not going to study, and why,
before the assessment begins will help to reduce this possibility. As an example, many
communities express concerns about perceived disease clusters. All stakeholders need to
understand that the risk assessment process is not used to evaluate disease clusters or
establish cause-effect relationships between air pollution and existing cases of disease.
However, stakeholders often raise this concern, and it is imperative that the planning and
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scoping team acknowledge these concerns and direct them to the appropriate resources.
Given the prevalence of this concern in areas with air toxics concerns, this Volume includes a
lengthy discussion in Part VI of this Volume on options for addressing such issues.
• What are the roles and responsibilities of each participant? Stakeholders often address
many administrative issues during planning and scoping, including who will lead the risk
assessment, who will perform each of the various tasks, who will pay for it, and when the
participants need the results.
• What are the available resources and schedules? Time and money are always limited;
therefore, the planning and scoping process will almost certainly involve trade-offs between
the amount and quality of information participants desire and the time and monetary
resources available to obtain and analyze the information. Participants often choose to
determine critical milestones and institute a clear, yet reasonably flexible, schedule to keep
the assessment on track.
• What documentation and other products are required? Regulatory requirements often
include specific types of information in specific formats. In a community-level analysis,
stakeholders may want specific information such as maps indicating estimated levels of air
pollutants in different parts of the community. Thus, documentation requirements are meant
to provide transparency throughout the risk assessment process, from the initiation of the
planning and scoping step to the presentation of the final product. Participants are urged to
document all important decisions, goals, discussions, schedules, resource allocations, roles
and responsibilities, data quality objectives. Participants also may document the analytical
approach such that anyone may follow the methodology of the risk assessment.
Finally, risk assessors, risk managers, and all other stakeholders generally recognize the
sensitivity of their roles throughout the risk assessment process. Specifically, there must be no
direct or indirect actions on the part of any stakeholder to influence the outcome of the science-
based analysis. Even the appearance of such activity can severely undermine trust in the risk
assessment as a valid analysis tool.
5.3.2.3 What is the Scope?
The risk assessment scope helps determine how comprehensive the analysis will be. The scope
of a risk assessment may be narrow or broad, depending on the specific risk management goals.
For example, a relatively broad goal such as "reducing risks from exposure to air toxics" may
require a relatively broad risk assessment that examine many types of sources (e.g., stationary,
mobile) and dozens of specific air toxics. In contrast, a more narrow goal such as "reducing the
potential cancer risk in the community" may result in a risk assessment that focuses more
narrowly on only those air toxics that contribute to cancer. Geography (e.g., political
boundaries), demographics (e.g., focusing on a subset of exposed populations), legal
requirements (e.g., statutes or regulations), or methodological or data limitations can all narrow
the scope. Most importantly, time and money will almost always limit the scope of the risk
assessment.
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Participants can determine scope by listing and answering critical assessment questions such as:
• What specific sources are to be included?
• What specific air toxics are to be included?
• What are the physical boundaries of the study area?
• What are the temporal constraints of the study?
• What potential exposure pathways will be evaluated?
• What potentially exposed populations will be assessed?
• What types of health risks will be evaluated?
The details of scope (e.g., what sources are to be included, what potential pathways will be
included) are developed during the problem formulation stage (see Chapter 6).
The goal of the scoping process is to produce a clear understanding of what the risk assessment
should and should not include and why. For example, if available data or methods make it
impossible to assess a potential exposure pathway, the planning and scoping team may need to
re-evaluate the goals and expectations of the risk assessment process.
5.3.2.4 Why is There a Problem?
The problem statement often summarizes
the end result of the scoping process,
describing the specific concerns that the risk
assessment will address. Problem statements
often also include statements about how the
risk assessors will evaluate these concerns.
The problem statement is commonly as
specific as possible and may also include
explicit statements of what will not be
assessed in the risk assessment.
5.3.2.5 How will Risk Managers
Evaluate the Concern?
Example Problem Statement
Air toxics emissions may be causing increased
long-term inhalation health risk (both cancer and
noncancer concerns) to people in the immediate
vicinity of Acme Refining Company. A
modeling risk assessment will be performed to
evaluate potential long-term human health
impacts of inhalation exposures to all air toxics
emitted by the facility. Inhalation risks for
populations within 50 km of the Acme property
boundary will be assessed under residential
exposure conditions. Non-inhalation pathways
will not be assessed for either human or
ecological receptors.
The risk assessments are most often designed
to provide input to risk managers to help
inform the decisions they must make. Part of the planning and scoping process is developing an
understanding of the types of information needed by the risk managers and the level of
uncertainty in that information that can be tolerated. It does not make sense to conduct an
expensive risk assessment if the eventual results will not be helpful to decision makers.
5.3.2.6 Lessons Learned on Planning and Scoping
EPA's Science Policy Council has evaluated the planning and scoping process, particularly as it
relates to cumulative risk assessments (http://www.epa.gov/osp/spc/2cumrisk.htm). From an
assessment of five case studies, a working group identified the following lessons learned:(8)
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• Early and extensive involvement of the risk manager (decision maker) helped focus the
process toward a tangible product.
• Purporting that planning and scoping will be quick and easy is likely to be counterproductive;
it is a lot more work than people assume. However, it ultimately saves time by helping to
organize everyone's thinking and usually results in a better quality assessment.
• Stakeholder engagement is essential at the beginning, because their patience is directly
proportional to their sense of influence in the process. They have been helpful in identifying
important public health endpoints that were not initially considered by EPA in the process of
developing a conceptual model.
• Conceptual models are helpful in demonstrating how one program relates to other regulatory
activities as well as the relationship between stressors and effects beyond traditional
regulatory paradigms.
• Debate over terminology and brainstorming sessions are necessary to reach a consensus. A
clear set of definitions aids this process.
• The planning and scoping process cannot be prescriptive, because the context of each
situation is different. Planning and scoping is particularly valuable when the assessment will
be complex, controversial, or precedential. At this time, planning and scoping usually
precede cumulative risk assessments.
• Clear objectives, resource commitments, and estimated schedules from management will
drive the approach and level of detail that can be considered.
• Explaining uncertainty to stakeholders is critical despite a hesitancy to reveal all that is
known and not known about chemical risks. While revealing these uncertainties may lead to
criticism and political ramifications, it can also develop a sense of trust, credibility, and
support for the decision making process.
It should also be noted that the entire planning and scoping (and risk assessment process) is
inherently iterative in nature. As the analysis proceeds and participants learn more about the
study area, participants may find the initial assumptions in the conceptual model inadequate and
they will need to modify the conceptual model (and, thus, the analysis plan). For example,
suppose a conceptual model was developed that assumed a chemical was released from a facility
that is generally thought to deposit quickly from the air, is highly persistent, and has a large
bioaccumulation potential, thus requiring a multipathway analysis. Once the emissions inventory
is verified, it is found that this chemical is actually not used or produced by facility, rendering the
multipathway analysis moot for this chemical. (Multipathway analysis may still be needed for
other chemicals in the emissions.)
When such changes are required in the conceptual model and analysis plan, all key stakeholders
maybe apprised of the change and ideally agree to any alterations in the goals of the overall
assessment. The initial goal of "no surprises at the end of the assessment" is still maintained in
light of evolving information.
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References
1. U.S. Environmental Protection Agency. 2003. Framework for Cumulative Risk Assessment.
Risk Assessment Forum, Washington, DC 20460, May 2003, EPA/630/P02/001F. Available
at http://cfpub.epa.gov/ncea/raf/recordisplay.cfm?deid=54944.
2. U.S. Environmental Protection Agency. 1999. Residual Risk Report to Congress. Office of
Air Quality Planning and Standards, Research Triangle Park, NC 27711, March 1999,
EPA/453/R99/001. Available at http://www.epa.gov/ttncaaal/t3/reports/risk_rep.pdf.
3. U.S. Environmental Protection Agency. 1992. Guidelines for Exposure Assessment. Federal
Register 57:22888-22938, May 29, 1992. Available at
http ://cfpub. epa. gov/ncea/raf/recordisplay .cfm?deid= 15263.
4. U.S. Environmental Protection Agency. 1997. Guidance on Cumulative Risk Assessment.
Part 1. Planning and Scoping Science Policy Council, Washington, B.C. Available at:
http ://www. epa. gov/osp/spc/cumrisk2.htm.
5. U.S. Environmental Protection Agency. 2003. Framework for Cumulative Risk Assessment.
Risk Assessment Forum, Washington, D.C. 2003. EPA/630/P02/001F. Available at:
http://cfpub.epa.gov/ncea/raf/recordisplay.cfm?deid=54944.
6. U.S. Environmental Protection Agency. 2001. Risk Assessment Guidance for Superfund
(RAGS): Volume I - Human Health Evaluation Manual (Part D, Standardized Planning,
Reporting and Review of Superfund Risk Assessments) Final. Office of Emergency and
Remedial Response, Washington, D.C. Available at:
http://www.epa.gov/superfund/programs/risk/ragsd/index.htm.
7. U.S. Environmental Protection Agency. 1999. Risk Assessment Guidance for Superfund:
Volume 1 - Human Health Evaluation Manual. Supplement to Part A, Community
Involvement in Superfund Risk Assessments. Office of Solid Waste and Emergency
Response, Washington, D.C. EPA/540/R98/042/PB99/963303.
8. U.S. Environmental Protection Agency. 2002. Lessons Learned on Planning and Scoping for
Environmental Risk Assessments. Science Policy Council, Washington, D.C. Available at:
http://www.epa.gov/osp/spc/handbook.pdf.
April 2004 Page 5-15
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Chapter 6 Problem Formulation: Inhalation Risk
Assessment
Table of Contents
6.1 Introduction 1
6.2 Developing the Conceptual Model 1
6.3 Developing the Analysis Plan 4
6.3.1 Identification of the Sources 5
6.3.2 Identification of the Chemicals of Potential Concern 6
6.3.2.1 Toxicity-Weighted Screening Analysis 6
6.3.2.2 Risk-Based Screening Analysis 7
6.3.3 Identification of the Exposure Pathways/Routes £
6.3.3.1 Characteristics of the Assessment Area 1_2
6.3.3.2 Scale of the Assessment Area 1_4
6.3.3.3 Use of Modeling versus Monitoring 1_4
6.3.3.4 Estimation of Exposure 1/7
6.3.3.5 Evaluation of Uncertainty 20
6.3.3.6 Preparation of Documentation 20
6.3.4 Identification of the Exposed Population 20
6.3.5 Identification of the Endpoints and Metrics 2J_
6.4 Data Quality in the Risk Assessment Process 22
References 24
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6.1 Introduction
This chapter discusses the problem formulation step, which takes the results of the planning and
scoping process and translates them into two critical products:
• A conceptual model that explicitly identifies the sources, receptors, exposure pathways, and
potential adverse human health effects that the risk assessment will evaluate (described in
Section 6.2); and
• An analysis plan that outlines the analytical approaches that will be used in the risk
assessment (described in Section 6.3).
An additional section on data quality (Section 6.4) is also included as a reference for those
portions of the risk assessment that involve data collection (e.g., emissions inventories,
monitoring). EPA's Framework for Cumulative Risk Assessment provides a more detailed
discussion of the problem formulation process.
6.2 Developing the Conceptual Model
The general concern and approach articulated in the problem statement usually receives more
detail in a study-specific conceptual model. This model explicitly identifies the sources,
receptors, exposure pathways, and potential adverse human health effects that the risk assessment
is going to evaluate. The study-specific conceptual model comprises both a picture and written
description that illustrate: the current understanding of what sources are releasing air toxics in a
particular place; how the chemicals maybe transported from the point of release to the point
where people can breathe them; and the types of health effects that may result. Risk assessors
commonly include both a pictorial illustration (such as a technical drawing) and a narrative
description of each of the above elements in the conceptual model.
The conceptual model establishes the physical boundaries of the assessment area and focuses the
risk assessment on several key elements, including sources, chemicals released, fate and transport
mechanisms, potentially exposed populations, potential exposure pathways and routes of
exposure (e.g., breathing, ingesting), and potential adverse effects. Although participants may
revise or refine the conceptual model during the risk assessment, it is important to develop an
initial conceptual model early on.
Critical elements to be included in the conceptual model include:
• The sources of air toxics. The identity, location (latitude/longitude), and physical nature of
the sources being evaluated (which may include factories, small businesses, cars/trucks,
forest fires, etc.), including general emissions characteristics (e.g., stack locations, heights,
other stack parameters, control device efficiency, operating schedules).
• Stressors. The specific air toxics that will be evaluated. Information on air toxics may come
from emissions inventories, previous monitoring or modeling studies, permits, or estimates
based on the principal processes or activities occurring at the source or site. Many risk
assessments begin with a relatively large number of stressors that are of potential concern
April 2004 Page 6-1
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(chemicals of potential concern, or COPC) and narrow these to the subset that contributes
most to exposure and risk.
The exposure pathways/media f Chemicals of Potential Concern (COPc)
of concern. The environmental
compartments into which the air
toxics move after they are released
and through which human
exposure can occur. Once
released from the sources, air
toxics begin to disperse by the
wind away from the point of
release and may remain airborne;
Chemicals of potential concern (COPC) are those air
toxics that are evaluated in the risk assessment because
they have the potential to affect the risk management
decision. The corresponding term for ecological risk
assessment are chemicals of potential ecological concern
(COPEC). The risk assessment often finds that most of
the risk is associated with a subset of the COPC. The
subset, which drives the risk management decisions, is
, . , ,-r-r- . 1 . \ referred to as chemicals of concern (COC).
convert into a different substance; V
and/or deposit out of the air onto
soils, water, or plants. People may be exposed to air toxics by breathing contaminated
outdoor and/or indoor air (inhalation); ingestion (for the small number of air toxics that can
accumulate in soils, sediments, and foods - a process called bioaccumulation); and skin
(dermal) contact with deposited air toxics. Air toxics risk assessments always evaluate the
inhalation exposure pathway. However, when sources release chemicals that persist and
which also may bioaccumulate, analysis of non-inhalation pathways may also be necessary
(see Parts in and IV for information on inhalation pathways).
• Routes of exposure. Potential routes of exposure include inhalation, ingestion, and dermal
absorption.
• Subpopulations. The human populations potentially receiving exposure to the air toxics,
including information about demographics (race, ethnicity, economic status, etc.) and
potentially sensitive subgroups (e.g., elderly, children). Depending on the goals of the risk
assessment, the conceptual model may need to consider populations currently living in a
given area as well as those that might move into the area in the future.
• Endpoints. The harmful effects that may result from exposure to air toxics, including
cancer, respiratory effects, birth defects, and reproductive and neurological disorders. Air
toxics can damage the organs at the initial point of contact or enter the body and move via the
bloodstream to other target organs or tissues. Choice of endpoints generally depends on the
toxic effects exhibited by the specific air toxics being assessed. Risk assessors generally
represent potential adverse health effects to humans from exposure to air toxics through the
inhalation pathway as cancer and noncancer outcomes (see Exhibit 5-3). Unless risk
assessors study a specific chemical that is linked to a specific health outcome (which is not
usually the case), a general statement that "risk of cancer and noncancer hazard will be
evaluated" is usually sufficient.
• Metrics. It should be determined how cancer risk and noncancer hazard will be estimated
and reported.
Exhibit 6-1 provides an example of a generalized conceptual model for air toxics risk
assessments with examples of possible linkages. The example shown is a graphical illustration;
April 2004 Page 6-2
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it would also be possible to develop a pictorial illustration. The conceptual model for a specific
risk assessment will likely include only part of this general model. For example, pathways
involving soil, water, and food will only be included if PB-HAP compounds are COPC. In the
conceptual model, the sources, pathways, and expected health outcomes are drawn to illustrate
what the assessors think may be happening in the study when sources are releasing air toxics to
the environment. For a specific study, risk assessors would augment the illustration with the
actual names/locations of sources, the COPC they release, the populations of concern and their
location, and the specific health outcomes of concern (the generic endpoints of cancer and
noncancer health outcomes, as drawn here, are usually sufficient for this stage of the assessment).
The accompanying narrative will describe each of the elements of the illustration in detail and
will provide sufficient information to clarify the critical elements of each piece of the picture.
Exhibit 6-1. Generalized Conceptual Model for Air Toxics Risk Assessments
Sources
Sfressors
Pathways/
Media
Routes
Subpopulations
Major
Industrial
1
Small "area"
sources
IJ
Mobile
ana off-r
I
33 Priority Urban HAPs
(including PBTst
I
on-
oad)
Extrinsic
"background" in air
F
Subset of PBTs
Indoor air
sources
I I
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i
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Endpoints
(Specific non-cancer
target organ
endpoints shown for
example purposes)
Metrics
HAP-spedfic and
cumulative (e.g., by
cancer type, weight of
evidence: by target-organ-
specific nszsrd index), by
Slate toy county (also ail
counties and atf urban
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African
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i
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Possible Carcinogen
Probable Carcinogens
Known Carcinogens
Distribution of
high-end cancer r.
risk estimates
Estimated percent of
opulation within specified
cancer risk ranges
Estimated
number of
cancer cases
_
Cardiovascular Hazard Index
Liv-i wrr.-Kidney Hn/dfi- IHtsx
CMS Hazard Index
Blood Hazard Index
Respiratory System Hazard Index
Distribution of
estimated
index values
Estimated percent of
population within specified
ranges of index values
This figure illustrates a general conceptual model for air toxics risk assessments with examples of
potential linkages. The conceptual model for a specific risk assessment will likely include only part of
this general model. In this figure, the heavy lines represent the conceptual model used for the initial
National-scale Air Toxics Assessment (Draft for EPA Science Advisory Board Review, available
online at http://www.epa.gov/ttn/atw/sab/sabrev.html). This assessment focused on 33 air toxics and
was limited to inhalation exposures. Cancer and noncancer endpoints were assessed using
distributions, estimated percentages of the population within specified risk or hazard index ranges, and
estimated incidence (only for cancer cases).
April 2004
Page 6-3
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^ NV
IfPB-HAP compounds identified in Exhibit 4-2 (or other air toxics that persist and may
bioaccumulate and/or bioconcentrate) are present in emissions, both the conceptual model and the
analysis plan may need to consider pathways other than inhalation (e.g., deposition to soil and
surface waters, uptake by biota, and ingestion of these media and biota) for human and ecological
receptors. For purposes of this Reference Manual, we discuss the elements/considerations for the
conceptual model and analysis plan that are particular to multipathway human health risk
assessment in Part III and ecological risk assessment in Part IV. However, the planning, scoping,
and problem formulation process specific to multipathway analyses is generally integrated with the
process for the inhalation analysis as early as feasible.
6.3 Developing the Analysis Plan
Risk assessors use the study-specific conceptual model as a guide to help determine what types,
amount, and quality of data are needed for the study to answer the questions the risk assessment
has set out to evaluate. Specifically, the analysis plan matches each element of the conceptual
model with the analytical approach that the assessors will use to develop data about that element
(Exhibit 6-2).
Most often, the analysis plan details the link between each element of the conceptual model and
the specific analytical approach. The participants would then describe each of the analytical
approaches in sufficient detail to provide the risk assessors with sufficient direction to allow
them to produce the desired high quality data. For example, when determining exposure
concentrations of COPC at the point of exposure to humans, the analysis plan will describe the
exact sampling/analytical lab methods and/or models that risk assessors will use to generate this
data, who will perform the analyses, when the analyses will be done, quality assurance/quality
control requirements (including data validation procedures), roles/responsibilities of analysts, and
documentation requirements. This section of the analysis plan would also provide a discussion
of how data gaps should be identified and documented and how assessors will address
uncertainties.
The analysis plan may also include a comparison between the level of confidence needed for the
management decision and the actual level of confidence it expects from alternative analytical
approaches; this will determine which alternative best meets the management goals, within the
constraints of time and resources. In addition, the analytical approach may include a phased or
tiered risk assessment approach to facilitate management decisions (see Section 6.4 below).
The analysis plan is most helpful when it contains explicit statements of how participants
selected the various analytical approaches, what piece of the conceptual model they intended the
approach to evaluate, how the approach integrates with other analytical elements, and specific
milestones for completing the risk assessment. Assessors generally include uncertainties
associated with analyses, and approaches for addressing these uncertainties, in the analysis plan
when possible.
April 2004 Page 6-4
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Exhibit 6-2. Important Elements to be Included in an Analysis Plan
Sources How will information on the sources in the analysis (e.g., source location,
important release parameters) be obtained and analyzed?
Pollutants How will chemicals of potential concern (COPC) be confirmed and their
emissions values be estimated?
Exposure pathways How will the identified exposure pathways be assessed? How will ambient
concentrations be estimated?
Exposed population^) How will exposures to populations of interest be characterized? How will
their exposure concentrations be estimated? What will be the temporal
resolution? What sensitive subpopulations may be affected?
Endpoints How will information on the toxicity of the COPC be obtained (what are the
data sources)? What risk metrics will be derived for the risk
characterization?
In addressing the above aspects of the analysis, the plan should also clearly describe the following:
• How will quality be ensured in each step (e.g., what will be included in the quality
assurance/quality control plans)?
• How will uncertainty and variability in the results be assessed?
• How will all stages of the assessment be documented!
• Who are the participants and what are their roles and responsibilities in the various activities?
• What is the schedule for each step (including milestones)?
• What are the resources (e.g., time, money, personnel) being allocated for each step?
The analysis plan may not result in just one document, but rather in a combination of multiple
work plans that, taken together, constitute "the analysis plan." For example, for a study where
assessors will perform both air dispersion modeling and air monitoring, participants may develop
a separate work plan for both modeling and monitoring. However, assessors usually develop a
master plan that describes all the different pieces and their relationship to one other.
The remainder of this subsection describes the important elements of the analysis plan, including:
• Identification of sources;
• Identification of chemicals of potential concern;
• Identification of exposure pathways/routes;
• Identification of exposed populations; and
• Identification of endpoints and metrics.
6.3.1 Identification of the Sources
As noted in Part I, EPA classifies sources of air toxics into a variety of categories for regulatory
purposes, including stationary sources, mobile sources, and indoor sources (see Chapter 4). In
addition, risk assessors also commonly group substances by their chemical and physical
properties to both better estimate the fate and transport of chemicals in the environment and to
April 2004 Page 6-5
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make inferences about the types of exposure pathways likely to be important in the exposure
assessment.
This part of the analysis plan specifies the approach to be used to identify the specific sources
that will form the initial focus of the analysis. Depending on the goals of the risk assessment,
these sources may be limited to a single source or multiple sources at a facility (i.e., facility-
specific risk assessments discussed in Volume II of this reference library) or may cover a wider
variety of sources, including mobile sources, stationary sources, and possibly other sources such
as indoor and natural sources (e.g., community-based risk assessments discussed in Volume HI of
this reference library). Identifying sources may be relatively straightforward (e.g., for facility-
specific risk assessments) or may involve considerable research, particularly when dealing with a
large number of smaller sources. In such an analysis, the initial tier of evaluation generally
focuses on all identifiable sources within the assessment area. In subsequent tiers, it may be
possible to remove some of these sources from the exposure assessment if one can determine that
they contribute a very small fraction to the total risk estimate. Chapter 12 contains the
techniques for conducting this type of screening.
6.3.2 Identification of the Chemicals of Potential Concern
This part of the analysis plan specifies the approach to be used to identify the most important air
toxics that sources release (i.e., the chemicals of potential concern, or COPC). The COPCs will
be the primary focus of the exposure and risk assessment. The initial tier of analysis often
includes all of the air toxics released from the identified important sources. Depending on the
specific air toxics of concern, the risk assessment also may need to consider secondary
compounds that are formed from the reaction in the atmosphere.
Two techniques are available to focus the risk assessment on the most important air toxics:
• During problem formulation, a simple toxicity-emissions weighted screening approach can be
conducted (discussed in Section 6.3.2.1).
• Once an initial risk characterization has been performed, subsequent tiers of analysis may
remove specific chemicals from the COPC list if they are determined to contribute only a
very small fraction to the total risk estimate (discussed in Section 6.3.2.2).
(Note that some assessors may wish to simply carry through the analysis all of the chemicals
emitted to the assessment area. This is appropriate; however, it may require sufficient resources
and result in little useful information.)
6.3.2.1 Toxicity-Weighted Screening Analysis
To determine which air toxics to include in the Tier 1 inhalation risk assessment, a relative risk
evaluation called a toxicity-weighted screening analysis (TWSA) may be calculated based on
the emissions data for all air toxics released from the facility/source being assessed. A TWSA is
particularly useful if there are a large number of air toxics in the facility/source emissions and
there is a desire to focus the risk analysis on a smaller subset of air toxics that contribute the most
to risk. A TWSA can be performed as described below.
April 2004 Page 6-6
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The TWSA is intended to be entirely emissions- and toxicity-based, without considering
dispersion, fate, receptor locations, and other exposure parameters. It essentially compares the
emissions rates of each air toxic to a hypothetical substance with an inhalation unit risk value of
1 per ug/m3 (for carcinogenic effects) and/or a reference concentration (RfC) of 1 mg/m3 (for
noncancer effects). It requires emissions (release) information as well as the applicable
dose-response values (see Chapter 12). However, is also can be used even with a single emission
point and many air toxics. The steps for emissions-based toxicity-emissions weighted screening
are presented below.
1. Identify all the inhalation unit risks (lURs) and RfCs for the air toxics in the facility/source
emissions.
2. Determine the emission rate (e.g., tons/year) of each air toxic.
3. Multiply the emission rate of each air toxic by its IUR to obtain a toxicity-emissions product.
4. Rank-order the toxicity-emissions products and obtain the sum of all products.
5. Starting with the highest ranking product, proceed down the list until the cumulative sum of
the products reaches a high proportion (e.g., 99 percent) of the total of the products for all the
air toxics. Include in the assessment all the air toxics that contributed that proportion (e.g.,
99 percent) of the total (see Exhibit 6-3 for an example calculation).
6. Repeat steps 3-5, but instead divide the emissions rate by the RfCs to obtain "noncancer
equivalent tons'Vyear (see Exhibit 6-4 for an example calculation).
Chemicals with no toxicity data will necessarily not be included in the initial list of COPCs
identified by the TWSA screening process. However, this does not necessarily mean that they
are not potential risk drivers. Chemicals with no toxicity data are to be evaluated as part of the
overall uncertainty analysis for the risk assessment. If there is sufficient evidence to support the
hypothesis that an omitted chemical is a potential risk driver, the risk assessment team may opt to
develop a toxicity value for the chemical (see Chapter 12 for more information on identifying
toxicity values for chemicals). Also, if evidence suggests that a chemical that is screened out
(e.g., is below the 99th percentile in the TWSA) would nevertheless have an individual HQ or
cancer risk greater than the selected screening level, the assessor may consider keeping the
chemical in the list of COPCs.
6.3.2.2 Risk-Based Screening Analysis
In subsequent tiers of analysis, a risk-based screening analysis can be used to further focus the
assessment on the significant air toxics of concern. This approach would be similar to the
TWSA except that estimated individual cancer risk and noncancer hazard estimates would be
used instead of toxicity-weighted emissions (an example risk-based screening analysis is
presented in Chapter 13). A risk-based screening analysis might include the following steps:
1. Using applicable input data, run a simple dispersion and/or exposure model and calculate
cancer risk at a selected point (e.g., maximum exposed individual location).
2. Rank-order the individual risk estimates for each emitted air toxic and obtain the sum of the
cancer risk.
3. Starting with the highest ranking cancer risk, proceed down the list until the individual air
toxics contributing a large proportion (e.g., 99 percent) of the total risk are included. Include
those air toxics in subsequent tiers of analysis.
4. Repeat steps 1-3 for noncancer hazard.
April2004 Page 6-7
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Exhibit 6-3. Example TWSA Calculation for Cancer Effects
Air Toxic
1,3 -butadiene
carbon tetrachloride
beryllium compounds
arsenic compounds
2,3,7,8-TCDD
chromium (VI) compounds
polycyclic organic matter00
cadmium compounds
formaldehyde
1 ,3-dichloropropene
allyl chloride
methylene chloride
benzene
Emissions
(tons/year)
8.2 x IQ1
1.5 x 102
8.6 x ID'1
4.2 x IQ-1
2.0 x ID'5
3.7 x ID'2
4.3
1.0 x 10'1
8.9
5.2
2.8
1.9 x IQ1
9.3 x 1Q-2
IUR
3.0 x 1Q-5
1.5 x lO'5
2.4 x 1C'3
4.3 x lO'3
3.3 x 101
1.2 x lO'2
2.1 x IQ-1
1.8 x lO'3
1.3 x lO'5
4.0 x 1Q-6
6.0 x 1Q-6
4.7 x lO'7
7.8 x lO'6
Total
Cancer
Equivalent
Tons/year
2.5 x lO'3
2.2 x lO'3
2.1 x lO'3
1.8 x lO'3
6.6 x lO'4
4.4 x lO'4
3.7 x ID'4
1.8 x 10'4
1.2 x lO'4
2.1 x lO'5
1.7 x 10'5
8.7 x ID'6
7.3 x lO'7
1.0 x lO'2
Percent
of Total
23.8%
21.3%
19.8%
17.5%
6.4%
4.3%
3.6%
1.8%
1.1%
0.2%
0.2%
0.1%
0.0%
100.0%
Cumulative
Percent
23.8%
45.1%
64.9%
82.4%
88.8%
93.1%
96.7%
98.4%
99.5%
99.7%
99.9%
100.0%
100.0%
Heavy line denotes 99% cutoff. In this example, 1,3-dichloropropene, allyl chloride, methylene
chloride, and benzene could be dropped from the cancer analysis.
(a) Cancer equivalent tons/year and IUR are based on the assumption that benzo(a)pyrene represents
5% of emissions.
6.3.3 Identification of the Exposure Pathways/Routes
This part of the analysis plan specifies the approach to be used to identify the specific exposure
pathways/routes that will be assessed. An exposure pathway/route describes the movement of air
toxics from the point of release to the point where exposure may occur and generally consists of
four elements:
1. A source and mechanism of release (emissions);
2. A transport medium (for inhalation, air);
3. A point of potential human contact with the contaminated medium (the exposure point); and
4. An exposure route at the contact point (e.g., inhalation).
April 2004
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Exhibit 6-4. Example TWSA Calculation for Noncancer Effects
Air Toxic
beryllium compounds
1,3 butadiene
arsenic compounds
cadmium compounds
carbon tetrachloride
allyl chloride
formaldehyde
2,3,7,8-TCDD
chromium (VI) compounds
toluene
1 ,3-dichloropropene
methylene chloride
benzene
Emissions
(tons/year)
8.6 x ID'1
8.2 x IQ1
4.2 x IQ-1
1.0 x ID'1
1.5 x 102
2.8
8.9
2.0 x ID'5
3.7 x ID'2
1.3 x 102
5.2
1.9 x 101
9.3 x ID'2
RfC
2.0 x ID'5
2.0 x ID'3
3.0 x ID'5
2.0 x ID'5
4.0 x ID'2
1.0 x lO'3
9.8 x ID'3
4.0 x ID'8
1.0 x ID'4
4.0 x 1Q-1
2.0 x ID'2
1.0
6.0 x ID'2
Total
Noncancer
Equivalent
Tons/year
4.3 x IQ4
4.1 x 1Q4
1.4 x 1Q4
5.1 x IQ3
3.7 x IQ3
2.8 x IQ3
9.1 x IQ2
5.0 x IQ2
3.7 x IQ2
3.2 x 1Q2
2.6 x IQ2
1.9 x IQ1
1.6
1.1 x io5
Percent
of Total
38.3%
36.7%
12.6%
4.6%
3.3%
2.5%
0.8%
0.4%
0.3%
0.3%
0.2%
0.0%
0.0%
100.0%
Cumulative
Percent
38.3%
75.0%
87.6%
92.1%
95.4%
97.9%
98.7%
99.1%
99.5%
99.8%
100.0%
100.0%
100.0%
Heavy line denotes 99% cutoff. In this example, chromium (VI) compounds, toluene, 1,3-
dichloropropene, methylene chloride, and benzene could be dropped from the noncancer analysis.
A critical determination in the exposure assessment is whether the potential exposure pathways
identified during scoping are complete (i.e., there is a plausible mechanism by which the air
toxic emitted from the source can reach the exposure point and a plausible mechanism by which
the human receptor can come into contact with the chemical at the exposure point). Exposure
cannot occur without a complete exposure pathway; and therefore if assessors determine that a
potential exposure pathway is incomplete, they will generally document and drop the exposure
from the risk assessment.
The exposures to be assessed depend on the needs articulated in the planning and scoping and
problem formulation steps, including the specific laws and regulations that mandate a potential
decision. For example, air toxics risk assessments commonly rely primarily on current land uses
when evaluating exposures, while risk assessments conducted in the Superfund program
commonly assess current and future land uses (i.e., air toxics risk assessments usually presume
that the current land use within the area of impact of a source(s) will remain unchanged into the
foreseeable future). The need, reasons, and methodology to evaluate alternate (e.g., future) land
use conditions may be carefully considered and fully articulated during the problem formulation
and planning/scoping phase of the assessment. As will be discussed later, in screening-level air
April 2004
Page 6-9
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toxics risk assessments, it is common to assess exposures at the point of maximum offsite
ambient concentrations, whether or not someone actually lives there (the maximum exposed
individual or MEI location).
In addition, advanced tools (such as the RAIMI approach; see Volume HI of this reference
library) allow exposure assessments to evaluate the contemporaneous impact of multiple sources
on a assessment area, identify the main contributors to the impact, and evaluate "what if
scenarios (e.g., what if this source cut its emissions by half; what if a roadway doubled its
traffic?). Ultimately, the needs of the risk manager will drive such decisions.
For inhalation risk assessments, assessors evaluate only one exposure pathway (inhalation);
multipathway risk assessments, on the other hand, focus on all relevant pathways (i.e., inhalation
and any other relevant pathway, such as ingestion or dermal; see Part HI of this Reference
Manual for a description of how multipathway analyses are done). Exhibit 6-5 illustrates the
exposure pathways/routes that are commonly assessed for air toxics inhalation risk assessments.
Note that depending on the types of sources and specific COPCs they release, some of these
pathways may or may not be relevant for any particular study.
Exhibit 6-5. Most Commonly Assessed Exposure Pathways/Routes for
Air Toxics Inhalation Risk Assessments
Outdoor emissions of vapor phase chemicals
f outdo or air
f indoor air (by penetration of outdoor air into indoor spaces)
Outdoor emissions of particles
f outdo or air
f indoor air (by penetration of outdoor air into indoor spaces)
Note:
• Other media/routes may be applicable for particular risk assessments;
• When available, information on indoor source contributions may also be considered.
Whether the exposures to be assessed include workers depends on the needs articulated in the
planning/scoping and problem formulation steps. For example, the Department of Labor's
Occupational Safety and Health Administration (OSHA) generally regulates the exposures of
workers to the chemicals they are exposed to in their workplace, and therefore these exposures
generally are not considered in an air toxics risk assessment. When workers are exposed to
chemicals not generated in their workplace (e.g., office workers exposed by a nearby factory), a
decision may be made to consider the risks.
Exhibit 6-6 provides an example of an exposure pathway evaluation summary for a hypothetical
study. The exposure pathways identified for further assessment will depend on the specific types
of chemicals released (including their chemical and physical form), the physical relationship of
the sources to the human receptors, meteorological conditions, and the relationship between
indoor and outdoor air for the chemicals under study (for indoor exposure component).
April 2004 Page 6-10
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Exhibit 6-6. Example Illustrating Possible Complete Exposure Pathways for a
Hypothetical Inhalation Air Toxics Risk Assessment
Potentially Exposed
Population
Current Land Use
Residents living in
Smallville, USA
Exposure Route,
Medium, and
Exposure Point
Inhalation of vapor
phase chemicals during
outdoor activities
Inhalation of p articulate
matter during outdoor
activities
Inhalation of vapor
phase chemicals during
indoor activities
Inhalation of particle
phase chemicals during
indoor activities
Pathway
Selected for
Evaluation?
Yes
No
Yes
No
Reason for Selection or
Exclusion
Residents live year-round in
Smallville
Preliminary analysis suggests that
no significant particulate matter is
released from sources in the
assessment area and that the
chemicals released remain in the
vapor phase
Residents live year-round in
Smallville and released chemicals
have the potential to penetrate
indoors; the COPC are also
released by indoor sources
Residents live year-round in
Smallville and no significant
particulate matter is released from
sources in the assessment area and
the chemicals released remain in
the vapor phase. There are no
known indoor sources.
Note: Assessment of completed non-inhalation exposure pathways are discussed in Part III of this
reference manual.
April 2004
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The approach for characterizing exposure pathways/routes in the analysis plan usually considers
a variety of information about the assessment area (as articulated in the conceptual model),
including how it will be bounded for the analysis. The analysis plan also specifies how exposure
will be estimated and quantified, including whether modeling and/or monitoring will be used.
The following subsections discuss:
• Characteristics of the assessment area;
• Scale of the assessment area;
• Use of modeling versus monitoring; and
• Quantification of exposure.
6.3.3.1 Characteristics of the Assessment Area
The physical characteristics of the assessment area provide a basis for identifying potential
exposure pathways/routes and receptor populations of concern. They also are important
considerations for selecting and providing input parameters for the air quality models to be used
and/or for establishing monitoring sites. There is no universal classification system for
describing the characteristics of the assessment area, but the following information is generally
important for inhalation exposure assessments:
• Urban versus rural setting. This distinction provides general information about the way
that air toxics will disperse in the environment once released and the expected number and
types of receptors. For example, releases in rural areas may tend to move downwind with a
relatively simple dispersion pattern, while releases in a large city are likely to disperse in very
complex patterns depending the size and placement of buildings. Additionally, some of the
newer dispersion models can adjust both for direction dependencies as well as time of year
due to changes in foliage.
• Simple versus complex terrain. Terrain affects both the way that air toxics will disperse in
the environment once released and the amount of dilution that will occur before they reach
receptors. For example, a plume might pass over nearby receptors in simple terrain, but
might intercept receptors located on elevated terrain (e.g., a plateau or hill) at the same
distance from the source. Assessors can determine the terrain of any area in the United States
from topographic maps available from the USGS (see below).
• Climate and meteorology. Climate features such as temperature and precipitation patterns,
and meteorological features such as wind speed and direction will affect the fate and
movement of air toxics in the atmosphere and after deposition. Seasonal and diurnal
conditions may be major factors affecting rates of contaminant migration where precipitation
rates or temperatures vary greatly according to the season or time of day. It also is important
to note whether unusual weather conditions occur frequently within the assessment area, as
these can have significant effects on contaminant fate and transport (see Appendix G).
• Other important geographic features. Nearby geographic features such as a lake or ocean
can have significant effects on contaminant dispersion and may require the use of special
dispersion models (see Chapter 9). For multipathway human health and/or ecological risk
assessments, exposure setting also may include such elements as water bodies and associated
watersheds, ecological receptors, and agricultural lands (see Parts III and IV).
April 2004 Page 6-12
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Current land use (and in limited instances, potential future land use) is an important factor to
consider in determining the exposure pathways and specific exposure points that are commonly
evaluated in the risk assessment (particularly for higher-tier risk assessments). Land use can
typically be identified by reviewing hard copy and/or electronic versions of land use land
classification (LULC) maps, topographic maps, and aerial photographs. Sources and general
information associated with each of these data types or maps are presented below. Also,
assessors may want to verify the Universal Transverse Mercator (UTM) coordinate system
format (North American Datum 27 (NAD27) or NAD83) to ensure consistency and prevent
erroneous geo-referencing of locations and areas.
• Land Use Land Cover (LULC) Maps. LULC maps can be downloaded directly from the
U.S. Geological Survey website (http://edc.usgs.gov/geodata/). at a scale of 1:250,000, in a
file type Geographic Information Retrieval and Analysis System (GIRAS) format. LULC
maps can also be downloaded from the website (http://www.epa.gov/ngispgm3/spdata/
EPAGIRAS/egiras/). at a scale of 1:250,000, in an Arc/Info export format. It is
recommended that the exact boundaries of polygon land use area coverages, in areas being
considered for evaluation, be verified using available topographic maps and aerial
photographic coverages.
• Topographic Maps. Topographic maps are readily available in both hard copy and
electronic format directly from USGS (http://mapping.usgs.gov/index.html) or numerous
other vendors. These maps are commonly at a scale of 1:24,000, and in a TIFF file format
with TIFF World File included for georeferencing.
• Aerial Photographs. Hard copy aerial photographs can be purchased directly from USGS
(http://mapping.usgs.gov/index.html) in a variety of scales and coverages. Electronic format
aerial photographs or Digital Ortho Quarter Quads (DOQQs) can also be purchased directly
from USGS, or from an increasing number of commercial sources, such as Microsoft's® areal
photo map server called "terraserver" (http://www.terraserver.com).
While these data sources do not represent the full universe of information available on human
activities or land use, they are readily available from a number of government sources (typically
accessible via the Internet), usually can be obtained at no or low cost, and when used together
provide a good starting point to identify and define, in a defensible manner, land use areas to be
considered for evaluation in the risk assessment. However, while the use of these or other data
can be very accurate, verifying identified land use areas "on the ground" may be important for
higher-tier risk assessments. Discussions with representatives of private and government
organizations which routinely collect and evaluate land use data (e.g., agricultural extension
agencies, U.S. Department of Agriculture, natural resource and park agencies, and local
governments) can also be helpful in updating current land use information or providing
information regarding future land use. Information on reasonable potential future land use can
also be obtained from local planning and zoning authorities, which may help determine what
level of development is now allowed under current regulations and what development is
expected in the future. EPA's Superfund program has developed a specific directive on the
process of how to go about determining future land use in a particular place.(2) This directive
may be consulted for information on how to formulate realistic assumptions regarding future land
use.
April 2004 Page 6-13
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6.3.3.2 Scale of the Assessment Area
The scale of the assessment area is determined to a large part by the specific question(s) or
problem(s) being addressed in the risk assessment. In determining the scale of the assessment
area, both the capabilities of the tools to be used and the physical characteristics of the
assessment area are considered by assessors. For example, some commonly used air dispersion
models are only considered by EPA to be valid out to about 50 km because of limitations in their
conceptual basis (e.g., Gaussian plume modeling has this limitation). A 50-km limit may be
sufficient for assessments that focus on highly impacted areas occurring within a few kilometers
of the emissions sources. However, other situations may involve a more distant area of
significant impact. For example, if there are unusual source characteristics such as very tall
stacks or unusual physical characteristics such as a nearby plateau where people live, modeling
may need to be extended to these more distant areas.
A separate, but related issue, is how to consider scale for assessments that incorporate monitoring
to characterize exposure. Since a monitor only assesses exposure at the point where the monitor
is located, the "scale" that this one point represents becomes much more difficult to determine.
Thus, the term "scale" can represent two different things for exposure assessment. When using
modeling, the "scale" of the assessment area is simply the geographical land area around the
sources within which modeling nodes will be placed and modeling will be done (for example, the
model may predict ambient concentrations at every point on a 100 x 100 m grid out to 50 km in
all directions from the sources). When assessors use monitoring to evaluate exposure, the
"scale" refers to the area around the monitoring location (and the types of exposures) the analysts
consider the monitoring data to represent (for example, a monitor located in an urban area that
does not directly receive the impacted of an identifiable point source is usually designated as an
"urban scale" monitor because it reflects general urban ambient air concentrations for
populations not directly impacted by point sources). A full discussion of this distinction is
provided in Chapter 9.
Scale can also refer more generally to the coverage of the analysis (see Exhibit 6-7). For
example, the 1996 NATA risk characterization provided risk estimates, at the county level, for
every county in the US. The "scale" of this analysis was nationwide. A real person, on the other
hand, who was outfitted with a personal monitoring device, might be described as "personal" or
"individual" scale.
6.3.3.3 Use of Modeling versus Monitoring
As this document has previously noted, risk assessors can base estimates of exposure
concentrations on either actual measurements (i.e., monitoring data) or air quality modeling.
Exhibit 6-8 provides a brief comparison of modeling and monitoring. Many studies may benefit
by using some combination of modeling and monitoring, because the two approaches can
complement one another.
Benefits of modeling include the ability to:
• Obtain a relatively quick, screening-level estimate of the potential for risk;
• Identify the subset of air toxics that contribute most significantly to the risk estimate;
• Identify the areas where the highest exposure concentrations are likely to occur;
April 2004 Page 6-14
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• Estimate concentrations over a broad assessment area; and
• Examine individual variability in exposure.
One of the limits in the usefulness of modeling may be the accuracy of the air toxics emissions
inventory (discussed in Chapter 7). Also, models can only provide estimates of exposure
concentrations; often monitoring is performed to confirm model predictions.
Exhibit 6-7. Air Toxics Risk Assessments May be Conducted at Different Scales
Area of Impact
Single Source
Multiple Sources
Air toxics risk assessments may be performed on a variety of geographical levels ranging from the
national level (e.g., the National-Scale Assessment), to the state, local, neighborhood, or even
individual levels. Within a given scale, the risk assessment could look at the impact from a single
source or multiple sources. The specific tools, approaches, and metrics used are likely to differ
depending on the geographic scale of interest.
Benefits of monitoring include the ability to:
• Provide actual concentrations, which often provide a stronger basis for leveraging emissions
reductions;
• Provide site-specific information to verify or calibrate model predictions;
• Provide time- and space-integrated measures of the actual concentrations at which individuals
are exposed when they move from place to place within the assessment area; and
• Measure episodic releases, which are otherwise difficult to measure and quantify and are not
well addressed in emissions inventories.
One of the limits in the usefulness of monitoring may be the representativeness of the location(s)
in which monitors are placed (i.e., if placed in the wrong locations, monitors can provide
incorrect and misleading information about exposures). Also, monitoring may not always be an
effective tool to link ambient concentrations to specific sources (if, for example, one is
monitoring benzene in an urban environment).
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Exhibit 6-8. Comparison of Modeling and Monitoring Approaches for
Estimating Ambient Air Concentrations
Modeling
Monitoring
Modeling is relatively fast and inexpensive. Many
screening-level models can be run in spreadsheet
formats and require relatively simple input parameters.
Many dispersion models, along with technical
reference manuals and other support documents, are
available for free download from EPA's Support
Center for Regulatory Air Models (SCRAM) website
(http://www.epa.gov/ttn/scram/). Resources normally
need to be expended to enhance the local air toxics
emission inventories to make air toxics modeling more
precise.
Monitoring takes time to build data, and there are
methodological limits and logistical issues. How
expensive monitoring is depends on what you are
trying to do and how much you have to buy or pay for.
Monitoring does not always require equipment
purchase and some states and local areas already have
equipment. Some less expensive monitoring
techniques are now available (i.e., passive samplers).
Modeling results can estimate concentration over a
large spatial area (e.g., a 50-km radius from a source)
and can provide a "big picture" view of the assessment
area. Modeling also allows for analysis of exposure
concentration at multiple points throughout the
assessment area. The downside of modeling, however,
is that these are predicted concentrations.
Monitoring results provide actual measured
concentrations. Multiple locations may be required to
characterize concentration over an area, although GIS
methods facilitate interpolation between locations. The
downside is that the monitoring may not be very
representative of a large geographic area.
Screening-level models can provide a predicted
estimate of whether significant concentrations are
likely. A simple screening analysis may be sufficient to
make a risk management decision that no action is
required.
Monitoring can be used to identify and measure
exposures for specific individuals at a specific location
of concern (e.g., a school). This data can provide a
quick screen to determine whether more extensive
monitoring is needed.
Models can be used to identify areas where maximum
concentrations are likely to occur, and thus to focus
efforts for additional tiers of the assessment.
Uncertainties in model parameters, and the discrete
division of the wind field used in models (often with
only eight wind directions) can result in incorrect
identification of the locations of maximal
concentration.
Monitoring can identify areas and actual levels of
exposures occurring at the monitoring sites.
Monitoring can also be used to indicate the point of
maximal exposure if the monitoring is designed for that
purpose. The selection of the monitoring locations is
critical; if placed in the wrong locations, monitors can
provide incorrect and misleading information about
maximal exposures.
Models can be used to identify the subset of COPC and
expo sure pathways/routes that have the greatest
contribution to risk. This can be helpful in focusing
efforts for additional tiers of the assessment as well as
determining appropriate risk management actions.
Monitoring can be used to confirm significant exposure
pathways and routes. (Measured concentrations can be
compared to risk-based screening levels.) It also can
be used to identify compounds that may not have been
suspected and, hence, were not included in models
(i.e., monitoring allows identification of gaps in the
emissions inventory).
Models allow "what if scenarios to be evaluated (e.g.,
what if a permitted emission were doubled?).
Monitoring can only evaluate current conditions.
More complex modeling may allow explicit prediction
and estimate of variability in exposure.
A large number of samples generally is needed to
characterize variability; this may be prohibitively
expensive. Monitoring, however, provides a direct and
reliable means to characterize variability.
Models often use simplifying assumptions and data
inputs that may or may not be representative of the
specific assessment area. This introduces uncertainty
into model predictions.
Monitoring can be used to confirm actual exposure
levels as well as investigate assumptions or calibrate
models to site-specific conditions, and to close gaps in
data, reducing uncertainties.
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6.3.3.4 Estimation of Exposure
An important element of the analysis plan is the specific approaches for developing numerical
estimates of exposure concentrations for each of the COPC for each of the populations the
assessment is studying (i.e., how exposure will be estimated and quantified). As noted in the
previous subsection, this may involve the use of air quality models and/or monitoring data.
Quantitation of exposure includes three general steps:
• Characterization of releases to the air. Characterizing the location, nature, and magnitude
of emissions released from the sources being evaluated, including release parameters such as
stack height and temperature of release (when modeling is being performed). This is
discussed Chapter 7.
• Estimation of chemical fate and transport. Modeling and/or measuring the ambient
concentrations of air toxics in the environment, as a result of transport, and including any
physical or chemical transformations that may occur during this movement, from the
emission point to the exposure points. This is discussed in Chapters 8, 9, and 10.
• Estimation of exposure concentrations. Developing a numerical estimate of exposure
concentrations of air toxics to the selected exposure points. This is discussed in Chapter 11.
For the inhalation route of exposure, the metric of ( „. ,. . . ~~ T , , ,. \
. . ,, . . ... 1 he Metrics 01 Exposure lor Inhalation
exposure is the concentration of the chemical in
The metric of exposure for inhalation is simply
the exposure concentration (EC) - the
concentration of a chemical in the air at the point
where a person breathes the air.
the air the population of interest is breathing over
the period of interest. This concentration is
called the exposure concentration (EC) and is
the primary quantitative output of the inhalation
exposure assessment. As we will see in Chapter N
11, this metric is intended to represent the time
weighted average exposure(s) to the population(s) of interest during the exposure period. (Note
that exposure models are often also applied to better reflect how different people interact with
contaminated air. In other words, the air quality model evaluates how chemicals move and
change in the environment. The exposure model evaluates how different types of people interact
with the resulting contaminated air - with the result that the EC is refined to provide more
realistic estimates of exposure. A discussion of exposure modeling is provided below.)
There are two general ways to estimate the EC (Exhibit 6-9); these are discussed in greater detail
in Chapter 11.
• Ambient Air Concentrations. For screening-level evaluations, assessors use the
concentration of air toxics generated at each modeling node (or interpolated nodes) or the
concentration determined by a monitor. The default assumption in such a screening
assessment is that the population of interest is breathing air continuously around-the-clock at
the modeled or monitor location. Proceeding in this manner, in the initial stages, is often
done because of the additional cost, time, and specialized expertise needed to run the
exposure model. Such results, depending on the purpose of the analysis, may be sufficient
for some risk management decisions (Chapter 3 provides a discussion on how to phase or
"tier" a risk assessment from simple but conservative to more complex yet realistic.)
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Exhibit 6-9. Two General Ways to Estimate Inhalation Exposure Concentration
100%
General Air Quality Assessment
Assessment Using Microenvironment Concept
The left-hand side illustrates the use of ambient air concentrations as a surrogate for the EC. In this
example, the analysis assumes that individuals spend 100 percent of their time at a given location, so
the estimate of ambient concentration thus represents the EC. The right-hand side illustrates the use of
exposure modeling. In this example, the analysis assumes that an individual spends 50 percent of
his/her time at home; 15 percent at a school; and 35 percent at an office. The EC is the weighted sum
of the product of the ambient concentrations at each location and the amount of time spent there. Both
indoor and outdoor concentrations usually are considered at each location.
• Exposure modeling. More comprehensive inhalation exposure assessments combine
estimates of ambient outdoor pollutant concentration (e.g., from air quality models) with
information about the population of interest, including the types of people present (e.g.,
ethnicity, age, sex), time spent in different microenvironments, and microenvironment
concentrations. The assessment objective is to obtain a representative estimate of the
pollutant concentration in the inhaled air in each microenvironment. For risk assessments
focusing on chronic effects resulting from chronic exposures, a long-term estimate of
exposure is the EC of interest. As discussed in Chapter 9, the resulting estimate is a refined
metric of personal exposure concentration (EC). This EC reflects the time spent in different
microenvironments (and the activities within these microenvironments) throughout the daily
routine of either representative individuals (selected statistically to be representative of the
potentially exposed population) or different groups of people with similar attributes (called
cohorts). The EC is essentially a time-weighted average exposure concentration for all of the
cohorts combined (see Exhibit 6-10).
People living in the vicinity of one or multiple air toxics sources have the potential to receive
exposure to emitted chemicals many different ways. For example, they might be exposed
occasionally, but to very high concentrations (e.g., when an accident occurs that releases large
amounts of chemical to the air in a very short amount of time). On the other hand, they might
receive exposure quite often (or even continuously) to low levels that would likely go unnoticed.
Air toxics inhalation exposure assessments usually focus on two of these different types of
possible exposure scenarios:
April 2004
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Exhibit 6-10. Example Cohort Group
Gender<2> Female
Race (4) { Af ric an
t A me Mean
Age (5) I
0-5 yrs
I
65+yrs
Example cohort: Male; African American; 18-64yrs
In this hypothetical example, cohort groups are defined based on gender (two categories); race (four
categories), and age (five categories). This example illustrates an African American male aged 18-64
years.
Mdnight
Home Census Tract Concentration
Work Census Tract Concentration
Act Jvity/Lo cation
SflWl
9A/1
Noon
3PM
6PM
9 PM Mdnght
15
15
12
1.1
* J
I
1.1
L
12
A
Sleeping Jog in
at home park
12
1B
1.5
3.8
2.8
4.5
*
1
1.7
A.
2.8
A
Working Drive
at office home
1
5
1.8
j
L
Sleeping
at home
Drive to
work
Eat in
restaurant
In this hypothetical example, daily exposure scenarios are developed based on ambient air
concentrations at work, and indoor and outdoor concentrations are assumed (for this example) to be
equal at a given location, and home and the specific activity patterns modeled for each cohort. In this
example, the African American male aged 18-64 years divides his activities among sleeping at home,
jogging in the park, driving to work, working at the office, driving home, and eating at a restaurant.
The daily exposure concentration is obtained by multiplying the time in each activity by the
appropriate ambient air concentration(s) for the time period(s) of interest, then summing the products.
For example, the product for jogging would be 1.2 (home concentration 3-6 AM) x 1.5 hours jogging
(during the 3-6 AM time period) + 1.1 (home concentration 6-9 AM) * 0.5 hours jogging (during the
time period 6-9 AM).
Chronic exposure refers to situations in which the exposure occurs repeatedly over a long
period of time (usually years to lifetime). If there is substantial variation in exposure
concentration during segments of the chronic period, it may be appropriate to evaluate the
segments separately using the appropriate dose-response values.
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• Sub-chronic exposure refers to situations in which the exposure occurs repeatedly over a
period of time that ranges between acute and chronic exposures (As toxicity values are less
widely available for this duration, it is less routinely assessed than the others. For air toxics
assessments, this exposure period is not commonly assessed.)
• Acute exposure refers to situations in which the exposure occurs over a short period of time
(usually minutes, hours, or a day) and usually at relatively high concentrations. The
averaging times commonly used to represent acute exposures concentrations (i.e., acute ECs)
are a 24-hour average, a one-hour average, or a 15-minute average.
The EC values the assessor develops to represent acute and chronic exposures should match the
assumptions built into the dose-response values that the assessor uses to characterize risk (see
Chapter 12). For example, it would be inappropriate to compare a one-week average exposure
concentration to a one-hour acute dose-response value. For chronic exposures, the scale of time-
weighted averaging performed to develop the exposure estimate should be generally similar to
that used in developing the dose-response value. For example, inhalation chronic RfCs are
derived from studies involving regularly repeated exposures (e.g., six hours a day, five days a
week in animal studies) over a chronic period. Thus, exposures occurring on a much lesser
frequency (e.g., a several days a week on a handful of occasions during a couple of years), should
not be averaged over the exposure period and compared to a chronic RfC. Such very infrequent
exposures may be more appropriately assessed as separate shorter-term or sub-chronic exposures.
6.3.3.5 Evaluation of Uncertainty
This part of the analysis plan specifies the approach to be used to evaluate uncertainty in the
exposure and risk estimates. Decision-makers will weigh the importance of the exposure (and
resulting risk) estimates in the eventual decision in the context of the uncertainties inherent in
these estimates. Assessment and presentation of uncertainty is discussed in Chapter 3.
6.3.3.6 Preparation of Documentation
This part of the analysis plan specifies the approach to be used to document all aspects of the risk
assessment. For most individual air toxics risk assessments, the exposure assessment represents
the majority of effort (and the majority of the documentation) and therefore may require the
greatest amount of work. A comprehensive documentation of the methods, assumptions, and
uncertainties associated with the exposure assessment is encouraged. Chapter 13 discusses
documentation in greater detail.
6.3.4 Identification of the Exposed Population
This part of the analysis plan specifies the approach to be used to characterize the location and
size of the populations of interest to the assessment. Additional information on population
characteristics may assist in characterizing exposure, and in identifying sensitive sub-
populations.
• Population data. In identifying and also characterizing a potentially exposed population, the
U.S. Census Bureau (www.census.gov) is the primary source of population information (e.g.,
the most recent data on the US population is contained in the 2000 Census).
April 2004 Page 6-20
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• Sensitive sub-populations. Human exposure and susceptibility and sensitivity to pollutant
effects may vary with factors such as age, gender, intensity and amount of activity, time spent
in microenvironments, diet, overall health, lifestyle, genetic factors, and the concentration of
pollutant. The extent to which these factors are considered in the risk assessment depends on
the purpose of the assessment as defined in the planning/scoping and problem formulation
steps, available resources, uncertainties in the assessment, and data quality and quantity.
6.3.5 Identification of the Endpoints and Metrics
This part of the analysis plan specifies which human health endpoints will be evaluated in the
risk assessment and the metrics by which they will be evaluated. For inhalation exposures, EPA
generally evaluates individual cancer risk and noncancer hazard (see Chapter 12 for a more
detailed discussion).
• Estimated individual cancer risk is generally expressed as a numerical probability that a
person will develop cancer over the course of their lifetime as a result of the exposures under
study.
• Noncancer effects are generally evaluated by comparing exposure concentrations to reference
concentrations (RfCs), which are estimates (with uncertainty spanning perhaps an order of
magnitude) of a continuous inhalation exposure to the human population (including sensitive
subgroups) that is likely to be without an appreciable risk of deleterious non-cancer effects
during a lifetime. Noncancer effects generally are assessed for both acute and chronic
exposure times.
Risk is usually described as either the risk experienced by different individuals within a
population or the risk experienced by groups of people. The former is called risk to an individual
(or simply individual risk), and the latter is called risk to a population (or simply population risk).
The difference between the two is that individual risk describes risk to one person at a time,
while population risk generally describes the number of people in a population experiencing the
same risk. Thus, in a city block containing 400 people with an estimated risk (calculated at the
block internal point) of two in 10,000 (2x 10"4), one could describe the risk to each of the
individual 400 people as "individual risk = 2x 10"4." Alternatively the population risk could be
described as "400 people living at a risk of 2x10"4." While this distinction may seem arbitrary,
risk often varies substantially over the exposed population. The use of both types of risk
estimates assists risk managers in balancing concerns of small numbers of highly exposed people
and larger numbers of people with lower exposures.
It generally is preferable to present a range of risk estimates, particularly in higher-tier
assessments. Distributions are often more useful than point estimates. However, since
developing fully distributional estimates of risk is usually out of the scope of most risk
assessments, a sense of the range of risks is usually provided by developing both central tendency
and high end point estimates.
• Central tendency estimates are intended to give a characterization of risk for the typical
individual in the population. This is usually either based on the arithmetic mean risk
(average estimate) or the median risk (median estimate).
April 2004 Page 6-21
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• High end estimates are intended to estimate the risk that is expected to occur in the upper
range of the distribution (e.g., risk above about the 90th percentile of the population
distribution).
Risk characterization is discussed in more detail in Chapter 13.
6.4 Data Quality in the Risk Assessment Process
All air toxics risk assessments involve some data collection (e.g., emissions inventories will be
developed to support air quality modeling, and/or monitoring data will be collected). For data
collection efforts, a central component to the analysis plan is data quality assurance. The
credibility of the risk assessment depends in part on the quality of the data that it uses. EPA uses
its Quality System to manage the quality of its environmental data collection, generation, and
use. The EPA quality website (http://www.epa.gov/quality) is an excellent resource for quality-
related information that assessors will want to become familiar with as they develop an analysis
plan for a risk assessment project.
As part of its effort to develop an Agency-wide data quality program, EPA has developed a
number of specific tools that have direct applicability in performing risk assessment projects,
including:
• Data quality assessment;
• Systematic planning (and the Data Quality Objectives Process);
• Quality assurance project plans;
• Standard Operating Procedures;
• Technical Audits; and
• Verification and Validation.
The use of these tools will help in the development of enough high quality data to allow assessors
to answer the assessment questions in a robust way. A brief discussion of each of these tools
follows. More in-depth discussion of each of these tools can be found on EPA's Quality website.
• Data Quality Assessment helps assess the type, quantity, and quality of data. This
assessment, in turn, helps to verify that assessors satisfy the planning objectives. A Quality
Assurance Project Plan components and sample collection procedures help ensure that the
data are suitable for its intended purpose. Data Quality Assessment is a five-step procedure
for determining statistically whether or not a data set is suitable for its intended purpose.
This assessment is a scientific and statistical evaluation of data to determine if it is of the
type, quantity, and quality needed and may be performed either during a project to check the
process of data collection or at the end of a project to check if objectives were met.
• Systematic Planning is necessary to define the type, quantity, and quality of data a decision
maker needs before collecting or generating environmental data. The Data Quality
Objectives Process is an example of a systematic planning process that assessors would use
to translate a decision maker's aversion to decision error into a quantitative statement of data
quality needed to support that decision. Data Quality Objectives are not required under
EPA's quality system; however, EPA does require that a systematic planning process such as
April 2004 Page 6-22
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the Data Quality Objectives Process be used for all EPA environmental data collection
activities. EPA recommends using the Data Quality Objectives Process when decision-
makers are using data to select between two opposing conditions, such as determining
compliance with a standard.
Quality Assurance Project Plan (QAPP) documents the planning, implementation, and
assessment procedures for a particular project, as well as any specific quality assurance and
quality control activities. It integrates all the technical and quality aspects of the project in
order to provide a "blueprint" for obtaining the type and quality of environmental data and
information needed for a specific decision or use. Note: All work performed or funded by
EPA that involves the acquisition of environmental data must have an approved QAPP.
• Standard Operating Procedures are written documents that describe, in great detail, the
routine procedures to be followed for a specific operation, analysis, or action. Consistent use
of an approved Standard Operating Procedure ensures conformance with organizational
practices, reduced work effort, reduction in error occurrences, and improved data
comparability, credibility, and defensibility. Standard operating procedures also serve as
resources for training and for ready reference and documentation of proper procedures.
• Technical audits are systematic and objective examinations of a program or project to
determine whether environmental data collection activities and related results comply with
the project's QAPP and other planning documents, are implemented effectively, and are
suitable to achieve its data quality goals. Technical audits are not management assessments
nor are they data verification/validation processes, which occur during the assessment phase
of the project. Technical audits include readiness reviews, technical systems audits,
surveillance, and performance evaluations.
• Data verification and validation is used to evaluate whether data has been generated
according to specifications, satisfy acceptance criteria, and are appropriate and consistent
with their intended use. Data verification is a systematic process for evaluating performance
and compliance of a set of data when compared to a set of standards to ascertain its
completeness, correctness, and consistency using the methods and criteria defined in the
project documentation. Data validation follows the data verification process and uses
information from the project documentation to ascertain the usability of the data in light of its
measurement quality objectives and to ensure that results obtained are scientifically
defensible.
Quality Assurance is an integral part of data collection and analysis throughout the risk
assessment project and the various activities addressed and documented in the QAPP cover the
entire project life cycle, integrating elements of the planning, implementation, and assessment
phases (Exhibit 6-11).
• Planning. The Data Quality Objectives (DQOs) are together a structured, systematic
planning process that provides statements about the expectations and requirements of the data
user (such as the decision maker).
April 2004 Page 6-23
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Implementation. The QAPP translates these requirements into measurement performance
specifications and QA/QC procedures for the data suppliers to provide the information
needed to satisfy the data user's needs.
Assessment. The QAPP includes plans for data validation and data quality assessment.
Exhibit 6-11. QA Planning and the Data Life Cycle
PLANNING
Data Quality Objectives Process
Quality Assurance Project Plan Development
IMPLEMENTATION
Field Data Collection and Associated
Quality Assurance/Quality Control Activities
ASSESSMENT
Data Validation
Data Quality Assessment
QA PLANNING FOR
DATA COLLECTION
Data Quality Objectives Process
OUTPUTS
Data Data
Quality Collection
Objectives Design
T INPUTS T
Quality Assurance
Project Plan Development
I
Quality Assurance
Project Plan
References
1. U.S. Environmental Protection Agency. 2003. Framework for Cumulative Risk Assessment.
Risk Assessment Forum, Washington, D.C., May 2003. EPA/630/P02/001F. Available at:
http://cfpub.epa. gov/ncea/raf/recordisplay.cfm?deid=54944.
2. U.S. Environmental Protection Agency. 1995. Land Use in the CERCLA Remedy Selection
Process. Office of Emergency and Remedial Response, Washington B.C., May 25, 1995.
OSWER Directive No. 9355.7-04. Available at:
http ://www. epa. gov/superfund/resources/landuse.htm.
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Chapter 7 Quantification of Exposure:
Development of the Emissions Inventory
for the Inhalation Risk Assessment
Table of Contents
7.1 Introduction 1
7.2 Process for Developing an Emissions Inventory 1
7.2.1 Planning 2
7.2.2 Gathering Information 3.
7.2.3 Estimating Emissions 3_
7.2.3.1 Direct Measurement 5
7.2.3.2 Emission Estimation Models 5
7.2.3.3 Emission Factors £
7.2.3.4 Mass Balance 9
7.2.3.5 Engineering Judgment 9
7.2.4 Compiling Data Into a Database 9
7.2.4.1 Selection of Production Rates 9
7.2.4.2 Unusual Conditions: Process Upsets, Accidental Releases, and Maintenance
H
7.2.5 Data Augmentation 1_2
7.2.6 Quality Assurance/Quality Control 13
7.2.7 Documentation 14
7.2.8 Access to Data 14
7.3 Data Sources 14
7.3.1 Permit Files 15.
7.3.2 Regional Inventories 15
7.3.3 Industry Profiles 16.
7.3.4 AP-42 Emissions Factors 1/7
7.3.5 Factor Information Retrieval System 1/7
7.3.6 Locating and Estimating Documents 18
7.3.7 RCRAMo 18
7.3.8 Emissions and Dispersion Modeling System (EDMS) 12
7.3.9 Summary 19
References 21
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7.1 Introduction
An emission inventory is a comprehensive listing, by source, of the air pollutant emissions within
a specific geographic area in a specific time period. EPA prepares a National Emissions
Inventory (NEI) with input from numerous state, local, and tribal (S/L/T) air agencies (see
Chapter 4 and http://www.epa.gov/ttn/chief/net/index.html for more information on the NEI).
NEI data are used for air quality modeling, regional strategy development, regulation setting, air
toxics risk assessment, and tracking trends in emissions over time. The NEI Input Format (NIF)
is the format most widely used by S/L/T agencies to transfer data to the NEI. The current
versions of the NIF and all user documentation are available on the website noted above. The
advantages, disadvantages, and uncertainties associated with NEI data are discussed in Chapter 4.
Emission inventories generally serve as the first step in quantifying exposure for an air toxics risk
assessment. In addition to source information (e.g., location, chemicals released), they provide
most of the critical input data for air quality models used to predict air toxics fate and transport in
the atmosphere. The Emission Inventory Improvement Program (EIIP)(1) has published a ten-
volume set of technical reports on the development of emissions inventories for the NEI.(2)
Related technical documents, updates, reports, and information regarding the organization and
progress of EIIP in developing new methods can be found linked to the main EIIP webpage.
These include training manuals that provide in-depth descriptions of each step of the process, for
various types of sources and air pollutants. Emissions inventories that are prepared in a manner
consistent with these methods and guidance will provide data of known quality for a risk
assessment.
For risk assessments, local enhancements of existing air toxics emissions inventories may be
advantageous to a particular air toxics assessment effort as a very critical initial step. Air toxics
inventories are not always at the quality that would provide the results desired in a modeling
assessment, and improving the entire statewide toxics inventory may be unrealistic. An
enhancement of the local air toxics inventory in the assessment area of interest may be beneficial
for providing more accurate and precise risk assessment results and, consequently, a better basis
for any air toxics risk- or airshed-program management decisions. Also, local emissions
inventory work in specific areas of concern or study makes these air toxics efforts smaller and
easier for agencies and participating facilities to manage and conduct, particularly in the shorter
time frames commonly sought in local air toxics assessment projects.
The remainder of this chapter describes a process that can be used to develop an emissions
inventory, including the general steps for developing an emissions inventory (Section 7.2), and
data sources (Section 7.3)
7.2 Process for Developing an Emissions Inventory
There are eight steps for developing an emissions inventory:(3) (1) planning; (2) gathering
information; (3) estimating emissions; (4) compiling data into a database; (5) data augmentation;
(6) quality control/quality assurance; (7) documentation; and (8) access to data. Each is
described in a separate subsection below.
April 2004 Page 7-1
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The Emissions Inventory Improvement Program (EIIP)
To develop a systematic method for preparing an emission inventory, EPA's Emission Factor and
Inventory Group (EFIG) has worked as a key member of the EIIP. The EIIP is a jointly sponsored
effort of the State and Territorial Air Pollution Program Administrators/Association of Local Air
Pollution Control Officials (STAPPA/ALAPCO) and EPA. Both of these organizations are
represented in the Standing Air Emissions Work Group (SAEWG), which endorsed the original EIIP
plan. Funding is provided by S/L/T agencies through the Federal 105 grant programs. While EPA
coordinates the EOF efforts, all of the tasks are performed by working committees. The EIIP Steering
Committee and technical committees are composed of S/L/T, industry, and EPA representatives.
Membership on technical committees is open to any S/L/T agency representative, industry group, and
the public; interested individuals can contact the appropriate committee co-chair for information.
v. _ ^
7.2.1 Planning
Planning is the first stage in preparing an emissions inventory. Perhaps the most important
activity in compiling an inventory, planning ensures a focused and streamlined process and
avoids later costly and embarrassing mistakes. The Inventory Preparation Plan (IPP) is
developed during the planning stage and is the overarching guidance document for the entire
emission inventory development process.(4) First, the IPP identifies the end-use(s) of the
inventory (e.g., to support a risk assessment) and subsequently, an acceptable data quality level
for those uses. Once the end-use(s) are determined, the risk manager defines the inventory to be
created, identifying the necessary components:
• The air toxics to be carried through the risk assessment (i.e., the COPCs);
• The specific sources or source categories to be assessed;
• The geographic area (scale) of the assessment area; and
• The time interval over which emissions are to be inventoried.
Generally, the IPP reflects the complexity of the risk assessment being conducted. That is, an
assessment of a single stationary source with known pollutants and well-documented emissions
would not require as elaborate a plan as would a risk assessment addressing multiple sources and
source types affecting a broad community. Exhibit 7-1 lists the steps in developing an IPP.
Exhibit 7-1. Steps in Developing an Inventory Preparation Plan
Identify the end-uses of the inventory
Determine Data Quality Objectives
Define the inventory to be created
Select an inventory data management and reporting system
Summarize data reporting and documentation
Establish QA/QC procedures
Determine staffing and resource requirements
Develop a schedule
Identify partners and develop a communication plan
(3)
Source: Pope, A. Inventory Preparation for Toxics.
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The level of precision for emissions data required may differ among different tiers of analysis.
For example, screening-level risk assessments often incorporate conservative assumptions (e.g.,
all sources are co-located, all emissions are of the most toxic species of a particular chemical) in
order to minimize the time and effort required to develop the emissions inventory. If the
screening-level analysis indicates that there is a potential for a risk, then additional effort is made
to characterize sources and emissions with greater precision. The IPP for a given risk assessment
will identify the requisite level of precision for each potential tier of analysis.
7.2.2 Gathering Information
The next step in the development of an emission inventory is to gather the relevant information
from existing sources. The information gathered should, at a minimum, include applicable
pollutants, their sources, and emissions data (e.g., chemicals, emissions rates over time). If air
quality modeling will be a part of the exposure assessment, the emissions inventory will need to
include all of the source term data required by the model(s) to be used (e.g., latitude and
longitude coordinates for each source, building size and shape for assessing downwash, chemical
speciation).
A comprehensive information search may include guidance documents, existing emissions data,
preliminary screening studies, emission factors, models, source characterization documents, and
activity data references. A good starting point in this search is EPA's Handbook for Air Toxics
Emission Inventory Development.^
7.2.3 Estimating Emissions
After gathering data from existing information sources, the analyst estimates the emissions to be
reported in the inventory. There are two main approaches for estimating emissions: the top-
down approach and the bottom-up approach.
• In the top-down approach, national- or regional data are allocated to a state or county based
on a surrogate parameter such as population or employment in a specific sector. This
approach typically is used for nonpoint sources when: (1) local data are not available, (2) the
cost to gather local information is prohibitive, or (3) the end-use of the data does not justify
the required cost. The top-down approach requires minimum resources, but at the expense of
emissions accuracy.
• In the bottom-up approach, the inventory is developed from site-specific information on
emissions sources, activity levels, and emission factors. This approach, typically used for
point sources, requires more resources, but results in more accurate estimates than the top-
down approach.
Exhibit 7-2 compares several methods for estimating point source emissions. Available methods
for nonpoint sources include material balance, emissions factors, emissions estimation models
(all listed in Exhibit 7-2), and surveys and questionnaires. Mobile source emissions estimates
come from models, such as EPA's NONROAD(6) model for nonroad mobile sources
(construction equipment, lawn mowers, airplanes, trains, and others) and MOBILE(7) for on-road
mobile sources (automobiles, trucks). Section 7.3 below provides additional information on
potential sources of emissions data.
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Exhibit 7-2. Point Source Emission Estimation Methods
Method
Advantages
Disadvantages
Continuous Emission Monitors
(CEM)
Measures actual emissions
Can be used to estimate
emissions for different
operating periods
Considered high quality data
Often cost prohibitive
Source (Manual Stack) Testing
Yields more accurate
estimates than Emission
Factors or Material Balance
Data can be used to develop
emission factors
Data can be extrapolated to
other representative
(nonpoint) emission sources
Cost prohibitive (especially
if large number of pollutants
to be tested)
Uncertainty issues due to
representativeness of
estimates over time
There may be no
standardized testing
reference methods
Material Balance
Useful when other
developed methods are not
available or practical
Useful for sources resulting
in evaporative losses
Must have specific
knowledge of all process
parameters (amount of
material entering and leaving
the process, amount of
material packaged as product
itself)
Fuel Analysis
Useful when other
developed methods are not
available or practical
Estimates not as accurate
due to inherent uncertainties
in input parameters
Emission Estimation Models
Useful for complex
calculations
Estimates not as accurate
due to inherent uncertainties
in input parameters
Emissions Factors
Ease of availability
Uncertain accuracy
Engineering Judgment
Useful as a last resort when
no other methods generate
accurate emission estimates
Estimates based on
individual judgment and
therefore not as defensible as
more developed methods
Determining the best method for estimating emissions requires a trade-off between cost and the
accuracy of results obtained. When estimating emissions, it is important to consider:
• Intended end-use of the inventory (as described in the IPP);
• Availability of data of the specified quality (preliminary screening can be helpful here);
• Practicality of the method for the specific source category;
• Source category priority; and
• Resources (time, staffing, funding) available to prepare the inventory.
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The Emissions Inventory Improvement Program (EIIP) series of documents provides further
guidance in choosing the most appropriate method for the specific inventory's needs.(1)
7.2.3.1 Direct Measurement
Direct measurement of source-specific emission rates is relatively infrequent except for certain
permitted facilities with specific monitoring requirements written into their permits. For
example, source monitoring is typically available for large point source releases at facilities
covered under the Title IV emissions tracking system associated with the acid rain control
program. Various state and local permitting programs that may also require intermittent or
continuous monitoring, depending on the nature of the process.
In some instances, source testing is required as part of the process of obtaining a permit. For
example, a hazardous waste incinerator must do stack testing during trial burns to ensure that the
incineration units and air pollution control equipment meet the limits established in the permit
before full operation is allowed to begin. Subsequent to full operation, the facility will usually be
required to perform continuous monitoring of stack emissions to ensure continued compliance.
EPA's Emission Measurement Center (EMC) provides linkages to available source monitoring
methodologies in five general categories (Exhibit 7-3).
7.2.3.2 Emission Estimation Models
Specific emission measurements are generally the best and most accurate method to quantify
emissions; however, source data are not always available and/or practical to obtain. As an
alternative, emission estimation software and accompanying models may be used to generate
emissions data. Emission estimation models are used when a large number of complex
calculations must be undertaken in order to estimate a given emission or when a combination of
parameters has been identified that affect emissions but individually do not provide a direct
correlation. EPA provides a variety of approved models that can be used to determine point,
nonpoint, and mobile source emissions based on a variety of known input parameters. Some of
these emission estimation models are discussed below.
CHEMDAT8
CHEMDAT8 is a Lotus® 1-2-3 spreadsheet prepared by EPA's Emissions Standards Division that
includes analytical models for estimating VOCs from treatment, storage, and disposal facility
processes. The models cover releases from disposal impoundments, closed landfills, land
treatment facilities, and aeration and nonaeration impoundment processes. Additional
information is available for download from the CHIEF software index website at:
http://www.epa.gov/ttn/chief/software/index.html.
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Exhibit 7-3. Categories of Source Monitoring Methodologies
EPA has established the EMC (http://www.epa.gov/ttn/emc/tmethods.html). as part of its Technology
Transfer Network, which is a collection of technical internet sites containing information about many
areas of air pollution science, technology, regulation, measurement, and prevention. The EMC
identifies five general categories of source monitoring methods:
• Category A: Methods Proposed or Promulgated in the Federal Register. These methods have
been proposed or promulgated in the Federal Register and codified in the Code of Federal
Regulations (CFR).
• Category B: Source Category Approved Alternative Methods. These methods are approved
alternatives to the methods required by 40 CFR Parts 60, 61, and 63 as described by the General
Provisions of the corresponding Parts.
• Category C: Conditional Methods. EPA has evaluated these methods, and they may be
applicable to one or more categories of stationary sources. EPA confidence for these methods is
based upon review of various technical information including, but not limited to, field and
laboratory validation studies, EPA understanding of the most significant quality assurance (QA)
and quality control (QC) issues, and EPA confirmation that the method addresses these QA/QC
issues sufficiently to identify when the method may not be acquiring representative data. The
method's QA/QC procedures are required as a condition of applicability.
• Category D: Preliminary Methods. The performance of these methods is not as well defined as
that of the conditional methods of Category C. EPA is providing these as they may be useful in
limited applications until more supporting information is available (i.e., can be '"gap filling'"
methods). EPA expects the methods to work under the conditions of the applicability statement but
is uncertain of the methods' applicability without additional data on broader application. EPA
encourages submission of data to support broader applicability.
• Category E: "Idea box." The idea box includes method concepts intended to promote
information exchange only, and the concepts may not be used by sources to fulfill Federal
requirements. These technical ideas have been provided to EPA for posting on the EMC web site.
Concepts in the idea box generally have had little or no EPA review or analysis and are not
technically supported by EPA. However, information that resides here may be considered for
further assessment by EPA and non-EPA entities for the purposes of method development for
placement into higher categories.
WATER9
WATER9 is a Windows-based computer program available for estimating air emissions of
individual waste constituents in wastewater collection, storage, treatment, and disposal facilities.
It also contains a database listing many of the organic compounds and describes procedures for
obtaining reports of constituent fates, including air emissions and treatment effectiveness.
WATER9 is a significant upgrade of features previously contained in WATERS, CHEM9 (a
compound properties processor that can estimate compound properties that are not found in
EPA's database of over 1000 compounds), and CHEMDAT8, and contains a set of models that
can provide a holistic picture of emissions from a facility. The models produce emission
estimates for each individual compound that is identified as a constituent of the wastes leaving
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the facility based on the physical/chemical properties of the compound and its concentration in
the wastes. Therefore, the analyst should be able to identify the constituent compounds and
provide their respective concentrations. WATER9 has the ability to use site-specific compound
property information and the ability to estimate missing compound property values. Estimates of
the total air emissions from the wastes are obtained by summing the estimates for individual
compounds. Program software maybe downloaded from
http://www.epa.gov/ttn/chief/software/water/index.html.
Landfill Gas Emissions Model v2.01
The Landfill Gas Emissions Model is a program specifically designed for use by state and local
regulatory agencies to monitor the air emissions from landfills. The system allows the user to
enter specific information regarding the characteristics and capacity of a landfill and to project
the emissions of methane, carbon monoxide, nonmethane organic compounds, and individual
HAPs over time using the Scholl Canyon decay model for landfill gas production estimation.
The Scholl Canyon Model is a first-order decay equation that uses site-specific characteristics for
estimating the gas generation rate. In the absence of site-specific data, the program provides
default values for regulatory uses of the model and provides default values drawn from EPA's
Compilation of Air Pollutant Emission Factors (AP-42) for inventory uses. For additional
information, contact EPA's Air Pollution Prevention and Control Division, Office of Research
and Development at (919) 541-2709. Program software may be downloaded from
http://www.epa.gov/ttn/chief/software/index.html.
TANKS
TANKS is a Windows-based computer software program that estimates emissions of volatile
organic compounds (VOCs) and hazardous air pollutants (HAPs) from fixed- and floating-roof
storage tanks and is designed for use by S/L/T and Federal agencies, environmental consultants,
and others who need to calculate air pollutant emissions from organic liquid storage tanks. The
calculations are performed according to estimation procedures outlined in EPA's Compilation of
Air Pollutant Emission Factors (AP-42). The user provides specific information concerning the
storage tank and its contents, and the program then estimates annual or seasonal emissions and
produces a report. The tank contents can consist of single or multiple liquid components. The
program may be downloaded from http://www.epa.gov/ttn/chief/software/tanks/index.html.
MOBILE6 Vehicle Emission Modeling Software
MOBILE6 is an emission factor model for predicting gram per mile emissions of hydrocarbons
(HC), carbon monoxide (CO), nitrogen oxides (NOX), carbon dioxide (CO2), particulate matter
(PM10 and PM2 5), and other toxics from cars, trucks, and motorcycles under various onroad
conditions. The program is available for download from http://www.epa.gov/otaq/m6.htm.
NONROAD Model
The Draft NONROAD Model is a Windows-based software program intended for use by
professional mobile source modelers for their use in estimating emissions specifically for
emissions inventory development. The model is still in draft form, so EPA warns that some
April2004 Page 7-7
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emission rates and activity levels predicted from NONROAD may substantially change in future
versions. The program is available for download from http://www.epa.gov/otaq/nonrdmdl.htm.
Please note that EPA's Office of Transportation and Air Quality is currently developing a new
modeling system, Multi-scale mOtor Vehicles and equipment Emission System (MOVES) that
will replace the existing MOBILE6 and NONROAD models. This new system will estimate
emissions for onroad and nonroad sources, cover a broad range of pollutants, and allow multiple
scale analysis, from fine-scale analysis to national inventory estimation. For further information
on MOVES, visit http://www.epa.gov/otaq/ngm.htm.
7.2.3.3 Emission Factors
Emission factors are constants that assessors can use to relate release rates to the amount of
specific activities that occur at a source. An emission factor is typically represented as a mass of
chemical released per unit of activity. For example, releases from a coal burning combustion
device are represented as pounds of pollutant emitted per BTU coal burned. Depending on the
emission source, there may be a lot of emissions testing data, just one or two measurements (the
usual case), or none. For a screening-level assessment it may be possible to obtain an estimate of
maximum emissions in one of several ways.
• If sufficient data are available, the assessment could use the highest available value.
• If only one or two measurements are available, the assessment could assume that all the
emissions occur in a short period of time (such as only for 8 hours a day) and/or assume that
all sources of emissions are co-located.
• If no data are available, the assessor may need to rely on professional judgment based on
similar types of sources.
Certain types of sources (e.g., incinerators) typically undergo various test or trial "burns" to
establish emissions factors pursuant to RCRA permitting requirements. Data to support the
development of emissions factors also may be collected to support compliance with maximum
achievable control technology (MACT) standards or Toxics Substances Control Act (TSCA)
permitting. For stable and well established processes, the emission factors are usually reliable
estimates. However, for sources that are subject to different operational conditions, with limited
testing, the emission factors may represent an estimate of a higher or lower release rate.
Frequently, emission factors contain an associated confidence level by species, which assists in
determining the appropriate emission factor. Thus, the use of the emission factor for any specific
source may over- or under-predict actual release rates. In some cases, accurate measurements of
the activity rates are not available and estimates of activity rates can also contribute uncertainty
to the release rate estimate for any particular source type. An example is for individual motor
vehicles; this source model estimates an average emission factor for a fleet of vehicles in a
particular location. Modeling approaches for traffic activity estimate the total amount of miles
driven by vehicle class. Finally, multiplying the emissions factor by the number of vehicle-miles
driven produces the total emissions. Thus, any individual motor vehicle may have a release rate
significantly far removed from the average, but when averaged across the fleet, the release rate
provides a more reliable estimate.
April 2004 Page 7-8
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EPA suggests emission factors for criteria pollutants and HAPs in its national database, Factor
Information Retrieval System (FIRE), which includes emission factors from EPA documents
(such as Compilation of Air Pollutant Emission Factors (AP-42) and the Locating and
Estimating Air Emission series) factors derived from state-reported test data, and factors taken
from literature searches. FIRE is available for download at
http://www.epa.gov/ttn/chief/software/fire/.
7.2.3.4 Mass Balance
Assessors can use the mass balance approach in complex processes in which a known amount of
air toxics material is introduced to a process, and at the end of the process, a known amount of
air toxics material is still retained in the final product. The difference between the two represents
the production release. Engineering estimates can then suggest into what medium the process
released the air toxic (e.g., to air or water, or as solid waste).
As an example, consider the use of a VOC as a carrier medium for a solid (e.g., paint particles).
In this surface coating situation, the organic solvent that suspends the solids makes application of
the coating possible. Once the mixture is exposed to the air, the solvent evaporates, leaving the
solid coating film on the object. Mass balance techniques in this type of application may assume
that 100 percent of the solvent is released to the air through evaporation. Other mass balance
estimates may assume that some stable amount of the solvent is retained in the product that is
shipped to customers. Mass balance estimates also may need to consider how much of the
solvent is recycled at various stages in its life-cycle.
7.2.3.5 Engineering Judgment
With engineering judgment, users can estimate emission releases through engineering and
operational observations about a process. For example, if a certain process must be operated at a
set temperature and pressure to achieve the ideal result, engineers who understand the history of
the process can often estimate how the release rate actually varies under changing operational
conditions. Engineering judgment is a less desirable approach for estimating releases than actual
measurements; however, it is often used because of a lack of any better information or options
(e.g., it may not be possible to measure all fugitive leaks at a large facility with thousands of
joints and valves).
7.2.4 Compiling Data Into a Database
After estimating the applicable emissions from each source, the analyst compiles the data into the
inventory database, based on the data management system delineated in the Inventory Preparation
Plan. Three elements of data compilation are of note for a risk assessment: selection of
production rates; unusual conditions; and how emissions are quantified for risk assessment
purposes. Each is discussed in a separate subsection below.
7.2.4.1 Selection of Production Rates
The variability in a source's emissions rate can make it difficult to arrive at a single source-
specific emissions level. Prior to collecting or reviewing data in support of a risk assessment,
assessors will need to decide whether to use release data that reflects either annual average
April 2004 Page 7-9
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emissions or "worst-case" operating conditions (or both). In some limited cases, it maybe
possible to obtain data on daily and seasonal variable emissions, although this is not common.
Likewise, information on both the actual release rates and maximum permitted or allowable
release or potential emission rate may be available. In addition to information on annual
releases, a description of the release pattern over the year (see examples in Exhibit 7-4) and
during the weeks of operation will be useful in characterizing the resultant ambient air
concentrations over the exposure duration (e.g., is release occurring around-the-clock or only
during the work week?).
Exhibit 7-4. Examples of Variable Patterns of Emissions
,_ Emissions
Q
3
,_ Emissions
Q
3
,_ Emissions
Q
3
Facility A
ua ry J une Decem ber
Time
Facility B
MA
uary June December
Time
Facility C
_J \
uary June December
Time
Emissions patterns may vary over
time. In this hypothetical example,
Facility A's emissions occur at a
fairly constant rate. In contrast,
Facility B's emissions levels
fluctuate with spikes in their
emissions evident at different times
of the year. Facility C's emissions
occur only during a specific part of
the year.
Information on variability in operating conditions and the factors or conditions influencing that
variability will be useful. This will assist in the selection of the release data for the scenario of
interest in the assessment. For example, if the assessment is evaluating what maybe released
under current permit conditions, it may be appropriate to use release rate data corresponding to
the maximum permitted release rate, regardless of reported actual rates. This method is best-
suited for screening-level analyses, where the objective is to conduct a risk assessment for the
purposes of screening out sources that pose negligible risk while efficiently conserving available
resources (i.e., time and money), which may be needed for a more refined analysis of the
remaining sources. However, use of reported release data (e.g., annual estimates) maybe more
appropriate for refined analyses of facilities with well-defined production capabilities and limited
April 2004
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operational variability. Note that more detailed information on variability may be needed for
analysis of air concentrations (and resultant exposures) over shorter periods (e.g., acute analysis).
7.2.4.2 Unusual Conditions: Process Upsets, Accidental Releases, and Maintenance
Release characteristics frequently differ during atypical operations. Process upsets often result in
the venting of large amounts of raw materials, intermediate products, finished products, or wastes
to the air. Sources often flare organic releases during process upsets (i.e., burned as the
chemicals are being released to the air) to reduce the mass of potentially toxic compounds, which
can result in releases of particulate matter or other chemicals as a result of incomplete
combustion. Shutting down and starting up processing equipment results in a period of time
when the process is operating at less than ideal conditions, and release rates can change
significantly during these shut down and start up procedures. Accidental releases associated with
truck accidents, train derailments, or chemical spills from shipping operations can also cause
significant releases that affect a local area for a short period of time.
Many operating permits require sources to report periods of process upset and maintenance
activities, although assessors may not estimate release rates during these periods because
measurement data are often unavailable. Local emergency authorities often possess information
on accidental releases from trucking accidents and train derailments. These reports may be
useful to provide modeling input data in subsequent acute risk assessment activities. Risk
assessors can contact local HazMat Teams, and state or federal emergency response personnel to
gather available information on accidental and upset releases. This type of information could be
quite useful in local episodic acute risk analysis,(a) but may not be included in long-term risk
evaluations.
Another source of startup/shutdown/malfunction data may be available in state/local/tribal permit
files for the facilities. Specifically, many permitted facilities must file routine reports in which
the provide information on spills, excursions, and other unusual circumstances where non-routine
releases occur.
7.2.4.3 Quantifying Emissions for the Risk Assessment
Once the assessor has compiled the above information about the source in question, he or she
would quantify the emission rate as the amount of pollutant released per unit of time. Most air
toxics releases are expressed as tons of pollutants released per year in emissions inventories.
However, as noted above, a yearly value may not provide the level of information required to
evaluate the risk assessment questions, and more detailed information may be necessary. For
example, are there seasonal fluctuations in emissions? Are the releases continuous around-the-
clock, seven days a week, or more intermittent with a different schedule? The particular air
dispersion model may require that emission rates be expressed in different units (e.g., pounds per
EPA's Chemical Emergency Preparedness and Prevention Program web page describes the development of
emergency management plans relying on such acute risk analysis to assist in the response to accidental releases:
http://vosemite.epa.gov/oswer/ceppoweb.nsf/content/RMPoverview.htm
April 2004 Page 7-11
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Process Upset and Accidental Release Information Sources
The National Response Center (NRC) has an on-line query system that provides access to all non-
Privacy Act data collected by the NRC since 1990. This information may be accessed at
http://www.nrc .use g.mil/foia.html.
The U.S. Chemical Safety and Hazard Investigation Board maintains a database of Incident News
Reports, which may contain information on process upsets and accidental releases. The Incident
News Reports database is available at http://www.chemsafety.gov/circ/.
RMP*Info is a national database that provides information on risk management plans (RMPs). Each
RMP contains a hazard assessment that includes an accident history covering the facility's previous
five years of operation. This information can be obtained by submitting a written request for the RMP
database (without the Offsite Consequence Analysis data) to the RMP Reporting Center, P.O. Box
. 1515, Lanham-Seabrook, Maryland 20703-1515.
> '
hour, grams per second). The NEI contains emission estimates of HAPs for periods of a year or
less. Risk assessors generally consult the emission period table in the NEI and use the emission
type field to determine the period for which emissions are reported. The EPA summarizes NEI
data in summary files to annual emissions, but more detail on the reporting period is available in
the NEI. The NEI also contains emissions estimates for actual, allowable, potential, and
maximum emissions for the same emission release points.
7.2.5 Data Augmentation
If previous efforts at estimating emissions fail to obtain data to assemble an emissions inventory
of sufficient quality or to provide the necessary inputs for an emissions model, the next step
would be data augmentation. The analyst first identifies any missing information, most notably
emission data, vent parameters, and location coordinates.
• Emissions data. When developing emission inventories for nonpoint sources, analysts
sometimes find that no direct measure of activity exists at the local level. In cases where this
occurs, national, regional, or state-level emission estimates already in existence maybe
allocated to the local level (i.e., a top-down approach). This practice is know as spatial
allocation and is a common form of data augmentation. Similarly, emissions can be
temporally allocated to the time period required by an emissions model. Other suggestions for
filling emission data gaps include:
- Additional searches of databases to identify appropriate surrogate data;
- Extrapolation of emissions from other geographic areas; and
- Estimation of emissions data from past inventories within the same geographic area.
• Vent parameters. Common vent parameters required for air quality modeling include height,
diameter, temperature, exit velocity, and flow rate. If measures for any of these parameters
are missing or incomplete, the NEI provides default lookup tables generated from Source
Category Classification (SCC) and Standard Industrial Classification (SIC) codes.
SCC codes serve as a primary identifying data element in the NEI (as well as other EPA
databases) and many S/L/T agency emissions data systems. These codes are assigned to
April 2004 Page 7-12
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specific release points within a facility based on the process to which the release point is
linked and on various characteristics of the release point. A complete listing of SCC codes
along with additional background information is available from EPA.(8)
SIC codes are numerical codes developed by the U.S. government as a means of consistently
classifying the primary business of business establishments. A list of the industry groups that
are required to report to the Toxics Release Inventory (TRI) is provided in Chapter 4 and also
can be found at http://www.epa.gov/tri/report/siccode.htm.
For facilities that are regulated pursuant to a National Emissions Standard for Hazardous Air
Pollutants (NESHAP), the MACT codes, based on the MACT source category into which a
specific process falls, may provide additional information about the nature of the business,
primary production processes, or activities related to the release of air pollutants.
If no SCC or SIC code is available for the emission source in question, the analyst may use the
national default values for each parameter (see Exhibit 7-5).
Exhibit 7-5. National Vent Parameter Default Values
Parameter
Height
Diameter
Temperature
Velocity
Flow Rate
Default Value
10ft.
1 ft.
72° F
15 ft/sec.
12 ft.Vsec.
Source: Pope, A. Inventory Preparation for Toxics .(3)
• Location coordinates may be identified from the NEI (stationary sources) or topographic
maps (discussed in Chapter 6).
7.2.6 Quality Assurance/Quality Control
Quality assurance and quality control (QA/QC) procedures are vital to the validity of the
emissions inventory and ensure that the modeling input parameters derived from the inventory
are of specified quality. The quality assurance plan (QAP) for the emissions inventory is usually
a part of the quality assurance project plan (QAPP) for the overall risk assessment that is
developed during problem formulation (see Chapter 6). The QAP documents the procedures of
the QA/QC elements of the emissions inventory. Quality control measures include:
• Technical reviews;
• Use of approved standardized procedures for emissions calculations;
• Data verification procedures;
• Completeness checks;
• Consistency checks;
• Accuracy checks; and
• Reasonableness tests.
April 2004
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To the extent practicable, risk assessors have emissions data verified by external review and audit
procedures conducted by a third party. Exhibit 7-6 identifies the typical errors that occur in
developing an emissions inventory.
Exhibit 7-6. Typical Errors in Developing an Emission Inventory
Facility Errors
• Missing facilities
• Duplicate facilities
• Closed facilities
• Improper facility
locations
Data Errors
• Missing operating or technical data
• Erroneous technical data
• Errors in calculations
• Data entry and transposition errors
• Data coding errors
• Failure to identify all HAPs
Double-counting Errors
• Overlap between point
and nonpoint sources
• Overlap between nonpoint
source categories
7.2.7 Documentation
Documentation is the next step in developing an emission inventory. The key documents to be
compiled into a final written report include:
• Inventory Preparation Plan (IPP);
• Quality Assurance Plan (QAP);
• Methods;
• Assumptions;
• Raw data (database); and
• Calculations.
7.2.8 Access to Data
The risk manager generally ensures appropriate access to the data compiled in the emission
inventory. A key part of the planning and scoping process for the risk assessment is determining
who needs access to the emissions data and how they will access the data. If it is necessary to
report the results of the emission inventory to the EPA as part of a S/L/T agency's
responsibilities under the Consolidated Emission Reporting Rule, data preparation and
submission procedures prepared by EPA for HAP data should be followed.
7.3 Data Sources
The two data sources for emissions inventory information that are most applicable to air toxics
risk assessments are S/L/T agencies and the NEI. The TRI can provide some helpful information
about the types of emissions from sources, but TRI data have not been collected to support air
toxics risk assessments and therefore may be of limited value. The following subsections
describe several other sources of information that may provide information to assist in
developing an emissions inventory for the risk assessment.
April 2004 Page 7-14
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7.3.1 Permit Files
Most stationary sources (especially large sources) are subject to one or more emissions limitation
standards to control criteria emissions and/or HAP emissions. These sources are usually subject
to a Title V operating permit that will include all of the operating and emissions limit
requirements subject to that facility. In addition, they may be subject to additional S/L/T
regulations. Operating permits require routine reporting to confirm that the operating conditions
and emission limits are being met. Frequently, these reports are based on some kind of
monitoring information that is directly related to the release process(es). In most cases, actual
release rates are reported. Therefore, permit compliance reports represent an excellent source of
information that will provide the actual release rate directly through continuous emissions
monitoring, or they will provide sufficient information to estimate the release rates with a fairly
high level of reliability.
Unfortunately, using the permit compliance system is not always an attractive source for data on
release rates that are suitable for risk assessment activities. EPA does not maintain a central
database of Title V permit or compliance information. Therefore, gathering data from the permit
program can be a time-consuming task if many sources are needed for the risk analysis. The
reports will also be represented in terms that match the requirements of the permit (e.g., if the
permit conditions specify an annual release limit, release rates may be presented as an annual
average; if the permit conditions specifies a maximum release rate for any hour, then the
compliance report will document the maximum hourly rate observed at the facility). Therefore,
some adjustments and assumptions may be necessary. In addition, the permit compliance report
will only include the specific pollutants named in the regulations to which the permit applies.
For example, for NESHAPs that are applicable to the source, only HAPs specifically listed in the
rule may be included on the permit; other HAPs may also be emitted which are not required to be
reported. Additionally, not all important HAP sources are required to have a Title V permit, and
even small annual release rates of certain highly toxic HAPs may post significant risk.
In general, EPA has made an effort to include permit data in the NEI database (via data
submissions from S/L/T offices) where appropriate and has taken steps to review the data. In
many cases, it may be more reasonable to consult the NEI prior to attempting to gather release
rates directly from permit files.
7.3.2 Regional Inventories
Several regional organizations provide emission data specific to their geographic area of concern.
For example, the Great Lakes Commission (a partnership among EPA, the eight Great Lakes
states, and the province of Ontario, Canada), with funding from EPA and the Great Lakes
Protection Fund, have developed the Regional Air Pollutant Inventory Development System
(RAPIDS). This ongoing initiative seeks to provide researchers and policy makers with detailed,
basin-wide data on the source and emission levels of toxic contaminants. Originally focused on
49 toxic air pollutants, the inventory database has been expanded to include 82 toxic air
pollutants which have been identified as significant contributors to the contamination of the
Great Lakes. RAPIDS uses the FIRE database to estimate emissions for both point and nonpoint
sources. The software may be downloaded from http://www.glc.org/air/rapids/.
April 2004 Page 7-15
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Additionally, EPA provides funding to five regional planning organizations throughout the U.S.
to address regional haze and visibility impairment issues. These organizations exist to evaluate
technical information to better understand how their states and tribes impact national park and
wilderness areas (Class I areas under the CAA) across the country and to then pursue the
development of regional strategies to reduce emissions of particulate matter and other pollutants
contributing to regional haze. To this end, each regional planning organization assesses its
member states' emission inventories, and some provide funding through EPA for the
development of regional emission inventories. Information regarding regional emission
inventorying activities may be found at the organizations' respective websites as listed below:
• Central Regional Air Planning Assocation (CENRAP) - http://www.cenrap.org/
• Western Regional Air Partnership (WRAP) - http ://www.wrapair. org/
• Midwest Regional Planning Organization (Midwest RPO) - http://64.27.125.175/
• Mid-Atlantic/Northeast Visibility Union (MANE - VU) - http://www.manevu.org/index.htm
• Visibility Improvement State and Tribal Association of the Southeast (VISTAS) -
http ://www.vistas-sesarm .org/
7.3.3 Industry Profiles
To help assessors understand the nature of releases from sources, EPA has compiled a variety of
guidance documents and information resources that explain how various industries operate and
the types and locations of emissions that commonly are associated with their processes. Two key
groups of these documents are the "Sector Notebooks" and the TRI Facility Specific profile.
The sector notebooks are a series of profiles or notebooks containing information on selected
major industries. These notebooks, which focus on key indicators that holistically present air,
water, and land pollutant release data, have been thoroughly reviewed by experts from both
inside and outside EPA. Each notebook provides:
• A comprehensive environmental profile;
• Industrial process information;
• Pollution prevention techniques;
• Pollutant release data;
• Regulatory requirements;
• Compliance/enforcement data;
• History government and industry partnerships;
• Innovative programs contact names;
• Bibliographic references; and
• Description of research methodology.
The notebooks cover a wide variety of activities, including:
• Agricultural chemical, pesticide and fertilizer industry;
• Dry cleaning industry;
• Ground transportation industry;
• Inorganic chemicals industry;
• Fossil fuel electric power generation industry;
• Metal fabrication industry; and
April 2004 Page 7-16
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• Organic chemical industry.
Regarding TRI resources, the TRI website provides a number of very industry-specific and
chemical-specific guidance documents that were developed to help stakeholders understand the
nature of major industrial process and how emissions may occur from those processes (see
http://www.epa.gov/tri/guide_docs/index.htm#industry_sp). Example titles include:
• Presswood and Laminated Products Industry;
• Coal Mining Facilities;
• Electricity Generating Facilities;
• Petroleum Terminals and Bulk Storage Facilities;
• Rubber and Plastics Manufacturing;
• Printing, Publishing, and Packaging Industry;
• Textile Processing Industry;
• Leather Tanning and Finishing Industry; and
• Semiconductor Industry.
Assessors can take advantage of these materials to help them better understand the nature of
potential risk posed by facilities on local populations.
7.3.4 AP-42 Emissions Factors
Emission factors and emission inventories have long been fundamental tools for air quality
modeling. The Emission Factor and Inventory Group (EFIG) in EPA's Office of Air Quality
Planning and Standards (OAQPS) develops and maintains emission estimating tools. The AP-42
series is the principal means by which EFIG can document its emission factors. It is available
from EPA online.(9) These factors are cited in numerous other EPA publications and electronic
databases, but without the process details and supporting reference material provided in AP-42.
Information about emission factors for mobile sources can be found on EPA's Office of
Transportation and Air Quality website (http ://www. epa. gov/otaq/).
So just what is an AP-42 Emission Factor? It is a representative value that attempts to relate the
quantity of a pollutant released to the atmosphere with an activity associated with the release of
that pollutant. These factors are usually expressed as the weight of pollutant divided by a unit
weight, volume, distance, or duration of the activity emitting the pollutant (e.g., kilograms of
particulate emitted per megagram of coal burned). Such factors facilitate estimation of emissions
from various sources of air pollution. In most cases, these factors are simply averages of all
available data of acceptable quality and are generally assumed to be representative of long-term
averages for all facilities in the source category (i.e., a population average).
7.3.5 Factor Information Retrieval System
The Factor Information Retrieval (FIRE) Data System is a database containing EPA's
recommended release rate estimation factors for criteria and hazardous air pollutants. FIRE 6.24
(released March 2004) is a Windows-based program. Users can browse through records in the
database or select specific emission factors by source category, source classification code (SCC),
pollutant name, chemical CAS number, or control device. FIRE 6.24 contains emission factors
from the Compilation of Air Pollutant Emission Factors (AP-42 Fifth Edition) through March
April 2004 Page 7-17
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2004, the Locating and Estimating (L&E) series of documents, and the retired AIRS/Facility
Subsystem Emission Factors (AFSEF) and Air Toxic Emission Factor Database Management
System (XATEF) documents. FIRE can be accessed at: http://www.epa.gov/ttn/chief/software/
fire/index .html.
7.3.6 Locating and Estimating Documents
This report series characterizes some of the source categories for which releases of a toxic
substance have been identified. These volumes include general descriptions of the emitting
processes, identifying potential release points and emission factors. Some of the locating and
estimating documents were prepared as early as 1984 and the information may be dated. Others
have been developed since 1994 and will provide more up-to-date information (see
http://www.epa.gov/ttn/chief/le/index.html). EPA does not maintain L&Es and has not
published new L&Es since the mid 1990s.
7.3.7 RCRAInfo
RCRAInfo is EPA's comprehensive information system providing access to data supporting the
Resource Conservation and Recovery Act (RCRA) of 1976 and the Hazardous and Solid Waste
Amendments (HSWA) of 1984. The RCRA law is the primary statute under which EPA
monitors and regulates the management of nonhazardous and hazardous solid waste by entities
that produce, store, treat, transport, or otherwise manage such wastes (all of which are potential
sources of air toxics emissions in a community). This RCRAInfo replaces the data recording and
reporting abilities of the Resource Conservation and Recovery Information System (RCRIS) and
the Biennial Reporting System (BRS).(10)
RCRIS was the national program management and inventory system of facilities that handle
RCRA hazardous waste/1!) Facilities fit one or more of the following categories: treatment,
storage, and disposal facilities (TSDFs); large quantity generators (LQGs); small quantity
generator (SQGs); and transporters. RCRIS contains the following information:
• General information on all handlers (e.g., name, address, activity type);
• Permitting and corrective action program status, and Standard Industrial Classification (SIC)
code information for TSDFs only; and
• Enforcement and compliance actions for specific facilities, regardless of type, which have
been subject to inspections or other enforcement activity.
States and regions populated RCRIS with data necessary for their program implementation.
Those portions of the data that were relevant for national program oversight and management
were contained in a RCRIS national database.
The BRS was the national system that collected data on the generation, management, and
minimization of hazardous waste. BRS captured detailed data on the generation of hazardous
waste from large quantity generators and data on waste management practices from treatment,
storage, and disposal facilities. These data were collected every other year, providing the ability
to perform trend analyses. The data were reported by the facilities to EPA on even years
regarding the hazardous waste activities of the previous year. EPA produced a report on
hazardous waste generation and management activity that included the data files. The BRS can
April 2004 Page 7-18
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be queried to identify facilities treating hazardous wastes with technologies that may generate air
toxics emissions. BRS reports are available from EPA through 2003 .(12)
RCRAInfo data is made available to the public through EPA's Envirofacts Data Warehouse03'
through monthly extracts or through the Right to Know Network.(14) The same files that are
provided to Enviro facts and the Right to Know Network are also available for downloading from
EPA's publically accessible FTP server.(b)
The RCRAInfo system that is replacing the RCRIS and the BRS allows tracking of many types of
information about the regulated universe of RCRA hazardous waste handlers. RCRAInfo
characterizes facility status, regulated activities, and compliance histories and captures detailed
data on the generation of hazardous waste from large quantity generators and on waste
management practices from treatment, storage, and disposal facilities. Although the BRS does
not contain emissions monitoring data, it does identify hazardous waste constituents, quantities
managed, and other facility information. For example, the RCRA files include trial burn data for
hazardous waste incinerators, certification of compliance test data, and facility plot plans, all of
which could be useful in risk assessments of air toxics.
7.3.8 Emissions and Dispersion Modeling System (EDMS)
For aircraft emissions, the Federal Aviation Administration has developed an emission
estimation method model, Emissions and Dispersion Modeling System (EDMS), Version 4.0.(15)
This model can be applied to specific airports and used to develop air toxics emissions for both
commercial and general aviation emissions. The primary basis for estimating emissions is based
on landing and take off data available from FAA's airport activity statistics database. EDMS
includes emissions and dispersion calculations, the latest aircraft engine emission factors from
the International Civil Aviation Organization (ICAO) Engine Exhaust Emissions Data Bank,
vehicle emission factors from EPA's MOBILESa, and EPA-validated dispersion algorithms.
7.3.9 Summary
Exhibit 7-7 lists the different data sources that provide information on air toxics emissions that
are being used or can be adapted for air toxics risk assessments.
The server is available at: ftp://ftp.epa.gov/rcrainfodata/brfiles/. A comprehensive web-enabled help
module (RCRAInfo_Flat_File_WebHelp.zip) is also available to explain the flat file specifications and data element
values (see ftp://ftp.epa.gov/rcrainfodata/rcra flatfiles/).
April 2004 Page 7-19
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Exhibit 7-7 Summary of Emissions Inventory and Related Information
Data Source
S/L/T Inventories
National
Emissions
Inventory (NEI)
Title V Permit
Conditions
EIIP
Clearinghouse for
Inventories and
Emission Factors
(CHIEF)
Emissions
Tracking System
(ETS)
RCRAInfo
Toxic Release
Inventory (TRI)
Maintained By
Individual S/L/T
agencies
U.S. EPA
States/EPA
States/EPA
U.S. EPA
U.S. EPA
U.S. EPA
U.S. EPA
Sectors Covered
Large point sources; nonpoint
sources; mobile sources from
selected S/L/T agencies;
coverage is variable
Point sources; nonpoint
sources; on-road and nonroad
mobile sources
Large stationary point sources
and limited coverage of
nonpoint sources; only HAPs
greater or equal to 10 tons/25
tons per year covered
Large point sources; nonpoint
sources; mobile sources
Collection of information,
tools, and guidance on
emissions from all sectors
Large electric generating units
Generally point sources; does
include information on waste
transporters
Generally only point sources;
includes only those sources
that are subject to reporting
thresholds
Comments
Many S/L/T agencies have specific information
collected for special studies; attempts have been
made to include most of the S/L/T-level data into
the NEI, but higher resolution data may be
availab le
Point sources are reported for individual release
points (includes other modeling data); nonpoint
and mobile sources are reported at the county
level
Source-specific operating conditions to achieve
permitted emissions levels; actual emissions
reported for compliance in many cases; includes
MACT requirements
Series of reports with recommended and
alternative emissions estimation methods, and
recommended emission factors
EPA's main web page for emissions inventories
and related data
Annual reports of actual monitored emissions of
SO2, NOx and CO2 from Title IV affected
facilities, no toxics reported
Reporting of releases from Hazardous Waste
Treatment Storage and Disposal Facilities
(TSDF); includes data from Biennial Reporting
System (BRS) and Resource Conservation and
Recovery Information System (RCRIS)
Self reported information at facility level; no
other data necessary for modeling are reported
(e.g., vent characteristics); updated annually;
source and pollutant coverage can be limited by
reporting thresholds; generally not recommended
for modeling
Address
Various S/L/T -specific and
other web pages
http://www.cleanairworld.org/
http : //www . epa. g o v/ttn/ch ief/n
et/index.html
Generally available in paper
format only; some regional
offices maintained databases
http : //www . ep a . go v/ttn/chief/ei
ip/index.html
http : //www . epa. g o v/ttn/ch ief/
http : //www . epa. g o v/airm arkets
/emissions/index. html
http://www.epa.gov/epaoswer/
hazwaste/data/index .htmffrcra-
info
http : //www . epa. g o v/tri/
April 2004
Page 7-20
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References
1. U.S. Environmental Protection Agency. 2004. Technology Transfer Network Clearinghouse
for Inventories & Emission Factors. Emission Inventory Improvement Program. Updated
March 2, 2004. Available at: http://www.epa.gov/ttn/chief/eiip/index.html. (Last accessed
March 2004).
2. U.S. Environmental Protection Agency. Technology Transfer Network Clearinghouse for
Inventories & Emission Factors. Emission Inventory Improvement Program: Technical
Reports. Updated November 5, 2002. Available at:
http://www.epa.gov/ttn/chief/eiip/techreport/index.html. (Last accessed March 2004).
3. Pope, A. and Finn, S. 2003. Inventory Preparation for Toxics. U.S. Environmental
Protection Agency. 12th Annual International Emission Inventory Conference, San Diego,
CA. April 29-May 1,2003.
4. U.S. Environmental Protection Agency. 2001. 1999 National Emissions Inventory
Preparation Plan - Revised (February 2001). Office of Air Quality Planning and Standards,
February 2001. Available at: http://www.epa.gov/ttn/chief/net/nei_plan_feb2001 .pdf.
5. U.S. Environmental Protection Agency. 1998. Handbook for Air Toxics Emission Inventory
Development. Office of Air Quality Planning and Standards, Research Triangle Park, NC.
EPA-454/B-98-002. Available at: http://www.epa.gov/ttn/chief/eidocs/airtoxic.pdf.
6. U.S. Environmental Protection Agency. 2004. Modeling and Inventories. NONROAD Model
(nonroad engines, equipment, and vehicles). Updated March 11, 2004. Available at:
http://www.epa.gov/otaq/nonrdmdl.htm. (Last accessed March 2004).
7. U.S. Environmental Protection Agency. 2004. Modeling and Inventories. MOBILE Model
(on-road vehicles). Updated March 12, 2004. Available at:
http://www.epa.gov/otaq/mobile.htm. (Last accessed March 2004).
8. U.S. Environmental Protection Agency. 2004. Technology Transfer Network Clearinghouse
for Inventories & Emission Factors. Source Codes. Updated February 24, 2004. Available at:
http://www.epa.gov/ttnchiel/codes/index.html. (Last accessed March 2004).
9. U.S. Environmental Protection Agency. 2003. Technology Transfer Network Clearinghouse
for Inventories & Emission Factors. Compilation of Air Pollutant Emission Factors, AP-42,
Fifth Edition, Volume I: Stationary Point and Area Sources. Updated December 10, 2003.
Available at: http://www.epa.gov/ttn/chief/ap42/. (Last accessed March 2004).
10. U.S. Environmental Protection Agency. 2003. Hazardous Waste Data. Updated December
17,2003. Available at: http://www.epa.gov/epaoswer/hazwaste/data/index.htmffrcra-info.
(Last accessed March 2004).
11. U.S. Environmental Protection Agency. 2004. Planning and Results: Data Sources.
Resource Conservation and Recovery Act (RCRA) Information (RCRAInfo). Updated
February 10, 2004. Available at: http://www.epa.gov/Compliance/planning/data/multimedia/
idea/datasources .html#RCR (Last accessed March 2004).
April 2004 Page 7-21
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12. U.S. Environmental Protection Agency. 2003. Wastes. Hazardous Waste Data, RCRAInfo.
Updated December 17, 2003. Available at: http://www.epa.gov/epaoswer/hazwaste/data/
index.htm#br (Last accessed March 2004).
13. U.S. Environmental Protection Agency. 2002. Envirofacts Data Warehouse. Resource
Conservation and Recovery Act (RCRAInfo); Overview. Updated September 16, 2002.
Available at: http://www.epa.gov/enviro/html/rcris/. (Last accessed March 2004).
14. OMB Watch. 2004. The Right-to-Know Network. Welcome. Available at:
http ://www.rtk.net/. (Last accessed March 2004).
15. Federal Aviation Administration, Office of Environment and Energy. 2003. Emissions and
Dispersion Modeling System. Updated August 8, 2003. Available at: http://www.aee.faa.gov/
emissions/EDMS/EDMShome.htm (Last accessed March 2004).
April 2004 Page 7-22
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Chapters Quantification of Exposure: Dispersion,
Transport, and Fate of Air Toxics in the
Atmosphere
Table of Contents
8.1 Introduction 1
8.2 Dispersion and Atmospheric Transport of Air Pollutants 1
8.2.1 General Types of Releases 2
8.2.2 Characteristics of Releases that Affect Dispersion and Transport 3.
8.2.3 Physical and Meteorological Factors Affecting Air Toxics Dispersion and Transport . 7
8.3 Fate of Air Toxics in the Atmosphere 13
8.3.1 Physical Processes Removing Air Toxics 13
8.3.2 Chemical Reactions that Remove Air Toxics 15
8.3.3 Chemical Reactions that Result in the Secondary Formation of Pollutants 16.
8.3.4 Overall Persistence of Air Toxics in the Atmosphere 1/7
References 19
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8.1 Introduction
This chapter describes the major physical processes that affect the movement of air toxics
through the atmosphere. Section 8.1 describes the mechanisms through which sources release air
toxics into the air and how specific release characteristics and meteorological factors affect air
toxics dispersion and transport. Section 8.2 discusses the major physical and chemical processes
that affect the fate of air toxics, including deposition and chemical reaction. The discussion of
air toxics fate in this chapter is focused on describing the presence of air toxics in the atmosphere
and processes that influence this presence. The fate of deposited air toxics in other media and
ecosystems is included in Chapter 17.
The atmosphere and atmospheric processes is a complex and expansive subject. An
understanding of at least the rudiments of this subject is central to an understanding of how air
toxics disperse and persist or are removed once released to the air. Appendix G provides an
overview of atmospheric and meteorological concepts and terms relevant to this chapter.
Appendix G also provides information on sources of meteorological data for modeling air toxics
dispersion and transport. Whenever possible, it recommended that a meteorologist be part of the
risk assessment technical team.
8.2 Dispersion and Atmospheric Transport of Air Pollutants
Several characteristics of the source can affect the movement of air toxics while they are still
close to the source (e.g., source height, gas exit temperature). Once air toxics are transported
beyond the immediate vicinity of the source, atmospheric and meteorological factors (particularly
wind speed and direction) govern air toxics dispersion and transport. This section describes how
the movement of air toxics is affected by source characteristics, chemical properties, and
atmospheric processes.
Dispersion, Transport, and Fate: What's the Difference?
Dispersion is a term applied to air toxics releases that means to spread or distribute from a source,
with (generally) a decrease in concentration with distance from the source. Dispersion is affected by
a number of factors including characteristics of the source, the pollutants, and ambient atmospheric
conditions.
Transport is a term that refers to the processes (e.g., winds) that carry or cause pollutants to move
from one location to another, especially over some distance.
Fate of air pollution refers to three things:
• Where a pollutant ultimately ends up (e.g., air distant from the source, soil, water, fish tissue);
• How long it persists in the environment; and
• The chemical reactions which it undergoes.
The fate of an air pollutant is governed both by transport processes and by the characteristics of the
pollutant (e.g., its persistence, its ability to undergo reaction, and tendency to accumulate in water or
soil, or to concentrate in the food chain).
April 2004 Page 8-1
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8.2.1 General Types of Releases
The discussion of air toxics sources in Chapter 4 described air toxics emissions from a regulatory
perspective (e.g., "stationary" versus "mobile" sources). This chapter focuses instead on
emissions from the perspective of the primary types of industrial or physical processes through
which sources release most pollutants to the air. The distinction between the major types of
releases is not always clear, and the same air toxic can often be released in more than one way
from a single source or process. Section 8.2.2 below discusses how the characteristics of these
different types of release affect dispersion and transport of air pollutants.
The following terms are routinely used to generally describe or categorize emissions at a facility:
• Stack or Vent Emissions. These emissions are how most people envision air pollution.
Stacks and vents include "smokestacks" that emit combustion products from fuel or waste
combustion, as well as vents that carry air toxics away from people or industrial processes.
The major characteristics that stack and vent emissions share are that the release is
intentional, they remove airborne materials from specific locations or processes, and they
channel the releases through dedicated structures designed specifically for that purpose.
Often, stack and vent releases involve the active "pumping" of pollutant-laden air to the
external atmosphere by using fans or the "draft" associated with the tendency of hot gases to
rise rapidly through cooler, denser air. For many industrial operations, stack and vent
emissions account for the bulk of releases (according to the most recent TRI reports from
large industrial sources, about 86 percent).(1) For this reason, firms often install pollution
control equipment in stacks or vents to reduce the concentration of potentially toxic
pollutants released to the environment.
• Fugitive Emissions. "Fugitive" emissions are uncontrolled air pollutant releases that
"escape" from physical, chemical, or industrial processes and activities, and which do not
travel through stacks or vents. Examples include dust or vapors that are generated by the
transfer of bulk cargo (e.g., coal, gravel, occasionally organic liquids) from one container to
another (e.g., from a tank or hopper car to a storage silo, tank, or bin). Another example
includes leaks from joints and valves at industrial facilities and evaporative emissions of fuel
from mobile sources.
"Fugitive dust" emissions often occur when quarrying, earth moving, construction, or
excavation activities produce particulates. Such emissions are often called "fugitive" because
they are uncontrolled (though this is not always the case). Historically, EPA has regarded
fugitive emissions as being less important than stack and vent emissions; this is because
either the amount of material released was relatively small or the characteristics of the release
(large particle size, for example) precluded transport over large distances. However, the
combined fugitive emissions from intensive or widespread industrial activities can be as
important a contributor to risk as stack emissions.
The following terms are routinely used to describe processes that generate emissions.
• Particle Suspension and Entrainment. Particle suspension refers to a set of physical
release mechanisms, without reference to specific types of sources and can overlap with the
April 2004 Page 8-2
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previous definition of fugitive emissions. Suspension and entrainment refers to any process
that results in the release of particles into the air from soils or other surfaces. Suspension and
entrainment can occur as a result of artificial soil disturbance; or the action of wind on loose
soil, sand or dust. Depending on the nature of the material and atmospheric conditions,
suspended particles transport only a few feet, or may transport very long distances before
redepositing (for example, dust storms that originate in the Sahara Desert may blow across
the Atlantic and impact Central and North America). In some sections of the western United
States, the majority of particulate matter detected in air is "crustal material" (soils and fine
rock particles) suspended and transported by the wind, rather than human-made pollutants.
Volatilization/Vapor Release. Many (^ ™...-,, .,,, , ,.,., \
r . J. Common Measures oi Chemical Volatility
organic compounds and some inorganic
compounds may "volatilize" to some
extent; this means that these compounds
tend to evaporate at normal atmospheric
temperatures and pressures when not
contained. Volatilization can occur for
chemicals contained in mixtures as well
as from concentrated or pure forms.
Common examples include the lighter
Henry's Law Constant. The ratio at
equilibrium of the gas phase concentration to the
liquid phase concentration of a gas. Note that the
Henry's Law constant can be defined in several
ways and expressed using different units.
Vapor pressure. The pressure exerted by a
vapor, either by itself or in a mixture of gases;
, f , • , , often taken to mean saturated vapor pressure,
components of gasoline such as benzene, ... . . . F F '
,., , ... rr- • 1 ! which is the pressure or a vapor in contact with
which volatilize to a sufficient degree that •<.,-•*£
„ , , , . I its liquid form.
they can be smelled (and sometimes seen) >
when cars are refueling at filling stations
without vapor control systems. Sources can release vapors when handling
highly-concentrated or pure organic compounds, as well as when solids and liquids with low
levels of organic contamination are exposed to the atmosphere. Volatilization releases are
common from chemical manufacturing and processing operations, from metal cleaning and
dry cleaning operations that use organic solvents, and from waste management facilities.
Volatilization also is important for many natural sources of organic emissions. For example,
in heavily forested areas, terpenes (volatile chemicals emitted from pines and other tree
species) can account for a large proportions of total organic air pollution.
Volatile organic compounds (VOCs) are not the only types of substances that vaporize.
Some metals (e.g., elemental mercury), organometallic compounds, and other inorganic
substances (e.g., ammonia and chlorine) have a high vapor pressure. Many semivolatile
organic compounds (SVOCs) also volatilize relatively quickly, albeit at a slower rate than
VOCs. Some solids also have a high vapor pressure (mothballs are a common example).
8.2.2 Characteristics of Releases that Affect Dispersion and Transport
EPA and others have developed several air "dispersion" models to predict the often-complex
behavior of air pollution releases. Most air dispersion models take into account a number of
characteristics of the source and pollutants released. The most common of these characteristics
are described below.
• Release Rate and Volume. The rate of release (exit velocity) strongly influences the
behavior of the pollutant plume as it moves through the atmosphere. In the case of stack and
April 2004 Page 8-3
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vent releases, sources can release pollutants as pure vapors, as dilute solutions of vapor in air
or other gases, or as suspended particles. Large volumes are often released at a relatively
high velocity from stacks or vents, which can also serve to drive pollutants higher in the
atmosphere. Air quality models often calculate volume from data on exit area and exit
velocity. In the case of fugitive releases or volatilization, the "volume" of release has less
meaning, and often does not receive explicit consideration in fate and transport modeling.
Concentration. Concentration (the mass of pollutant per unit volume of released gases) is
the other half of the equation that determines the amount (mass) of pollutant released.
Pollutants at higher concentrations may also be more likely to condense onto particles or
liquid droplets.
Temperature. The temperature of a plume emitted from a stack or vent influences the
dispersion and transport of pollutants. A plume that is warmer than the surrounding air will
generally rise, which tends to increase the distance over which pollutants will be transported.
The combination of temperature and vertical velocity of stack emissions combine to affect
the height to which the plume will rise and the layer of the atmosphere in which it will
initially be transported. As with concentration, the temperature of the plume also affects the
physical form of pollutants, with less volatile pollutants condensing faster from cooler
plumes.
Source Characteristics Affecting Dispersion
Release rate
ttu™hoeJii = Hs+ AH
*P%sical release teighi (fib)
• Froma stack
*Phimeri!e(AH)
• Exit velocity
• Stack teniteratuie
• Wind speed
IT
Height. Pollutants may also be
released into the atmosphere at
different heights, and the height of
release can strongly affect dispersion
and transport. Greater release
heights generally result in increased
pollutant dilution in the atmosphere,
lower ground-level concentrations,
and a greater distance to peak
ground-level concentrations.
Release height also is important in
evaluating local effects on air
transport, such as building
downwash. While power generation
or industrial activities may release combustion products from stacks that are hundreds of feet
tall, volatilization releases or suspension of particulate pollutants often occur at or near the
ground surface.
Timing and Duration. Multiplying the release duration by the release rate produces the total
mass of pollutant released. The timing of release relative to specific meteorological
conditions determines the particular dispersion and transport of pollutants. Unfortunately,
only total annual or average daily release data are available for most sources, making it
difficult to fully characterize time varying releases. Fortunately, chronic exposure
assessments usually focus on the average long-term (annual) concentrations. Acute exposure
assessments, however, usually focus on the maximum short-term (24-hours or less)
concentration. Acute exposures are derived from conservative meteorological factors that
April 2004
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lead to the highest short term peak values for a screening exercise; for a more detailed
exercise, the actual meteorology should determine the short term peaks.
Physical Form. The physical form of pollutant releases greatly affects the dispersion,
transport and chemical reactions that pollutants undergo. Generally, pollutants are
characterized as being vapors (not bound to particles, but existing as single molecules or
very small aggregates "dissolved" in air - also called gaseous), particle-bound (reversibly
absorbed or condensed onto the surface of particles), or particulate (irreversibly incorporated
into airborne particles). The distribution of pollutants in these three "phases" is known as
partitioning. Partitioning is a function of the chemical and physical properties of the
pollutants and the temperature and pressure of the atmosphere into which the chemicals have
been released (e.g., the partitioning behavior of pollutants can vary greatly with temperature).
As noted above, sources can emit chemical pollutants in the vapor phase at relatively high
temperatures, and these pollutants can condense into or onto particulates as the emitted gases
cool in the atmosphere. Sources generally emit most metals (with the important exception of
mercury) as particles in the atmosphere.
Particle Size. When sources release pollutants as particles (or if released as gases, if these
pollutants condense into particles or absorb onto the surface of existing particles), the rate of
pollutant removal from the atmosphere to surfaces (e.g., plants, soils, surface water) depends
upon particle size. The typical size of particles that different activities and processes emit
into the air can vary by many orders of magnitude (powers often). As the size of particles
increases, the rate at which particles fall due to gravity (the settling velocity) increases. Thus,
fine particles (approximate diameter less than a few microns)(a) may remain suspended in air
indefinitely, but particles larger than about 20 microns in diameter settle rapidly and may not
transport far from sources of release.
For purposes of air toxics risk assessment, particles less than 10 microns in diameter are of
primary concern because they are small enough to be taken into and deposited in the lung
after inhalation. These particles are divided into two size ranges: "fine" particles less than
2.5 micrometers in size (PM25), and "coarse" particles covering the range from 2.5 to 10
micrometers in diameter (PM10). (Thus, monitoring analyses for metals in particulates, for
example, would commonly collect particulate samples of PM25 and PM10 for analysis, not
total suspended particulate (TSP), because such samples contain particles that are too large to
be effectively respired - thereby leading assessors to overestimate inhalation risk).
Particles emitted from combustion and high-temperature chemical processes can be very fine,
on the order of 0.01 to 1.0 microns in diameter. Such fine particles tend to condense to form
larger aggregates up to the limit of perhaps a few microns, and participate in a wide range of
chemical reactions.
One micron is one one-millionth of a meter, or about 0.00004 inches.
April 2004 Page 8-5
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Aerosols and Participate Matter
Aerosols are mixtures of fine solid or liquid particles in a gas. They can be emitted directly as
particles or formed in the atmosphere by gas-to-particle conversion processes. The terms dust, smoke,
fume, haze, and mist all describe different types of aerosols. Dust refers to solid particles produced
by disintegration process; smoke and fume are particles formed from the gas phase. Mists are
composed of liquid droplets. Some aerosols occur naturally, originating from volcanoes, dust storms,
forest and grassland fires, living vegetation, and sea spray. Human activities, such as the burning of
fossil fuels and the alteration of natural surface cover, also generate aerosols.
Participate matter is the term given to the tiny particles of solid or semi-solid material found in the
atmosphere. Particulates less than about 50 micrometers in size are called total suspended particulates
(TSP). Particles larger than that range tend to quickly settle out of the air. Particulate matter 10
micrometers in diameter and smaller (PM10) is considered inhalable. These particles are divided into
two size ranges: fine and coarse.
"Fine" particles less than 2.5 micrometers in size (PM2 5) are responsible for causing the greatest harm
to human health. 1/2Oth the width of a human hair, these fine particles can be inhaled deep into the
lungs, reaching areas where the cells replenish the blood with oxygen. They can cause breathing and
respiratory symptoms, irritation, inflammation, damage to the lungs, and premature deaths. Some
PM2 5 are released directly to the atmosphere from industrial smokestacks and automobile exhaust, but
a large percentage is actually formed in the atmosphere from other pollutants such as sulphur dioxide,
nitrogen oxides, and volatile organic compounds.
"Coarse" particles covering the range from 2.5 to 10 micrometers in diameter are also known to cause
adverse health effects, such as aggravation of respiratory disease. When inhaled, particles larger than
10 micrometers tend to be deposited in the upper parts of the respiratory system, from which they can
be eventually expelled back into the throat. Coarse particles generally remain in the form in which
they are released into the atmosphere without chemical transformation, eventually settling out under
the influence of gravity. While some of these coarse particles are generated naturally by sea salt
spray, wind and wave erosion, volcanic dust, windblown soil, and pollen, they are also produced by
human activities, such as construction, demolition, mining, road dust, tire wear, and grinding
processes of soil, rocks, or metals.
> '
Chemical Form. Chemical form is generally more of a concern for inorganic pollutants,
because organic chemicals tend to have well-defined chemical compositions and properties.
The most important chemical properties of inorganic metal compounds, for example, include
the oxidation or valence state of the cationic metal, the identity of the anionic counterion,
and the chemical and physical properties of the compound that the cation and anion comprise.
As an example of the importance of valence state, consider the metal chromium. When
emitted in the hexavalent form (with six positive charges - Cr6+), chromium is highly reactive
chemically and is readily reduced under certain conditions to the trivalent form, which is
Cr3+. Cr6+ can cause respiratory irritation and cancer in humans. Cr3+, on the other hand, is
much more stable, is much less toxic to humans and animals (and is actually an essential
mineral), and is not thought to cause cancer.
April 2004 Page 8-6
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Available air pollution dispersion models differ in the ways in which they use these
characteristics. While Chapter 9 presents a general discussion of these, users can find specific
details in the documentation for the various models at EPA's (Support Center for Regulatory Air
Models) SCRAM website.(2)
8.2.3 Physical and Meteorological Factors Affecting Air Toxics Dispersion and Transport
Wind Speed and Direction Affect Plume Dispersion
This section describes some of the most
important physical and meteorological
factors that affect the movement of air
pollutants after their release. For
definitions of and further details about
the atmospheric and meteorological
terms this section uses, refer to
Appendix G.
Although this section focuses on
releases from stationary point sources
(i.e., stacks), most of the factors may
apply to releases from other source types
as well. Stacks come in all sizes, from a
small vent on a roof to stacks hundreds
of feet in height. The function of a stack
is to remove pollution of high concentration and to discharge it to the atmosphere for dispersion
and transport. Stacks release pollutants high enough above the earth's surface that pollutants can
sufficiently disperse in the atmosphere before reaching ground level. All else being equal, taller
stacks disperse pollutants more effectively than shorter stacks because the pollutants release into
higher wind speeds and travel through a greater depth of the atmosphere before reaching ground
level.
The wind will determine which direction the plume
goes and how fast it gets there. To look at long-term
impacts (chronic exposure) a wind-rose (a distribution
of winds around a compass) can be used to determine
the areas of persistent wind; downwind of the largest
persistent winds will generally be the areas to expect
the maximum long-term impacts.
The air space the stack pollutant
occupies can be described as a
plume. As the plume travels, it
spreads and disperses, reducing
ambient pollutant concentrations
even though the cross sectional
mass of the plume remains the
same. Eventually, the plume may
intercept the ground. The
combination of emission velocity,
emission temperature (see below),
vertical air movement and
horizontal airflow all influences
how high a plume will rise and
how fast and far it travels.
Another factor is wind meander
(i.e., changes in wind direction
during light wind speed
Concentrations of Air Toxics in a Plume
Decrease With Distance
Plume grows and spreads
as more air is entrained
(the plume disperses)
Cross sectional mass stays
the same as plume expands
(i.e., concentration decreases)
As a plume grows, it entrains clean ambient air and disperses.
In other words, the amount of pollutant mass at any given
cross section in the plume is generally the same; thus, as the
plume spreads, its concentration goes down.
April 2004
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conditions), which can cause the plume to deviate in the horizontal direction due to turbulence
and wind fluctuation.
As the gases exit the stack, they mix with ambient air. This mixing of ambient air into the plume
is called entrainment. The plume grows in volume as it entrains ambient air and travels
downwind. Because stack gases are often warmer than the ambient outdoor air, the gases may be
less dense and than the outdoor air and are therefore buoyant (like a helium filled balloon).
Gases that stacks emit are often pushed out by fans giving the gas momentum as it enters the
atmosphere. The combination of this momentum and the buoyancy of the stack gases that are
warmer than the ambient air cause the gas to rise.
Example of a Wind Rose
NORTH
h \ \
/ /6% / /
/ / L
10%
A wind rose illustrates, for a given locality or area, the frequency and strength
of the wind from various directions for a selected time period, typically a year
or longer. In this example, the length of the bars indicates the percentage of
the year the wind blows in each of 16 directions and the colors indicate the
percent of time at that wind speed for each of these directions.
This plume rise allows air toxics emitted in this stack stream to be lofted higher in the
atmosphere. Since the plume is higher in the atmosphere where the winds are generally stronger,
the plume will generally disperse more before it reaches ground level. Plume rise depends on the
stack's physical characteristics and on the effluent's exit temperature and velocity.
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Vertical Air Motions
When air is displaced vertically, atmospheric behavior is a function of atmospheric stability. A stable
atmosphere resists vertical motion, and air that is displaced vertically in a stable atmosphere tends to
return to its original position. This atmospheric characteristic determines the ability of the
atmosphere to disperse pollutants. To understand atmospheric stability and the role it plays in
pollution dispersion, it is important to understand the dynamics of the atmosphere as they relate to
vertical atmospheric motion.
The degree of stability of the atmosphere is determined by the temperature difference between an air
parcel and the surrounding air. This difference can cause the parcel to rise or fall. There are three
general categories of atmospheric stability.
• In stable conditions, vertical movement tends not to occur. Stable conditions occur at night when
there is little or no wind. Air that lifts vertically will remain cooler, and therefore denser than the
surrounding air. Once the lifting force ceases, the air that has lifted will return to its original
position.
• Neutral conditions ("well mixed") neither encourage nor discourage air movement. Neutral
stability occurs on windy days or when there is cloud cover such that there is neither strong heating
nor cooling of the earth's surface. Air lifted vertically will tend to remain at the higher level once
the lifting force ceases.
• In unstable conditions, the air parcel tends to move upward or downward and to continue that
movement. Unstable conditions most commonly develop on sunny days with low wind speeds
where strong solar radiation is present. The earth rapidly absorbs heat and transfers some of it to
the surface air layer. As warm air rises, cooler air moves underneath. The cooler air, in turn, may
be heated by the earth's surface and begin to rise. Such conditions enhance vertical motion in both
directions and considerable vertical mixing occurs.
Inversions occur whenever warm air over-
runs cold air and "traps" the cold air
beneath. Within these inversions there is
little air motion, and the air becomes
stagnant. High air toxic concentrations can
occur within inversions due to the limited
amount of mixing between the "trapped" air
and the surrounding atmosphere.
Inversions can limit the volume of air into
which emissions are dispersed, even from
tall stacks.
April 2004
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The condition of the atmosphere (i.e., the vertical profile of the winds and temperature) along the
path of the plume also determines how far the plume rises in the atmosphere. As described in
Appendix G an inversion layer (formed when a layer of warm air "traps" a layer of cold air
beneath) may act as a barrier to vertical mixing. The height of a stack in relation to the height of
the inversion layer may often influence ground-level pollutant concentrations (Exhibit 8-1).
The initial velocity of the plume (stack
exit velocity) reduces quickly as the
plume entrains ambient air and acquires
horizontal momentum from the wind.
This momentum causes the plume to
bend over. The greater the wind speed,
the more horizontal momentum the
plume acquires. Wind speed usually
increases with height above the earth's
surface. Therefore, as the plume
continues upward the stronger winds tilt
the plume even further. This process
continues until the plume may appear to
be horizontal to the ground. The point
where the plume looks level may be a
considerable distance downwind from
the stack (Exhibit 8-2).
Wind Speed Affects Plume Rise
When the wind s are light,
the plume rise is high
When the winds are high,
the plume bends over
(p hime rise is minimal)
The strength of the wind will help determine how high
the plume rises; a strong wind will "knock-over" the
plume right away, while a light wind will allow a
plume to rise from its own buoyancy and initial inertia. ,
Due to configuration of the stack or adjacent buildings, the plume may not rise freely into the
atmosphere. The way in which the wind moves around adjacent buildings and the stack can
force the plume toward the ground instead of allowing it to rise in the atmosphere. Stack-tip
downwash can occur where the ratio of the stack exit velocity to horizontal wind speed is small.
In this case, low pressure in the wake of the stack may cause the plume to draw downward
behind the stack. Pollutant plume rise reduces when this occurs and elevates pollutant
concentrations immediately downwind of the source. As air moves over and around buildings
and other structures, it forms turbulent wakes. Depending upon the stack height, it may be
possible for the plume to be pulled down into this wake area. The reduction in plume height is
known as aerodynamic or building downwash (Exhibit 8-3).
Once air toxics have equilibrated with ambient conditions (e.g., temperature, velocity),
atmospheric and meteorologic factors primarily influence dispersion and transport of air toxics.
In particular, the rate of dispersion is influenced by both the thermal structure of the atmosphere
and mechanical agitation of the air as it moves over the different surface features of the earth (see
Appendix G). As the next section describes, exposure to solar radiation and moisture, as well as
other properties in the atmosphere, complement the factors above and contribute to the eventual
fate of the air toxics.
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Exhibit 8-1. Effects of Boundary Layer Conditions on Plume Dispersion
(a) Looping
(a) Looping. When the atmosphere is very unstable
through a deep layer, convective currents carry the
plume up and down, forming a looping pattern and
rapidly diluting the plume through intense vertical
mixing.
(b) Coning
(b) Coning. Under neutral conditions, the vertical
mixing also transports freely, but the turbulent motions
that irregularities of the ground and shearing of the
wind introduce are about equal, and the plume
resembles a cone.
(d) Lofting
MAXIMUM CONCHNTRATION
(c) Fanning. When the plume rises into an inversion
layer, the stability limits diffusion up or down, so that
the only spreading of the plume is sideways and when
viewed from above has a fanning appearance.
(d) Lofting. When conditions are unstable or neutral
above an inversion, the release of a plume above the
inversion is more likely to result in effective dispersion
and lower ground-level concentrations around the
source
(e) Fumigation. If the plume is released overnight just
under an inversion layer, it can become trapped. As
solar radiation warms the ground in the morning, the
air below an inversion layer becomes unstable. If the
unstable conditions then extend upwards and reach the
plume that is still trapped below the inversion layer, the
pollutants can be rapidly transported down toward the
ground. Ground-level pollutant concentrations can be
very high when fumigation occurs.
Graphics courtesy of Doug Parker, University of Leeds, and available at: http://www.env.leeds.ac.uk/
envil 250/lectures/lectl 1 .html.
April 2004
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Exhibit 8-2. Plume Rise Schematic
Temperature difference
causes buoyancy
Ve (Exit Velocity)
As emissions exit a stack, they can be lofted higher into the atmosphere as a result of plume rise.
Plume rise is caused by (1) buoyancy resulting from emissions with higher temperatures than ambient
air (i.e., Te > Ta) and (2) the initial momentum (i.e., exit velocity) of the emissions leaving the stack.
The effective stack height of a stack is equal to the actual physical height of the top of the stack (Hs)
plus the plume rise, minus any downwash associated with wake turbulence behind objects on the
ground (see Exhibit 8-3).
Exhibit 8-3. Aerodynamic or Building Downwash
Nearby structures can disturb the horizontal flow of the wind (indicated by the dashed line) and cause
a plume to get "downwashed" to the ground quickly. This is how a snow fence works.
April 2004
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Examples of Plume Rise
The picture on the left is an example of an elevated point source that probably has a hot plume or high
exit velocity, as the plume rise indicates. Because of the light wind and neutral or unstable
atmospheric conditions, there are essentially no impacts at ground level near the source. The picture
on the right is another example of elevated point sources, but this time with higher winds. There is
little plume rise, and the plumes fan straighter out from the stacks, resulting in narrower plumes.
8.3 Fate of Air Toxics in the Atmosphere
This section discusses the major physical and chemical processes that affect the fate of air toxics
in the atmosphere. The scope of this section is limited to processes that remove air toxics from
the atmosphere. Part IE of this reference manual discusses the fate and transport of air toxics in
other environmental media and the ecosystem once a chemical has been removed from the air.
8.3.1 Physical Processes Removing Air Toxics
A number of important physical processes (processes that do not alter the chemical nature of
pollutants) affect how air toxics move in and out of the atmosphere. In particular, this section
discusses how gravity and precipitation remove air toxics from the atmosphere. The process
through which particulates fall (or settle) to the surface in the absence of precipitation is known
as dry deposition, and the removal of pollutants from the air through precipitation events is
called wet deposition.
• Dry Deposition. As the previous section noted, dry deposition is the settling of particles due
to gravity. The maximum speed at which a particle will fall in still air is known as the
settling velocity (settling rate). A particle's settling velocity is a function of its size,
density, and shape. Larger, denser particles settle more rapidly, and particles with more
irregular shape settle more slowly (Exhibit 8-4). For particles smaller than a few microns in
diameter (fine and ultrafine particles), the gravitational settling rate is so slow that other
forces, such as local air currents and collisions with gas molecules, tend to offset it. Thus, in
the absence of other removal mechanisms (e.g., condensation and/or aggregation to form
larger particles, wet deposition), particles in this size range tend to remain suspended in the
April 2004
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air for long periods of time. Depending on the conditions, fine particles may persist in the
atmosphere for days or weeks and travel hundreds or thousands of miles from their source.
At the other extreme, coarse dust particles (> 50 microns in diameter), such as those
generated while handling materials, have large settling velocities. Under normal conditions,
such particles generated near the ground will deposit on the surface within a few seconds or
minutes, generally within less than a kilometer of the source. Particles in between these two
extremes in the size distribution will settle at intermediate velocities, and will distribute at
intermediate distances from their sources.
Exhibit 8-4. Approximate Settling Rates for Typical Particles in Air
Equivalent Diameter* (microns)
0.01
0.1
1.0
10
100
Settling Rate (cm/sec)
0.00001
0.0002
0.01
0.6
40
* Diameter of a sphere that is approximately equivalent to a particle's diameter
In typical air dispersion models, the modeler must specify a particle size distribution, classifying
what proportion of the emitted particles are within particular size ranges. In initial screening-
level analyses of pollutant levels in air, users assume that particulate settling does not occur.
This is conservative relative to the air concentration - if the amount deposited to the ground is the
key issue of concern, then a high removal rate from the atmosphere would be "conservative."
Users can assess dry deposition for low-volatility pollutants that partition out of the air primarily
onto airborne particles in the same fashion as non-volatile particulates. Volatile chemicals that
exist primarily in the vapor phase have negligible settling velocities, and modelers generally need
not consider dry deposition for these pollutants. In the case of pollutants whose vapor-particle
partitioning is unclear, it is common to run air dispersion models assuming a range of
partitioning behavior from fully particle-bound to fully vapor phase.
• Wet Deposition. Wet deposition involves the "washing out" of pollutants from the
atmosphere through precipitation events (including rain, snow, and in some cases hail). Wet
deposition affects both particulate and vapor-phase pollutants. For larger particles and vapor
phase pollutants that are soluble in water, precipitation is very efficient at removing
pollutants from the air and depositing them on the earth's surface. Wet deposition may be
less efficient at removing fine particulates, and has limited effect on the levels of gaseous
pollutants with high Henry's Law constants (indicating low solubility in water compared to
vapor pressure). Because wet deposition depends on the occurrence of precipitation events, it
is best characterized over long periods (e.g., seasons or years). The relative importance of
precipitation in removing pollutants from the air depends on the climatic conditions in the
areas affected by pollution.
April 2004 Page 8-14
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Transport and Deposition of Mercury
Mercury is a natural trace element in nearly all coal, and the large quantities burned in major electric
power plants can release considerable mercury. In both municipal and medical incinerators the
variety of waste materials burned can include mercury. Some mercury remains in the ash-materials,
some may be captured by pollution controls on exhaust, and the rest is emitted to the air in three forms
or chemical "species:" gaseous elemental mercury (Hg(0)), gaseous ionic or "inorganic" mercury
(Hg(II)), and particle-bound mercury (Hg(p)). Elemental mercury gas is nearly insoluble in water and
rather inert chemically, so it can be transported up to thousands of miles while gradually being
converted to other forms and deposited. The ionic form, Hg(II) or Hg (2+), is soluble in water and
thus incorporated into rain, fog, and snow. Also, Hg(II) is both physically and chemically active and
is known as "reactive gaseous mercury" or ROM. Most of the Hg(n) emitted is deposited via both
precipitation and dry gases within about 30 to 60 miles from a stack. In many cases, this "local"
deposition can be the most important impact of mercury from combustion sources. The fate of
particle-bound mercury depends on the size of the particles, though generally they deposit to earth
within a few hundred miles of the emitting stack.
8.3.2 Chemical Reactions that Remove Air Toxics
Chemical Transformations Can Occur
in the Atmosphere
• • • u light
X + Y *• Z
In addition to deposition, chemical
reactions may occur that reduce air
toxics concentrations. Air toxics may be
destroyed through the action of sunlight,
through reactions with atmospheric
chemical pollutants, or through a
combination of these pathways. In
estimating the ambient air concentration
associated with air toxics releases, it is
therefore necessary to consider chemical
reactions as well as deposition. As will
be discussed in the next section, not all
chemical reactions result in the
destruction of air toxics, or their
conversion to less harmful products.
Potentially harmful pollutants may also
be formed as a result of atmospheric
chemical reactions (a process that is called secondary production or secondary formation).
This section, however, focuses on atmospheric chemical reactions which are known or believed
to destroy air toxics (i.e., resulting in less toxic forms).
• Major Chemical Reactions of Air Toxics. Generally, organic compounds are much more
susceptible to chemical reactions in the atmosphere than metals or other inorganic
contaminants. The major chemical reactions undergone by organic chemicals in the
atmosphere include:
- Photolysis (destruction by sunlight alone);
- Reactions with the hydroxyl radical (OH>);
Numerous complex chemical transformations may
occur in the atmosphere, some of which are
photochemical in nature (i.e., reactions in the presence
of light to form new chemicals).
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- Reactions with the nitrate radical (NO3»); and
- Reaction with ozone (O3).
Often these reactions occur in combination with reactions that are strongly affected by sunlight.
While reaction rates vary widely for pollutants, under typical atmospheric conditions, reactions
with the hydroxyl radical are the most rapid, and account for a large portion of pollutant
degradation during daylight hours. Reactions with nitrate radical occur primarily during the
night, and reactions with ozone occur both day and night. Except in the case of a few pollutants,
"pure" photolysis is a relatively minor reaction process. Other reactive species such as the
hydroperoxide radical (OOH>) may also participate in pollutant degrading reactions under some
conditions. The relative importance of these reactions is dependent not only on climatic factors
(e.g., duration and intensity of sunlight), but also on the overall concentrations of pollution
present. For example, high levels of nitrogen oxide (NOX) emissions and emissions of VOCs
increase the levels of nitrate radicals and ozone in the atmosphere, thereby increasing reaction
rates for subsequent reactions where these species are involved.
8.3.3 Chemical Reactions that Result in the Secondary Formation of Pollutants
As noted previously, not all chemical reactions result in the destruction of pollutants or in
reaction products that are of less concern than the pollutants from which they derive. In some
cases, the immediate reaction products result in products that are more toxic and/or more
persistent than the chemicals that were originally released into the atmosphere.
Examples of large-scale
chemical reactions that result in
products that can be hazardous
to health include the generation
of acid particulate through
photo-oxidation after the
release of sulfur dioxide (SO2)
and NOX from combustion
sources (i.e., to make sulfuric
acid and nitric acid), and the
formation of ozone and
photochemical oxidant in areas
with high levels of NOX and
volatile organic emissions. In
addition, there are many
reactions of specific organic
pollutants that generate air
toxics of concern, as Exhibit
8-5 shows. The extent to
which these reactions are important at any given location depend, of course, on the emissions and
resulting concentrations of the precursor materials. In addition, many of these reactions are
catalyzed directly and indirectly by sunlight, so weather and climatic factors are important in
judging the importance of secondary formation. While it is difficult to generalize, the secondary
formation of formaldehyde and acrolein are thought to be important in many regions of the
country with significant industrial and mobile source emissions/3'
Exhibit 8-5. Examples
Pollutant
acetaldehyde
acrolein
carbonyl sulfide
o-cresol
formaldehyde
hydrogen chloride
methylethyl ketone
N-nitroso-N-methylurea
N-nitrosodiethylamine
N-nitrosomorpholine
phosgene
propionaldehyde
of Secondary Pollutants
Formed From
propene, 2-butene
1,3 -butadiene
carbon disulfide
toluene
ethene, propene
nitric acid, chlorinated organics
butane, branched alkenes
N-methylurea
dimethylamine
morpholine
chlorinated solvents
1 -butene
Source: Rosenbaum et al., 1998(3)
April 2004
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8.3.4 Overall Persistence of Air Toxics in the Atmosphere
In analyzing the potential impacts of air toxics releases, it is necessary to combine considerations
of all the above processes to characterize the overall pattern of air toxics concentrations and
estimate the time periods and distance scales over which air toxics impacts need to be evaluated.
Detailed quantitative comparisons of removal pathways maybe too complex and expensive to
include in most risk assessments. However, air pollution scientists have developed a number of
simple models and gathered data on a large number of pollutants that enable them to assess the
relative impacts of different physical processes and chemical reactions on single chemicals under
typical conditions. The most common model uses the simplifying assumption that pollutant
removal through each chemical and physical processes can be approximated using processes that
have characteristic half-lives and atmospheric lifetimes (Exhibit 8-6).
Under the most commonly used approach (many variations exist), the overall lifetime of a
pollutant in the environment is:
(Equation 8-1)
Coverall 'ptysical
That is, the overall lifetime (l/roverall) of a chemical in the environment is equal to the sum of the
atmospheric lifetime when considering only physical processes (l/rphysical) plus the lifetime when
considering only chemical processes (l/rchemical). This equation is the same as saying that the
overall rate constant for pollutant removal/destruction (roverall) is equal to the sum of the rate
constant for physical removal (rphysical) plus the rate constant for chemical reaction (l/rchemical).
This relationship follows from the nature of first-order reaction kinetics, and is known to be only
an approximate description of actual physical processes (see Exhibit 8-5). It is a useful
approximation, however, that can be used to evaluate the importance of atmospheric processes
for many pollutants.
As noted in Section 8.2.2, organic chemical pollutants can undergo a number of chemical
reactions that maybe important under different sets of conditions. Thus, the atmospheric
lifetime for chemical reactions in the above equation is often broken down to consider
contributions from each important reaction:
Ill 1
1- + + (Equation 8-2)
rchsmical
where the terms on the right side of the equations represent the rates of pollutant removal through
the reactions with hydroxide radical, nitrate radical, ozone, and photolysis, respectively.
For any given air toxic, overall persistence in the atmosphere depends on particle-vapor
partitioning behavior, particle size distribution (if the material is non-volatile), and susceptibility
April 2004 Page 8-17
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to various types of chemical reactions. Atmospheric half-lives due to deposition (wet and dry)
tend to be highly variable depending on particle size, ranging from a few minutes for coarse
particles to many days for very fine particles. Most fine particles (less than a few microns) are
removed from the troposphere (the lower level of the atmosphere where most weather takes
place) with an average lifetime of between 5 and 15 days.
Exhibit 8-6. Example First-Order Decay of Pollutant Concentration
Example of First-Order Decay of Pollutant Concentration
Showing Half-Life (T ^^ and Atmospheric Lifetime (T)
0)
E
I
0)
o
1
Q)
U
=
O
(J
-(-•
ra
o
a.
40
80 120
Time (arbitrary units)
160
Simple physical and chemical reactions often proceed according to what are called "first-order
kinetics." In a first-order reaction, the rate of the reaction at any given time is proportional to the
concentration of one reactant (in this case, the air toxic that is being destroyed). The overall rate of
the reaction is governed by the first-order (or "pseudo first-order") rate constant, "k." A higher rate
constant implies a higher reaction rate for a given concentration of reactant. First-order reactions have
the properties that the "half-life" of the reaction (the time in which one-half of the original
concentration of reactant is destroyed) is the same no matter what the initial concentration. Air
pollution scientists also measure the "atmospheric lifetime" of pollutants, which is abbreviated as the
Greek letter T (tau) or the letter "r," which is equal to 1/k. In this example, the rate constant (k)
represents the sum of both physical and chemical removal.
Exhibit 8-7 presents estimated chemical half-lives for a few example chemicals based on
measured reaction rates. Estimated atmospheric lifetime for chemical reactions ranges from
many thousands of hours for the least reactive chemicals to only a few hours for chemicals that
are more reactive. As noted above, the lifetimes for reactions with the hydroxide radical (rOH) are
the shortest, indicating that this pathway is the most important for most of the chemicals in the
table, at least during daylight hours. Reactions with ozone and nitrate radicals are much slower
April 2004
Page 8-18
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for most of the chemicals. "Pure" photolysis is not important for most chemicals, with the
notable exceptions of the two aldehydes, where it is a major degradation pathway.(4)
Exhibit 8-7. Typical Atmospheric Half-lives for Chemical
Reactions (hours) for Selected Pollutants for Reactions with
Hydroxide, Nitrate, Ozone, and for Photolysis
Compound
methane
ethane
benzene
toluene
1 -butene
isoprene
formaldehyde
acetaldehyde
rOH
28,000
8,40
180
37
7.4
2.3
19
12
r03
2xl08
3xl07
4xl06
3xl05
26
20
5,600
rNO3
2xl06
IxlO5
4xl06
3xl05
93
1.4
photolysis
-
—
—
5.5
2.7
Source: California Air Resources Board Toxic Air Contaminant Fact Sheets*4'
Data such as those in Exhibit 8-7 are available to some degree for many chemicals, and can help
assessors to judge the distance scales over which to analyze air toxics impacts. As noted above,
persistence on the order of less than a day suggests transport of about ten miles, while persistence
for several days suggests regional transport (500-1,000 miles) before being substantially
degraded. Atmospheric reactivity is not well-studied for some chemicals, requiring the use of
assumptions about persistence that span a reasonable range of reactivity. For non-volatile air
toxics that partition primarily into particles, physical processes (wet and dry deposition) may be
the most important in determining overall atmospheric lifetimes/4' Some chemicals that are very
persistent in the atmosphere and in terrestrial and aquatic systems may require special
consideration, as described in Chapter 17. Chapter 9 builds upon the discussion above and
identifies how well available dispersion models address chemistry/physical removal.
References
1. U.S. Environmental Protection Agency. 2003. 2001 Toxics Release Inventory (TRI) Public
Data Release Report. Office of Environmental Information, Washington, D.C., July.
Available at: http://www.epa.gov/tri/tridata/triO 1 /index.htm.
2. U.S. Environmental Protection Agency. 2004. Technology Transfer Network. Support Center
for Regulatory Air Models. Updated February 23, 2004. Available at:
http://www.epa.gov/ttn/scram/. (Last accessed March 2004).
3. Rosenbaum, A.S., Ligocki, M.P., and Wei, Y.H. 1998. Modeling Cumulative Outdoor
Concentrations of Hazardous Air Pollutants, Volume 1: Text. SYSAPP-99-96/33r2,
Prepared for U.S. Environmental Protection Agency, Office of Policy, Planning and
Evaluation, by Systems Applications International, Inc., San Rafael, CA.
4. California Air Resources Board. 1998. Toxic Air Contaminant Fact Sheets. Available at:
http://www.arb.ca.gov/toxics/tac/tac.htm. (Last accessed March 2004).
April 2004
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Chapter 9 Assessing Air Quality: Modeling
Table of Contents
9.1 Introduction 1
9.2 Air Quality Modeling I
9.2.1 The Overall Structure of an Air Quality Model 1
9.2.2 Types of Models: Scientific Principles 6
9.2.3 Modeling Deposition 7
9.2.4 Screening vs. Refined Models £
9.2.5 Specific Data Required for Modeling 9
9.2.6 Sources of Air Quality Models and Information H
9.2.7 Examples of Air Quality Models 12
9.2.8 Emissions from Soil 18
9.3 Air Quality Modeling Examples 18
References 19
-------
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9.1 Introduction
Models have been used for decades to approximate physical systems and make estimates about
the nature of the system under study. The types of models most frequently used in air toxics
exposure assessments are mathematically-based models, which attempt to approximate all of the
important physical and chemical processes affecting contaminant fate and transport within the
environment. The physical and chemical processes are described as a set of mathematical
expressions which characterize the behavior of contaminants released into the environment.
One specific type of model, called an air quality model, is used by EPA to understand the
impact of pollution on air quality for a variety of purposes. For example, under the Clean Air
Act (CAA), EPA uses air quality models to facilitate the regulatory permitting of industrial
facilities, demonstrate the adequacy of emission limits, and project conditions into future years.
For several of the criteria pollutants, regulatory requirements call for the application of air quality
models to evaluate future year conditions as part of State Implementation Plans to achieve and
maintain the National Ambient Air Quality Standards (NAAQS). Model simulations are also
used to assist in the selection of monitoring locations.
Air quality models, when combined with emissions inventory and meteorological data, can be
used as part of risk assessments that may lead to the development and implementation of
regulations or voluntary reduction measures. For example, under National Air Toxics
Assessments (NATA), EPA has conducted a national-scale assessment using air quality models
for some 33 priority air toxics (see Chapter 2) to identify broad national air toxics issues and to
help focus efforts. This Chapter provides an overview of air quality modeling used in air toxics
risk assessments.
9.2 Air Quality Modeling
A variety of methods, data, and tools used for modeling the fate and transport of air toxics
released to the environment have been developed; for a summary of methods, the reader can refer
to Chapter 3 and other parts of EPA's Residual Risk Report to Congress.m While the Report to
Congress is oriented toward assessment of residual (i.e., post-Maximum Achievable Control
Technology [MACT]) risks from facilities regulated by the Clean Air Act, it also provides a
good, general overview of general modeling procedures for air toxics assessments at the local
scale. Another key reference for air quality models is the EPA's Support Center for Regulatory
Air Models (SCRAM) website (http://www.epa.gov/ttn/scram/).(2)
9.2.1 The Overall Structure of an Air Quality Model
Air quality models provide estimates of ambient air concentrations and/or deposition rates for
one or more chemicals emitted from one or more sources. All air quality modeling systems are
comprised of three major components (see Exhibit 9-1) which, when combined, provide a picture
of predicted fate and transport of air toxics once released into the environment:
• An emissions (release) model (Chapter 7 discusses developing the emissions inventory);
• A meteorology model (Chapter 8 discusses atmospheric phenomena and physical properties
that affect the fate and transport of air toxics after release); and
April 2004 Page 9-1
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An air quality model that predicts the movements of chemicals through the atmosphere along
with any physical and chemical changes that may occur (e.g., chemical reactions that degrade
the pollutant).
Exhibit 9-1. Basic Components of an Air Quality Modeling System
Quantification
of Releases
*
r
Control Strategy
Development
Release
Model
Processed
Releases
Air Quality
Model
Meteorological
Obser^itions
Meteorology
Model
Processed
Meteorology
Specifically, the emissions and meteorology data are fed into the model (or the various
components of the model) which are then run through various algorithms that simulate the
physical and chemical processes in the atmosphere to provide estimated concentrations of
chemicals (e.g., for inhalation exposure assessment, the exposure concentration at the point of
exposure). Depending upon the specific model
application being used, the release and ^
meteorological data may simply be input to a
single air quality model that includes both release
and meteorological modules or the release and
meteorological modules may be separated
initially to "pre-process" the data and
subsequently combined for the remaining
calculations.
Air quality models provide estimates of ambient
air concentrations at specific points distant from
the source(s) being modeled. These are either
predetermined within the model or selected by
the analyst. In the simplest models (e.g.,
SCREEN3), the points are laid out along a vector
(straight line) from the source. Many other
models use a grid system to calculate ambient
concentrations at specific exposure points at
specified "nodes"(see Exhibit 9-2). The model
does not always automatically provide an
estimate of concentration at every desired
location, and extrapolation to desired locations is
often required. A discussion of where and how to
choose exposure points is provided in Chapter 11.
Air Toxics Modeling Issues
A recent study identified several issues that affect
uncertainties associated with air toxics modeling,
including:
• Uncertainties associated with emissions;
• Meteorological conditions that are difficult to
simulate (e.g., calm conditions, complex terrain,
land/sea breezes, precipitation events);
• Spatial coverage, temporal resolution, and
detection limits in monitoring data;
• Chemical transformations in the atmosphere;
• Removal via dry and wet deposition;
• Indoor sources; and
• Population activity patterns.
The study recommended a combination of modeling
and monitoring for air toxics exposure assessments.
For further information, see:
Coordinating Research Council and U.S. Department
of Energy. 2002. Critical Review of Air Toxics
Modeling, August 2002. CRC Project Number A-42-
1, available at: http://www.crcao.com.
April 2004
Page 9-2
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Exhibit 9-2. Model Grids and Interpolation
Many air quality models calculate ambient concentrations at specific exposure points at specified
"nodes" using either a polar coordinate grid system (i.e., the intersections of a series of concentric
circles and radial lines [above, left]) or on a standard Cartesian coordinate system (above, right).
(Note that the nodes, in both of these types of grids, are simply the points where two lines intersect.)
The locations of these nodes often do not fall precisely on the locations of interest for a given risk
assessment.
Interpolation to Centroid
(beyond 3.S km
In cases where the nodes and locations of
interest do not align, a process of
interpolation is used to estimate the ambient
air concentration at the location. For polar
grids, a two-step interpolation is used,
starting with the modeled concentrations at
the nearest locations (e.g., al, a2, a3, and a4
in the graph to the left). The first
interpolation is in the radial direction (i.e.,
along the two adjacent radial lines [aI,a2]
and [a3, a4] in the graph). The
concentration is estimated at the intersection
of each radial line with the concentric circle
that intersects the receptor location (at the
same radial distance from the source as the
internal point). This interpolation is
performed under the assumption that the
logarithm of the concentration decreases in proportion to the increase in the logarithm of the distance
from the source (i.e., a log-log interpolation). The second interpolation is in the azimuthal direction
(i.e., along the concentric circle that intersects the internal point). This interpolation is performed
under the assumption that the change in concentration is proportional to the distance around the circle
between the two radial lines (i.e., linear interpolation).
April 2004
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Illustrations of Three Common Types of Air Quality Models
Gaussian Plume Models: Model a continuous release downwind from a source
^
Gaussian plume models estimate the transport and mixing of pollutants in the dispersing plume as it
moves downwind from the source. They assume that dispersion in the vertical and lateral dimensions
will take the form of a normal Gaussian curve, with the maximum concentration at the center of the
plume.(a)
Gaussian Puff Models: Model either Steady-state or Non-steady state releases
Steady-State Approach: Plume = Puff
Non Steady-State Approach: Puffs follow Air
Puff models use a series of overlapping puffs to represent emissions. As shown by the illustration of
the non-steady state approach, changes in wind direction over time and through space bring about
changes in the plume's shape.'
(b)
April 2004
Page 9-4
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Illustrations of Three Common Types of Air Quality Models (continued)
Numerical Grid Models: Model reactive pollutants in complex topography
Modeling Domain
Numerical grid models assume that emissions from area and line sources are mixed throughout the volume
of each surface cell within the modeling domain. Emitted species react with each other and the incoming
solar radiation with resulting chemical reactions taking place. Point source emissions, typically emitted
from elevated stacks, are emitted into upper layers of the modeling domain based on a plume rise
calculation. The point source emissions are then mixed throughout the volume of the elevated layer. Some
models may modify this widespread dispersal by including a plume in grid module which acts to minimize
the instantaneous mixing across the grid cell volume. These reactions are simulated to generate volume-
average concentrations as a function of time within each cell.(c) The cells of the grid, representing discrete
portions of the atmosphere, are superimposed on the modeling domain. (d)
.11-l-lM III';::
MPQHT
Individual surface cell
a U.S. Environmental Protection Agency. 1970. Office of Air Programs, prepared by Turner, D.B. Workbook of
atmospheric dispersion estimates. Publication AP-26. NTIS PB 191 482.
b National Oceanic and Atmospheric Administration. 2003. Prepared by Irwin, J.S. Modeling Air Quality
Pollutant Imp acts. Research Triangle Park, NC, 15 Oct. 2003. Available at: http://www.meteo.bg/EURASAP
/40/paperl.html .
c U.S. Environmental Protection Agency. 1984. Office of Research and Development, prepared by Schere, K.L.
and Demerjian, K.L. User's guide for the photochemical box model (PBM).. Research Triangle Park. EPA-600/8-
84-022a
d Systems Applications International. 1991-1993. Urban Airshed Modeling National Training Workshops.
April 2004
Page 9-5
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Results from air toxic modeling are highly dependent upon the quality of data used as input to the
models. The degree to which a user has reliable information on releases, meteorology, and
setting will determine the accuracy of the modeled concentrations. Because model inputs are
only estimates, even the most sophisticated models will have inherent uncertainties and will have
the potential to underestimate or overestimate actual concentrations. (Monitoring data can assist
in this regard as a way of evaluating the modeled results and to look for important gaps in the
emissions inventory - see Chapter 10).
The uncertainty associated with the meteorology data includes measurement of key variables of
wind speed/direction and atmospheric stability, and to a lesser extent, temperature and
precipitation. Uncertainty is also associated with the terrain specification. Use of a model
designed for fiat terrain will likely provide inaccurate estimates of concentrations if the terrain is
actually more complex (e.g., a facility located in a river valley modeled as being located on fiat
terrain).
In addition to the model inputs, uncertainties also arise from the model formulation used to
describe the physical and chemical processes that take place in the atmosphere. In general,
models are most accurate in simulating long-term averages of ambient concentrations and
deposition rates in settings with simple topography.
9.2.2 Types of Models: Scientific Principles
In general, air quality models can be categorized as one of two types: steady-state and non-
steady state models. The movement of mass away from the source (i.e., advection) and
turbulent diffusion (e.g., dispersion) are modeled in both types of models. The steady-state
model assumes that no variations occur over a certain time period (typically, one-hour); the non
steady-state allows time-varying changes, but this capability imposes the need for additional
model inputs, increased computation resources, and increased model formulation complexities.
For additional information on air dispersion modeling, refer to NOAA's Real-time
Environmental Applications and Display sYstem (READY) website.(3)
• Steady-state models are models which assume no time-varying processes occur over the
period of interest. Hence, material released travels infinitely in only one direction over the
time period (e.g., one hour). Often, these models assume that the material is distributed
normally (also termed a "Gaussian distribution") and are thus called "Gaussian plume"
models (see illustration above). The steady-state model typically uses meteorological
information obtained near the source and assumes it holds true throughout the modeling
region (e.g., a 50 kilometer radius). Wind direction, wind speed, and atmospheric stability
are used to predict concentrations. This type of model is most widely used for stationary
sources and for non-reactive pollutants (although models can take into account deposition
and simple linear decay). The models are least applicable in areas with rapid time-varying
conditions, over spatially varying terrain and land use, over large spatial scales (> 50 km),
and where complex atmospheric chemistry takes place.
• Non-steady state models are models which can simulate the effects of time- and space-
varying meteorological conditions on pollutant transport, transformation, and removal. The
modeling region is typically divided into grid cells, and the model simulates movement of
pollutants between cells by taking into account advection, degradation, and other physical
April 2004 Page 9-6
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and chemical processes. These models are often used for chemically reactive pollutants or
where there is complex topography or meteorology (e.g., complex sea breeze circulation).
They require complex wind flow characterization and other detailed meteorological
information for dispersion. For chemical transformation, they require information on the
important chemical compounds as well as chemical kinetics to properly characterize the
transformation and removal of air toxics. These models often take the form of grid models
with the calculation of the physical and chemical processes taking place at each grid location.
Other model types include "puff models" (illustrated above), which use a series of
overlapping puffs to represent emissions. The calculations of the physical and chemical
processes are made for each "puff."
Another type of non-steady state model, the atmospheric trajectory model, uses meteorological
data and mathematical equations to simulate transport in the atmosphere. The position of a
parcel of air with time are calculated based on externally provided meteorological data such as
wind speed and direction, temperature, humidity, and pressure. Model results depend on the
spatial and temporal resolution of the meteorological data used, and also on the complexity of the
model itself. Simpler models may deal with only two-dimensional transport by winds assuming
the material emitted into the parcel stays at the same level, while more complex models may
include 3-dimensional chemical and thermodynamic processes such as aerosol formation,
convection, and turbulent diffusion.
9.2.3 Modeling Deposition
Deposition is the transfer of chemicals from the plume to the earth's surface (i.e., to soil, water
bodies, or living organisms such as plant surfaces). Although the primary route of exposure for
many air toxics is inhalation of ambient concentrations, deposition rates can be important for the
multimedia fate and transport assessments required for persistent bio accumulative hazardous air
pollutant (PB-HAP) substances (see Chapter 18). Air quality models all simulate ambient air
concentrations, and many also simulate deposition. Based on the simulated ambient air
concentration at a location, the deposition flux (i.e., mass of pollutant deposited per unit area)
can be simulated based on a number of assumptions (see Chapter 8 for a discussion of
mechanisms of deposition). Two types of deposition are usually modeled:
• Dry deposition is determined from the ambient air concentration and the deposition velocity.
Particle-phase air toxics are the principal pollutants removed through dry deposition by
particle settling. In addition, semi-volatile toxics (air toxics that exist both in the gas and
particle phases) can also be removed through dry deposition. Dry deposition of some vapor-
phase air toxics is also possible for some chemicals (e.g., divalent mercury).
• Wet deposition is determined from a combination of the ambient concentration and a
scavenging ratio. The scavenging ratio accounts for the propensity of the modeled chemical
to partition into precipitation in the atmosphere, based on physical and chemical
characteristics of the pollutant, the nature of the precipitation (liquid or frozen), and the
precipitation rate. The term "scavenger" is a general term that can apply to anything
chemical or physical that removes a pollutant from the atmosphere. In this example, rain is a
scavenger because it is removing (by dissolution) an air toxic from the atmosphere and
transferring it to a surface.
April2004 Page 9-7
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9.2.4 Screening vs. Refined Models
The overall accuracy and precision of results determined by a model is generally proportional to
the complexity of the model, which in turn affects input data requirements and overall resources.
• Screening-level models are designed to provide conservative (i.e., high) estimates, and are
useful for applications such as identifying facilities and/or air toxics that appear likely to
contribute the greatest risk among a group of sources and chemicals released. Data
requirements are generally low (e.g., emission rates, some stack parameters), and running the
models is generally easy and requires few resources.
• Refined models take into account more complex chemical behavior and a greater degree of
site-specific information, generally producing more accurate results. Data requirements are
higher (e.g., site-specific meteorology, terrain, chemistry data), and application of more
refined models may require expert judgment in developing model inputs and setting model
options. Some models can be used both as a screening model and refined model if additional
site-specific information is used in the application.
The selection of a model for a specific application depends on a number of factors, including:
• The nature of the pollutant (e.g., gaseous, particulate, reactive, inert);
• The meteorological and topographic complexities of the area of concern;
• The complexity of the distribution of sources;
Exposure Concentrations: Units are Important
Air toxics exposure concentrations (ECs) should in general be reported as (ig/m3. Dose-response
values often are reported as parts per million (ppm), parts per billion (ppb), or mg/m3. In the risk
characterization step, ECs are compared to dose-response values, and therefore the units for the EC
must match the units for the dose-response values.
The conversion from mg/m3 to ppm can be expressed as:
Concentration [ppm] = Concentration [mg/m3] x 24.45 [L/mole] / MW
and the conversion from ppm to mg/m3 is:
Concentration [mg/m3] = Concentration [ppm] x MW / 24.45 [L/mole]
where MW is the molecular weight of the air toxic in g/mole and 24.45 is the volume in liters of one
mole of an ideal gas at 1 atmosphere and 25 degrees Celsius.
Note also that ppb = 1,000 x ppm and that here, ppm is volume-based. Also, (ig/m3 = 1,000 x mg/m3.
Tip: In the development of the analysis plan, stipulate that all laboratory and modeling results be
reported in (ig/m3. This will save time (and reduce computational errors) in the remaining
phases of the risk assessment.
April 2004 Page 9-b.
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• The spatial scale and temporal resolution required for the analysis;
• The level of detail and accuracy desired for the study and the amount of uncertainty that the
analyst/risk manager is willing to accept; and
• The technical expertise of user.
For example, steady-state models are not considered appropriate for downwind distances beyond
a 50 km range, primarily because the steady-state wind speed and direction over that distance
become unrealistic over the typical one-hour simulation period. This is especially true where
complex terrain or meteorology is present.
Because screening models are applied with fewer resources and data to provide conservative
estimates of concentrations, screening models are often applied prior to any refined modeling in
order to narrow the set of sources or air toxics to be modeled. Such an iterative approach is
generally recommended by EPA, where screening results are used to generate a subset of
potentially higher-risk sources or chemicals for more refined assessment. General guidance on
screening-level modeling has been published by EPA.(4) Additional guidance on air modeling is
incorporated into EPA's Guideline on Air Quality Models.(2)
Risk assessors generally work out the development of a modeling protocol to be used in the
assessment during the planning/scoping and problem formulation phase of the assessment.
Providing this protocol will help establish the modeling approach for not only review and
comment by interested parties up front, but will help to establish technical credibility and provide
for consensus building among all interested parties.
9.2.5 Specific Data Required for Modeling
As described above, meteorology, terrain, and emissions data are processed and used as primary
input data for air quality models. Depending on the level of refinement of the model, the
required input data for an air quality model will include (but not necessarily be limited to) the
following parameters:
• Emission rate. In general, the rate at which emissions are released into the atmosphere are
specified as a rate of release for each chemical in units of mass per unit time.
• Physical/chemical characteristics of emissions. These data are closely related to emission
rates (i.e., from measurements and/or emission factors; see Chapter 7). For some models, the
phase of emission must be specified (e.g., gas, particulate, or semi-volatile). For chemicals
present as particulate matter or as semi-volatile substances, particle size distribution and
fraction of particle phase as a function of temperature, for each chemical, may be necessary
inputs. In some cases, information may only be available on the basis of total volatile organic
compounds or total particulates. This information may be speciated based on the emissions
source type through the use of sources such as EPA's SPECIATE database. (The most recent
version of SPECIATE, Version 3.2, was last updated with new profiles in October 1999.) (5)
• Type of release point. The required input data, modeling approach, and model selected for
assessment can depend on the type of release being modeled. Chapter 4 discussed types of
sources from a regulatory perspective (e.g., stationary, mobile). The following discussion is
focused on types of sources from a modeling perspective.
April 2004 Page 9-9
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- Point sources (modeling sense) are releases from stacks and isolated vents, and typically
have plume rise associated with the release due to the buoyancy or momentum of the
effluent.
- Area sources (modeling sense) are sources which are usually low level or ground level
releases with no plume rise (e.g., fugitive emissions from the summary of equipment
leaks across a facility; uncontrolled emissions that escape from the windows along a
building wall; releases of dust from a road or work site; slag dumps; storage ponds).
Depending on the type of area source, the modeler may opt to evaluate it as emissions
occurring from a two-dimensional surface (i.e., an area source in the modeling sense) or
as a three-dimensional volume source (see below). If a large number of sources are to be
modeled, a common approach is to spread these sources uniformly across the modeling
domain if no appropriate spatial surrogate is available. Alternatively, these sources may
be allocated based on spatial surrogates. Typical examples include census tract
population and commercial, residential and industrial land-uses.
- Volume sources are releases that are modeled as emanating from a 3-dimensional
volume (such as a box) . Examples include releases from conveyor belts or the collective
releases from the gas pumps at service stations. Volume sources differ from area sources
in that they have a vertical dimension to their release. Like area sources, they do not have
plume rise.
- Line sources are releases that are modeled as emanating from a two-dimensional area.
Examples include rail lines and roadway segments. Line sources differ from area sources
in that they have aspect ratios (length to width) much higher than 10:1. Like area sources,
they do not have plume rise.
- Specialized release types include multiple parallel release lines that result in increased
buoyant dispersion (e.g., coke ovens, aluminum smelters); dense gas release; and
exothermic gas release, jet-plume release and horizontal venting that may be defined and
modeled using special techniques or models depending on the characteristics of the
emission source.
• Release point parameters. Depending on the type of source being modeled, the user may
need to specify the physical characteristics of the release point. Key parameters may include
the following:
- Release height above ground level (e.g., stack height, average height of fugitive
emissions).
- Area of the release point (for point sources, stack diameter; for area sources, length and
width of the area across which releases occur).
- Other stack parameters of the release stream for point sources that can alter the effective
release height, which include temperature, stack orientation, the presence of obstructions
to flow (i.e., rain caps), and exit velocity or flow rate. Flow rate is expressed in terms of
the total volume of material released per unit of time. In general, most of the flow rate is
made up of nontoxic exhaust gases, with a small fraction being composed of chemical
contaminant.
- Facility building dimensions, if building downwash (i.e., the effects on plume dynamics
due to structures located near the source) is modeled.
• Location of special receptors. The location of known sensitive receptors (e.g., a school or
day-care center) may be a critical input when determining where to model ambient
concentrations. If these special receptor locations are not identified, the model will only
April 2004 Page 9-10
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provide concentration estimates at the nodes of the modeling grid that is initially laid out
around the source.
• Information on the surrounding land-use and terrain heights. For dispersion models,
classification of the surrounding area as urban or rural is usually required (this classification
can affect the rate of dispersion). In addition, more refined modeling that takes into account
complex terrain (e.g., ground surfaces higher than release height elevation) will require
terrain elevation data.
• Chemical-specific data. If transformation/removal is being modeled, rates of
transformation or removal for the chemicals being modeled are required (transformation
processes are discussed in Chapter 8).
• Boundary or background concentrations. Ideally, emissions from modeled source(s) are
responsible for the modeled concentrations. However, background concentrations, or
boundary conditions in the case of grid models, may be important contributors to the total
concentrations. This is particularly relevant where modeled concentrations are compared to
observed concentrations. There are three basic approaches to estimating background
concentrations:
- Default values based on supporting documentation from the literature (this is the simplest
approach);
- Data collected from monitoring stations within the study area; and
- Estimates made from larger regional scale models that cover the study area.
For grid type models, users should be aware that with a smaller modeling domain, there is
more potential for the boundary concentrations to play a more important role in determining
the total concentration.
In general, air quality modeling results will be most sensitive to the emission rate when studying
a single or few release points. However, when studying multiple release locations over a broad
area, source location becomes the most important parameter. For a Gaussian-type dispersion
model (e.g., ISC3, AERMOD; see Section 9.2.7 below), the ambient concentration will be
directly proportional to the emission rate (enabling the use of unit emission rates). Other inputs,
especially stack height and distance to fenceline, can also affect the results because these
parameters can have a direct impact on the location of higher ambient chemical concentrations
and potential off-site receptors. In general, however, the sensitivity of air modeling results to
specific input parameters can vary widely according to site-specific and chemical-specific
factors. Site-specific analyses are generally required to derive accurate sensitivity results for a
specific air modeling application. Additional discussion on sensitivity analysis can be found at
the EPA Region 6 Air Modeling for Combustion Risk Assessments website.(6)
9.2.6 Sources of Air Quality Models and Information
Numerous models (both screening and refined) have been developed by EPA, other government
agencies, and private sources. EPA models in particular undergo extensive evaluation and
statistical measures of performance. Some private industry models are also available to the user
at little or no charge. (If a public domain model is not available and a private model must be
April 2004 Page 9-11
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used, the user should request information about the theoretical basis for the model and the result
of any peer review.) Important sources of information include EPA's Guideline on Air Quality
Models^ and Dispersion Modeling of Toxic Pollutants in Urban Areas: Guidance, Methodology
and Applications.(7) Both are available at EPA's SCRAM website
(http://www.epa.gov/ttn/scram/). EPA's primary resource for Agency air modeling information.(2)
At the SCRAM site, EPA maintains an up-to-date collection of the executable files, source
codes, and user guidance for EPA air quality models. The EPA Office of Air Quality Planning
and Standards maintains an on-line Air Pollution Training Institute (APTI) that is managed by
the Education and Outreach Group (EOG) and offers additional information and training
opportunities for air quality modelers.(8)
9.2.7 Examples of Air Quality Models
A variety of models are available for air toxics risk assessments, with some models having been
designed for specific air toxics application. The SCRAM website provides detailed information
regarding individual models, including software/code for each model, user's manuals, and other
support documentation.
The extent to which a specific air dispersion model is suitable for the evaluation of air toxic
source impacts depends upon several factors, such as the nature of the pollutant (e.g., gaseous,
particulate, reactive, inert), the meteorological and topographic complexities of the area, the
complexity of the source distribution, the spatial scale and resolution required for the analysis,
and the level of detail and accuracy required for the analysis. For example, steady-state Gaussian
plume models are not considered appropriate for downwind distances outside of the 0.1 km to 50
km range. Because of the assumption in Gaussian models of a steady wind speed and direction
over the entire modeling domain for each hour, a > 50 km distance may be inappropriately long
in many areas, especially where complex terrain or meteorology is present. In such cases, a non-
steady state model would be more appropriate.
Exhibit 9-3 provides an overview of the /C, ^ ,, „ ., ,, „ ,7T^ \7- \
r The Draft Guidance on the Development, Evaluation,
key physical processes simulated in the
most widely used air quality models
oriented toward assessment of risks from
facilities. Exhibit 9-4 shows the spatial
and temporal scales over which these air
quality models are typically applied.
Exhibit 9-5 identifies some common
applications for these air quality models.
and Application of Regulatory Environmental
Models recommends best practices to help determine
when a model, despite its uncertainties, can be
appropriately used to inform a decision. The
Knowledge Base (KBase) is a web-accessible
database of information on some of EPA's most
frequently used models. The draft guidance
recommends what information about models to
document, while the Knowledge Base is the
T^. , , , , /~i A-FT/"»TT/~I repository where this information is documented.
Finer scale models, such as CAL3QHC F J ^DCA/T • + + -+
Both products are available at the CREM internet site
at http://www.epa.gov/crem.
and CALINE4, are most typically applied
to exposure studies from mobile sources.
The UAM-TOX and CMAQ models are
examples of models which can simulate photochemically active air toxic species, including
secondary formation of pollutants like formaldehyde. Because the complex secondary formation
processes are nonlinear and can occur at locations distant from the emission source, these models
are designed to be applied to an exhaustive set of sources over a large region, rather than to
individual facilities or small groups of facilities. The models more typically applied to single or
April 2004 Page 9-12
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multiple facilities include SCREENS, ISCST3, ISCLT3, AERMOD, ASPEN, CALPUFF, and
UAM-TOX. Brief descriptions of these models are provided below. Some modeling studies
have combined the application of a regional model with a neighborhood-scale model in order to
address secondary and background concentration contributions, while capturing finer spatial
resolution for primary pollutant predictions.
SN
Community Multi-scale Air Quality (CMAQ) Modeling System
The CMAQ modeling system has been designed to approach air quality as a whole by including
state-of-the-science capabilities for modeling multiple air quality issues, including tropospheric ozone,
fine particles, toxics, acid deposition, and visibility degradation. In this way, the development of
CMAQ involves the scientific expertise from each of these areas and combines the capabilities to
enable a community modeling practice. CMAQ was also designed to have multi-scale capabilities so
that separate models were not needed for urban and regional scale air quality modeling.
The target grid resolutions and domain sizes for CMAQ range spatially and temporally over several
orders of magnitude. With the temporal flexibility of the model, simulations can be performed to
evaluate longer term pollutant climatologies as well as short term transport from localized sources.
With the model's ability to handle a large range of spatial scales, CMAQ can be used for urban and
regional scale model simulations. By making CMAQ a modeling system that addresses multiple
pollutants and different spatial scales, CMAQ has a "one atmosphere" perspective that combines the
efforts of the scientific community. Improvements will be made to the CMAQ modeling system as the
scientific community further develops the state-of-the-science. Additional information about CMAQ
. can be found at: http://www.epa.gov/asmdnerl/models3/cmaq.html.
V S
SCREENS
• Screening-level Gaussian dispersion model that estimates an hourly maximum ambient
concentration based on an average, constant emission rate (concentration results can be
scaled up to annual average using simple conversion factors as specified in EPA guidance;(4)
results are not direction-specific (i.e., wind direction is not taken into account).
• Data requirements are relatively low; uses site-specific facility data (e.g., stack height,
diameter, flow rate, downwash); does not use site-specific meteorology data.
• Data processing requirements are low; easy to use for quick assessment of a single facility.
• Model does not estimate deposition rates.
April 2004 Page 9-13
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Exhibit 9-3. Key Modeling Attributes of Some Widely Used Air Quality Models for Residual Risk Assessment
Modeling Attribute
Point
Volume
Area
Meteorology
Wet Deposition
Dry Deposition
Complex Terrain
Overwater Effects
Vertical Wind Shear
Building Down wash
Model Formulation
and Plume
Distribution
Chemical
Transformation
Relative Complexity
SCREENS
Yes
Yes
Yes
Built-in
worst-case
meteorology
No
No
Yes
No
No
Yes
Steady-
state,
Gaussian
None
Simple
ISCST3
Yes
Yes
Yes
Hourly (National
Weather Service)
or site-specific
equivalent
Yes
Yes
Yes
No
No
Yes
Steady-state,
Gaussian
Simple decay
Moderate
ISCLT3
Yes
Yes
Yes
Frequency
array of
meteorology
data
No
Yes
No
No
No
Yes
Steady-state,
Gaussian
sector average
Simple decay
Moderate
AERMOD
Yes
Yes
Yes
Hourly (National
Weather Service) or
site-specific
equivalent
Yes*
Yes*
Yes
No
Yes
Yes
Steady-state
Gaussian stable &
neutral conditions,
bi-Gaussian in
unstable conditions
Simple decay (SO2)
Moderate
ASPEN
Yes
Yes
Yes
Multiple hourly
observations
(National Weather
Service or site-
specific equivalent
Yes
Yes
No
No
No
Yes
Steady-state,
Gaussian sector
average
Difference between
precursor inert and
precursor decay
Moderate
CALPUFF
Yes
Yes
Yes
Hourly user-defined 3-
D fields, usually from a
meteorological model
with multiple
meteorological stations
Yes
Yes
Yes
Yes
Yes
Yes
Non-steady-state,
Gaussian puff
Simple psuedo-
first-order effects
Complex
UAM-TOX
Yes
Yes
Yes
Hourly user-defined 3-
D fields, usually from a
meteorological model
with multiple
meteorological stations
Yes
Yes
Yes
No
Yes
No
Non-steady-state grid
model
Complete chemical
mechanism for most
gas-phase toxics
Complex
*AERMOD version 02222 is now available for review and comment on EPA's SCRAM website (http://www.epa.gov/scram001/).
This version includes algorithms for dry and wet deposition as well as an improved downwash algorithm known as PRIME.
April 2004
Page 9-14
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Exhibit 9-4. Spatial and Temporal Scales of Widely Used Air Quality Models
Year -
_ Month
-------
Exhibit 9-5. Typical Applications for Common Dispersion Models
Screening Models
Refined Models
Averaging Period
Short Term
(1-24 hour average)
Long Term
(Monthly- Annual)
Short Term
(1-24 hour average)
Long Term
(Monthly- Annual)
Terrain
Type
Simple
Complex
Simple
Complex
Simple
Complex
Simple
Complex
Single Source
Rural
SCREENS
SCREENS,
ISCST3
ISCLT3
ISCST3
ISCST3,
AERMOD
AERMOD,
CALPUFF
ISCST3,
AERMOD
CALPUFF,
AERMOD
Urban
SCREENS
SCREENS,
ISCST3
ISCLT3
ISCST3
ISCST3,
AERMOD
AERMOD,
CALPUFF
ISCST3,
AERMOD
CALPUFF,
AERMOD
Multiple Sources
Rural
ISCST3,
AERMOD
ISCST3
ISCLT3,
ASPEN
ISCST3
ISCST3,
AERMOD
AERMOD,
CALPUFF
ISCST3,
AERMOD
CALPUFF,
AERMOD
Urban
ISCST3,
AERMOD
ISCST3
ISCLT3,
ASPEN
ISCST3
ISCST3,
AERMOD,
UAM-TOX
AERMOD,
UAM-TOX,
CALPUFF
ISCST3,
UAM-TOX,
AERMOD
CALPUFF,
UAM-TOX,
AERMOD
Industrial Source Complex - Long Term aSCLT3Va)
• Similar to ISCST3, but uses seasonal frequency distribution of meteorological inputs rather
than hourly data; runs more rapidly than ISCST3, but can only produce concentrations
averaged over a relatively long period of time; not considered as accurate as ISCST3.
• Unlike ISCST3, it cannot simulate wet deposition or complex terrain (terrain higher than the
stack height).
aEPA is no longer actively updating the model with improvements or additional capabilities. It still is one
of EPA's preferred models and can be used in appropriate situations. For most single or limited source applications,
the ISCLT3 model can be used without any overwhelming computational burden.
April 2004
Page 9-16
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AMS/EPA Regulatory Model (AERMOD)
• Replacement model for ISCST3 using new or improved algorithms on the parameterization
of the earth's boundary layer turbulence and state-of-the-science dispersion modeling;
deposition algorithms should be available soon.
• Like ISCST3, is a Gaussian formulated model.
• Similar to ISCST3, but includes dispersion algorithm for both convective and stable
boundary layers and allows plume penetration into elevated inversions.
• Incorporates new algorithms for building downwash.
• Unlike ISCST3, it simulates vertical profiles for wind, turbulence, and temperature.
• No wet or dry deposition (although planned future improvement).
• Requires surface characteristics as inputs (e.g., albedo, Bowen ratio, surface roughness),
which allow user to differentiate between different types of terrain.
ASPEN
• A Gaussian dispersion model used to estimate toxic air pollutant concentrations over a large
scale domain from regional to continental scale. (This is the model used for NATA risk
characterization analyses.)
• Employs a dispersion algorithm similar to ISCLT3.
• However, unlike ISCLT3, it includes treatment of wet deposition for particles, and more
detailed treatment of chemical transformation than ISCLT3 or ISCST3, although less detailed
thanUAM-Tox.
• In contrast to ISCLT3, ASPEN can utilize meteorological information from several locations,
and includes a simplified treatment of secondary formation of gaseous air toxics.
CALPUFF
• A Gaussian puff model designed for long-range transport (> 50km) assessment, but may also
be applied for near-source in situations with complex meteorology. As described previously,
a puff represents a continuous plume as a number of discrete packets of pollutant material.
• Has all the functional capabilities of ISCST3, but also includes capabilities for including
3-dimensional wind fields, vertical wind shear, and overwater effects.
• Not as extensively evaluated and tested as ISCST3 model.
• Requires a substantially higher level of air quality modeling expertise to use the model
(compared to ISCST3).
April 2004 Page 9-17
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UAM -Tox (Urban Airshed Model - Toxics Version)
• A three-dimensional, grid-type model used to model pollutants in urban areas. Derived from
the Urban Airshed Model (UAM), designed to calculate ozone concentrations under
short-term, episodic conditions lasting three to four days resulting from emissions of oxides
of nitrogen (NOx), volatile organic compounds (VOC), and carbon monoxide (CO).
• Simulates the most photochemically active air toxics (i.e., acetaldehyde, 1,3-butadiene, and
formaldehyde), as well as secondary formation of acetaldehyde and formaldehyde, tracking
primary and secondary fractions separately.
• Requires a substantially higher level of air quality modeling expertise to use this model
(compared to ISCST3).
9.2.8 Emissions from Soil
In addition to the air quality models described above, it is sometimes necessary to model
emissions of chemicals from soil. Emissions from soil may occur as a result of the volatilization
of chemicals from contaminated soil or as a result of the resuspension of study area soils.
Models that predict emission rates for volatile chemicals or dust require numerous input
parameters, many of which are study area-specific. For volatile chemicals, emissions models are
available from several EPA sources.(9) Emissions due to suspension of soils may result from
wind erosion of exposed soil particles and from vehicular disturbances of the soil. To predict
soil or dust emissions, a number of modeling approaches have been developed. These include
EPA's fugitive dust model for a site-specific assessment.(10) For road dust, other techniques are
generally used.(11) After emissions have been estimated or measured, air dispersion models can
be applied to estimate air concentrations receptor points.
In addition, chemicals in contaminated soils and groundwater may also evaporate into homes and
buildings through cracks in the floor. The models used to assess these types of exposures (often
called "basement models" because this type of problem can be exacerbated when a room is
buried in the contaminated medium) are commonly used by hazardous waste site cleanup risk
assessors to determine whether people living on or near contaminated sites are being adversely
affected by chemicals evaporating into their living or working spaces. This type of analysis is
less common for ambient air toxics risk assessment of the type that will generally be performed
in an urban setting or in the evaluation of source impacts on nearby populations. However, this
issue does come up on occasion and the topic is mentioned here for completeness.
One of the primary vapor intrusion models is the Johnson and Ettinger model
(http://www.epa.gov/oerrpage/superfund/programs/risk/airmodel/johnson_ettinger.htm). and
EPA has developed a users guide for evaluating vapor intrusion into buildings through the use of
this model (http://www.epa.gov/superfund/programs/risk/airmodel/guide.pdf).
Another chemical, radon, is also an issue for homes and buildings in certain parts of the country
(see Chapter 2). EPA's Indoor Environments Division (http://www.epa.gov/iaq/) provides a
comprehensive set of informational materials on risks associated with radon and mitigation
methods (see http://www.epa.gov/iaq/radon/pubs/).
April 2004 Page 9-18
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9.3 Air Quality Modeling Examples
EPA's Air Toxics Community Assessment and Risk Reduction Projects Database has been
compiled to provide a resource of planned, completed, and ongoing community-level air toxics
assessments across the country. The projects included in the database provide examples of the
applications of air quality modeling at real-world sites. Project descriptions and related
information can be obtained from the database website at:
http://yosemite.epa.gov/oar/CommunityAssessment.nsfAVelcome7OpenForm.
/"^
Additional Reference Documents
Although the list of following documents are now somewhat dated in terms of computational
limitations for application of the models, the documents do provide overall methodology and guidance
on procedures to consider when conducting air toxic modeling:
Guidance on the Application of Refined Dispersion Models for Hazardous/Toxic Air Releases,
USEPA/OAQPS, Research Triangle Park, NC, EPA-454/R-93-002, May 1993.
Air/Superfund National Technical Guidance Study Series, Volume V - Procedures for Air Dispersion
Modeling at Superfund Sites, EPA/OAQPS, Research Triangle Park, NC, February, 1994.
Dispersion Modeling of Toxic Pollutants in Urban Areas, Guidance, Methodology And Example
Applications, EPA/OAQPS, Research Triangle Park, NC, EPA-454/R-99-021, July 1999.
Guidelines on Air Quality Models. 40 CFR Part 51 and Part 52, Appendix W; Environmental
.Protection Agency, AH-FRL-5531 -6. ,
References
1. U.S. Environmental Protection Agency. 1999. Residual Risk Report to Congress. Office of
Air Quality Planning and Standards, Washington, D.C., 1999. EPA/453/R-99/001.
2. U.S. Environmental Protection Agency. 1994. Volume V - Procedures for Air Dispersion
Modeling at Superfund Sites. Air/Superfund National Technical Guidance Study Series.
Office of Air Quality Planning and Standards, Research Triangle Park, NC, February 1994.
Available at: http://www.epa.gov/scramOO 17tt25.htm#guidance. (Last accessed March 2004).
U.S. Environmental Protection Agency. 1999. Dispersion Modeling of Toxic Pollutants in
Urban Areas. Office of Air Quality Planning and Standards, Research Triangle Park, NC,
July 1999. EPA/454/R-99/021. Available at: http://www.epa.gov/ttn/scram/. (Last accessed
March 2004).
U.S. Environmental Protection Agency. 2003. Guideline on Air Quality Models. Federal
Register 40 CFR Part 51 Appendix W, April 15, 2003. Available at:
http ://www.epa. gov/scramOO 17tt25 .htm#guidance.
3. National Oceanic and Atmospheric Administration. 2003. Air Resources Laboratory.
Realtime Environmental Applications and Display sYstems. Updated December 12, 2003.
Available at: http://www.arl.noaa.gov/ready.html (Last accessed March 2004).
April 2004 Page 9-19
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4. U.S. Environmental Protection Agency. 1992. Screening Procedures for Estimating the Air
Quality Impact of Stationary Sources, Revised. Office of Air and Radiation. Research
Triangle Park, NC. EPA/454/R-92/019. Available at: http://www.epa.gov/ttn/scram/. (Last
accessed March 2004).
5. U.S. Environmental Protection Agency. 2004. Clearinghouse for Inventories & Emission
Factors. CHIEF Software and Tools. Updated March 2004. Available at:
http://www.epa.gov/ttn/chief/software/speciate. (Last accessed March 2004).
6. U.S. Environmental Protection Agency, Region 6. 2004. Air Modeling for Combustion Risk
Assessments. Updated February 5, 2004. Available at:
http://www.epa.gov/earth 1 r6/6pd/rcra_c/pd-o/comb_air.htm. (Last accessed March 2004).
7. U.S. Environmental Protection Agency. 1999. Dispersion Modeling of Toxic Pollutants in
Urban Areas, Guidance, Methodology and Applications. Office of Air Quality Planning and
Standards, Research Triangle Park, NC, July 1999. EPA/454/R-99/021. Available at:
http://www.epa.gov/ttn/scram/. (Last accessed March 2004).
8. U.S. Environmental Protection Agency. 2002. The Air Pollution Training Institute (APTI).
Updated August 22, 2002. Available at: http://www.epa.gov/air/oaqps/eog/apti.html. (Last
accessed March 2004).
9. U.S. Environmental Protection Agency. 1990. Air/SuperfundNational Guidance Study
Series. Volume II: Estimation of Baseline Air Emissions at Superfund Sites. 1990.
EPA/450/1-89/002a. Available at: http://www.epa.gov/superfund/resources/soil/part_3.pdf.
10. U.S. Environmental Protection Agency. 1988. User's Guide for the Fugitive Dust Model
(FDM) (Revised). EPA/910/9-88/0202R
11. U.S. Environmental Protection Agency. 2003. Emission Inventory Improvement Program,
EIIP Document Series - Volume IX. Updated February 11, 2003. Available at:
http://www.epa.gov/ttn/chief/eiip/techreport/volume09/. (Last accessed March 2004).
April 2004 Page 9-20
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Chapter 10 Assessing Air Quality: Monitoring
Table of Contents
10.1 Introduction 1
10.2 Air Toxics Monitoring: Recent Advances 2
10.3 Monitoring for Air Toxics Risk Assessments: Why Monitor? 4
10.4 Planning for Air Toxics Monitoring 9
10.4.1 General Planning Approach K)
10.4.2 Specific Planning Issues 14
10.5 Implementing Air Toxics Monitoring \9_
10.5.1 Locating Monitors and Selecting Sample Size 12
10.5.1.1 Locating Monitors 12
10.5.1.2 Selecting Sample Size 24
10.5.1.3 Setting Up a Monitoring/Sampling Program 25
10.5.2 Data Analysis and Reporting 2£
10.5.3 The Use of Monitoring Data to Calculate Exposure Concentrations 2_2
10.6 Monitoring Methods, Technologies, and Costs 3J_
10.6.1 Ambient Air Monitoring 33.
10.6.2 Sampling Costs 35
10.7 Archiving Air Toxics Monitoring Data 35.
10.8 Using Air Monitoring Data to Evaluate Source Contribution 37
References 38
-------
-------
10.1 Introduction
In environmental investigations, the term "monitoring" describes the collection of actual samples
of environmental media and then subjecting those samples (usually) to chemical analysis to
determine the identity and concentration of the various pollutants in the sample. A distinction
may also be made between sampling (i.e., stack testing) and monitoring (i.e., for ambient
concentrations). In air toxics risk assessment, this process commonly consists of collecting air
samples and either evaluating the samples at the monitoring station itself, or sending them to a
laboratory for evaluation.
For air toxics risk assessments, monitoring and analysis can help determine the concentration of
both those pollutants in air and those that have migrated into other media, such as soil, water,
sediments, and biota. This chapter discusses the use of monitoring to evaluate pollutants in air.
Chapter 19 discusses the use of monitoring in media other than air.
Many aspects of a monitoring program will depend on the spatial scale of the assessment being
supported by the measurement program:
• Micro-scale - highly localized regions up to 100 meters in size; these might reflect city
blocks or individual households.
• Middle-scale - regions of several blocks with sizes of 100 to 500 meters.
• Neighborhood-scale - an extended area with uniform land use (and, hence, relatively
homogeneous receptor population), extending up to several kilometers in size.
• Urban-scale - overall city or county conditions, perhaps up to 50 km in size.
• Regional- or national-scale - a state, several states, or the entire nation.
Air toxics risk assessments often examine exposure to relatively large numbers of people over
relatively large geographic areas (e.g., a neighborhood or urban area, county, or larger). In these
instances, the risk managers and analysts must carefully use their planning and scoping activities
to develop the questions they want to answer and identifying the types of data they will need to
answer those questions. For some questions and data needs, monitoring is the preferred tool for
estimating inhalation exposure concentrations for air toxics risk assessment, either as the primary
way of determining concentrations in air or as a way to test and normalize model results (and
look for gaps in the emissions inventory).
This chapter provides an overview of monitoring, including recent advances by EPA (Section
10.2); the reasons for monitoring (Section 10.3); how to plan a monitoring program (Section
10.4); implementation (Section 10.5); available air monitoring methods (Section 10.6); archiving
monitoring data (Section 10.7); and using monitoring data to evaluate source contribution
(Section 10.8).
April 2004 Page 10-1
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10.2 Air Toxics Monitoring: Recent Advances
EPA recently published a draft
National Air Toxics Monitoring
Strategy that describes the structure of
the national air toxics monitoring
program, including its history, status,
and expected products/1' At the start
of the program, EPA's focus was on
"nationally pervasive" priority
pollutants. In recent years, EPA has
initiated local scale monitoring studies
to address potential air toxics problem
areas.
EPA's air toxics monitoring is
structured into four groups - national
level, local scale, persistent
bioaccumulative toxics (PBTs), and
"other" EPA-specific programs.
• The National Air Toxics Trends
System (NATTS) program is a
network of monitoring stations at
EPA's Ambient Monitoring Technology
Information Center (AMTIC)
AMTIC (http://www.epa.gov/ttn/amtic/welcome.html) is
centered around the exchange of ambient monitoring
related information. Established in 1991 as an electronic
Bulletin Board System (BBS), AMTIC has evolved with
changing technology into a page on the World Wide
Web. AMTIC is operated by EPA's Office of Air
Quality Planning and Standards (OAQPS) through the
Monitoring and Quality Assurance Group (MQAG).
AMTIC contains information on all the Reference and
Equivalent methods for the Criteria pollutants, the toxic
organics (TO) Methods for air toxics and other
noncriteria pollutant methodologies, Federal Regulations
pertaining to ambient monitoring, ambient monitoring
quality assurance/quality control (QA/QC) related
information, information on ambient monitoring related
publications, ambient monitoring news, field and
laboratory studies of interest, and updates on any new or
developing EPA Ambient Air standards.
22 urban or rural locations across the country (see Exhibit 10-1). The focus for these sites is
on seven "nationally pervasive" priority pollutants (formaldehyde, arsenic, chromium,
benzene, 1,3-butadiene, acrolein, and light absorbing carbon). All of the stations are
expected to become operational in early 2004.
Local scale monitoring studies are designed to complement NATTS, but they are shorter-
term (less than 2 years) and have more flexible study requirements to go beyond the scope of
the NATTS. Local-level studies provide information of urban/local interest that is not
achievable with a single monitoring site at a city. For example, these studies may address
specific source categories or better characterize pollutant levels associated with different
locations in a metropolitan area. EPA plans to implement 10 to 15 local scale monitoring
projects that are implemented by state, local, and tribal (S/L/T) air pollution control agencies.
Programs that monitor atmospheric deposition of PBTs include (1) the National Atmospheric
Deposition Program - Mercury Deposition Network (NADP - MDN), a multi-agency
program with approximately 90 monitoring sites; (2) the Integrated Atmospheric Deposition
Network (IADN), a partnership between EPA and Canada, which is measuring PBTs in the
Great Lakes Region; and (3) the National Dioxin Air Monitoring Network (NDAMN), a 30-
site research program.
A variety of EPA Regional air toxics monitoring activities that existed prior to NATTS
continue.
April 2004
Page 10-2
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Exhibit 10-1. National Air Toxics Trends Stations (NATTS) Sites
January 2003 Startup
January 2004 Startup
Pilot Programs
Providence, RI
Roxbury, MA
New York, NY
Washington, DC
Decatur (Atlanta), GA
Hazard, KY*
Detroit, MI
Deer Park (Houston), TX
St. Louis, MO
Bountiful, UT
Grand Junction, CO*
San Jose, CA
Seattle, WA
Chittenden County, VT*
Rochester, NY
Tampa, FL
Chesterfield, SC*
Chicago, IL
Mayville, WI
Harrison County, TX*
Phoenix, AZ
La Grande, OR*
Barcelona/San Juan, PR
Providence, RI
Keeney Knob, WV*
Tampa, FL
Detroit, MI
Rio Rancho, NM
Cedar Rapids, IA
San Jacinto, CA
Grand Junction, CO*
Seattle, WA
* rural site
Source: EPA's Latest Findings on National Air Quality^'
EPA has encouraged a significant effort over the past few years to increase reporting of air toxics
sampling results to EPA's AirData database website (http://www.epa.gov/air/data). For example,
the Lake Michigan Air Directors Consortium (LADCO), the Northeast States for Coordinated
Air Use Management (NESCAUM), and the California Air Resources Board (CARS) "mined"
existing data from approximately 300 existing monitoring sites across the U.S. to provide
information about the spatial pattern, temporal profile, and general characteristics of air toxics
compounds. EPA collected additional data for this analysis from a year long monitoring study
carried out in four urban areas and six smaller city/rural areas. A number of reports, newsletters,
and related documents describing EPA's air toxics monitoring efforts are available at EPA's
Ambient Monitoring Technology Information Center website.(3)
April 2004
Page 10-3
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10.3 Monitoring for Air Toxics Risk Assessments: Why Monitor?
Air toxics programs have long used monitoring to evaluate the concentration of chemicals in air.
In general, monitoring (sampling and analysis) results may help:
• Identify and estimate current exposures to ambient concentrations of air toxics (outdoor
and/or indoor) at a specific location of concern (e.g., a school or neighborhood). As an
example, EPA tracks ozone concentrations at numerous locations around the country, with
results available over the Internet (http://www.epa.gov/airnow/) for many locations, virtually
in real-time. As another example, air toxics monitoring can be used to evaluate the impacts
of a specific source on a nearby receptor ("source-oriented" monitoring).
• Develop or refine values for specific parameters needed by air dispersion models (for
example, study-specific release data, meteorological conditions).
• Validate the predictions of a model in specified circumstances (e.g. validate that the location
of highest exposure predicted by the model is correct, which increases confidence that a
maximally exposed subpopulation has been identified - may be difficult to do without a very
dense monitoring network).
• Track trends in air quality levels (e.g. to determine whether air pollution programs have
generally been effective at reducing exposures).
• Identify gaps in emissions inventories (e.g., monitoring identifies an airborne chemical that is
not reported in existing emissions inventories) or close gaps that might be present in existing
data (e.g., concentrations of specific air toxics in specific releases).
• Determine compliance with air toxics legal requirements (e.g., permit limits at a factory,
emissions limitations on motor vehicles).
• Gather data in support of enforcement actions.
Ultimately, the choice of whether to monitor or model (or both) depends on the goals of the
assessment, the exposure setting, other specific project circumstances (e.g., many communities
want monitoring as part of a risk assessment), and the assessing entity. For example, to
understand the exposure an actual individual receives as they move about their daily activities,
personal monitoring is the best option because it reflects the pattern of this movement. However,
such studies are rarely done outside of research settings. As another example, compliance with a
permitted release rate may also require monitoring as the preferred method of measurement.
Exhibit 10-2 provides a brief comparison of modeling versus monitoring.
April 2004 Page 10-4
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Exhibit 10-2. Comparison of Modeling and Monitoring Approaches for
Estimating Ambient Air Exposure Concentrations (ECs)
Modeling
Monitoring
Modeling is relatively fast and inexpensive compared to
monitoring. Many screening-level models can be run in
spreadsheet formats and require relatively simple input
parameters. Many dispersion models, along with technical
reference manuals and other support documents, are
available for free download from EPA's Support Center
for Regulatory Air Models (SCRAM) website
(http://www.epa.gov/ttn/scram/). Resources normally need
to be expended to enhance the local air toxics emission
inventories to make air toxics modeling more precise.
With monitoring, it takes time to build data, and
there are methodological limits and logistical
issues. How expensive monitoring is depends on
what you are trying to do and how much you are
willing to pay. Monitoring does not always require
equipment purchase, and some states and local
areas already have equipment. Some less
expensive monitoring techniques are now available
(e.g., passive samplers).
Modeling results can estimate concentrations over a large
spatial area (e.g., a 50-km radius from a source) and can
provide a "big picture" view of the assessment area.
Modeling also allows for analysis of EC at multiple points
throughout the assessment area. The downside of
modeling, however, is that these are predicted
concentrations.
Monitoring results provide actual measured
concentrations. Multiple locations may be required
to characterize concentrations over an area,
although Geographic Information Systems (GIS)
methods facilitate interpolation between locations.
The downside is that the monitoring may not be
representative of a large geographic area.
Screening-level models can provide a predicted estimate of
whether significant concentrations are likely. A simple
screening analysis may be sufficient to make a risk
management decision that no action is required.
Monitoring can be used to identify and measure
exposures for specific individuals at a specific
location of concern (e.g., a school). This data can
provide a quick screen to determine whether more
extensive monitoring is needed.
Models can be used to identify areas where maximum
concentrations are likely to occur, and thus where to focus
efforts for additional tiers of the assessment. Uncertainties
in model parameters and the discrete division of the wind
field used in models (often with only eight wind directions)
can result in incorrect identification of the locations of
maximum concentration.
Monitoring can identify areas and actual levels of
exposure occurring at the monitoring sites.
Monitoring can also be used to indicate the point of
maximal exposure if the monitoring is designed for
that purpose. The selection of the monitoring
locations is critical; if placed in the wrong
locations, monitors can provide incorrect and
misleading information about maximal exposures.
Models can be used to identify the subset of chemicals of
potential concern (COPCs) and exposure pathways/routes
that have the greatest contribution to risk. This can be
helpful in focusing efforts for additional tiers of the
assessment as well as determining appropriate risk
management actions.
Monitoring can be used to confirm significant
exposure pathways and routes. (Measured
concentrations can be compared to risk-based
screening levels). It also can be used to identify
compounds that may not have been suspected and,
hence, were not included in models (i.e.,
monitoring allows identification of gaps in the
emissions inventory).
Models allow "what if scenarios to be evaluated (e.g.,
what if a permitted emission were doubled?).
Monitoring can only evaluate current conditions.
More complex modeling may allow explicit predictions
and estimates of variability in exposure.
A large number of samples generally is needed to
characterize variability; this may be prohibitively
expensive. Monitoring, however, provides a direct
and reliable means to characterize variability.
Models often use simplifying assumptions and data inputs
that may or may not be representative of the specific
assessment area. This introduces uncertainty into model
predictions.
Monitoring can be used to confirm actual exposure
levels, to investigate assumptions or calibrate
models to site-specific conditions, and to close gaps
in data, reducing uncertainties.
April 2004
Page 10-5
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Air toxics risk assessments, however, tend to examine potential exposures to hazardous air
pollutants (HAPs) and other air toxics for a relatively large number of people over relatively
large geographic areas (e.g., a neighborhood or urban area, county, or larger). In these instances,
the risk managers and analysts must carefully use their planning and scoping activities to develop
the questions they want to answer and to identify the types of data they will need to answer those
questions. For some questions and data needs, monitoring is the preferred tool. For others,
modeling is better. In general, most air toxics risk assessments will benefit from some
combination of both modeling and monitoring to provide the depth and breadth of information
that will be necessary to answer the assessment questions (see hypothetical example in Exhibit
10-3).
Exhibit 10-3. Hypothetical Example of a Combined Modeling and Monitoring Program
Monitoring
Location
S4
S3
O
O
S2
SI
West-East
This figure illustrates a hypothetical set of isopleths for annual average air concentrations that a
dispersion model predicted, assuming a single source (black dot) near the center of the geographic
region. Note that the model predicts the point of maximal exposure to be somewhere within the area
bounded by grid points 2, 4, SI, and S3, based on the existing information on release rate, wind
direction, and effective release height. In this hypothetical example, a monitoring station was used to
measure ambient concentrations as a means of evaluating the model predictions. Note that the
monitoring location is not in the area of estimated highest concentration and, therefore, might not
provide a better estimate of maximum exposure.
Indeed, most air toxics risk assessments that evaluate exposures to populations receiving impacts
from one or more sources should generally consider using modeling as their primary tool to
evaluate and characterize exposures and risks. In certain instances, assessors may use monitoring
as the primary tool to evaluate exposure concentrations for potentially exposed populations. The
utility of modeling for neighborhood and larger scale analyses is that it provides a better picture
of the variation of exposure conditions over the assessment area domain (i.e., modeling provides
spatial resolution) and allows a more straightforward approach to source allocation (i.e., what
portion of the risk is caused by each of the modeled sources).
April 2004
Page 10-6
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Monitoring, on the other hand, only provides estimates of concentrations at the point at which
samples are taken, and it is often difficult to clearly define the spatial coverage that those
measured concentrations represent. In addition, it is often difficult to use monitoring data for
source allocation (especially for chemicals emitted by numerous sources). Monitoring plays a
crucial role in identifying important chemicals that the emissions inventories may not have
captured. In rarer instances, assessors can use monitoring as the primary tool to evaluate
exposures for potentially exposed populations; however, this method carries a corresponding
increase in the uncertainty of the results (see Section 10.4 on how to use ambient monitoring data
to develop estimates of exposure concentration). (Note that, in limited circumstances,
geostatistical techniques such as kriging are sometimes applied to estimate concentration
variation between a set of monitors. This topic is beyond the scope of this reference manual;
however, assessors are encouraged to carefully consider the uncertainties associated with this
type of approach and whether alternate tools, such as air dispersion modeling, would provide a
better understanding of concentration gradients across the study area. In addition, the average
concentration of atmospheric pollutants across a study area is sometimes estimated by averaging
the results of all the monitors in the area. However, since pollutant concentration can change
rapidly across space and time, combining data across monitors may "average out" very important
information about exposure at a particular monitoring location. It is for this reason that
combining data across monitors is not commonly performed and assessors are encourage to
carefully consider the pros and cons of attempting such an analysis. If monitors are combined,
the results should, nevertheless, be reported alongside the results of each of the individual
monitors.)
If assessors make the choice to implement a monitoring program, it is important to carefully
design the sampling and analysis approach to provide meaningful input into the risk management
decision. Because sampling and analysis are relatively expensive and time consuming, a well-
designed monitoring program can ensure the efficient use of resources. Well designed and
implemented monitoring programs quantify not only the concentrations but also information
related to the associated data uncertainty. The study-specific conceptual model and analysis plan
that assessors develop during the planning and scoping phase help ensure a well-designed
sampling and analysis program that will yield results suitable for decision-making purposes.
Monitoring programs are commonly designed to:
• Use a sampling methodology that results in scientifically defensible data and that meets
regulatory criteria or other concerns - it is important to utilize methodologies that are
scientifically defensible and acceptable within a regulatory context;
• Identify and quantify air toxics (or their breakdown products) of interest with respect to
contribution to risk in all media of interest (including, in some cases, non-air media; see
Chapter 19);
• Attain quantitation requirements (e.g., quantitation limits) sufficient to compare to dose-
response values (e.g., the sensitivity should be sufficient to allow reliable measurements
below concentrations anticipated to produce adverse health effects);
• Demonstrate acceptable confidence in the data set to be used for decision-making based on
quality assurance benchmarks including benchmarks for precision, accuracy,
representativeness, completeness, and comparability; and
April 2004 Page 10-7
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• Provide for a clear and unambiguous data validation and reporting methodology so
monitoring results can be tracked, verified, and validated when they are used in decisions.
The design of a monitoring program that meets data quality objectives (DQO) and quality assurance
project plan (QAPP) requirements depends on the answers to four questions:
1. What is the risk management decision to be made, and how will assessors use
monitoring results in that decision? Monitoring programs typically are a component of
risk assessments that support risk management decisions; these decisions normally focus on
how best to reduce risks from exposure to air toxics through reducing or otherwise limiting
emissions.
Quality Assurance Project Plan (QAPP) and Data Quality Objectives (DQO) Process
As Chapter 6 introduced, a QAPP is part of the overall risk assessment analysis plan that ensures the
quality of data used in decisions. Generally included in the data quality program is the DQO process,
which establishes the criteria that must be met if data are to meet the needs of a decision-maker (e.g. it
establishes the error bounds on data, which are related in turn to the uncertainties a decision-maker,
can tolerate in reaching a defensible decision). Assessors can accomplish this goal through the
following seven steps:(a)
1. State the problem.
2. Identify the decision to be made.
3. Identify inputs to the decision (i.e., which data are needed).
4. Define the study boundaries (i.e., what factors, scenarios, etc., will be included in the study to
produce these data).
5. Develop a decision rule (i.e., how the data will relate to a specific decision to be made).
6. Specify limits on decision errors (i.e., how much uncertainty can exist and still allow a defensible
decision to be made).
7. Optimize the design of the study to ensure the data quality meets the decision rule.
The QAPP specifies precisely how to collect and analyze the data to meet the goals established by the
DQO process. The QAPP establishes specific procedures that assessors follow to meet DQOs. These
DQOs include procedures for identifying reliable methods, choosing sample locations and
frequencies, handling samples, calibration of equipment, recording and archiving of data, and analysis
of the data. The DQO goal is to ensure that all members of the project team understand, and follow,
procedures that will ensure the results of the study meet the data quality needs of a decision. Once
these DQOs have been established, it is necessary to develop a plan as to how the participants will
meet them in practice while collecting the data for the study.
(a)U.S. Environmental Protection Agency (EPA). 1994. Guidance for the Data Quality Objectives
Process, EPA QA/G-4, Office of Research and Development, EPA/600/R-96/055; available at
http://ww.epa.gov/swerustl/cat/epaqag4.pdf
April 2004 PagelO-i
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2. How accurately must the results be to be useful in these decisions? The reliability of
monitoring program results must be adequate for the needs of the risk management decision.
For example, risk assessors need to quantify air concentrations and/or exposures within some
bounds of accuracy and/or precision. It is important to meet these criteria of accuracy and
precision, but not necessarily to exceed them. As noted in Appendix H, the data quality
objectives must provide results that allow reliable decision-making. However, resources that
participants devote to one aspect of a monitoring program, such as choosing a larger number
of sampling sites, will draw resources away from another aspect of the program, such as
sampling for a larger number of air toxics. This is why it is essential to understand fully the
decision that the given set of results will support, other results that assessors will need to
support that same decision, and how participants can balance monitoring results across these
different data needs to reduce the levels of uncertainty to acceptable levels. Assessors can
achieve this goal by conducting a sensitivity analysis(a), which determines what aspects of a
full monitoring program will require the greatest attention and resources; monitoring results
that play the most significant role in a decision may require the greatest allocation of
resources.
3. What methodologies are available to monitor at a particular level of quality? The
choice of monitoring method depends on the specific air toxic(s) to be analyzed, the objective
of the monitoring (as the DQOs specified), the time over which a result is to apply, and
available resources. It is important to note here that there do not currently exist valid
methods (either field, lab, or both) for a large number of chemicals that may be of interest;
for methods that do exist, the achievable sensitivity may not match the DQOs (this is another
reason that modeling is often used as the primary decision making tool since these issues are
irrelevant to models).
4. What resources are available for the monitoring program? The choice of a monitoring
strategy often depends primarily on available resources (e.g., time, money). These factors are
of particular concern in air toxics monitoring because most studies of chronic exposure
generally require a minimum of one full year of data to characterize chronic exposure. It is
not uncommon to have a lag time of two years or more from the beginning of a monitoring
study to a final report when one considers the time it takes to plan the monitoring study,
obtain access to land, build the monitoring structures, run the study, analyze the samples,
validate the results, and write the data report.
10.4 Planning for Air Toxics Monitoring
As noted above, planning is a critical part of any air toxics monitoring program. The discussion
of planning below first describes a recommended general approach (Section 10.4.1) and then
outlines several specific planning issues (Section 10.4.2). EPA has developed resources that
provide additional details on operating procedures, with discussions of data quality issues,
definitions, and applications to specific methodologies/4'
aA sensitivity analysis shows the relative effect of uncertainty in each aspect of an assessment on the overall
uncertainty in that assessment. Ideally the data quality objectives will be more stringent for those measurements that
play a larger role in the final decision, since narrowing the uncertainty in these measurements significantly reduces
uncertainty associated with the decision.
April 2004 Page 10-9
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10.4.1 General Planning Approach
Planning an air toxics monitoring program involves a step-wise integration of sampling protocols
with data quality criteria and data analysis processes that are consistent with the study-specific
conceptual model (CM), QAPP, and DQO processes. Although presented step-wise, the process
is actually iterative, and decisions at one step may require verification or modification of
assumptions or decisions made at previous steps.
1.
4.
Understand the problem. As noted above, assessors may design monitoring programs to
support a number of different types of management decisions. For risk assessments, the CM
can focus participants' understanding of both the scope and the breadth of the problem that
the sampling and analysis are to address. The most important questions to answer
immediately are: whether assessors will use monitoring results to characterize exposure and
risk, whether they will use results to evaluate air quality model performance and look for
gaps in the emissions inventory, or whether they will use results for both reasons. This is a
critical question for participants to answer, because the data needs can be drastically
different, depending on how the assessors will use the monitoring data.
Identify existing data. Sampling and
analysis for risk assessment may not be
necessary if the information to be
developed is already available from other
sources and meets the quality
requirements for decision making. The
data sources discussed in Chapter 4 may
provide sufficient information for the risk
management decision.
Itemize data needs. Where existing data
are insufficient to answer the
study-specific questions, it will be
necessary to obtain new data through
monitoring. Potential data needs include:
filling gaps in emissions inventory data;
providing input data for models and
validating modeling results; generating new data to more fully characterize exposures in
areas, populations, or pathways; establishing trends over time; or supplementing a body of
data to increase their quality for the risk management decision. The process for itemizing
data needs includes articulating critical decision criteria (which may drive data quality needs
and/or selection of specific methods), applying these criteria to determine areas where
existing data are insufficient, and identifying the manner in which new data can supplement
existing data to meet the decision criteria. In many ways, the identification and enumeration
of data needs acts a bridge between the conceptual model and the DQO process.
Define data quality needs. The reliability (e.g., accuracy and precision) of monitoring
results must be adequate to meet the needs of the risk management decision. However, given
finite resources, even well-designed studies may not be able to achieve all quality criteria.
That limitation makes it important to determine which criteria are essential for addressing the
Examples of Study-Specific Questions
What is the maximum plausible value of EC
for the population in a geographic region,
taking into account spatial and temporal
variability and uncertainty?
What is the location of this maximal value
within the geographic region?
Which air toxics are found at the highest
concentrations with respect to their dose-
response values (e.g., which air toxics have
the greatest potential to produce a hazard
quotient above one)?
Do monitoring results generally agree or
disagree with the value of air concentrations
identified by existing models?
April 2004
Page 10-10
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study-specific decision problem and for focusing resources on meeting (and not necessarily
exceeding) those criteria.
The DQO process determines general data quality objectives to meet specific needs. This
process can be informed both by a well specified decision statement and by a sensitivity
analysis to determine which aspects of a full monitoring program will require the greatest
attention and resources to support that decision. Identification of data quality needs at this
level is targeted on the specific problem identified in Step 1, but is independent of the
specific methods to be applied. It is important to base data quality criteria at this step on
what is required to answer the problem identified in Step 1, not on impressions of best
available analytical methods, approaches used in the past, or consideration of questions that
might be of general scientific interest but are not of direct use in the decision problem. A
common approach is to consider all aspects of sample and data handling from collection to
data report writing, as these affect the confidence with which decisions can be made through
the introduction of random or systemic errors. A number of factors affect data quality,
including bias related to sampling error (e.g., taking only a single sample at one location,
which may or may not be representative of actual ambient concentrations) and relative
precision related to analysis methods.
5. Select monitoring methods to meet data quality needs. The choice of monitoring method
depends on the scale of the assessment, specific contaminant(s) to be analyzed, the sampling
time over which the result is derived (e.g., a sample collected over 15 minutes versus a
sample collected over 24 hours), the decision criteria or other reporting limit needs, and the
resources available (see Section 10.3). Methodologies include the sampling methods and
techniques, sampling program design (i.e, sampling frequency, coverage, and density), as
well as analytical methods. The data quality needs identified in Step 4 represent the total data
quality requirements of all aspects of the sampling and analysis process necessary to support
risk-based decision-making. Therefore, evaluation of all aspects of sampling and analysis
with respect to data quality needs is necessary for proper method selection.
The QAPP process involves balancing decisions for method selection to meet data and
quality needs. Selection of the methods for both sampling and data analysis defines the
approach and defines what is termed the measurement quality objectives. Although there is
a natural tendency to select sampling and analysis methods based on previous data, it is
important that the benefit of consistency and likely improved comparability are not
outweighed by data gaps that Step 3 identified. For example, in a risk assessment for
chlorinated volatile solvents, the presence of fiuorinated volatile solvents may cause
assessors to overestimate chlorinated concentrations due to analytical interferences. The
method selection generally takes into account the known or suspected presence of other
chemicals having similar toxic effects, symptoms, and mechanisms, and/or that which
otherwise may affect sampling and analysis results. To take this into account, the study may
require adding chemicals to the target analyte list, selecting a method where these compounds
are not potential interferents, or limiting the scope of the study with stated assumptions about
contributions from these undefined factors (e.g., stating only that the measured concentration
is the sum of a defined set of analytes and not applicable to any one analyte in the mixture).
April 2004 Page 10-11
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Detection Limits and Limits of Quantitation
The detection limit is the minimum concentration that an analyst can reliably expected to find (i.e.,
detect) in a sample, if it is present. For any given method (e.g., the method to analyze for volatile
organic compounds [VOCs] in air), this limit is established in each lab for each instrument and is
called the method detection limit or MDL. An MDL of 1 ng/m3, indicates that a field sample that
contains 1 (ig/m3 or below of contaminant will probably not be detected by the instrument in question.
The limit of quantitation (LOQ), on the other hand, is the minimum concentration for which the
analyst can reliably say that the substance is present in the sample and at a specific concentration
within some pre-established limits of precision and accuracy. If the limit of quantitation is 2 (ig/m3,
then measurement results above 2 (ig/m3 may be reported as not only indicating the presence of the
substance in the sample, but as indicating the specific concentration measured (i.e., positive
identification, certain concentration). Measurements between the MDL and the LOQ , indicate the
presence of the substance in the sample, but analysts can only make an estimate of the concentration
(i.e., certain identification, uncertain concentration). NOTE: It is common (but incorrect) to refer to
the quantitation limit as the detection limit. The LOQ, practical quantitation limit (PQL), estimated
quantitation limit (EQL), and sample quantitation limit (SQL; see below) are all limits of quantitation,
not detection. Thus, when one says "benzene was not detected at a detection limit of 5 fig/m3," this
most likely actually means "benzene was not detected; the limit of quantitation was 5 fig/m3."
Likewise, when a lab reports a measurement as "<5 fig/m3," this most likely means "not detected; the
limit of quantitation was 5 fig/m3." There is much confusion on this point and analysts must clarify
with the laboratory exactly what they mean in their lab reports (and what the analyst needs to have
reported to them for their risk assessment activities). For air toxics risk assessments, the MDL is
largely irrelevant for purposes of estimating exposure and the limit of quantitation is the critical
information that needs to be reported (see Chapter 7).
In establishing limits of detection and quantitation, it is
necessary to give the confidence level associated with the
detection limit and the limit of quantitation. In this figure, the
confidence level is 99 percent. The Limit of Detection (LOD) is
then the minimum concentration that has a 99 percent
probability of producing a result above background noise
(background is shown in the figure as a horizontal bar) using a
specific method. The LOD includes two considerations: an
instrument detection limit, accounting for variation in the
instrument when it is presented with repeated samples at the
same concentration, and additional variation caused by the need
] to sample, handle the sample, etc. (which can cause variations
— in the relationship between the concentration in the
environmental medium and the concentration presented to the
instrument). The LOD is the horizontal line in the bar marked A. Note that the range of variation of
results from a concentration at the LOD (shown as the bar marked A), and the lower end of this range
just barely avoids moving into the range of background variability.
c
o
I
•1"
E
3
LOD
LOQ
PQL
Background Variability
April 2004
Page 10-12
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Detection Limits and Limits of Quantitation (continued)
The LOQ assumes best practice in performing the measurements. It also is of interest to ask what the
LOQ would be using more common, routine practice. The Practical Quantitation Limit (PQL) is the
minimum concentration that has a 99 percent probability of producing a result above the LOD under
routine lab conditions (shown as the bar marked C). Under these conditions, the variation will be
larger than under ideal conditions, and so the PQL is higher than the LOD. Each lab must establish
these parameters for each method on each analytical instrument. When actual environmental samples
are evaluated on an instrument, the actual PQL reported for any given sample may vary (for example,
if a sample is highly concentrated and needs dilution before analysis, the resulting PQL for that
sample will be elevated by an amount proportional to the dilution). It is for this reason that PQLs
reported for actual samples are referred to as a sample quantitation limits or SQLs. When using
analytical monitoring data for air toxics risk assessment purposes, the MDL is irrelevant. The SQL is
the key factor in developing exposure concentrations (see Chapter 7).
Having established these terms, some system then is needed to "flag" results as being either usable or
unusable for the purposes of decision-making. For example, in the Superfund program,(a) results are
flagged "/?" if the data are unusable for some reason and "J" if the data fall between the SQL and the
MDL. A more thorough description of data qualifiers if presented in Appendix I.
(a)U.S. Environmental Protection Agency. 1992. Guidance for Data Usability in Risk Assessment (Part
A). Office of Emergency and Remedial Response, Washington, D.C. EPA Publication 9285.7-09A;
. available at http://www.epa.gov/superfund/programs/risk/datause/parta.htm. .
6. Develop systems to ensure that data meet decision requirements. Setting the objectives
and selecting sampling and methods capable of meeting the DQOs are the prelude to
determining whether and to what degree the data may support risk management decisions.
Having collected and analyzed the data, it will be necessary to determine whether decisions
can now be made with the desired confidence. For example, the actual data collected must be
assessed for quality and compared against any decision criteria such as toxicity dose-response
values. Where the quality is insufficient to support the decision (e.g., insufficient to
determine whether the benchmark is or is not exceeded), the previous steps may need to be
re-assessed.
It is also important to evaluate the contribution to uncertainty that is related to sample
collection and sample program design as well as analytical method uncertainty. Sampling
uncertainty is decreased when sampling density increases, however resource limits often
constrain sample density. Typically, errors in the collection of field samples are much greater
than errors introduced by preparation, handling, and data analysis; yet, most sampling studies
have devoted resources to assessing and mitigating laboratory errors. Ultimately, the proper
use of a QAPP that considers the entire process (sample collection through lab data reporting)
allows for evaluation of and reduction in uncertainty across all the activities of the
monitoring program, focusing resources on those aspects contributing most significantly to
uncertainty affecting decision-making.
April 2004 Page 10-13
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7. Develop documentation. The QAPP and other planning documents must record the results
of the environmental data collection design process. Information to be documented includes
the assumptions, findings, outliers, biases, data confidences, and other factors that are critical
to implementation, as well as evaluation and eventual interpretation of the data collected.
Data collected and analyzed is often reviewed thoroughly to ensure they are adequate to
support decisions; sufficient documentation allows such a review.
10.4.2 Specific Planning Issues
The design of the monitoring program also raises some specific issues:
• Select appropriate monitoring or sampling methods for the chemical(s) to be measured.
In general, it is important that the methods selected have the sensitivity needed to monitor at
concentrations likely to be of health and/or regulatory concern. At a minimum, the PQL or
SQL should be below any relevant health benchmarks (e.g., the human health dose-response
values discussed in Chapter 12). For some chemicals, the limit of the current technology may
not allow for a PQL or SQL that is below a health benchmark (or, that level may be reached,
but at a higher cost). In such instances, the planning and scoping team must decide how best
to balance resources to support data quality needs.
• Select appropriate monitoring sites, sample collection frequency, and length of
sampling time for the spatial and temporal variation of the scale being assessed and for
the objective of the air toxics monitoring being conducted. The way monitoring captures
this variation depends on the particular measure(s) needed to support the risk management
decision. For example, the monitoring goal might be to estimate the average long-term
exposure to people spread over a large geographic region (e.g., the average urban exposure
for a typical resident in a town). In this case, measurements spaced on a grid throughout that
region, or selected with a spatial density proportional to population density, may be
appropriate. On the other hand, if the goal is to identify or verify the maximum modeled
exposure or to perform a screening-level assessment in a population living down-wind from
an industrial source, sampling should be performed at the location likely to represent the
highest exposure, or in several different regions to identify the site representing the highest
exposure. Again, issues such as atmospheric photochemistry and differential settling of
metals are important considerations.
Assessors often make similar decisions when considering temporal variation. For example,
samples may vary over time due to fluctuations (e.g., emission rates from a facility may
fluctuate over time) or a systematic temporal trend (e.g., a facility might change its
production methods or products over time). In the former case, it is necessary to obtain
enough samples spread over a large interval of time to estimate the mean over the
measurement interval. In the latter case, the samples must be spaced in time so as to capture
the trend (i.e., a time-trend study must be performed). In addition, the objective of a study
may be to capture high short-term spikes in chemical concentrations. In this case, samples
collected over a 24-hour period may "dilute out" these spikes, and frequent shorter term
samples (e.g., collected over 15 minutes) maybe required.
April 2004 Page 10-14
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A recent evaluation of many of the issues regarding variability was recently published using
data from a wide range of monitoring sites throughout the United States (see also Exhibit
10-4).(5) These results support the conclusions that: (1) environmental variability is a more
important source of uncertainty than analytical uncertainty, emphasizing the need to carefully
select the location and timing of monitoring; (2) temporal variability dominates data
variability, emphasizing the need to not only carefully select the timing of monitoring, but to
ensure that results are properly averaged over relevant exposure periods; and, (3) analytical
uncertainty becomes a more significant contributor to overall uncertainty as ambient
concentrations approach background levels.
Most often, the monitoring efforts address the four main sources of variability in
measurements. These four sources are:
- Analytical. The same sample analyzed repeatedly yields different concentrations.
- Sampling. Duplicate samples collected using two identical monitoring devices from the
same location and time yield different concentrations. This type of duplicate sampling is
often performed to determine the precision of the method. In general, a minimum of 10
percent of the measurements in a monitoring program should be co-located to collect
duplicate samples.
- Temporal. Repeated samples at different times at the same location yield different
concentrations.
- Spatial. Samples from different locations at the same time yield different concentrations.
Ideally, assessors allocate monitoring resources in a manner that is consistent with the
relative contribution of these four sources to uncertainty. However, uncertainty may not be
evident prior to establishing the sampling program. Some insights on the relative
contributions can be obtained from the recent study of monitoring variability/5' but it
generally will be necessary to perform an analysis of the analytical uncertainty, the precision,
and the degree of spatial and temporal variability before a firm judgment of the relative
contributions can be made.
As noted previously, ambient air monitoring data may not provide a completely accurate
picture of exposure. There are several reasons for this limitation. First, air toxics monitors
usually are physically located to provide an estimate of air concentration at a specific
location. The assessor must then determine how representative the results are to populations
in the geographic area around the monitor. For some chemicals, monitoring results can be
reasonably representative, especially if the concentration does not show high levels of spatial
variability. For other chemicals, results may not be very representative at all, especially at
some distance from the monitor. In addition, because people move around outside, their
exposures are an average of the ambient air concentrations over the geographic regions in
which they move; this exposure may not correspond to the average at any particular
monitoring location. People also receive protection from the ambient environment, either in
vehicles or by moving indoors or through filters. Thus, ambient air concentrations measured
through monitoring and analysis can be taken as an indication of the potential for exposure at
a given location.
April 2004 Page 10-15
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Exhibit 10-4. Temporal and Spatial Sources of Variability in Formaldehyde Sampling
The foi
sequen
of vari
Original data, centered (variability = spatial + sampling + analytical)
2 -
1- ; : i =
"3T *
-§ ' ' '• * I "•
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"S* "5 • ! :
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V \\\v^ \s\\\\v\\\
Data with spatial component removed (variability = temporal + sampling + analytical)
2 -
1 - .
1 , . : 5 i = : .
"S . ; : i | * ; *
s ° • ; ; ! , • ; :
£ • . ' ' ! i ! I
"=" '• l '•
-i -
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3
\^ \\\Vx \\\\\\> \\\
ar graphs in this exhibit summarize the results of Bortnick and Stetzer,(4) obtained by
tially removing sources of variability. Note that the analytical variability is the smallest source
ability in this case, followed by sampling variability and temporal/spatial variability. Clearly in
April 2004
Page 10-16
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Exhibit 10-4 (continued)
3 -
2 -
i -
"3T
o>
1 o -
-1 -
this cas
since t<
sample
-2 -
-3
Data with spatial and temporal components removed (variability = sampling + analytical)
'- ' i = 5 f i - I i • ~ ! i « *
l i i i i i i i i i i i i i i i
N^ ^ \o \% \ \ **° \ \ \ \ %o "\^ \ % \-
3 -
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Data with spatial, temporal, and sampling components removed (variability = analytical)
i i i i i i i i i i i i i i i i i
>e, a choice of sampling focused on temporal and spatial contributions to variability is needed;
anporal variability dominated, primary attention would focus first on that component in each
d geographic region.
Page 10-17
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Follow and define standard operating procedures. Risk assessors follow and define
standard operating procedures both in the field (during sample collection and transport to the
laboratory) and in the laboratory (during sample analysis). Procedures include those related
to sample collection, sample transport, sample storage (including prevention of sample
degradation), and chain of custody procedures, as well as sample analysis, validation, and
data reporting. Procedures to identify potential problems are put in place. Periodic audits
(both field and lab) are commonly performed to ensure procedures are being followed and
that measurement and analytical devices are working properly.
Determine quantitation and compare limits. A common approach is to determine
quantitation limits and compare them against relevant decision needs, including health
benchmarks and likely environmental levels. These quantitation limits should be below the
health benchmarks and environmental levels to provide data of use in risk-based decisions.
Properly calibrate measurement processes. One way to ensure the accuracy of the method
is to properly calibrate measurement processes. To accomplish this, assessors perform
calibration on a time schedule shorter than the time needed for the equipment to "drift"(b)
further than is permitted under the criteria of accuracy and precision. It is for this reason that
it is essential that systems be re-calibrated periodically, on a schedule that is related to the
data quality objectives. In addition, it is desirable to cross-calibrate measurement methods by
comparing results from several individuals and labs. In an inter-laboratory comparison, split
and duplicate samples are submitted to several labs simultaneously, the results are collected,
and variation between labs are assessed. Ideally, sample analysis in a monitoring study
would be conducted at a laboratory that has participated in such an inter-laboratory
comparison and has been certified to produce results within acceptable data quality limits.
Adequately record and archive results. The best monitoring program can fail due to
improper record-keeping. A periodic, random check of the archived records (e.g., computer
files) is commonly made against "hard copies" to ensure the integrity of the process of
recording the data. The recording of all results, including a description of the QA/QC and
Data Quality Indicators, is essential because risk managers will use the results in their
decisions.
Match measurement intervals to the relevant modeling assumptions or health
endpoints. Different health effects require varying averaging time-periods. Cancer and
other chronic effects generally require averages over relatively long periods such as a year or
more (up to a lifetime). In this case, samples may be taken randomly or systematically
throughout the year, with the criterion of obtaining an accurate estimate of the mean. Acute
effects, however, require an understanding of the temporal variability over short periods of
time. For example, monitors need to measure benzene concentrations within shorter time
intervals (e.g., 15 minute, one-hour, 24-hour) for comparison with a health benchmark
reflective of the same time period.
"Drift" refers to the fact that monitoring systems that are calibrated generally change their electronic and
other characteristics in time, so the calibration factor also changes in time.
April 2004 Page 10-18
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• Ensure that temporal sampling reflects diurnal (time-of-day) and seasonal variability.
It is important to recognize that source terms and meteorological conditions can vary
systematically both over a day and throughout the seasons. Monitoring programs commonly
reflect this pattern, providing proper averages throughout a day (by sampling at selected time
points in a day) and between the seasons (by sampling in the different seasons).
In general, most monitoring schemes that are designed to attenuate and validate a model will
collect samples and analyze a relatively short list of "indicator compounds." If attenuation and
validation are the primary motivation for sample collection, it may not be necessary to measure
every compound being modeled, as long as it can be assumed that unmodeled compounds would
be expected to behave similarly. However, the amount and type of data collected in the
monitoring program designed to validate predicted model results should match the assumptions
of the modeling program. For example, if the goal of the modeling program is to estimate long
term (usually annual average) concentrations, then monitoring data must also be collected in
sufficient quantity to develop an annual average value to compare to the model results. (In
general, monitoring samples collected every six days for a year are required to develop a stable
estimate of annual average.)(2)
10.5 Implementing Air Toxics Monitoring
Implementing a monitoring program raises two issues in addition to the items above that relate to
planning for a monitoring study. These include selecting the actual location of monitors and
selecting methods for data analysis and reporting. Each is discussed in a separate subsection
below.
10.5.1 Locating Monitors and Selecting Sample Size
Determining the location of an air toxics monitor depends on a number of factors, including the
specific purpose of the monitoring (e.g., confirm modeled concentrations at a specific location,
estimate background concentrations), meteorological and terrain constraints, and the relative
magnitude and location of the source(s) of concern versus other emissions sources that might
contribute to measured air concentrations. For example, locations too close to a source may
underestimate exposure concentrations if the plume has not yet reached ground level where
people can come into contact with the contaminants. Locations too far from the source may also
underestimate exposure concentrations for large groups of people due to the dispersion that takes
place between the point of touch-down of the plume and the point of monitoring.
10.5.1.1 Locating Monitors
EPA's Quality Assurance Handbook for Air Pollution Measurement Systems^ provides a set of
consistent QA practices that will improve the quality of the nation's ambient air quality
monitoring data and ensure comparability among sites across the nation. Although these
practices were developed specifically for criteria air pollutants, they provide useful guidance for
air toxics risk assessments. Exhibit 10-5 summarizes some of the Handbook's guidance on the
relationship between topography, air flow, and the location of monitoring locations. The
following factors are usually considered when siting monitors:
April 2004 Page 10-19
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Perform measurements at locations that are representative of exposure. Determining the
location will depend on whether the goal is to quantify exposures in general, or exposures to
the maximally exposed individual. In the latter case, locations too close to a source may
underestimate exposure if the plume has not yet reached ground level where people can come
into contact with the contaminant. Locations too far from the source may also underestimate
exposure to large groups of people due to the dispersion that takes place between the point of
touch-down of the plume and the point of monitoring. Exhibit 10-3 above presented an
example of this issue. In that hypothetical example, the area of maximum concentrations
predicted by the air quality model falls somewhere within the area bounded by grid points 2,
4, SI, and S3. If the goal of monitoring is to verify these maximum concentrations, then the
ideal location for the monitor would be on the plume centerline at the exact point of touch-
down of the plume. However, if the goal of monitoring is to verify maximum concentrations
at the point of actual exposures, location at the site indicated in Exhibit 10-3 may be more
appropriate (measurements at the point of plume touch-down may overestimate maximum
actual exposure if there are no individuals within that area). It is essential to determine
whether monitoring will estimate exposures to existing individuals or to hypothetical
individuals who might move into currently unoccupied areas.
Exhibit 10-5. Relationships of Topography, Air Flow, and Monitoring Site Selection
Station Category
A (ground level)
B (ground level)
C (ground level)
D (ground level)
E (air mass)
F (source-oriented)
Characterization
Heavy pollutant concentrations, high potential for pollutant buildup. A site
3-5 m (10-16 ft) from a major traffic artery that has local terrain features
restricting ventilation. A sampler probe that is 3-6 m (10-20 ft) above ground.
Heavy pollutant concentrations, minimal potential for a pollutant buildup. A
site 3-14 m (15-50 ft) from a major traffic artery, with good natural
ventilation. A sampler probe that is 3-6 m (10-20 ft) above ground
Moderate pollutant concentrations. A site 15-60m (5-200 ft) from a major
traffic artery. A sampler probe that is 3-6 m (10-20 ft) above ground.
Low pollutant concentrations. A site > 60 m (> 200 ft) from a traffic artery.
A sampler probe that is 3-6 m (10-20 ft) above ground.
A sampler probe that is 6-45 m (20-150 ft) above ground. Two subclasses: (1)
good exposure from all sides (e.g., on top of a building), or (2) directionally
biased exposure (probe extended from a window).
A sampler that is adjacent to a point source. Monitoring that yields data
directly relatable to the emissions source.
Source: Table 6.5 of EPA's Quality Assurance Handbook for Air Pollution Measurement Systems(6>
When source location is the goal of monitoring, the siting of a monitor depends on the
meteorological conditions and the spatial locations of suspected sources. Again, the
hypothetical example in Exhibit 10-3 provides some insights. If the source is suspected to be
at the center of the geographic area, and if the wind direction is predominantly towards the
east (as it is in that example), the monitor or sampler would be located to the east of the
source and operated both at times when the wind blows towards the east and when the wind
blows in the opposite (or another) direction. Support for the claim that the source is located
April 2004
Page 10-20
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at the origin, and dominates exposures in the area around the monitor, would then be
strongest if the ambient concentration increases significantly when the wind blows towards
the east and drops significantly when it blows in other directions. If the data did not indicate
this effect, then the source is not at the center, or there is an additional, and perhaps more
significant, source in the area.
Take into account shielding and concentrating effects. Buildings, hills, and trees can have
shielding and concentrating effects. These effects may cause assessors to underestimate
exposure if either measurement sites are shielded from normal air flow or if these same
structures produce high concentrations downwind due to lee effects. Unless there is a pattern
of movement of people that make sites near buildings and other structures of particular
interest, assessors should perform measurements away from the influence of these structures.
It is particularly important to locate monitors away from such structures if the goal is to
locate sources, as the flow patterns for air are highly complex near these structures, greatly
complicating the ability to identify the source location from monitoring data.
Be aware that sources of air toxics from mobile sources (cars, trucks, etc.) can
complicate measurements of ambient air concentrations produced by stationary
sources. For the estimates of exposures from stationary sources, it may be preferable to
make measurements at locations away from roads. Monitoring should occur at distances
ranging from 3 to 61 meters from a major traffic artery (see Exhibit 10-5). These roads
provide, in a sense, a "background" level, or noise, above which the source must rise to
create a discernible signal. Of course, if total ambient exposure from all sources is to be
estimated, and the exposed population spends a significant fraction of time near roads, this
factor may be captured by selecting a sample of sites near those roads.
Make sure that the heights of monitoring and sampling devices are consistent with the
breathing zones of people when public exposures are being evaluated. This is generally
between 1 and 2 meters (the lower end being for children and the upper end for adults).
While less important for highly dispersed gases (i.e., gases with high diffusion coefficients),
this consideration can be important for heavy gases and particulates, which produce
significant vertical gradients of concentration.
Keep in mind that background concentrations can be difficult to determine. Although
background concentrations can be difficult to determine, it is important to estimate this factor
as accurately as possible at the location of measurement (see below for a discussion of
background concentrations). Unfortunately, even background levels can vary dramatically
over time and over a geographic area, and so assessors should exercise caution in using past
studies and studies from other geographic areas in establishing background for a
measurement location. Meteorological and pollutant source information must also be
carefully considered in selecting an appropriate background monitoring location. The
location must not be near major sources of the contaminant, or in the predominant down-
wind direction of those sources. The number of background samples should be determined
during planning/scoping/problem formulation stage, and be based on statistical testing criteria
specified in the DQOs.
April 2004 Page 10-21
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The choice of monitoring or sampling locations depends on the spatial scale of the assessment
being supported by the measurement program (i.e., micro, middle, neighborhood, urban,
regional, or national). Note that samples collected (generally) at the micro-scale, middle-scale, or
neighborhood-scale for the specific purpose of determining the impact of a source or co-located
groups of sources on a specific population are called source-oriented monitoring samples.
In each case, selection of sites for the monitoring program should consider whether:
• A mean value is needed for a region (in which case, the sampling must be sufficient to allow
interpolation of a surface concentration across that region, from which a mean may be
estimated, or a mobile monitor/sampler must be used while moving throughout the region).
• A mean value is needed for an area. In this case, the monitor would be placed so as to
capture the average of all the sources in the area (i.e., it is usually not oriented towards one
source).
• A maximum value is needed (for example, for a screening assessment or an estimate of the
maximum exposure to an individual from a particular source or co-located groups of sources;
in this case, the task is to identify a location as close as possible to this point of maximal
exposure).
• A distribution of exposures across the population in the region is needed, in which case
sampling might be performed across a region. Information on the number of monitoring
stations needed to perform this analysis with an acceptable level of accuracy/precision was
recently evaluated and discussed by the Lake Michigan Air Directors Consortium
(http ://www.ladco. org/toxics.html).
• A test of a model is being conducted (in which case the location is selected to provide the
most meaningful and unambiguous test of the model predictions under established source
term and meteorological conditions).
In all five cases above, it is important to determine compounds that might interfere with the
measurement of target compounds and, to the extent feasible, locate sampling devices in areas
where such interference is small (without compromising the need to cover a geographic region).
It also is important to establish one or more "background" and/or "control" locations so the
elevation of concentrations or exposures at sampling locations due to sources not located in the
assessment area can be determined.
In each case, site selection can improve through use of release data (source terms) and dispersion
models. An accurate estimate both of average exposures and distributions of exposure (i.e.,
concentration measured across different monitors) generally will require adequate sampling in
geographic regions characterized by the highest concentrations in addition to sampling in less
impacted areas. Since such regions may represent a small fraction of the area in the overall
study region, it may be necessary to "over-sample" in the highest exposed areas to ensure the
points of maximal exposure are not missed. This process might be accomplished, for example,
by sampling on a grid, with the grid density higher in the area surrounding the suspected point of
maximal exposure; this will be particularly important if initial monitoring/sampling indicates
high spatial variability in the area around the point of maximal exposure. For example, regions
April 2004 Page 10-22
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near known, large emissions sources, and downwind of the predominant wind direction, should
probably receive increased attention in sampling if a distribution of concentration is being
developed across a larger assessment area. If samples were taken only in relatively non-
impacted areas, the resulting distribution might not reflect the actual exposure of many area
residents. (Ultimately, this is one of the prime reasons for using modeling to evaluate exposure;
namely, that models can estimate exposure concentration at as many geographic points in a
assessment area as the analyst wishes and for which sufficient emissions inventory data and
computing power are available. Thus, modeling obviates these monitoring concerns.)
s s
Background and Control Samples
Background monitors are monitors that are place in the predominant upwind direction (relative to
sources) in the assessment area to measure the concentrations of the COPC in air that is moving into
the assessment area. The results of such monitoring is helpful in understanding the monitoring results
obtained in the assessment area; however, background monitoring results should not be subtracted
from assessment area monitoring results because of the uncertainties in the background monitor as a
truly representative measure of long term ambient background concentrations. Instead, EPA
recommends bar charts that compare contemporaneous concentrations of a chemical in a background
monitor to the same chemical at assessment area monitors; these charts provide a sense of the
potential influence of background concentrations on the assessment area.
Unlike a background monitor, which is located upwind of the assessment area, a control monitor is
located within the assessment area and is sited in such a way as to determine the average
concentration of all pollutant sources, once mixing has occurred (including chemicals blowing into
the assessment area from outside sources, mobile source emissions, and stationary source emissions
within the assessment area). Control monitors should be located away from direct influence of any
one or group of sources in the assessment area. Similar to background monitoring results, control
monitor results should not be subtracted from other assessment area monitoring results (or modeling
results). Instead, a simple bar chart comparison is usually adequate to compare the general "urban
soup" to more focused monitors.
For the case of model testing, random sampling is not required or even desired. Instead,
sampling is performed specifically in one or more locations where the conditions of emissions
and dispersion are well established, and where there are no interfering sources or compounds.
An ideal situation is a single, known source and a stable wind pattern during the period of
sampling. Even in such cases, however, it will be necessary to provide a sampling grid covering
the plume dimensions, since small errors in assigning wind direction can result in significant
differences between model results and measurements. By sampling at a variety of locations in
the plume, it is possible to adjust the model to determine whether a better fit might be obtained
by more accurate information on the wind field, effective stack height, and other parameters.
As part of the national-scale assessment component of the 1996 National-Scale Air Toxics
Assessment (NATA) activities, EPA compared monitoring to modeling results by using selected
locations and compounds (seven HAPs) throughout the U.S. (see
www.epa.gov/ttn/atw/nata/mtom_pre.html). The comparison goal was to assess the closeness of
modeling and monitoring results, which would expose the overall uncertainty in estimating
exposures. They found, for example, that modeled results generally underestimated results at
monitors when the modeling was performed to predict air concentrations at the precise location
April 2004 Page 10-23
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of the monitor; however, results were more comparable when the maximum concentration that
the model predicted was compared against the maximum monitor concentration, without the
requirement that modeling and monitoring be at the same location. These results indicate that
uncertainties in the modeling produced errors that shifted the location of the point of maximal
exposure, but not necessarily the magnitude of maximal exposure. A significantly more detailed
uncertainty analysis currently is underway, with results expected in 2004 (these will be available
at the NAT A website).
10.5.1.2 Selecting Sample Size
With respect to determining the quality of any estimates of mean concentration or exposure at a
location, the coefficient of variation (CV) should be calculated to determine the number of
samples needed to meet DQOs established by the decision problem. If a is the standard
deviation of a set of N measurements performed randomly throughout a geographic region and
randomly in time, and |i is the mean for that sample set, the value of CV is:
CV =
(Equation 10-1)
The target value of CV depends on the decision criteria establishing the needed accuracy of an
estimate of concentration or exposure, but a general target of less than 0.5 (50 percent) is
suggested and a value of 0.2 or less should be possible. (This discussion assumes that the
samples are representative of the geographic area and time period for which the average is being
calculated.)
The above calculation of CV requires knowledge of a and |i, which can only be obtained after
the sampling program has been underway. It is possible, however, to estimate a from an initial
guess of the mean concentration or exposure, |i, through regression functions such as those
established by Bortnick and Stetzer.(5) An example of such a regression is shown below based on
a scatter plot of data from benzene monitoring.
0.1
0.1
1 I
IB
1 ' I
HO
Aitul Arihnric Min
Note that a increases as |i increases. The authors use a lognormal relationship between a and |i:
April 2004 Page 10-24
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\ncr- \na+ \n^ or cf- aj2 (Equation 10-2)
They perform a weighted least-squares regression (solid line in the figure above) and obtain for
the case of benzene:
0.54
CV - J~N (Equation 10-3)
0.2//
The approximate size of N needed to produce the desired value of CV may then be estimated
from the above equation if an estimate of |i is available from either past monitoring data, similar
geographic regions, or models.
10.5.1.3 Setting Up a Monitoring/Sampling Program
While the design of a monitoring program will depend in many ways on the kind of monitoring
to be conducted, there are some general aspects of all monitoring programs that assessors should
consider. EPA guidance describes many of these issues in detail.(7)
The general aspects related to designing a monitoring program that supports risk assessment are
developed and written down in the planning, scoping, problem formulation phase (particularly,
much of the following information is included in the study-specific conceptual model and the
analysis plan and QAPP for monitoring activities). This activity involves three steps: (1)
identify the sources, including the contaminants, the concentrations, the timing and locations of
releases, as well as the hypotheses you want to test (e.g., whether a source exists, its relative
contribution to overall exposures, etc.); (2) determine the exposure pathways (which in the case
of air monitoring is inhalation and perhaps dermal absorption through immersion in air); and (3)
determine the receptors of interest, including any sensitive subpopulations, their locations, how
they are exposed, and relevant health benchmarks (e.g., lURs or RfCs). The conceptual model
can be used to identify where significant exposures are likely to occur to receptors of interest,
which in turn helps to guide the selection of monitoring sites. The following steps are then often
used to develop, conduct, and evaluate the results of monitoring:
1. Collect and review existing air monitoring information for the site. This information should
include data on concentrations, sources, locations of receptors, and other environmental data
(e.g., meteorological data) needed to guide decisions. The sources of these data will depend
on the location of the site, but a good start is to consider results from some of the national
monitoring networks.
2. Determine the level of sophistication needed by the monitoring program. This level is
established in the QAPP and the DQOs. The sophistication might range from simple
screening procedures (e.g., to determine whether there are any exposures of concern) to more
sophisticated methods intended to develop accurate maps of exposure across the region.
3. Develop a clear air monitoring plan, including determining the following: types of air
monitors (these depend on the compounds identified as being of interest); the number and
April 2004 Page 10-25
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location of monitors; the frequency and duration of monitoring, sampling and analysis of
samples; and any QA/QC procedures that must be in place to meet DQOs.
4. Develop a detailed, written plan for day-to-day activities related to how equipment will be
maintained and calibrated, and how to document results and QA/QC procedures. The data
maintenance plan should include development of a system of logbooks for entering data,
along with procedures to ensure the data are entered correctly and the logbooks are archived.
There should be a clear procedure for maintaining chain-of-custody for both the samples and
the logged results.
5. Evaluate the air monitoring results for their validity and reliability, including summary
indicators of data quality (e.g., the data qualifiers discussed elsewhere in this chapter), and
summarize these results so decision-makers can understand this quality and ensure the quality
meets decision needs. This evaluation should include a summary of the statistical procedures
used and the air concentration results, and an estimate of uncertainty in results deemed usable
by the analyst (including uncertainty due to monitoring equipment, handling of samples, and
sample analysis).
There are a number of specific issues that arise in Step 3 above that relate to the development of
the monitoring program. These issues are summarized here in roughly the order in which they
would be approached in developing a real program:
• Establishing sampling locations. Sampling may be
purposive, random, or systematic. Purposive sampling
refers to locating the monitor at a particular location
because that location is of special interest. While such
sampling can be useful to address specialized questions
(such as the impacts of a specific source, or the reliability
of model results), they generally are less useful for risk
assessment purposes, and care should be taken when
averaging the results along with results from the other
forms of sampling. Random sampling involves selecting
monitoring locations in a random and unbiased manner,
with no correlation between locations (other than,
perhaps, the fact that they are all in a defined region).
Assessors could establish locations by creating a grid, and
then randomly selecting the two coordinates (x and y) in
that grid. Random sampling has the advantage of well
established and relatively easy to apply statistical methods
for evaluating results, but runs the risk of missing some
"hot spots" of exposure. Systematic sampling involves
establishing a grid and placing monitors systematically on
the grid nodes. This ensures that sampling is uniform across an area, although statistical
analysis is more complex because the samples are not truly random. Exhibit 10-6 illustrates
common types of sampling programs.
There also are practical considerations in selecting locations, regardless of which of the three
procedures above is used. Monitors and samplers will require access to land, both in terms of
A typical monitoring station,
located at a site with easy
access, power, and protection
for the equipment
April 2004
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permission to locate the equipment and the ability to reach the site. It must also be possible to
provide electrical power, and some protection of the equipment against theft, vandalism, and
other disturbance; therefore, a fence may be needed.
Exhibit 10-6. Common Types of Sampling
Purposive
sampling
Are a estimated to
have highest
concentration
Grid
sampling
n
i .
1 :'
i
i "2
n
121
T'""
1-
l_i
1
T-
14
il,
v
p
i
f. :
1 ;
£
n
Random ^ / -:
sampling • Q .
.
Q '" "0
Purposive sampling focuses the sampling effort in specific locations (in this example, the area
estimated to have the highest concentration). Most air quality sampling is purposeful (i.e.,
monitoring stations are located in areas where monitoring is feasible (e.g., locations that are
accessible), areas of direct (e.g., maximum) impact, or where concerns about potential
exposures have been raised). Grid sampling consists of regularly-spaced samples in a
predetermined grid. Random sampling consists of samples in locations selected by chance.
Determining the types of equipment and samples. The sampling/monitoring method will
depend on the compound being sampled, as well as the need for grab samples or composite
(continuous) monitoring. See Section 10.6.1 for more detail on this issue.
Conducting field screening. Before establishing the monitoring site, it is useful to conduct
some limited screening of the region using relatively simply methods. This will help identify
locations likely to be of interest (e.g., likely locations of maximal exposure). If this isn't
possible, modeling results might be used. Guidance on this issue can be found in EPA's
Field Screening Methods Catalog.(K} These results generally should not, however, be used in
April 2004
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the risk assessment of chronic exposures because a small number of samples taken over a
short period of time will not provide an accurate estimate of long term exposure.
Accounting for temporal and meteorological factors. Sampling must account for the fact
that concentrations will fluctuate in time, in part because of meteorology (e.g., the wind
blows in different directions during the day, carrying the contaminant to different locations).
Where variability is high, a larger number of samples will be needed to achieve a desired
level of accuracy. The sampling program should include a full annual cycle covering the
seasons for a chronic exposure assessment. Where this is not possible due to limits on
resources, the sampling should at least include two temporal extremes (e.g., under windy
conditions blowing from major sources to the monitor, and under calm conditions). It is
essential to include the variability of the samples in any estimates of accuracy for the
monitoring location.
Field Blanks
A field blank is a clean sample, carried to the
sampling site, exposed to sampling conditions,
returned to the laboratory, and treated as an
environmental sample. Field blanks are used to
demonstrate that:
• Equipment cleaning has adequately removed
contamination introduced by sampling at
previous sites;
• Sampling and sample processing have not
resulted in contamination; and
• Sample handling and transport, lab transport,
and lab measurement have not introduced
contamination.
• Implementing QA/QC measures. It is
essential that well-established, clear and
documented methods for assuring the
quality and reliability of data be
developed. Many of these issues are
described in the text box on the QAPP
discussed in Section 10.3. A sampling
protocol must be developed detailing (1)
conditions under which samples are
collected; (2) how training of individuals
will be conducted; (3) how the precision
and accuracy will be ensured so results are
obtained reproducibly; and (4) the
analytical strategies that will be used to
ensure quantitation limits are met. ^ •/
Measures are also put into place to ensure
that samples are handled appropriately from collection through analysis (e.g., chain-of-
custody requirements, allowable sample holding times).
Sampling devices used to collect, store, preserve, and transport samples must not alter the
sample in any way that complicates analysis. Samples should be stored in a way that keeps
the concentration as close as possible to that in the field. QC samples must be collected,
stored, transported, and analyzed in a way that is identical to the treatment of site samples.
For example, both field and trip blanks, which are sampling devices that have not been used
for sampling in the field but otherwise are brought through all of the other procedures to
which field samples will be subjected, must be treated identically to the actual field samples.
These field and trip blanks provide information on the extent to which samples might become
contaminated by non-site-related materials during handling in the field (field blanks) and
subsequent transport back to the lab for analysis (trip blanks).
10.5.2 Data Analysis and Reporting
As Section 10.4.1 mentions, adequate data analysis, recording, and archiving is essential to the
design and conduct of a monitoring program. It is important that assessors enter each data point
April 2004
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into a file with relevant qualifiers, including location of sample; date and time of sample; method
of sampling and relevant operating characteristics (e.g., flow rate); transfer process; storage time;
analysis method; and identity of people performing all stages of the measurement. The integrity
of this database should then be assessed periodically by comparing a random sample of file
information against hard copies (e.g., laboratory books) to ensure reliability of transcription. For
results using a common methodology, there should be a record of several key aspects of the
method that assure reliability:
• A description of the calibration process, including certification of any standards used in that
calibration.
• Results of any inter-laboratory comparison of uses of the method, and certification that the
laboratory performing the analysis for the sampling program falls within a reasonable range
of these inter-laboratory results.
• A record of background levels and levels in blanks, allowing a comparison of these against
sample results.
• A summary of the frequency of "detects," or fraction of samples with values above the MDL
or SQL (see Exhibit 10-7). If this fraction is small and the chemical is thought to be present,
it may indicate that improvements in the method are needed. Of course, if the SQLs are well
below any health benchmark, a small fraction of detects or quantifiable results need not
trigger a call for improvements.
• A policy on significant digits and how these are related to the accuracy of the method. All
results should be reported only with a number of digits consistent with this accuracy. In
addition, rounding rules should also be established and followed.
• A description of how summary quantities such as means are calculated. This description
includes such factors as how outliers are identified and dealt with, the possible influence of
this process on sample mean and variance, and how results below the SQL are handled. For
example, some laboratories will report a chemical that they detect below the SQL as "not
detected" simply because it is below the SQL and they cannot accurately quantify it. Other
labs will report such a chemical as detected, but with an estimated concentration and qualify
the value as "J." In general, labs should report detected chemicals, regardless of whether they
can accurately quantify their concentration. The use of J-qualified data for risk assessment
purposes is described below.
• A detailed description of the QA/QC flags that are used by the lab to report data and a clear
description of how the lab deals with samples that are associated with blanks that are
contaminated.
10.5.3 The Use of Monitoring Data to Calculate Exposure Concentrations
As the above noted, monitoring data can, under limited circumstances, be used to estimate
exposure concentrations in the vicinity of the monitor. Some general rules that apply to this
activity are as follows:
April 2004 Page 10-29
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Data from different monitors should not be combined to estimate exposure concentrations
(with the exception of co-located duplicate monitors - see below).
Exhibit 10-7. Illustration of SQL and MDL
Positive detection, positive
identity, c ertain comcentratjon
(these are catted "detects")
Sample Quaatitatioa Lim &
(SQL)
•I
Positive detection, p ositive identity,
estimated c oncentration (these are
usually calfcd "J" values)
_ _ _ -i> Method Detection Limit
(MDL)
Literally "not detected,"
hut still may NOT he zero
People often refer to the SQL as the "detection limit." When a lab reports a result as "undetected" (U) or "not
detected" (ND), this is the level to which they are usually referring. The SQL is really a limit of quantitationthat
can vary between samples (the MDL, on the other hand, is a true "detection limit"). For example, a result of
"5U |Ig/m3" usually means "not detected at a sample-specific quantitation limit of 5 |-lg/m3." When a chemical is
detected, but below the SQL (i.e., a "J" value), risk assessors often use the J value as is (i.e., the J value is used
with no modification). When a chemical is not detected in a sample, but there is reason to believe it may be
present, even at very small amounts (e.g., the chemical is found in some samples, but not in others), risk assessors
often use Vz the SQL as a surrogate concentration for risk assessment purposes (in the example above, half of
"5U" is 5/2 = 2.5). It is usually not appropriate to use 1A the MDL as a surrogate for concentration for exposure
assessment purposes. The process of assessing and combining monitoring data for exposure assessment purposes
is discussed in more detail in Appendices H and I.
Monitoring data at a location are not generally used to describe variation of exposure
concentrations experienced by individuals in a population of people, although temporal
differences for the population as a whole (e.g., exposure to the population during the
winter versus exposure to the population during the spring) maybe appropriate.
Variation in exposure concentration within a population is preferably described by
looking at exposure concentrations across a set of monitors in the assessment area.
The representativeness of the exposure concentrations, as represented by any one
monitor's data, depends on the amount and quality of the data collected, and the
individual chemicals involved. For example, some pollutants may be "regional" in
nature, meaning that their concentration tends to be relatively homogeneous over a large
area. In that case, a given monitor may be broadly representative of ambient
concentrations throughout the region. Some compounds, on the other hand, show sharp
April 2004
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concentration gradients over space and the monitor may only be reflective of exposure
concentrations for people living very near to the monitoring station.
• To assess acute exposures with monitoring samples, the results from the individual
samples (not their average) should be compared to acute health benchmarks, and the
sampling time should match the averaging time of the acute health benchmark (see
Chapter 13).
• For chronic exposure assessment, all the valid samples collected and analyzed for a
monitor (taken routinely throughout the course of at least one year) are averaged (see
below) to provide an estimate of the long term exposure concentration.
Appendix I provides a general overview of how monitoring data should be evaluated, processed,
and displayed to develop estimates of exposure concentration.
10.6 Monitoring Methods, Technologies, and Costs
EPA has developed a number of methods to measure the concentration of air toxics in ambient
air. The majority of this information is found on EPA's Ambient Monitoring Technology
Information Center (AMTIC) website (Exhibit 10-8), and assessors involved in monitoring
should become familiar with this website and its contents. Given the breadth and scope of this
website's contents, it is not possible here to fully review all of the information here. This section
only provides an introduction to the methods. Appendix E summarizes relevant information
from two key EPA compendia of methods, primarily for ambient air monitoring. In addition, this
chapter does not examine indoor air measurements, as EPA has provided monitoring
recommendations only for radon.
EPA has developed a Compendium of Methods for the Determination of Toxic Organic
Compounds in Ambient Air to assist federal, state, and local regulatory personnel in developing
and maintaining necessary expertise and up-to-date monitoring technology for characterizing
organic pollutants in the ambient air (Exhibit 10-9).(9) The Compendium contains a set of 17
peer-reviewed, standardized methods for the determination of volatile, semi-volatile, and
selected toxic organic pollutants in the air. The Compendium, along with updates and addenda,
is available at EPA's AMTIC Website at http://www.epa.gov/ttn/amtic/airtox.html.
Exhibit 10-8. EPA's Ambient Monitoring Technology Information Center (AMTIC)
Information on ambient concentrations for a wide variety of compounds can be found through AMTIC
(http://www.epa.gov/ttn/amtic/welcome.html). This Center facilitates the exchange of ambient
monitoring-related information collected throughout the U.S., and can provide valuable insights into
the selection of monitoring methods. Established in 1991 as an electronic bulletin board system
(BBS), AMTIC has evolved with changing technology into a page on the World Wide Web. It is
operated by EPA's OAQPS through the Monitoring and Quality Assurance Group (MQAG). The
database contains information on all the Reference and Equivalent Methods for the criteria pollutants,
the toxic organic (TO) Methods for air toxics and other noncriteria pollutant methodologies, Federal
Regulations pertaining to ambient monitoring, ambient monitoring QA/QC related information,
information on ambient monitoring related publications, ambient monitoring news, field and
laboratory studies of interest, and updates on any new or developing EPA Ambient Air standards.
April 2004 Page 10-31
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Exhibit 10-9. EPA's Toxic Organic (TO) Monitoring Methods
Method
TO-1
TO -2
TO -3
TO-4A
TO -5
TO -6
TO -7
TO -8
TO-9A
TO-10A
TO-11A
TO-12
TO-13A
TO-14A
TO-15
TO-16
TO-17
Description
Method for the Determination of Volatile Organic Compounds (VOCs) in Ambient Air using
Tenax® Adsorption and Gas Chromatography/Mass Spectrometry (GC/MS)
Method for the Determination of VOCs in Ambient Air by Carbon Molecular Sieve Adsorption
and Gas Chromatography/Mass Spectrometry (GC/MS)
Method for the Determination of VOCs in Ambient Air using Cryogenic Preconcentration
Techniques and Gas Chromatography with Flame lonization and Electron Capture Detection
Determination of Pesticides and Polychlorinated Biphenyls in Ambient Air Using High Volume
Polyurethane Foam (PUF) Sampling Followed by Gas Chromatographic/Multi-Detector
Detection (GC/MD)
Determination of Aldehydes and Ketones in Ambient Air Using High Performance Liquid
Chromatography (HPLC)
Determination of Phosgene in Ambient Air Using High Performance Liquid Chromatography
(HPLC)
Method for the Determination of nitrosodimethylamine (NDMA) in Ambient Air Using Gas
Chromatography
Method for the Determination of Phenol and Methylphenols (Cresols) in Ambient Air Using
High Performance Liquid Chromatography
Determination of Polychlorinated, Polybrominated, and Brominated/Chlorinated Dibenzo-p-
Dioxins and Dibenzofurans in Ambient Air
Determination of Pesticides and Polychlorinated Biphenyls in Ambient Air Using Low Volume
Polyurethane Foam (PUF) Sampling Followed by Gas Chromatographic/Multi-Detector
Detection (GC/MD)
Determination of Formaldehyde in Ambient Air using Adsorbant Cartridge Followed by High
Performance Liquid Chromatography (HPLC)
Method for the Determination of Non-methane Organic Compounds (NMOC) in Ambient Air
Using Cryogenic Preconcentration and Direct Flame lonization Detection (PDFID)
Determination of Polycyclic Aromatic Hydrocarbons (PAHs) in Ambient Air Using Gas
Chromatography/Mass Spectrometry (GC/MS)
Determination of VOCs in Air Using Specially Prepared Canisters with Subsequent Analysis by
Gas Chromatography
Determination of VOCs in Air Collected in Specially-Prepared Canisters and Analyzed by Gas
Chromatography/Mass Spectrometry (GC/MS)
Long-Path Open-Path Fourier Transform Infrared Monitoring of Atmospheric Gases
Determination of VOCs in Air Using Active Sampling Onto Sorbent Tubes
April 2004
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10.6.1 Ambient Air Monitoring Methods and Technologies
The term "monitoring method" is a comprehensive term that includes everything from the sample
collection devices to analytical laboratory methods. These methods fall into three broad
categories related to the time scale over which concentration will be averaged:
• Grab samples provide a quasi-instantaneous measurement of a concentration. They
generally are obtained in the field usually over a period of 24 hours or less and then returned
to the laboratory for analysis. The sampling may be automated, allowing a time-series of
samples to be drawn, but all samples still are generally returned to the laboratory for analysis.
In rare instances, a mobile laboratory may be co-located with the sampling location, in which
more "real-time" data is possible.
• Continuous monitors provide a time series of measurements in the field, with a stream of
data at selected intervals (e.g., once each 24 hours). These monitors maybe fully automated
versions of grab sampling, taking samples at a set interval but then analyzing the samples
internally rather than returning to the lab. An alternative is a continuous flow monitors,
which draw ambient air through a chamber and analyzes it in real time (e.g., the
semi-continuous formaldehyde monitor developed by the EPA, which runs through one
complete cycle of sampling and analysis in 10 minutes).
• Time-integrated samples are collected over an extended period of time. Only the total
pollutant collected is measured, and so only the average concentration during the sampling
period can be determined. As with grab samples, these measurements generally are obtained
in the field and returned to a laboratory for analysis.
Monitoring methods/systems can also be divided into a different set of categories based on the
method of collection:
• Integrated air sampling devices use a pump to draw air continuously into the sample
chamber, over a reactive medium, or through a filter during a prescribed period of time; the
sample is returned to the laboratory for analysis.
• Direct-read monitors draw air through a measurement system and provide a direct reading
of the concentration without returning samples to the lab.
• Automated monitoring systems collect samples, perform the analysis, and report results at
regular intervals in the field.
• Air deposition monitors rely on deposition properties of compounds (e.g., particulates), and
may consist of active and/or passive, wet and/or dry sampling methods.
• Passive monitors allow the compound to diffuse into contact with an active material; these
generally are analyzed in the lab, although some indicate the presence of a compound by a
color change.
April 2004 Page 10-33
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• Grab sampling devices use an essentially instantaneous sampling method, such as an
evacuated chamber into which ambient air is allowed to enter at a fixed rate; the sample
collected is returned to the laboratory for analysis.
In some circumstances, grab samples may be collected by volunteers (for example, when
residents near an industrial complex organize to capture samples when a strong odor is present).
This process is commonly referred to as a "bucket brigade." Bucket brigades may provide useful
information that a problem may exist that warrants more in-depth evaluation. They are also
helpful, in some circumstances, to help the affected community become more involved in the air
toxics evaluation process. Nevertheless, care should be taken to ensure that all of the necessary
sampling and analysis protocols and QA/QC are established, understood, and followed by the
bucket brigade team members to ensure that the grab samples are of sufficient quality to be used
for decision making purpose at hand.
Mobile air monitoring platforms are sometimes used to evaluate air quality parameters. A
"mobile platform" can be anything from a VOC sampling apparatus on a movable trailer to a
sophisticated multi-pollutant sampling and analytical mobile trailer. The utility of mobile
platforms is that they can be moved from place to place relatively easily (e.g., for hotspots
analysis) and may only require a place to park the platform and an electrical hookup (as opposed
to the more difficult process of establishing fixed monitoring locations, which requires access to
land, often by establishing a leasing agreement, and permanent security measures, such as
fencing).
Exhibit 10-10. 33 Urban HAPs (Nationwide Basis)
acetaldehyde
acrolein
acrylonitrile
arsenic and compounds
benzene
beryllium and compounds
1, 3-butadiene
cadmium and compounds
carbon tetrachloride
chloroform
chromium and compounds
coke over emissions
1, 2-dichloropropane
dioxin
ethylene dibromide
ethylene dichloride
ethylene oxide
formaldehyde
hexachlorbenzene
hydrazine
lead and compounds
manganese and compounds
mercury and compounds
methylene chloride
nickel and compounds
polychlorinated biphenyls
polycylic organic matter
propylene dichloride
quinolene
1 , 1 ,2,2-tetrachloroethane
tetrachloroethylene
trichloroethylene
vinyl chloride
Compounds monitored in the NATA National Scale Assessment pilot
sites are indicated by italics.
Most existing air toxics
monitoring programs have
focused on the 188 HAPs, and
especially on the 33 urban HAPs
identified by OAQPS on a
nationwide basis (Exhibit 10-10)
as generally presenting the
greatest contribution to risk to
public health from air toxics in
urban areas. Note that the
highest-risk HAPs in a specific
region or community may differ
from this list. A significant
database exists on national
exposures to these compounds,
especially those monitored by the
National-Scale Air Toxics
Assessment (see Chapter 2 and
the website at
www.epa.gov/ttn/atw/nata). A
general starting point for most
monitoring efforts should be an
initial screening analysis to identify the COPCs. A description of the general process for
screening analyses of this type is provided in Chapter 1.
April 2004
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EPA has not developed methods for many compounds, including some of the 33 urban HAPs.
Potential deficiencies in particular monitoring methods include:
• Quantitation limits are not low enough relative to environmental levels and/or health
benchmarks;
• Lack of available standards for monitoring protocols (e.g., standards developed by the
National Institute of Science and Technology);
• Methods are not practical or easy to implement;
• Compound stability is so poor that the compound degrades significantly between the time it
is collected and the time it is analyzed, resulting in poor to no recovery at the time of
analysis;
• Recover efficiencies are too low, resulting in poor precision and/or quantitation limits that
are not low enough for use relative to health benchmarks;
• Methods have not been sufficiently tested in the laboratory and field;
• Methods are not producing results that are comparable to established methods; and
• Poor reliability.
The deficiencies noted in Exhibit 10-11 are particularly important and have been identified by
EPA as needing methodology development/10' Because they present a similar challenge, EPA
has targeted several VOCs for programs to improve monitoring capabilities (Exhibit 10-12). In
addition, both diesel exhaust (a complex mixture), acrolein, and arsenic require additional
method development to yield accurate, reliable, and field-tested monitoring methods.
10.6.2 Sampling Costs
There is no general guideline for the costs associated with monitoring programs, as they depend
on quite an array of factors. Several of the more critical include:
• Whether samples are analyzed "in house" or contracted out.
• Whether monitoring equipment is available or must be purchased or leased.
• The number of monitoring results or samples required (there is some economy of scale, but
increased numbers of results also increases cost).
• Whether personnel must be hired and/or trained.
• The potential cost of leases and insurance for monitoring sites.
• Laboratory analytical costs for special analytes. For example, dioxin samples can run as high
as $1,000 per sample, making an extensive dioxin sampling scheme generally out of reach for
most studies.
10.7 Archiving Air Toxics Monitoring Data
When appropriate, results of a monitoring program should be submitted to the relevant air toxics
database, such as EPA's Air Quality System (AQS).(11) The AQS website
(www.epa.gov/ttn/airs/airsaqs/sysoverview.htm) provides detailed information on submitting and
retrieving such data, including instructions on the file format for the data. Archived data may be
accessed at the AQS site.(12)
April 2004 Page 10-35
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Exhibit 10-11. Identified Deficiencies in Available Monitoring Methods
Compound
1,3 -butadiene
1 ,2-dibromoethane
1 ,2-dichloroethane
acrylonitrile
ethylene oxide
1 , 1 ,2,2-tetrachloroethane
arsenic and compounds
beryllium and compounds
mercury and compounds
acrolein
2,3,7,8-tetrachlorodibenzo-p-dioxin
Candidate Method
TO14A/15
TO14A/15
None/NIOSH 1614
TO- 15
10-3
None
10-5
None
TO-9A
Deficiency
sensitivity issue;
false highs
NIST standard needed;
recovery problems
poor storage stability
NIST standard needed
sensitivity issues;
filter contamination;
resource intensive
resource intensive;
XRF sensitivity issue
requires special equipment
TO-1 1A results in unstable derivative
poor recovery
resource intensive
Exhibit 10-12. VOC Compounds Needing Improved
Monitoring Methods
vinyl chloride
1,2-dichloroethene
dichloromethane
chloroform
1,2-dichloroethane
benzene
carbon tetrachloride
1,2-dichloropropane
trichloroethene
cis- and trans-l,3-dichloropropene
1,1,2-dichoroethane
1,2-dibromoethane
tetrachloroethylene
1,1,2,2-tetrachloroethane
hexachlorobutadiene
acrylonitrile
1,3-butadiene
ethylene oxide
April 2004
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10.8 Using Air Monitoring Data to Evaluate Source Contribution
Caution should be used in interpreting the
results of a measurement as being uniquely
associated with a given source. Most
measurements from monitoring data are,
depending on the chemical, a combination of
background concentrations and the same
chemical released from possibly multiple
sources. Benzene, for example, is present in
background air, is released from mobile
sources, and is used and released from
multiple types of stationary sources. This is
not to say that monitoring data cannot be used
to identify releases from a source. Under
certain circumstances, analysis of multiple
measurements at different locations may
indicate a spatial pattern consistent with the
known air dispersion pattern accompanying
that source (and inconsistent with the patterns
from other sources).
Use of Historical Monitoring Data
Historical monitoring data for an assessment area
may be of use in developing the analysis plan.
They can help with a range of uses, including:
• Identifying the types of chemicals that may be
present in the air;
• Selecting locations for monitors;
• Performing preliminary screening level risk
estimates; and
• Establishing acceptable monitoring protocols.
The utility of historical data will, of course, be
based on an assessment of the quality of the data.
For example, data that were not collected with
sufficient QA/QC, may not be useful for any of
the above purposes.
\ s
EPA also has developed "receptor models" which make use of monitoring data, together with
emissions inventories, to perform source apportionment analyses, which provide a quantitative
estimate of what percent of each pollutant comes from each identified source. EPA's Chemical
Mass Balance Model is one such example (available on EPA's SCRAM website at
http ://www. epa. gov/scramOO 17tt23 .htm). This model uses chemical concentrations measured in
samples from sources (emissions) and receptor locations to estimate the contributions of source
types to ambient air pollutant concentrations. The model is used primarily in the development of
State Implementation Plans for PM10. The model allows the user to select samples, chemical
species, and source types for modeling, calculate source contributions and their standard errors,
evaluate goodness-of-fit and validate the model results, prepare output documentation, and graph
results.
April 2004
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References
1. U.S. Environmental Protection Agency. 2004. National Air Toxics Monitoring Strategy,
Draft. Office of Air Quality Planning and Standards, Research Triangle Park, NC, January
2004. Available at: http://www.epa.gov/ttn/amtic/files/ambient/airtox/atstrat 104.pdf.
2. U.S. Environmental Protection Agency. 2003. Latest Findings on National Air Quality; 2002
Status and Trends. Office of Air Quality Planning and Standards, Research Triangle Park,
North Carolina. EPA 4547 K-03-001. Available at: http://www.epa.gov/air/airtrends
/2002_airtrends_final.pdf
3. U.S. Environmental Protection Agency. 2004. Technology Transfer Network Ambient
Monitoring Technology Information Center. Updated March 4, 2004. Available at:
http://www.epa.gov/ttn/amtic/airtxfil.html. (Last accessed March 2004.)
4. U.S. Environmental Protection Agency. 2003. Laboratory Operations and Quality Assurance
Manual. Science and Ecosystem Support Division, Analytical Support Branch, Region 4,
Athens, GA. January 2003. Available at: http://www.epa.gov/region4/sesd/asbsop
/asbsop.html
U.S. Environmental Protection Agency. 2003. Quality Assurance Management Plan for
Region 4. U.S. Environmental Protection Agency, Region 4, Atlanta, GA. May 2003.
Available at: www.epa.gov/region4/sesd/oqa/r4qmp598.html.
5. S. Bortnick and S. Stetzer. 2002. Monitoring Methods and Network Design. Air Toxics
Exposure Assessment Workshop. June 25-27', 2002. San Francisco, California.
6. U.S. Environmental Protection Agency. 1998. Quality Assurance Handbook for Air Pollution
Measurement Systems, Volume II, Part 1: Ambient Air Quality Monitoring Program Quality
System Development. Office of Air Quality Planning and Standards, Research Triangle Park,
NC, August 1998. EPA-454/R-98-004. Available at: http://www.epa.gov/ttn/amtic/files/
ambient/qaqc/redbook.pdf
7. U.S. Environmental Protection Agency. 1989. Risk Assessment
Guidance for Superfund, Volume I, Human Health Evaluation Manual (Part A), Interim
Final. Office of Emergency and Remedial Response, Washington, B.C., December 1989.
EPA/540/1-89/002. Available at:
http://www.epa.gov/oerrpage/superfund/programs/risk/ragsa/index.htm.
U.S. Environmental Protection Agency. 1989. Procedures for Dispersion Modeling and Air
Monitoring for Superfund Pathway Analysis (Volume IV of Procedures for Conducting Air
Pathway Analyses for Superfund Applications). Office of Air Quality Planning and
Standards, Research Triangle Park, NC. EPA/450/1-89/004.
8. U.S. Environmental Protection Agency. 1988. Field Screening Methods Catalog: User's
Guide. Office of Emergency and Remedial Response, Washington, B.C., September 1988.
EPA 540-2-88-005 (NTIS / PB89-134159) .
April 2004 Page 10-38
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9. U.S. Environmental Protection Agency. 1999. The EPA Compendium of Methods for the
Determination of Toxic Organic Compounds in Ambient Air. Center for Environmental
Research Information, Washington, D.C., January 1999. EPA/625/R-96/10b. Available at:
http://www.epa.gov/ttn/amtic/airtox.html.
U.S. Environmental Protection Agency. 1999. The EPA Compendium of Methods for the
Determination of Inorganic Toxics Compounds in Ambient Air. Office of Research and
Development, Washington, D.C., June 1999. EPA/625/R-96/01a. Available at:
http ://www. epa. gov/ttn/amtic/inorg.html.
10. Whitaker, D. 2002. New Trends in Monitoring Methods. Air Toxics Exposure Assessment
Workshop. June 25-27, 2002. San Francisco, California.
11. U.S. Environmental Protection Agency. AirData. About the AQSDatabase. Updated
October 3, 2003. Available at: http://www.epa.gov/air/data/aqsdb.html (Last accessed
March, 2004.)
12. U.S. Environmental Protection Agency. 2004. Technology Transfer Network Air Quality
System. Download Detailed AQS Data. Updated March 11, 2004. Available at:
http://www.epa.gov/ttn/airs/airsaqs/archived%20data/downloadaqsdata.htm. (Last accessed
March 2004.)
U.S. Environmental Protection Agency. 1999. 1997 Urban Air Toxics Monitoring Program
(UATMP). Office of Air Quality Planning and Standards, Research Triangle Park, NC,
January 1999. EPA-454/R-99-036. Available at:
www. epa. gov/ttnamti 1 /files/ambient/airtox/r99-03 6a.pdf.
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Chapter 11 Estimating Inhalation Exposure
Table of Contents
11.1 Introduction 1
11.2 Estimating Inhalation Exposure Concentrations 1
11.2.1 General Approaches for Deriving Exposure Concentrations 2
11.2.2 Common Ways to Estimate Exposure Concentrations 3.
11.3 Exposure Modeling 6
11.3.1 Inhalation Exposure Modeling 9
11.3.2 Microenvironment Concentration: How is it Developed? 12
11.3.3 Sources of Data for Human Activity for Inhalation (and other) Exposure Assessments
13
11.3.4 Examples of Inhalation Exposure Models 16.
11.3.5 Exposure Modeling Examples 12
11.4 Personal Monitoring 20
11.5 Exposure to a Population: Common Descriptors 22
11.6 Evaluating Uncertainty 22
11.7 Presenting the Results of an Exposure Assessment 23_
References 23
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11.1 Introduction
The previous three chapters discussed how to quantity exposure and release rates and estimate
chemical fate and transport. This chapter discusses the final step of estimating exposure. This
chapter will discuss inhalation exposure only. Unless persistent bioaccumulative hazardous air
pollutants (PB-HAPs) are present in source emissions, most air toxics risk assessments will only
estimate inhalation exposure concentrations. Limiting the exposure assessment this way is
possible because the dose-response values that characterize inhalation risk (e.g., reference
concentrations, inhalation cancer unit risk estimates - see Chapter 12) take into consideration the
complex physical and pharmacokinetic processes that influence how the chemical reaches the
target organ, which maybe a region of the respiratory tract or a remote site (see Chapter 12 for a
more detailed discussion). Specifically, other than exposure modeling to account for things like
time in different microenvironments and microenvironment concentrations, no adjustment for
other exposure parameters (e.g., body weight and inhalation rate) are warranted. For
multipathway risk assessments, however, where ingestion intake rate is the exposure parameter,
it will be necessary to consider parameters such as body weight and contact rate (e.g., amount of
soil ingested, fish eaten) for the indirect exposure pathway metrics of exposure (see Chapter 19).
Assessors determine human exposure to an environmental pollutant via inhalation by estimating
the concentration of that pollutant in the ambient air and the contact of an individual with that air
(along with the characteristics of the contact). Because concentrations in the air vary over space
and time, it is important to know where and how long people spend their time in relation to the
contaminated air under study. Through air quality modeling and monitoring, the ambient
concentrations of pollutants in air can be estimated geographically and temporally. Through the
use of exposure modeling, estimates of exposure via the inhalation route can be adjusted from
modeling data to take into account the demographics of people in the study area and the time they
may spend in various microenvironments.
The remainder of this chapter discusses how to estimate inhalation exposure concentrations for
the risk assessment (Section 11.2); exposure modeling (Section 11.3); personal monitoring
(Section 11.4); common descriptors (Section 11.5); evaluating uncertainty (Section 11.6); and
presenting the results of an exposure assessment (Section 11.7).
11.2 Estimating Inhalation Exposure Concentrations
The ambient air exposure concentrations (ECs) can be estimated using either (or both of) two
general methods: air quality modeling and air quality monitoring. As discussed in Chapter 9, air
quality modeling involves defining the pollutant sources and release characteristics and modeling
pollutant fate and transport (how the air toxic is transported, dispersed, and transformed over the
area of interest). As Chapter 10 discussed, monitoring involves measuring ambient
concentrations of chemicals. Because of the time/expense and other limitations associated with
monitoring (most notably, questions about representativeness), modeling is the most common
approach for estimating ambient air concentrations to be used in the air toxics risk assessment.
Monitoring is often used, instead, as a secondary tool to provide input data to the models and
validate the model results and to look for important gaps in the emissions inventory used to run
the model.
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11.2.1 General Approaches for Deriving Exposure Concentrations
There are two general ways to derive the EC for a given risk assessment (see Exhibit 11-1). Both
may incorporate the results of air quality modeling and/or monitoring efforts.
Exhibit 11-1. Two General Ways to Estimate Inhalation Exposure Concentration
100%
General Air Quality Assessment
Assessment Using Microenvironment Concept
The left-hand side illustrates the use of ambient air concentrations as a surrogate for the EC. In this
example, the analysis assumes that individuals spend 100 percent of their time at a given location, so
the estimate of ambient concentration thus represents the EC. The right-hand side illustrates the use of
exposure modeling. In this example, the analysis assumes that an individual spends 50 percent of
his/her time at home; 15 percent at a school; and 35 percent at an office. The EC is the weighted sum
of the product of the ambient concentrations at each location and the amount of time spent there. Both
indoor and outdoor concentrations usually are considered at each location.
Ambient Air Concentrations as a Surrogate. For screening-level evaluations, assessors
use the concentrations of air toxics generated at each modeling node (or interpolated nodes)
or the concentrations determined by a monitor (if modeling is not performed) as surrogates of
the inhalation exposure concentrations for the populations in the study locations. The default
assumption in such a screening assessment is that the population of interest is breathing
outdoor air continuously at the modeled or monitor location. This is believed to be a
conservative assumption since indoor air concentrations of air toxics are expected to be the
same or lower than the outdoor concentrations (when the indoor concentrations are produced
solely by inflow from outside air).
Exposure modeling. More comprehensive inhalation exposure assessments combine
estimates of ambient pollutant concentrations (e.g., from air quality models) with information
about the population of interest, including the types of people present (e.g., ethnicity, age,
sex), time spent in different microenvironments, and microenvironment concentrations. The
assessment objective is to identify a representative estimate of the pollutant concentration in
the inhaled air in each microenvironment and combine it with an estimate of the time spent in
different microenvironments (and the activities within these microenvironments) throughout
the daily routine of different groups of people with similar attributes (called cohorts).
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11.2.2 Common Ways to Estimate Exposure Concentrations
Risk assessors commonly use several different ways to estimate exposure concentrations. Some
ways are used primarily for screening-level (Tier 1) assessments; others are used primarily for
more refined assessments. Exhibit 11-2 illustrates several different ways to estimate exposure
concentrations when ambient air concentrations are used as surrogates.
• Monitoring locations. Sites where air monitors are located provide a direct measure of
ambient air concentrations at those locations. However, these locations may or may not be
representative of ambient air concentrations in other parts of the study area. If monitors are
not located where people live, the monitoring results may not be of much value for the risk
assessment other than to check the accuracy of modeling. Monitoring results may be used as
inputs to exposure modeling.
• Point of maximum modeled concentration. This is the modeling node where the maximum
modeled ambient air concentration occurs, regardless of whether there is a person there or
not. This generally provides a conservative estimate of exposure and could be used as the EC
in a screening-level evaluation (for example, using the SCREEN3 model). This point can be
used to provide an estimate of "high-end" exposure to the risk manager because, although no
one may actually be living there at the present, someone might move their in the future. This
point may be referred to as the point of the "maximum exposed individual (MEI)."
• Point of maximum modeled concentration at an actual receptor location. This is the
modeling node where the maximum ambient air concentration occurs to an actual person in
the area of impact, usually at an actual residence (or, if the residence falls between modeling
nodes, an interpolated value). To identify this point precisely, it is necessary to know
detailed information about the location of actual people in the study area. As with the point
of maximum modeled concentration above, this point can be used to provide an estimate of
"high-end" exposure to the risk manager (in this case, based on current actual exposures).
This point may be referred to as the point of the "maximum individual risk (MIR)."
Block Group/Enumeration District
Census tract/block internal point. The U.S. Census
Bureau provides information about populations in
geographic units called census tracts, which are subdivided
into block groups/enumeration districts and blocks. In
cases where there is only limited information about the
census tract (e.g., nothing is known other than the number
of people living within the tract), the Census Bureau's
"internal point" (sometimes referred to as a centroid) for
the tract typically is used as the point of exposure for all the
population in the tract. The internal point is a set of
geographic coordinates that generally represents the
approximate geographic center of a geographic subdivison
(see box on next page). The Census Bureau provides an
internal point for each of its geographic subdivisions (i.e., tracts, blocks, and block groups).
Note that the internal point is not population weighted (i.e., it is not located "in the direction
of where the people are").
Location = latitude
and longitude of
the centroid
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Exhibit 11-2. Illustration of Common Ways to Estimate Exposure Using Ambient Air
Concentrations as Surrogates for Exposure Concentration
i
o
2
100 meter modeling grid
In this hypothetical example, the risk assessors have modeled a release of a volatile organic HAP from a facility
using a computerized air quality model, and the ambient air concentration is used as a surrogate for the exposure
concentration (EC). The area of impact surrounds the facility and is generally greater in the direction of the
primary wind flow (and decreases in concentration with distance from the source). The model was set to make
estimates of annual concentration at 100-meter distances from the source in a rectangular grid pattern. The points
where the model makes estimates are called "modeling nodes" or "receptors." Note, however, that modeling
receptors do not necessarily coincide with actual people (who are also sometimes referred to as receptors) - that
is, there may or may not be a person at any given modeling node. There also is one monitoring site.
Knowing only the information displayed in the first version of the map (A), it is difficult to say much about
exposure since we do not know where the people are in relation to the facility or the area of impact. To remedy
this, our next step is to obtain demographic data (usually from the Census Bureau) and overlay it on the above
map. We may also have first-hand knowledge of exactly where people live in the vicinity of the of the facility
which we can also include on the map. Performing this analysis and redrawing the map gives picture B (next
page).
In the second version of the map (B), we have included the census tract boundaries (dotted lines) and we also
know from study area reconnaissance that there is an uninhabited national forest to the west of the facility, a
farmer (Mr. MacDonald) directly to the north, and a small town in the northeast. (Note that the town, Smallville,
actually can be further subdivided into smaller census blocks; however, they are not shown here to keep the
picture simple.) Now that we have a better idea of where people are in relation to the facility (and the area of
impact caused by the VOC release), we are in a better position to start making some statements about how people
are exposed. Some of the more common ways to characterize the exposures that may be occurring include:
1. Monitoring Site. The monitoring site is located in one of the higher parts of the area of impact, but it is
southwest of the facility and far from most of the area's populations. This monitoring site would not be
appropriate for describing exposure for the people of Smallville, but it could be used for people in the
immediate vicinity of the facility and to check the accuracy of the modeling.
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Page 11-4
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Exhibit 11-2 (continued)
B
a
a.
2. Point of Maximum Modeled Concentration. In this example, this point is located on the facility boundary,
where no one currently lives. This point is called the Maximum Exposed Individual or MEI which is defined
as the highest estimated risk to a hypothetical exposed individual, regardless of whether people are expected
to occupy that area.
3. Point of Maximum Concentration at a Location Occupied by People. In this example, this point occurs at
Mr. MacDonald's farm. This point is called the Maximum Individual Risk, or MIR, which is defined as the
highest estimated risk to an exposed individual in areas that people are believed to occupy. Actually, the
concentration used to represent Mr. MacDonald could be described using either an estimate of exposure at a
point (e.g., his house) or some other estimate of exposure for the larger farm if there were a good justification
for doing so (e.g., an average of all the farm's modeled points, since Mr. MacDonald spends much of his time
working around the farm).
4. Census Tract Internal Point. In this example, we could simply use the census tract internal point to
represent exposure for all people living in the census tract. This is sometimes used, especially when you do
not have any first-hand knowledge of the area (i.e., you only have general demographic data from the Census
Bureau). However, in this example the census track internal point would not be a very good estimate of
exposure concentration because it is higher in concentration than that experienced by most of the population
(i.e., the people of Smallville) and it is lower in concentration than that of the highest exposed person (i.e.,
Mr. MacDonald).
5. Census Block Internal Points. So far, this example has focused on characterizing an individual person's
exposure living at defined points within the study area (either a real person like Mr. MacDonald, or a
hypothetical person like the MIR). What if we wanted to know something more about how many people in
the study area are living at different levels of exposure? One way to do this is to develop a frequency
diagram that displays the exposure concentration at each of the census block internal points and identifies the
number of people living in that block (see below). This kind of representation is very helpful to the risk
managers because it gives them a sense of the range of exposures and the numbers of people living at
different levels of exposure. (In addition, the assessor may also choose to represent the exposure with
isopleths of risk (as in the above graphic) and by listing the approximate number people living within each
isopleth.)
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The internal point with the highest impact in the study area may also be referred to as the
point of maximum concentration at a receptor location, although it may not be as precise as
the example above where more local knowledge is applied to locate this point.
• Population-based approaches. Exposures may be evaluated by tracking individual
members of a population and their inhalation through time and space. Such analyses may
incorporate a user-specified number of simulated individuals or population groups (cohorts)
to represent the population in the study area. A cohort is defined here as a group of people
within a population with the same demographic variables who are assumed to have similar
exposures. In this approach, the exposure analysis process consists of relating chemical
concentrations in air (outdoor and/or indoor) and tracking the movement of a population
cohort through locations where chemical exposure can occur according to a specific activity
pattern. Population-based analysis is generally accomplished using exposure models (as
described in Section 11.3 below).
• Personal monitoring. Exposures may be estimated directly by placing monitors on
individuals, which allows collection of more detailed information specific to the exposure
pattern for that individual. Such monitors are referred to as personal monitors because they
provide information on exposure to that individual, rather than to the general area in which an
individual might be moving. Personal monitoring is discussed in Section 11.4 below.
Note that the units for the EC estimates are typically expressed in terms of micrograms (or
milligrams) of pollutant per cubic meter of air. For pollutants adsorbed to particles, inhalation
exposure estimates should be provided as the concentration of these pollutants on the particles,
not the concentration of the particles themselves.
11.3 Exposure Modeling
This section discusses exposure modeling, which uses the ambient air concentration estimates
along with information about the population of interest and information on how the pollutant
concentration can vary in different microenvironments to derive estimates of exposure
concentration over the period of exposure. Information on human exposure modeling for air
toxics can be found on EPA's Fate, Exposure, and Risk Assessment (FERA) website at
http://www.epa. gov/ttn/fera/.
For example, suppose an analyst uses the air quality model, ISCLT3, to estimate the annual
average concentration of benzene from a petroleum refinery at each census tract internal point for
every census tract within 50 km of the source (for illustration, assume this is 25 census tracts). In
a screening level analysis, the analyst may simply use the predicted ambient air concentration as
a surrogate for the population chronic exposure concentration of benzene at each of the 25
internal points.
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Internal Point or Centroid: Which is Correct?
When evaluating exposure to people in a given place, the modeled air quality at the "internal point" of
a geographic entity (such as a census tract or census block) is often used as a starting point to
represent exposure for the people in that geographic entity. According to the U.S. Census Bureau:
An internal point is a set of geographic coordinates (latitude and longitude) that is
located within a specified geographic entity. A single point is identified for each
entity; for many entities, this point represents the approximate geographic center of
that entity. If the shape of the entity causes this point to be located outside the
boundary of the entity or in a water body, it is relocated to land area within the
entity. In computer-readable products, internal points are shown to six decimal
places; the decimal point is implied. The first character of the latitude or longitude is
a plus (+) or a minus (—) sign. A plus sign in the latitude identifies the point as being
in the Northern Hemisphere, while a minus sign identifies a location in the Southern
Hemisphere. For longitude, a plus sign identifies the point as being in the Eastern
Hemisphere, while a minus sign identifies a location in the Western Hemisphere.
To illustrate how internal points are established, consider the following two examples. In census tract
A, the internal point (q) is simply the geographic center of the square. In census tract B, a river flows
along the western edge of the tract and makes a sharp bend towards the tract's eastern edge. In this
case, the "geographic center" of census tract B is actually outside the tract itself. Since the Census
Bureau requires that the internal point be within the physical boundaries of the geographic entity, the
Bureau physically moves the point into the tract, as shown (to a point that is no longer the geographic
center).
Note that the internal point is generally set to reflect the geographic center of the entity in question,
regardless of where people actually live in that entity. In other words, the point is not "population
weighted" (the Census Bureau does not provide population weighted internal points for census tracts
or block groups). Without population weighting, an exposure concentration estimated at the internal
point might not be representative of the concentrations to which persons living in the census entity
might be exposed. Analysts routinely modify the Census Bureau internal points for census tracts and
census block groups (using census block data) to locate them to a spot more representative of where
people are actually located within the geographic entity (e.g., a "population weighted" internal point).
Source: U.S. Department of Commerce, U.S. Census Bureau. 2000. Geographic Glossary (Census
2000). Available at: http://www.census.gov/geo/www/tiger/glossry2.pdf.
April 2004
Page 11-7
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However, a limitation of this is that each person in a census tract is not breathing air at the
ambient concentration continuously. There are a variety of reasons why this is so. For example:
• People come and go from the census tract for work, play, or travel. They may go to another
census tract in the vicinity with either a higher or lower concentration of benzene.
• People do not spend all their time outdoors (which is what our analyst has presumed in our
hypothetical example). In fact, most people spend most of their time (with some estimates of
about 90 percent) indoors. The chemical concentration of benzene may be higher or lower
indoors than outdoors.
• The benzene concentration throughout the census tract, in our example, is probably not
always the same as that at the internal point we selected (we have just assumed it was for
computational ease).
Exposure modeling was developed to try and help move an analysis into considering these
details. Thus, air quality modeling estimates how contaminated the air is in the different
locations within a study area. Exposure modeling simulates how different types of people
interact differently with that contaminated air to derive integrated (e.g., time weighted) estimates
of their exposure for the duration of interest.
This section focuses on exposure models to evaluate inhalation exposures. Exposure models are
also available for other routes of exposure as well (e.g., a model may be employed to track
patterns of food and drinking water consumption across a population). These indirect pathway
exposure models are discussed in Chapter 18.
The estimation of population exposure is a very difficult task because it requires information on
the activity patterns of the population as well as information on the air toxics concentrations
(indoor and outdoor) to which that population is exposed. Although several databases have been
developed to characterize activity patterns (see Section 11.3.3), various sources of variability
(e.g., among individuals and geographical regions) introduce uncertainty. Three main factors
affect the overall accuracy of exposure modeling:
• Uncertainties associated with indoor air toxics concentrations (note that most people spend
the majority of their time indoors);
• How well the subgroups (or cohorts) selected for analysis provide a realistic description of
the population composition in a given area; and
• Uncertainty and variability associated with the inputs and parameters of exposure models.
Exposure models can be formulated in a deterministic framework, where the value for each
input and output variable is characterized by a point estimate (i.e., a single value assumed to
apply uniformly). Alternatively, the framework may be stochastic or probabilistic, with one or
more input variables characterized by a frequency or probability distribution(a) (see Exhibit 11-3).
These terms are introduced and defined in Part VI of this Reference Library.
April 2004 Pagell-i
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If the input distributions represent variability^ across the population, the resulting output
distribution correspondingly represents the variability of exposures across the population. On the
other hand, if the input distributions represent uncertainty1^ about input parameters, the output
distributions will represent uncertainty about exposure levels. Some of the newer exposure
models address both variability and uncertainty separately (see Section 11.3.4).
Exhibit 11-3. Deterministic versus Stochastic/Probabilistic Approaches to Exposure Modeling
Deterministic Approach
Input parameters are
point es ti mates
Outputs are
point es titrates
Stochastic/Probabilistic Approach
Inputs
Outputs
In the Deterministic Approach, the
assessment assumes that each input
to the model is a specific number
(and the answer is a number).
In the Stochastic/Probabilistic
Approach, the assessment assumes
that the inputs to the model may be
specified as a distribution (and the
answer is a distribution).
Value of X
Value of a
11.3.1 Inhalation Exposure Modeling
Inhalation exposure is characterized by the pollutant concentration in the air (i.e., the exposure
concentration) reaching an individual's nostrils and/or mouth (in units of ug/m3). Estimates of
air concentrations from modeling or monitoring can be used in inhalation exposure modeling.
When derived from monitoring measurements, exposure concentrations are an aggregate of the
contributions from all emissions sources impacting the monitor. When derived from modeling
studies, the estimated exposure concentrations reflect only the sources that were included in the
modeling exercise. Models have an added benefit of allowing the analyst to determine the
contribution of a source to the estimated exposure concentration for any of the exposed
population groups. (Trying to determine "what source" contributed "how much" to a monitoring
result can be a challenging and perhaps impossible task, depending on the chemical and number
of sources in the study area).
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Lead Exposure Modeling
Lead (Pb) poisoning presents potentially significant risks to the health and welfare of children all over
the world today. The Integrated Exposure Uptake Biokinetic Model for Lead in Children (IEUBK)
attempts to predict blood-lead concentrations (PbBs) for children exposed to lead in their
environment. The model allows the user to input relevant absorption parameters (e.g., the fraction of
lead absorbed from water) as well as intake and exposure rates. Using these inputs, the IEUBK model
rapidly calculates and recalculates a complex set of equations to estimate the potential concentration
of lead in the blood for a hypothetical child or population of children (6 months to 7 years of age).
Measured or estimated blood-lead concentration is not only an indication of exposure, but also a
widely-used index for discerning future health problems. For additional information see
http://www.epa.gov/superfund/programs/lead/ieubk.htm. .
s /
Because air pollutant concentrations vary over time and space, inhalation exposure models
combine information on human activity patterns and microenvironmental concentrations to
estimate exposure concentrations. Activity patterns are defined by an individual's or cohort's
allocation of time spent in different activities in various microenvironments and various
geographic locations. A microenvironment is a defined space that can be treated as a
well-characterized, relatively homogeneous location with respect to pollutant concentration for a
specified time period (e.g., rooms in homes, restaurants, schools, offices; inside vehicles;
outdoors).
A common exposure model for inhalation that combines information on microenvironment
concentrations and activity patterns calculates a time-weighted average of all exposures from
the different microenvironments in which a person spends time during the period of interest:
(Equation 11-1)
* v ; /
where:
ECA = the adjusted average inhalation exposure concentration (ug/m3),
T = total averaging time (T = £ t^ years),
Cj = the average concentration for microenvironment y' (ug/m3), and
tj = time spent in the microenvironment y' (years).
Note that the two critical parameters that need to be evaluated in this equation are the
concentration of a chemical in a microenvironment and the amount of time spent in that
microenvironment. Exhibit 11-4 presents a simple example. General information on how
assessors go about obtaining such data is provided below. As a practical matter, most air toxics
risk assessments will not actually gather such activity pattern data for study-specific exposure
assessments. Rather, available exposure models have already incorporated much of this
information for use by the general risk assessment community. However, every model is
different and the data input requirements vary from model to model. Usually, assessors carefully
review each model's documentation before deciding to use it to determine if it will answer the
April 2004 Page 11-10
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question that needs to be answered and what resources would be needed to develop the required
inputs.
Exhibit 11-4. Simple Example of How to Estimate Exposure Concentration (EC)
for Exposure Modeling
EC. The following exposure profile has been developed for one year (which represents, for example,
the 30 years of "work") for a representative individual within the population of interest:
Duration Spent in Each
Microenvironment (% year)
10 = outside
50 = at work
40 = inside house
Average Concentration of Pollutant A
in Each Microenvironment (jig/m3)
80
20
10
The EC for that individual is calculated as:
EC = (0.1 x 80) + (0.5 x 20) + (0.4 x 10) = 22 ug/m3
Lifetime EC. To derive a lifetime exposure concentration for that individual, annual estimates are
combined as follows:
Duration Exposed to Each Annual
Concentration (no. years)
1 = newborn
4 = pre-school
12 = school
4 = college
30 = work
19 = retirement
Annual Average Concentration of
Pollutant A (ng/m3)
10
40
30
30
22
40
The Lifetime EC is calculated as:
Lifetime EC = (I x 10) + (4 x 40) + (12 x 3Q) + (4 x 3Q) +QQ x 22) + (19 x 40) = 30 ug/m3
70
Screening exposure estimate. One way to perform a screening level assessment using these data is to
set the EC equal to the highest air concentration modeled (e.g., 80 ug/m3 for annual adjusted or 40
ug/m3 for lifetime adjusted - see examples above) for all microenvironments. If the hazard and risk,
respectively, prove to be below acceptable risk values, the risk manager may conclude that no further
evaluation is necessary.
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11.3.2 Microenvironment Concentration: How is it Developed?
Microenvironments can be indoors (e.g., school, office, car, bus) or outdoors (e.g., filling station,
roadway). Indoor microenvironment concentrations are comprised of contributions from a
chemical in outdoor air penetrating the indoor environment and from indoor emission sources of
that same chemical (if indoor sources are within the scope of the analysis). They maybe derived
from direct measurements or estimated from modeling.
There are two common approaches to modeling indoor microenvironment concentrations. One is
the microenvironment factors method, where the outdoor contribution is estimated from the
outdoor concentration and a microenvironment factor that represents the ratio of the
microenvironment concentration to the outdoor concentration. Microenvironment factors are
typically derived from concurrent measurements of concentrations in the microenvironment
(containing no indoor emission sources) and outdoors. The indoor contribution is then added to
estimate the overall microenvironment concentration (when indoor sources are included in the
scope of the assessment). A general equation for the microenvironment factors method is:
C- = MjC0 + Cs (Equation 11 -2)
where:
Cj = concentration in microenvironment y
Mj = microenvironment factor for microenvironment y'
C0 = concurrent outdoor concentration
Cs = concentration contribution to the microenvironment y' concentration from an indoor
emission source
The second approach is the mass-balance method. The mass balance method typically assumes
that an enclosed microenvironment is a single well-mixed "box," although multi-chamber
configurations are possible. The time-varying concentration of an air pollutant in such a
microenvironment is estimated from several variables (see Exhibit 11-5). A general formulation
for the change in concentration in an enclosed microenvironment over time is:
d
dt
V — C, = pQC0 + S- JtC, - QC, (Equation 11-3)
Hf 3 J J
where:
V = volume of microenvironment enclosure
Cj = concentration in microenvironment y'
p = penetration factor (only applies to incoming air)
Q = air flow rate
k = pollutant removal rate (includes all types of removal, including atmospheric decay,
surface reactivity, surface adsorption, wall deposition, etc.)
C0 = concurrent outdoor concentration
S = indoor source emission rate
April 2004 Page 11-12
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The solution to this differential equation can be used to predict a time sequence of
microenvironmenty concentrations.
Exhibit 11-5. Illustration of Mass Balance Method for Modeling Indoor Microenvironments
Outdoor
Concentration
of pollutant (C0)
Pollutant
removal rate (k)
^i
^
Air flow rate (Q)
/
MICROEN
VOID
Micro
cones
of pol
Penetration
facto r(p)
^ + ~
VIRONMENT
me(V)
environment
>ntration
lutant (Cj)
Pollutant
emission rate (S)
Indoor
source
nf pollutant
11.3.3 Sources of Data for Human Activity for Inhalation (and other) Exposure
Assessments
Numerous EPA and related databases provide information useful for conducting exposure
assessments, including information on activity pattern and demographic information useful for
inhalation exposure modeling. Types of information included are human activity surveys,
standard values for physiological processes and consumption of food and water, measured
exposure data, health status surveys and measurements, nutrition surveys, and data on the spatial
distribution of populations. This section provides several of the more notable information
sources, some of which are important for inhalation exposure modeling, and some of which are
important for modeling exposures through pathways other than inhalation (e.g., ingestion of
contaminated fish, soil, and groundwater). Because they are so important for an understanding of
exposure, we introduce them here (even though the focus of this Chapter is on inhalation). We
will revisit many of these sources in Part III (Multipathway Exposure Assessment).
April 2004
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Indoor vs. Outdoor Concentrations
Indoor air concentrations may be an important consideration in an air toxics risk assessment.
Depending on the pollutant and the sources being assessed, concentration levels may be substantially
higher outdoors, in one or more indoor microenvironments, or inside vehicles. In general, pollutants
that have important indoor emission sources will have higher concentrations indoors than outdoors.
Important indoor emission sources include combustion sources, building materials, consumer
products, and occupant activities like cigarette smoking. Similarly, pollutants that are primarily
emitted by motor vehicles would be expected to have higher in-vehicle concentrations than at outdoor
locations distant from roadways.
Information that may be useful to the various methods used to estimate microenvironment
concentrations is available from studies involving measurements of indoor and personal exposure
concentrations. These include the following EPA studies:
• The Building Assessment, Survey and Evaluation (BASE) study, which was a cross-sectional
study of 100 buildings. Information relating to BASE is currently being updated to include basic
summary results from the 100 buildings studied. The raw data collected for the 100 buildings is
scheduled for release soon.(1)
• The Longitudinal Temporal Indoor Monitoring and Evaluation (TIME) Study in federal
buildings/1'
• The Los Angeles Total Exposure Assessment Methodology (TEAM) study,(2) which collected
concurrent indoor and outdoor samples of 18 VOCs for two consecutive 12-hour periods in 1987,
around 45 homes in February and 40 homes in July.
• EPA Consolidated Human Activity Database (CHAD). CHAD contains data obtained
from human activity studies that were performed at city, state, and national levels. CHAD is
intended to provide input data for exposure/intake dose modeling and/or statistical analysis/3'
CHAD is a master database providing access to other human activity databases using a
consistent format. This facilitates access and retrieval of activity and questionnaire
information from those databases.
The studies contained in CHAD cover a range of geographic areas. In addition to the
National Human Activity Pattern Study (NHAPS) with information about residents from 48
states, there are studies targeting residents of Baltimore, Cincinnati, Denver, Los Angeles,
Valdez, Washington DC, and the states of California and Michigan. Because the individual
studies differed based on what information was collected, not all fields in the CHAD
database are populated for all the records.
Each CHAD diary record consists of a 24-hour sequence of activities. Specified for each
activity is a start time, end time, duration, one of 113 location codes, and one of 145 activity
codes. Each diary record is tagged with a CHAD ID, which relates it to a record in the
demographic database identifying information about the subject of the diary. Demographic
fields include personal characteristics (age, gender, ethnicity, weight), social characteristics
(education, occupation, income), residential location (state, county, zipcode) and housing
characteristics (heating fuel, cooking fuel). In addition, CHAD has the capability to estimate
April 2004 Page 11-14
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the relative metabolic rate for each activity in a record using random sampling from
distributions derived from clinical studies.
• EPA Exposure Factors Handbook. The Exposure Factors Handbook provides a statistical
summary of the available data on various parameters and variables used in assessing human
exposure. This Handbook is used by risk assessors who need to obtain data on standard
factors to calculate human exposure to toxic chemicals. These factors include human activity
factors and residential characteristics. Recommended values are for the general population
and also for various segments of the population who may have characteristics different from
the general population. Included are full discussions of the issues that assessors may want to
consider in deciding how to use these data and exposure parameter recommendations. (The
Exposure Factors Handbook is in final form, but as new data become available updates will
be posted).(4)
• EPA Human Exposure Database System (HEDS). HEDS is a web-enabled data repository
for human exposure studies.(5) Its mission is to provide data sets, documents, and metadata
for human exposure studies that can be easily accessed and understood by a diverse set of
users. HEDS provides only data and accompanying documentation from research studies; it
does not provide interpretations. It allows a user to download documents for review or data
sets for analysis on their own computer system. Currently contained in HEDS are various
components of the National Human Exposure Assessment Survey (NHEXAS).
• National Human Exposure Assessment Survey (NHEXAS). The National Human
Exposure Assessment Survey was developed by US EPA's Office of Research and
Development (ORD) in the 1990's to provide information about multimedia and
multipathway population exposure to chemicals of various types. Phase I consists of
demonstration/scoping studies using probability-based sampling designs. Volunteer
participants were randomly selected from several areas of the U.S. These studies included
personal exposure, residential concentrations, and biomarker measurements. The Arizona
study measured metals, pesticides, and VOCs. The Maryland study measured metals,
pesticides, and polycyclic aromatic hydrocarbons (PAHs). The Region 5 study, conducted in
Ohio, Michigan, Illinois, Indiana, Wisconsin, and Minnesota, measured metals and VOCs.
Researchers worked with the participants to measure the level of chemicals in the air they
breathed, in the foods and beverages they consumed (including drinking water), in the soil
and dust around their homes, and in their blood and urine. Participants completed
questionnaires to help identify possible sources of chemical exposure. Sample collection
occurred between 1995 and 1997. The confidentiality of participants is strictly protected.
Information about the studies can be found in the related study entries in EIMS and in the
Journal of Exposure Analysis and Environmental Epidemiology.^
• CDC National Health and Nutrition Examination Survey (NHANES). NHANES is a
survey conducted by the National Center for Health Statistics (NCHS), Centers for Disease
Control and Prevention.(7) This survey has been designed to collect information about the
health and diet of people in the United States. NHANES is unique in that it combines a home
interview with health tests that are done in a Mobile Examination Center. The current
NHANES is eighth in a series of national examination studies conducted since 1960. The
results of these surveys are compiled in databases and summarized in a variety of tables and
reports. Data from direct examination, testing, and measurement of national samples of the
April 2004 Page 11-15
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civilian noninstitutionalized population provide the basis for (1) estimates of medically-
defined prevalence in the US and the distribution of the population with respect to physical,
physiological, and psychological characteristics, and (2) analysis of relationships among
various measurements without reference to an explicit finite universe of persons. Reports
also present information about dietary patterns in various segments of the US population.
• U.S. Census Data. The U.S. Census provides data on the spatial distribution of population
and population subgroups at several geographic levels: national, state, county, tract, block
group and block. (For detailed analysis, Summary File 3 is most useful.) Examples of useful
spatially-resolved data for exposure assessment include: population by age, gender, and
ethnic group; house heating fuel use; estimated travel time to work by various modes of
transportation; and levels of employment in various industries. Associated geographic data
specifying boundaries of the various geographic entities for mapping are also available in
Topologically Integrated Geographic Encoding and Referencing (TIGER) files.(8)
• LandScan USA. LandScan is a high resolution population distribution database for the
continental U.S. currently under development, following the methodology used to create a
similar global database called LandScanl998 (updated in 2000).(9) LandScan uses satellite
imagery in population distribution modeling to produce population distribution data at a
much finer resolution than previously available. LandScan 1998 and 2000 have a grid cell
size of 30 seconds (<1 kilometer) and use census data in combination with many other
geospatial data, such as land use/cover, topography, slope, roads, and nighttime lights, in
order to improve the estimation and prediction of the spatial distribution of residential
populations. Future LandScan updates will use a much smaller grid cell size of 3 seconds
(<100 meters). Currently, a pilot study in a 29 county area in southeast Texas (around
Houston and Port Neches) is being conducted. LandScan will be very useful for exposure
modeling, environmental justice studies, and other types of risk assessments.
11.3.4 Examples of Inhalation Exposure Models
Several exposure models have been or are being developed by EPA and others for a variety of
purposes. Some of the important characteristics that vary among the models include:
• Ambient concentrations
- Modeling or monitoring estimates
- Time scales (e.g., averaging time)
• Exposure concentration time scale
- Time increment for calculations (e.g., by minute, hourly, seasonally, annually)
- Averaging time for reporting (e.g., hourly, annually)
• Spatial scale
- Geographic resolution of predictions (e.g., Census tracts, Census blocks, grids)
- Potential size of modeling domain (e.g., neighborhood, county, nation)
• Population activity data
- Type (e.g., time in microenvironments, commuting locations, food and water ingestion
rates)
April 2004 Page 11-16
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- Temporal resolution (e.g., by minute, hourly, seasonally, annually)
- Area specific resolution (e.g., national or regional)
- Demographic resolution (e.g., by age, gender, or ethnic group)
• Framework
- Deterministic: inputs and outputs are characterized as point estimates
- Stochastic or probabilistic: inputs and outputs are characterized as distributions
representing variability and/or uncertainty, Monte Carlo techniques are used to randomly
select input values from the distributions for repeated simulations
The remainder of this section provides brief descriptions of some of the most recently developed
inhalation exposure models. The features of each model described are summarized in Exhibit
11-6.
Exhibit 11-6. Comparison of Inhalation Exposure Model Features
Model
HEM-3
HAPEM
TRIM.Expo
(a.k.a. APEX)
CPIEM
Population
Activity Data
none
(screening model)
micro-environment
time/sequence,
commuting
micro-environment
time/sequence,
commuting
micro-environment
time/sequence,
commuting
Source of Ambient
Concentrations
ISCST3
external model or
monitoring data
external model or
monitoring data
external model or
monitoring data
Spatial Resolution
census blocks
(additional points
can be specified)
census tract
depends on
resolution of air
quality and
demographic inputs
user-specified for
the selection of
activity patterns
(e.g., state, region)
Framework
deterministic
stochastic
stochastic
stochastic
Human Exposure Model (HEM)
The Human Exposure Model (http://www.epa.gov/ttn/fera/humanjiem.htmn was designed to
screen major stationary sources of air pollutant emissions efficiently, ranking the sources
according to the potential cancer risks and noncancer hazard associated with long-term (annual)
average exposure concentrations/10' The current version, Version 3 (HEM-3), is implemented on
a Windows platform for ease of use. HEM-3 contains a version of the Gaussian atmospheric
dispersion model ISCLT2 (with included meteorological data), and U.S. Census Bureau
population data (2000) at the Census block level. A limited amount of source data are required
as model inputs (e.g., pollutant emission rates, facility location, height of the emission release,
stack gas exit velocity, stack diameter, temperature of the off-gases, pollutant properties, and
source location). HEM-3 estimates the magnitude and distribution of ambient air concentrations
of pollutant in the vicinity of each source. The model usually estimates these concentrations
April 2004
Page 11-17
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within a radial distance of 50 kilometers (30.8 miles) from the source. Exposure concentrations
for the residents of each Census block are assumed to be the outdoor concentration at the Census
block "internal point." This actually represents a surrogate for exposure, as important exposure
variables (e.g., indoor-outdoor concentration differences, human mobility patterns, residential
occupancy period, breathing rates) are not explicitly addressed. Multiple facilities (including
clusters of facilities, each having multiple emission points) can be addressed by HEM-3.
Variability and uncertainty in input data and parameters are not considered.
The Hazardous Air Pollutant Exposure Model (HAPEM5)
The latest version of EPA's Hazardous Air Pollutant Exposure Model (HAPEM5) is a stochastic
screening-level inhalation exposure model appropriate for assessing average long-term (annual)
exposures of the general population, or a specific sub-population, over spatial scales ranging
from urban to national (http://www.epa.go v/ttn/fera/humanJiapem.html). This application
requires a moderate level of computer modeling skills.
HAPEM5 uses the general approach of tracking representatives of specified demographic groups
as they move among 37 indoor, in-vehicle, and outdoor microenvironments and among
geographic locations. The estimated pollutant concentrations in each microenvironment visited
are combined into a time-weighted average concentration, which is assigned to members of the
demographic group (the cohorts). Microenvironment concentrations are estimated from outdoor
concentrations with the factors method. HAPEM5 uses five primary sources of information:
population data from the U.S. Census; population activity data from CHAD commuting data
developed by the Bureau of the Census; user supplied air quality data either from measurements
or an air dispersion model; and microenvironmental factors data.
The previous version of HAPEM5, namely HAPEM4, was used in the NATA national scale
assessment of the 1996 NEI to develop estimates of risk, by census tract, for each of the 33 HAPs
(http://www.epa.gov/ttn/amtic/netamap.html). Specifically, HAPEM4 was used to predict
population exposure for each of 10 demographic groups in each tract.
Total Risk Integrated Methodology Exposure Event Model (TRIM.ExpoInh3l3tion), also
known as Air Pollutants Exposure Model (APEX)
The Air Pollutants Exposure Model (APEX) comprises the inhalation port ion of the TRIM
exposure module, TRIM.Expo (http://www.epa.gov/ttn/fera/human_apex.html).(b)
TRIM.Expo (a.k.a. APEX) uses a personal profile approach rather than a cohort simulation
approach. That is, individuals are selected for simulation by selecting combinations of
demographic characteristics and finding an activity pattern to match it, rather than directly
selecting an activity pattern. If the selection probabilities for the demographic characteristics are
the same as within the population to be simulated, this approach will provide a representative
sample of that population's activity patterns without the need for post-simulation weighting of
results.
EPA has developed the Total Risk Integrated Methodology (TRIM) for use in the assessment of air
pollutants (both hazardous and criteria). APEX comprises the inhalation exposure component of TRIM.
April 2004 Page 11-18
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The current version (APEX3, available on the web) includes a number of useful features
including automatic site selection from large (e.g., national) databases, a series of new output
tables providing summary statistics, and a thoroughly reorganized method of describing
microenvironments and their parameters. The model has the capability to estimate
microenvironment concentration from the mass-balance method, but also provides the option of
using the factors method. Most of the spatial and temporal constraints were removed or relaxed
in APEX3. The model's spatial resolution is flexible enough to allow for the use of finely
resolved modeled air quality values, as well as sparser measured values. Averaging times for
exposure concentrations are equally flexible. Like HAPEM5, the user must supply the air quality
data (from modeling or monitoring) to the model.
California Population Indoor Exposure Model (CPIEM)
The CPIEM(11) is a stochastic inhalation exposure model developed for the California Air
Resources Board's (ARB's) Indoor Program to evaluate indoor exposures for the general
California population as well as certain sub-populations. CPIEM combines indoor air
concentration distributions with Californians' location and activity information to produce
exposure and dose distributions for different types of indoor environments.
The temporal resolution and averaging time are user-selected from the options of 1-hour, 8-hour,
12-hour, and 24-hour. The spatial resolution and modeling domain similarly are specified by the
user according to county, state region, or the entire state. Although outdoor concentrations may
be included in the application, the focus is on indoor exposures and indoor emission sources.
The model is implemented on a Windows-based platform for ease of use.
The model uses location/activity profiles that were collected in ARB studies. Microenvironment
concentrations are derived from measurement studies for up to nine microenvironments.
Concentration distributions from measurement studies for many pollutants and
microenvironments are included in the CPIEM database. However, for pollutants and
microenvironments not included in the database, the CPIEM presents two alternatives. The first
is to estimate indoor air concentration distributions based on distributional information for mass
balance parameters with a mass-balance module. The second is for the user to directly specify
concentration distributions.
11.3.5 Exposure Modeling Examples
The following applications of air quality modeling and exposure modeling at real-world sites
provide useful insights into air toxics modeling. The TRIM.Expo (a.k.a. APEX) inhalation
exposure model has also been used with the ISCST3 air quality model to predict human
inhalation exposures. A report documenting this aspect of the case study will be available at:
http://www.epa.gov/ttn/fera/human_apex.html.
National-scale Air Toxics Assessment (NATA). EPA's NATA is designed to provide a
comprehensive evaluation of air toxics exposure and risk across the U.S. Activities include
expansion of air toxics monitoring, improving and periodically updating emission inventories,
improving national- and local-scale modeling, continued research on health effects and exposures
to both ambient and indoor air, and improvement of assessment tools. As noted previously, one
component of NATA is a National Scale Assessment conducted with the ASPEN and the
April 2004 Page 11-19
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HAPEM4 to estimate annual average exposure concentrations of the 33 urban air toxic pollutants
in every US Census tract. Specific examples of the results of the National Scale Assessment and
additional information on NATA activities can be found on-line.(12)
Houston Case Study. This study was carried out by EPA's Office of Air Quality Planning &
Standards (OAQPS) and the Office of Transportation and Air Quality (OTAQ) as a component of
the Integrated Urban Strategy/13' For the Houston metropolitan area, ISCST3 modeling was
applied, using emissions data for point, non-point, and mobile sources from EPA's 1996
National Toxics Inventory. Ambient air concentrations for numerous air toxics were predicted at
the census tract level with ISCST3 and HAPEM, which were then employed to obtain estimates
of population exposures. Modeling results were compared to the results obtained through studies
of this area carried out as part of the NATA National Scale Assessment. The study demonstrated
that modeling using ISCST3 and an improved emissions inventory provides more realistic
patterns and better agreement with monitoring data. In addition, elevated concentrations (hot
spots) were found that were not detected in the national scale analysis.
11.4 Personal Monitoring
Thus far, we have focused on monitoring devices that generally are located in a secure compound
(and sometimes on rooftops) that measure air quality that is representative of some specific
geographic scale. An alternative to such an approach is to place monitors directly on individuals,
which allows collection of more detailed information specific to the exposure pattern for that
individual. Such monitors are referred to as personal monitors because they provide
information on exposure to that individual, rather than to the general area in which an individual
might be moving. An advantage is that personal monitors reflect the time-varying concentrations
(unless they are integrating monitors) an individual experiences as he or she moves about through
various activities. Personal monitors have seen increasing use in recent years due to two factors:
they are more readily available, reliable, and cheaper than in the past, and there is growing
evidence that personal exposures may at times be correlated poorly with average values derived
for larger geographic areas (see Exhibit 11-7).
Two modes of personal monitoring have been developed. One relies on direct measurements of
air concentration for toxics in the breathing zone or otherwise on/near the body of an individual
(these are called direct measurement methods). The other relies on changes in biological
properties such as blood level of an air toxic (or metabolite). The latter is not considered here
because it does not strictly measure ambient air concentrations or estimate exposure. Personal
monitors, as with area or fixed monitors described previously in this chapter, are available in two
types:
• Active monitors use a small air pump to draw air through a filter, packed tube, or similar
device. They can be both continuous and integrated. Such a personal exposure monitor is
available to measure PM10 and PM2 5 in air using a 37 mm Teflon filter and a 4 L/min flow
rate. The pump and battery pack are worn in a bag, while the filter can be located essentially
anywhere on the body. In addition, cyclone personal samplers are available for measuring
particulates in air (the term "cyclone" refers to the fact that the sampler measures the
particulates by "spinning" the particles in an air stream, which then collect on the sides of the
device for collection and analysis). Combinations of impactor and denuder filter packs are
April 2004 Page 11-20
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available to sample both aerosols and gases such as SO2, NH3 and HNO3. Different coating
materials on the diffuser tube can be used to collect different gases.
Exhibit 11-7. Examples of the Use of Personal Monitoring
Relationship of Indoor, Outdoor and Personal Air (RIOPA) study.(14) Indoor and outdoor
concentrations of 30 polycyclic aromatic hydrocarbons (PAHs) were measured in 55 homes in Los
Angeles, CA, Houston, TX, and Elizabeth, NJ. The study focused on areas in each city
characterized by worst-case conditions in the outdoor air, generally located close to major sources.
Integrating MSP samplers, polyurethane foam cartridges, and quartz fiber filters were used for the
field sampling, and the samples were analyzed subsequently in the lab. Among many results, the
study showed that indoor air was dominated by outdoor sources for these compounds, with
reasonably strong correlations between the indoor and outdoor air concentrations.
National Human Exposure Assessment Survey (NHEXAS).(15) The NHEXAS program was
designed to "describe the distribution of human exposure to multiple chemicals from multiple
routes on a community and regional scale, and its association with environmental concentrations
and personal activities." It is being conducted in three stages: (1) design, field evaluation and
demonstration projects; (2) exposure field studies; and (3) special studies to examine issues such
as highly exposed populations and long-term exposures. Extensive statistical analyses of the data
have been performed, including characterizations of background levels of exposure to selected
chemicals, as well as correlations among environmental concentrations, individual exposures,
biomarkers, and survey data on personal activities.
EPA's Total Exposure Assessment Methodology (TEAM) studies06' estimated exposures of
about 800 persons to 25 VOCs; about 300 persons to 32 pesticides; and 1,200 persons to carbon
monoxide. The general approach in all four of the main TEAM studies was the same: a
probability-based selection of respondents, so that they would represent a much larger population
(e.g., the 800 persons in the TEAM VOC studies actually represented about 800,000 persons in 8
cities); the use of personal monitors as well as outdoor monitors to estimate actual personal
exposure; and the use of an Office of Management and Budget (OMB)-approved questionnaire
and activity diary to try to pinpoint local sources. In two of the TEAM Studies for VOCs and
carbon monoxide, an effort was made to measure body burden, by collecting a breath sample from
each of the 2,000 persons involved. This was important in identifying active smoking as the main
source of exposure to benzene and styrene, for example. Also, the breath measurements identified
a "dirty dozen" pollutants that were prevalent in almost every person. The Centers for Disease
Control later collected blood samples from 800 different persons and found essentially the same
dozen pollutants prevalent in blood.
• Passive monitors rely on sorption, entrapment, etc., driven largely by diffusion. They are
primarily integrated sampling devices, giving a estimate of average exposure over the
sampling period. Examples include diffusion tubes, badges, and detector tubes. Diffusion
badges currently are available for measurement of NO2, O3, SO2, CO and formaldehyde.
Organic vapors can be measured in passive devices using activated charcoal badges, although
the range of compounds, aside from organics, that can be sampled in this way is small.
Reviews of such methods of personal sampling can be found in Bower et al. (1997).(17) However,
many of the same limitations as ambient methods exist, and in some cases additional quantitation
limit and precision problems are present.
April 2004 Page 11-21
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In general, air toxics risk assessments that rely on monitoring to characterize exposure will
generally not rely on personal monitoring because of the highly complex and resource intensive
nature of this technique, and because personal monitoring and its findings are currently more
geared toward basic research.
11.5 Exposure to a Population: Common Descriptors
There are a wide variety of ways to describe exposure to a population, some of which may be
legally required, others which may be chosen based on the requirements of the risk manager. No
matter what specific measure is chosen, the risk assessment needs a clear and scientifically
supportable rationale for the approach taken; risk assessors generally describe that approach
clearly and thoroughly in the exposure assessment portion of the risk assessment documentation.
Risk assessors aim for there to be no ambiguity about what was done in the exposure assessment.
EPA policy and guidance recommend that exposure to a population be described using several
different ways to give the risk manager a sense of the range and magnitude of the exposures. For
example, a "high end" exposure estimate might describe the exposure experienced by actual
people in the most highly concentrated part of the area of impact, while a "central tendency"
exposure estimate might describe the exposure experienced by people in the study area who
experience more modest concentrations.
A variety of statistical values are used to describe high-end and central tendency exposures,
including 95th percentile exposures (for high-end) and 50th percentile values for central tendency.
Risk assessors will want to obtain and become familiar with EPA's Risk Characterization
Handbook to better understand various ways exposure and risk can be adequately
characterized/18' EPA's Guidelines for Exposure Assessment^ is also invaluable in this regard.
Some of the alternative approaches for characterizing air toxics exposures are illustrated in
Exhibit 11-2 above.
11.6 Evaluating Uncertainty
Uncertainty includes the assumptions and unknown factors inherent in the exposure assessment.
Discussing uncertainty places the risk estimates in proper perspective. Specific uncertainties
associated with the chemical monitoring data, fate and transport models, and the input data
(especially emissions inventory data) that assessors use to estimate exposure concentrations
usually account for the bulk of uncertainty within the assessment. Exposure models also
contribute to the overall uncertainty in exposure assessment. The assessor needs to understand
the extent to which variability and uncertainty are considered in all the fate and transport and
exposure models that are used. HAPEM and other exposure models can accept input data on the
distributions of time spent in different micro-environments and produce time-average exposure
estimates for defined populations.
The assessor should be familiar with the extent to which the various components of the exposure
assessment can and do accommodate uncertainty and variability analyses. In addition, it is
important to consider the compatibility of models in the various steps in the exposure assessment
(emissions, transport, etc.) with regard to addressing important sources of uncertainty. Once the
capabilities and data requirements of the various models are known, the assessor should consider
April 2004 Page 11-22
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the appropriate level of detail for addressing uncertainty in specific variables, and approaches for
integrating uncertainty analyses across the models.
11.7 Presenting the Results of an Exposure Assessment
The summary of exposure assessment for air toxics consists of presenting the ECs for each
chemical of potential concern (COPC) with the duration of exposure for the populations of
interest, as well as characterizing salient features of the study populations), particularly those
that may be influencing their exposure and resultant risk (e.g., size and proximity to sources and
/or locations of highest ambient concentrations). The assumptions used to develop these
estimates should also be presented and discussed. In addition to the summary tables, it is useful
to show sample calculations for each pathway to aid in the review of the calculations. (If
exposure modeling is used, a thorough discussion with sample calculations is usually also
provided.)
References
1. U.S. Environmental Protection Agency. 2003. Building Assessment, Survey and Evaluation
Study (BASE) Study, updated June 17, 2003, and Longitudinal Temporal Indoor Monitoring
and Evaluation (TIME) study in federal buildings. Available at:
http://www.epa.gov/iaq/largebldgs/base_page.htm. (Last accessed March 2004).
2. Wallace L., W. Nelson, R. Ziengenfus, E. Pellizzari, L. Michael, R. Whitmore, H. Zelon, T.
Hartwell, R. Perritt and D. Westerdahl. 1991. The Los Angeles TEAM Study: Personal
Exposures, Indoor-Outdoor Air Concentrations, and Breath Concentrations of 25 Volatile
Organic Compounds. J. Expos. Anal. Environ. Epidem., 1(2): 157-192.
3. U.S. Environmental Protection Agency. 2003. Consolidated Human Activity Database
(CHAD). Updated November 20, 2003. Available at: http://www.epa.gov/chadnet 1 /. (Last
accessed March 2004).
4. U.S. Environmental Protection Agency. 2002. The Exposure Factors Handbook. Updated
December 30, 2002. Available at:
http://cfpub.epa.gov/ncea/cfm/exposfac.cfm?ActType=default. (Last accessed March 2004).
5. U.S. Environmental Protection Agency. 2003. Human Exposure Database System (HEDS).
Updated February 11, 2003. Available at: http://www.epa.gov/heds/. (Last accessed March
2004).
6. Journal of Exposure Analysis and Environmental Epidemiology, Vol. 5, No. 3, 1995.
7. Centers for Disease Control. 2003. National Health and Nutrition Examination Survey.
Updated October 30, 2003. Available at http://www.cdc.gov/nchs/nhanes.htm. (Last accessed
March 2004).
8. U.S. Census Bureau. 2004. Index of/census _2000/datasets/Summary_File_3. Available at:
http://www2.census.gov/census_2000/datasets/Summary_File_3/ (Last accessed March
2004).
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U.S. Census Bureau. Topologically Integrated Geographic Encoding and Referencing system
(TIGER). Updated March 5, 2004. Available at:
http ://www. census .go v/geo/www/tiger/index.html. (Last accessed March 2004).
9. U.S. Environmental Protection Agency. 2003. Port Neches Environmental Justice Study and
Demonstration Project for the Development of Landscan USA. Updated December 30, 2003.
Available at: http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=22406. (Last accessed
March 2004).
10. U.S. Environmental Protection Agency. 2003. Human Exposure Modeling - Human
Exposure Model (HEM). Updated April 23, 2003. Available at:
http://www.epa.gov/ttn/fera/human_hem.html. (Last accessed March 2004).
11. ICF Consulting. 2002. California Population Indoor Exposure Model, Version 2: User's
Guide. Prepared for the California Environmental Protection Agency, California Air
Resources Board.
12. U.S. Environmental Protection Agency. 2002. The National-Scale Air Toxics Assessment.
Updated September 18, 2002. Available at: http://www.epa.gov/ttn/atw/nata/. (Last accessed
March 2004).
13. U.S. Environmental Protection Agency. 2004. Technology Transfer Network. Air Toxics
Strategy: Overview. Updated February 10, 2004. Available at:
http://www.epa.gov/ttn/atw/urban/urbanpg.html. (Last accessed March 2004).
14. Naumova, Y., Eisenreich, S., Turpin, B., Weisel, C., Morandi, M., Colome, S., Totten, L.,
Stock, T., Winer, A., Alimokhtari, S., Kwon, J., Shendell, D., Jones, J., Maberti, S. and Wall,
S. 2002. Polycyclic Aromatic Hydrocarbons in the Indoor and Outdoor Air of Three Cities in
the U.S. Environmental Science and Technology, 36: 2552-2559.
15. U.S. Environmental Protection Agency. 2003. Human Exposure Measurements: National
Human Exposure Assessment Survey (NHEXAS). Updated July 21, 2003. Available at:
http://www.epa.gov/heasd/edrb/nhexas.htm. (Last accessed March 2004).
16. Ozkaynak H., J. Xue, R. Weker, D. Butler and J. Spengler. 1995. The Particle TEAM
(PTEAM) Study: Analysis of the Data, Volume III, Draft Final Report. U.S. Environmental
Protection Agency, Research Triangle Park, NC.
Ozkaynak H., J. Xue, J. Spengler, L. Wallace, E. Pellizzari, and P. Jenkins. 1996. Personal
exposure to airborne particles and metals: results from the Particle TEAM Study in
Riverside, California. Journal of Exposure Analysis and Environmental Epidemiology,
6(l):57-78.
Pellizzari, E. D., K. W. Thomas, C. A. Clayton, et al. 1992. Particle Total Exposure
Assessment Methodology (PTEAM): Riverside, CA Pilot Study Vol. I. U.S. Environmental
Protection Agency, Research Triangle Park, NC. (EPA 600/R-93-050).
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Sheldon, L., A. Clayton, J. Keever, et al. 1992. PTEAM: Monitoring of Phthalates and
PAHs in Indoor and Outdoor Air Samples in Riverside, California. Final Report. California
Air Resources Board. Sacramento, California.
Wallace, L. 1987. The Total Exposure Assessment Methodology (TEAM) Study: Summary
and Analysis: Volume 1. U.S. Environmental Protection Agency, Office of Research and
Development, Washington, D.C. EPA/600/6-87/002a.
Wallace, L. 1989. Major sources of benzene exposure. Environ. Health. Perspect.,
82:165-169.
Wallace L., W. Nelson, R. Ziengenfus, E. Pellizzari, L. Michael, R.Whitmore, H. Zelon, T.
Hartwell, R. Perritt and D. Westerdahl. 1991. The Los Angeles TEAM Study: Personal
Exposures, Indoor-Outdoor Air Concentrations, and Breath Concentrations of 25 Volatile
Organic Compounds. J. Expos. Anal. Environ. Epidem., 1(2): 157-19.
17. Bower et al. 1997. A Practical Guide to Air Quality Monitoring. National Environmental
Technology Centre, England.
18. U.S. Environmental Protection Agency. 1992. Guidance on Risk Characterization for Risk
Managers and Risk Assessors. Risk Assessment Council, Washington, B.C., February 26,
1992.
19. U.S. Environmental Protection Agency. 1992. Guidelines for Exposure Assessment. Federal
Register 57:22888-22938, May 29, 1992. Available at
http ://cfpub. epa. gov/ncea/raf/recordisplay.cfm?deid= 15263
April 2004 Page 11-25
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Chapter 12 Inhalation Toxicity Assessment
Table of Contents
12.1 Introduction 1_
12.1.1 Hazard Identification and Dose-Response Information 1_
12.1.2 Dose-Response Assessment Methods 5
12.2 Hazard Identification £
12.2.1 Weight of Evidence - Human Carcinogenicity 9
12.2.2 Identification of Critical Effect(s) - Non-Cancer Endpoints H
12.3 Dose-Response Assessment for Cancer Effects 1_2
12.3.1 Determination of the Point of Departure (POD) 13.
12.3.2 Derivation of the Human Equivalent Concentration 1_4
12.3.3 Extrapolation from POD to Derive Carcinogenic Potency Estimates 1/7
12.4 Dose-Response Assessment for Derivation of a Reference Concentration \9_
12.4.1 Determination of the Point of Departure and Human Equivalent Concentration 20
12.4.2 Application of Uncertainty Factors 22
12.5 Sources of Chronic Dose-Response Values 24
12.6 Acute Exposure Reference Values 26
12.7 Evaluating Chemicals Lacking Health Reference Values 31_
12.7.1 Use of Available Data Sources 31_
12.7.2 Route-to-Route Extrapolation 3J.
12.8 Dose-Response Assessment for Mixtures 32
References 35
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12.1 Introduction
The purpose of the toxicity assessment is to weigh available evidence regarding the potential for
toxicity in exposed individuals (hazard identification) and to quantify the toxicity by deriving
an appropriate dose-response value (dose-response assessment). Toxicity assessment is the
second part of the general risk equation. Although the toxicity assessment is an integral and
important part of the overall air toxics risk assessment, it is usually accomplished prior to the risk
assessment. EPA has completed this toxicity assessment for many HAPs and has made available
the resulting toxicity information and dose-response values, which have undergone extensive
peer review (see Appendix C).1
/- x
Risk = / (metric of exposure, metric of toxicity)
Toxicity Assessment is a 2-Step Process:
1. Hazard Identification - What types of effects does the chemical cause? Under what
circumstances?
2. Dose-response Assessment - How potent is the chemical as a carcinogen and/or for noncancer
effects?
In most air toxics risk assessments, little new toxicological evaluation of primary data will be
required. However, it is important to understand how the available data were analyzed to
produce the dose-responses values used in a risk assessment. In the risk characterization step, the
risk assessor will need to describe the nature of the available toxicological evidence and the
uncertainties inherent in the development of the dose-response values used in the inhalation risk
assessment (see Chapter 13).
Additionally, in the event that there are significant data analysis and interpretation issues, or if a
dose-response value does not exist and needs to be developed for a particular air toxic of interest,
this chapter provides information about how to locate toxicity assessments, accompanying dose-
response values, and relevant guidance documents. However, development and interpretation of
toxicity information and dose-response values requires toxicological expertise and should not be
undertaken by those without appropriate training and experience.
12.1.1 Hazard Identification and Dose-Response Information
As part of the hazard identification step, evidence is gathered from a variety of sources regarding
the potential for an air toxic to cause adverse health effects in humans. These sources may
include human data, experimental animal studies, and supporting information such as in vitro
laboratory tests. The source of data affects the overall uncertainties in the resulting human dose-
response values, as discussed below.
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Human data. Human toxicity data associated with exposures to air toxics maybe located in
epidemiological studies, controlled exposure studies, or studies of accidental exposures.
Well-conducted epidemiological studies that show a positive association between exposure to
a chemical and adverse health effects often provide evidence about human health effects
associated with chronic exposures.
Such data, however, are available
Epidemiology is the study of the distribution and
determinants of disease or health status in a population.
only for a limited number of air
toxics. Epidemiological data also are
very difficult to interpret, because the
number of exposed individuals may be small, the incidence of effects may be low, doses are
usually not well-characterized, and there may be complicating factors such as simultaneous
exposure to multiple chemicals and heterogeneity among the exposed group in terms of age,
sex, diet, and other factors. Controlled exposure studies provide stronger evidence, since
both the exposure duration and exposure concentrations are more accurately known.
However, such studies with humans are generally limited to acute exposure durations.
Studies reporting health effects associated with accidental exposures may be helpful,
although exposure concentrations to air toxics may be high, and effects may be acute rather
than chronic. Also note that small sample size is often a significant limitation to interpreting
controlled and accidental exposure studies.
Animal data. The toxicity database for most air toxics is drawn from experiments conducted
on non-human mammals such as rats, mice, rabbits, guinea pigs, hamsters, dogs, or monkeys.
The underlying assumption is that the susceptibility of humans and these animals to the
effects of the chemicals is broadly similar because we share many common biological
attributes (e.g., similar organs, similar and, in some cases, identical metabolic processes).
However, some observations in animals maybe of uncertain relevance to humans (e.g., if
tumors are observed in an animal experiment, but the organ in which the tumor is formed
does not exist in humans). Also, it is necessary to adjust the results from animal studies to
humans due to differences in body mass, anatomy, metabolic rate, and other species-specific
factors (see, for example, Section 12.3.3). This is why derivation of dose-response values
from animal studies requires considerable expertise.
Supporting data. Metabolic, pharmacokinetic, and genotoxicity studies are sometimes used
to infer the likelihood of adverse effects in humans. Metabolic studies on absorption,
distribution, metabolism, and elimination can provide information about the mechanisms of
toxicity associated with a particular chemical in humans. In physiologically based
pharmacokinetic (PBPK) models,(a) the body is subdivided into a series of anatomical or
physiological "compartments" that represent specific organs or lumped tissue and organ
groups, and the behavior of the chemical is modeled in each compartment. Data on a
chemical's pharmacokinetics, genotoxicity, and possible mode of action can be used to refine
a toxicity assessment. In some cases, computer models using structure-activity relationships
(i.e., predictions of toxicological activity based on analysis of chemical structure) also maybe
used as supporting evidence. EPA considers these types of data to be supportive, not
definitive, evidence of a chemical's toxicity.
aA PBPK model estimates the dose to a target tissue or organ by taking into account the rate of absorption
into the body, distribution among target organs and tissues, metabolism, and excretion.
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Information from these sources is considered in the hazard and dose-response assessment steps in
characterizing a chemical with regard to the type(s) of effect a chemical produces (the hazard)
and the circumstances in which this occurs, as well as the level of exposure required to produce
that effect. The output of the dose-response assessment is the relationship between dose (the
level of exposure) and the resulting response (the increased incidence and/or severity of adverse
effects). A dose-response assessment is the process of quantitatively evaluating toxicity
information, characterizing the relationship between the dose of the contaminant received (or the
inhalation exposure concentration, for inhalation assessments) and the incidence of adverse
health effects in the exposed subjects (which maybe animal or human) and then, as appropriate,
extrapolating these results to human populations. Depending on the type of effect and the
chemical, there are two types of dose-response values that traditionally may be derived:
predictive cancer risk estimates, such as the inhalation unit risk estimate (IUR), and predictive
non-cancer estimates, such as the reference concentration (RfC).(b) Both types of dose-
response values maybe developed for the same chemical, as appropriate.
/"" ~"\
Inhalation Dose-Response Values(a)
Inhalation Unit Risk (IUR): The upper-bound excess lifetime cancer risk estimated to result from
continuous exposure to an agent via inhalation per (ig/m3 over a lifetime. The interpretation of the
IUR would be as follows: if IUR = 2 x 1Q"6 ug/m3, not more than 2 excess tumors are expected to
develop per 1,000,000 people if exposed continuously for a lifetime to 1 fig of the chemical per cubic
meter of inhaled air. The number of expected tumors is likely to be less; it may even be none.
Reference Concentration (RfC): An estimate (with uncertainty spanning perhaps an order of
magnitude) of a continuous inhalation exposure to the human population (including sensitive sub-
populations) that is likely to be without an appreciable risk of deleterious effects during a lifetime.
Generally used in EPA's noncancer health assessments.
-------
Exhibit 12-1. Examples of Dose-Response Curves
Enzyme Concentration
A. Continuous Response Data
Simple example of a dose-response curve for
graded responses of a specific physiological
parameter to increasing exposure.
Dose/Response Curve for
Non-Carcinogen
100 500 1000 2000 5000 10000 20000
Exposure Concentration (mg/m3)
B. Different Responses in a Population
Simple example of the incidence of three
different effects in an exposed population in
response to different exposure concentrations
(over the same duration).
While the primary focus of this chapter is on description of dose-response values relevant to
chronic (long-term) exposures, the information reviewed for developing those values may
include effects associated with acute (short-term) exposures. Additionally, information on acute
exposures is essential to the development of acute exposure reference values (see Section 12.6).
• Acute exposures are usually relatively short in duration, but relatively high in concentration
and may result in immediate respiratory and sensory irritation, chemical burns, narcosis, eye
damage, and various other effects. Acute exposures also may result in longer-term health
effects.
• Chronic exposures are usually relatively long in duration, but relatively low in concentration
and may result in health effects that do not show up immediately and that persist over the
long term, such as cardiovascular disease, respiratory disease, liver and kidney disease,
reproductive effects, neurological damage, and cancer.
Generally, chronic reference values are derived for exposure periods between seven years and a
lifetime. Acute reference values (see section 12.6) are generally developed for very short
exposures (e.g., hours to days; Exhibit 12-2). For intermediate exposures, subchronic reference
values are available from some sources (e.g., ATSDR). Most air toxics risk assessments will
focus on chronic and acute evaluations; however, under more limited circumstances, subchronic
evaluations may be performed.
April 2004
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Exhibit 12-2. Reference Values of Different Durations
In the Agency's Review of the Reference Dose and Reference Concentration Processes,2 it was
recommended that in addition to the traditional chronic reference value (i.e., RfC or RfD) included in
the IRIS database, values of several shorter durations also be developed, where possible. As a first
step in this direction, the Review proposed the following definitions. EPA currently is considering
these and other recommendations made in the Review. These definitions are based on exposure
durations for humans, and were not intended to be rigid specifications, but simply general descriptions
of the relevant exposure time period.
• Acute: Exposure by the oral, dermal, or inhalation route for 24 hours or less.
• Short-term: Repeated exposure(a) by the oral, dermal, or inhalation route for more than 24 hours,
up to 30 days.
• Longer-term: Repeated exposure by the oral, dermal, or inhalation route for more than 30 days,
up to approximately 10 percent of the life span in humans(b) (more than 30 days up to 90 days in
typically used laboratory animal species(c)).
• Chronic: Repeated exposure by the oral, dermal, or inhalation route for more than approximately
10 percent of the life span in humans (more than approximately 90 days to 2 years in typically
used laboratory animal species).
(a)A repeated exposure may be either continuous, periodic, or intermittent. A continuous exposure is a daily
exposure for the total duration of interest. A periodic exposure is one occurring at regular intervals (e.g.,
inhalation exposure 6 hours/day, 5 days/week; or oral exposure 5 days/week). An intermittent exposure is one in
which there is no effect of one exposure on the effect of the next; this definition implies sufficient time for the
chemical and its metabolites to clear the biological system before the subsequent (i.e., noncumulative
pharmacokinetics). A periodic exposure may or may not be intermittent.
^An average of 70 years is typical default used for chronic exposures.
(c)Examples of typically used laboratory species include rats, mice, and rabbits.
12.1.2 Dose-Response Assessment Methods
Depending on whether a substance causes cancer and whether its dose-response curve is thought
to have a threshold, EPA may use either of two approaches in a dose-response assessment. One
approach produces a predictive estimate (e.g., inhalation cancer risk estimate), and the other
produces a reference value (e.g., RfC). Historically, the use of a predictive estimate has been
limited to cancer assessment. That is, dose-response assessments for cancer have been expressed
as predictive cancer risk estimates based on an assumption that any amount of exposure poses
some risk. Assessments of effects other than cancer usually have been expressed as reference
values at or below which no harm is expected. Many substances have been assessed both ways:
the first for cancer and the second for adverse effects other than cancer. While this use of
predictive estimates for cancer and reference values for other effects is still the practice for the
vast majority of chemicals, EPA now recognizes that there are chemicals for which the data
support an alternate approach.
April 2 004 Page 12-5
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An important aspect of dose-response relationships is whether the available evidence suggests
the existence of a threshold. For many types of toxic responses, there is a threshold dose or
dose rate below which there are thought to be no adverse effects from exposure to the chemical.
The human body has defenses against many toxic agents. Cells in human organs, especially in
the liver and kidneys, break down many chemicals into less toxic substances that can be
eliminated from the body in urine and feces. In this way, the human body can withstand some
chemical exposure (at doses below the threshold) and still remain healthy. For example, many
air toxics are naturally occurring substances to which people routinely receive trace exposures at
non-toxic levels.
Identification of a threshold dose depends on the
type of response and the way in which the toxic
chemical produces it. EPA has developed
guidelines 3 for assessing the dose-response for
various types of adverse effects, which provide
more information about evaluating evidence to
determine if a threshold exists.
All substances are poisons: there is none
which is not a poison. The right dose
differentiates a poison and a remedy.
- Paracelsus ,
Different Responses Exhibit Different Dose-Response Curves
100% -
Both the point at which the
dose-response curve begins
to ascend (its threshold,
which may be zero) and
the slope of the curve (its
steepness) provide
information about the
toxicity of a chemical
(Exhibit 12-3). The
potency of a chemical is a
measure of its strength as a
toxicant compared with
other chemicals.
Therefore, the lower the
threshold dose, the more
potent (or toxic) the
chemical. The slope of the curve is a measure of the range of doses from the threshold dose (at
which the adverse effect is first measured) to the dose at which the effect is complete (i.e., higher
doses produce no additional incidence of that effect, although other adverse effects may begin to
appear). The steeper the dose-response curve, the smaller the range between the first appearance
of an effect and a substantial response.
Lowest
DOSE
Highest
Line A - A sharp increase in response with increasing dose
Line B - A more gradual increase in response with increasing dose
April 2004
Page 12-6
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Exhibit 12-3. Dose-Response Relationships for Carcinogens and Noncarcinogens
A. Example Linear Carcinogen
O £
Q.O
10%
o%
Environmental
Exposure Levels
of Interest
Empirical
Range of
Observation
Range of
Extrapolation
LEC. EC,.
Exposure Concentration
In the absence of clear evidence to the contrary, EPA assumes as a matter of science policy that even a very low
exposure to a cancer-causing pollutant can increase the risk of cancer (albeit a small amount). Experimental data
are used to construct a dose-response relationship and identify the point of departure - the dose that can be
considered to be near or in the range of observed responses and, thus, no significant extrapolation is needed. To
estimate the dose-response relationship at doses below the point of departure, the dose-response relationship
between the point of departure and zero is assumed to be linear. Thus, at doses below the point of departure, with
each unit of increase in exposure (dose), there is an increase in cancer response. Where evidence supports the
acceptance of a non-linear mode of action, a reference concentration approach may be employed, as shown in "B"
below. LEC50= lethal effective concentration for 50 percent of the population; EC10= effective concentration that
causes an observable adverse effect in 10 percent of the population.
B. Example Non-linear Approach
o
'•S
o
a.
I
o
E
4
Apply
_ _
Uncertainly
Factors
Liver Toxicily
(Critical Effect)
Tremors
P
I _
/ * Enzyme
'}"" Change
NOAEL
RfC
Exposure Concentration
A dose may exist below the minimum health effect level for which no adverse effects occur. EPA typically
assumes that at low doses the body's natural protective mechanisms prevent or repair any damage caused by the
pollutant, so there is no ill effect at low doses. Even long-term (chronic) exposures below the threshold are not
expected to have adverse effects. The dose-response relationship (the response occurring with increasing dose)
varies with pollutant, individual sensitivity, and type of health effect. NOEL = no-observed-effect-level; NOAEL
= no-observed-adverse-effect-level; LOAEL = lowest-observed-adverse-effect-level.
April 2004
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Epidemiologic and toxicologic data on air toxics typically result from exposure levels that are
high relative to environmental levels. Therefore, low-dose extrapolation (prediction) is
necessary to derive an appropriate dose-response value. For a few air toxics (e.g., the criteria air
pollutants ozone and carbon monoxide), data are sufficient to characterize dose-response
relationships at environmental levels. In such cases, there is no need for extrapolation of toxicity
data to lower doses. Such is not the case for most air toxics. Low-dose extrapolation requires
either information or assumptions about the type of dose-response curve likely under low dose
situations. EPA risk assessment guidelines provide more detailed information on how EPA
performs low-dose extrapolation for chemicals with various toxic effects, such as developmental
effects or neurotoxic effects.(3)
12.2 Hazard Identification
The hazard identification, which is usually
part of an existing dose-response assessment
for each chemical, provides a summary of the
available toxicity information for the air
toxics being studied, and includes the weight
of evidence determination and identification
of critical effects. This step should answer
the following questions:
• Can exposure to a chemical be linked
causally to particular health effects?
Could these effects occur at environmentally relevant concentrations?
What is the nature and strength of the evidence of causation?
Items to Include in the Hazard Identification
of an Air Toxics Risk Assessment
• List of chemicals detected
• Summaries of toxic effects and quality of the
toxicological evidence
• Discussion that focuses the risk assessment on
chemicals most likely to cause adverse effects
By definition, all HAPs and many other air toxics have the
potential to cause adverse effects in the exposed population.
Exhibit 12-4 provides examples of cancer and non-cancer
effects, and Appendix C identifies which HAPs have been
associated with carcinogenic (cancer) effects or non-cancer
effects, along with the strength and ratings of the toxicity
evidence that has been evaluated by EPA or other international
environmental agencies.
Exhibit 12-4. Examples of
Adverse Health Effects
Birth defects
Tremors
Infertility
Skin rash
Melanoma
An air toxics risk assessment should include in its hazard identification a summary of the quality
of the toxicological evidence (i.e., the nature and strength of the evidence of causation) for the
chemicals of concern. Study factors such as the route of exposure used, the type and quality of
health effects, the biological plausibility of findings, and the consistency of findings across
studies all contribute to the strength of the hazard identification statement.
April 2004
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12.2.1 Weight of Evidence - Human Carcinogenicity
A major determination made during the hazard identification step concerns the potential of a
chemical to cause cancer in humans. This determination, which involves considering (or
weighing) all the available evidence, is called the weight of evidence determination. This
determination is complicated by possible inadequacies of the published studies, as well as
differences in body processes between people and laboratory animals. EPA's Guidelines for
Carcinogen Risk Assessment guide scientists in interpreting available studies to assess the
potential human carcinogenicity of environmental pollutants. (EPA's carcinogen risk assessment
guidelines were first published in 1986. Revisions were proposed in 1996 and 2001 and the July
1999 draft of the revisions was adopted as interim guidance. A subsequent 2003 draft of the
Guidelines has been released for public and scientific review prior to adoption as final. The
guidelines are available on the web.)4 When compared with EPA's original 1986 guidelines, the
1999 interim Guidelines recommend a more comprehensive evaluation of the evidence with
regard to a chemical's potential mode of action, and a more complete description of the context
of a chemical's carcinogenic potential (e.g., "likely carcinogenic by inhalation and not likely
carcinogenic by oral exposure"). The weight of evidence determination now includes one of five
descriptors, and is accompanied by additional text that more completely summarizes EPA's
interpretation of the evidence. The narrative statements consider the quality and adequacy of
data and the consistency of responses induced by the agent in question (see Exhibit 12-5).
Exhibit 12-5. Information Regularly Included in a Narrative Statement Describing the
Characterization of Weight of Evidence for Carcinogenicity (1999 Interim Guidelines)
• Name of agent and Chemical Abstracts Services number, if available
• Conclusions (by route of exposure) about human carcinogenicity, using one of five standard
descriptors: "Carcinogenic to Humans" "Likely to be Carcinogenic to Humans" "Suggestive
Evidence of Carcinogenicity, but Not Sufficient to Assess Human Carcinogenic Potential" "Data
are Inadequate for An Assessment of Human Carcinogenic Potential" "Non Likely to be
Carcinogenic to Humans".
• Summary of human and animal tumor data on the agent or its structural analogues, their relevance,
and biological plausibility
• Other key data (e.g., structure-activity data, toxicokinetics and metabolism, short-term studies,
other relevant toxicity or clinical data)
• Discussion of possible mode(s) of action and appropriate dose-response approach(es)
• Conditions of expression of carcinogenicity, including route, duration, and magnitude of exposure
Source: EPA (1999) Guidelines for Carcinogen Risk Assessment. Review Draff"}
Many existing carcinogen assessments were developed pursuant to EPA's 1986 Guidelines for
Carcinogen Risk Assessment, which used a simpler but less informative weight of evidence
system (see Exhibit 12-6).
Information bearing on the qualitative assessment of carcinogenic potential may be gained from
human epidemiological data, animal studies, comparative pharmacokinetic and metabolism
studies, genetic toxicity studies, structure-activity relationship (SAR) analysis, and other studies
of an agent's properties. Information from these studies helps to elucidate potential modes of
action and biological fate and disposition.
April 2004 Page 12-9
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Exhibit 12-6. EPA's Weight of Evidence Classification for Carcinogens (1986 Guidelines)
Group A: Human Carcinogen (sufficient evidence of carcinogenicity in humans)
Group B: Probable Human Carcinogen (Bl - limited evidence of carcinogenicity in humans; B2 -
sufficient evidence of carcinogenicity in animals with inadequate or lack of evidence in
humans)
Group C: Possible Human Carcinogen (limited evidence of carcinogenicity in animals with
inadequate or lack of human data)
Group D: Not Classifiable as to Human Carcinogenicity (inadequate or no evidence)
Group E: Evidence of Noncarcinogenicity for Humans (no evidence of carcinogenicity in adequate
studies)
Source: EPA (1986). Guidelines for Carcinogen Risk Assessment
Upon such consideration, both EPA systems assign a consensus interpretation to the weight of
evidence, evaluating the likelihood that the agent is a human carcinogen. Toxicological evidence
is characterized separately for human studies and animal studies as: sufficient, limited,
inadequate, no data, or evidence of no effect. The characterizations of these two types of data are
combined, and based on the extent to which the agent has been shown to be a carcinogen in
experimental animals or humans, or both, the chemical is given a weight of evidence
classification.
Generally, no single factor is determinative. For example, strength of association is one of the
criteria for causality. A strong association between exposure and cancer in animals is more likely
to indicate causality than a weak association. However, finding of a large cancer incidence in a
single study must be balanced against the lack of consistency as reflected by null results from
other equally well-designed and well-conducted studies. In this situation, the positive association
of a single study may either suggest the presence of chance, bias, confounding factors, or
different exposure conditions. On the other hand, evidence of weak but consistent associations
across several studies suggests either causality or that the same confounder may be operating in
all of these studies.
If information is available to consider the mode of action for carcinogenicity, the carcinogenicity
assessment will evaluate that information and draw conclusions that influence the dose-response
method for the substance. If the evidence is sufficient to support a conclusion of nonlinear dose-
response, then the information on carcinogenicity may be considered in combination with the
information on other effects in deriving a reference value such as an RfC (see section 12.4).
Otherwise, a linear dose-response approach leading to a predictive risk estimate, such as an IUR,
will usually be pursued. If the information supports it, the guidelines also accommodate the
development of a non-linear predictive risk estimate.
April 2004 Page 12-10
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Biological Effects of Carcinogens
Carcinogens are chemicals that induce cancers. Examples include:
• 4-Aminobyphenol, which targets the bladder;
• Benzene, which targets the tissue that make white blood cells;
• Asbestos, which targets the lung's tissue;
• Benzidene, which targets the bladder;
• Beryllium, which targets the lungs;
• Chromium, which targets the respiratory tract;
• Radionucleotides, which targets bone marrow and the lungs; and
• Vinyl chloride, which targets the liver.
There are various types of carcinogens, including:
• Primary Carcinogens: A primary carcinogen is a substance that is carcinogenic as it occurs in the
environment.
• Procarcinogen: A procarcinogen is a substance that becomes carcinogenic only after conversion
from some benign form. Most environmental carcinogens are of this type.
• Cocarcinogen: A cocarcinogen is a substance that is not carcinogenic by itself, but potentiates the
carcinogenic effect of other chemicals.
Chemicals also can serve as mutagens, causing changes in genetic material that can disrupt cell
function and lead to cancer or other health problems.
v y
12.2.2 Identification of Critical Effect(s) - Non-Cancer Endpoints
As part of the characterization of the available information on non-cancer health effects (or
including cancer, if a threshold mode of action has been established), the targets of chemical
toxicity within the body are identified, along with what have been termed "critical effects"
associated with the toxicity. A critical effect is described as "either the adverse effect that first
appears in the dose scale as dose is increased, or as a known precursor to the first adverse effect."
Underlying this designation is the assumption that if the critical effects are prevented, then all
other adverse effects observed at higher exposure concentrations or doses are also prevented/0'
Note that not all observed effects in toxicity studies are considered adverse effects. The
identification of the critical effect(s) depends on a comprehensive review of the available data
with careful consideration of the exposure conditions associated with each observed effect, so
that comparisons of effect levels or potential reference values are made on a common basis (see
Section 12.4). A more comprehensive discussion of hazard identification and the evaluation of
the underlying database for non-cancer effects is included in the EPA documents Methods for
Derivation of Inhalation Reference Concentrations and Application of Inhalation Dosimetry
(1994) and^4 Review of the Reference Dose and Reference Concentration Process (2002).5
A similar, more recent term, "key event," is defined as "an empirically observed precursor" to an adverse
effect (e.g., liver cancer or other liver toxicity) consistent with a particular mode of action. The phrase "mode of
action" refers to the way a given chemical may act in the body to initiate one or more adverse effects.
April 2004 Page 12-11
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12.3 Dose-Response Assessment for Cancer Effects
The process for deriving a quantitative dose-response estimate for cancer (e.g., a cancer slope
factor) involves the following three steps:
1. Determination of the concentration associated with the point of departure or POD (Section
12.3.1);
2. Derivation of the human equivalent concentration corresponding to the POD (Section
12.3.2); and
3. Extrapolation from the POD (expressed as human equivalent concentration) to derive
carcinogenic potency estimates (Section 12.3.3).
The first two steps are also performed in the derivation of reference values such as the RfC
(Exhibit 12-7); in that case, these steps are followed by the application of uncertainty factors (see
Section 12.4).
Exhibit 12-7. Steps involved in deriving an RfC or IUR From an Animal Study
POD from Animal Study Discontinuous Exposure
Biologically-based Dose-
Response Model
Duration Adjustment
POD (Animal)fldjusted
Continuous Exposure
Interspecies Extrapolation
for linear default,
slope to origin
Uncertainty Factors
HEC- human equivalent concentration
April 2004
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12.3.1 Determination of the Point of Departure (POD)
Dose-response assessment for cancer and other effects begins with identification of the point of
departure (an exposure concentration or intake) from the experimental data. This point (in terms
of its human equivalent), while within the range of observation, is the point from which
extrapolation begins, either for the purposes of deriving a cancer risk estimate (the IUR) or a RfC
for non-cancer health effects.
/" "\
Example POD for Benzene
EPA's characterization of the carcinogenic effects of benzene was updated in 1998. The IUR for
benzene is based on epidemiologic studies showing clear evidence of a causal association between
exposure to benzene and leukemia. The specific mechanisms by which benzene and its metabolites
lead to cancer remain uncertain.
EPA selected the Rinsky et al. 1981 epidemiologic study of 1,165 Pliofilm rubber male workers at
three facilities in Ohio as the data set for the dose-response relationship for determining the IUR. The
workers had been employed between 1940 and 1965 and were followed through 1981. Rinsky et. al.
expanded the study to include additional workers and published it in 1987. The Rinsky data suffers -
as many epidemiologic studies do - from uncertainties about exposure levels in the early years. There
are no measurements of benzene in the facilities' air prior to 1946, so exposures for these years must
be estimated.
Using one set of exposure estimates with the Rinsky et al. study, EPA concluded that exposure to
benzene increases the risk of leukemia at a level of 40 ppm-years of occupational exposure (8
hours/day, 5 days/week, 50 weeks/year). Below this number, the shape of the dose-response curve
cannot be determined. Converting the occupational exposure of 40 ppm-years to an equivalent
lifetime of environmental exposure yields 120 ppb, as a POD, below which the shape of the dose-
response curve is uncertain.
EPA decided there is not sufficient evidence to demonstrate that the dose-response relationship below
the POD is non-linear. As a science policy default, EPA assumed low-dose linearity for extrapolation
from the POD to zero. Given a range of plausible exposure estimates for the Rinsky et al. study, the
Agency determined that the benzene inhalation unit risk at 1 ug/m3 ranges from 7.1 x 10"3 to 2.5 x 10"2
depending on the exposure estimates and modeling approach used to derive the POD.
Source: U.S. EPA. 1998. Carcinogenic Effects of Benzene: An Update. Office of Research and
Development, National Center for Environmental Assessment, Washington, D.C. EPA/600/P-
97/001F.; Rinsky, R.A., Young, R.J., and Smith, A.B. 1981. Leukemia in benzene workers. American
Journal of Industrial Medicine. 2(3) 217:245.
v y
The POD may be the traditional no observed adverse effect level (NOAEL), lowest observed
adverse effect level (LOAEL), or benchmark concentration (BMC).(d) EPA has recommended
the use of the BMC approach, where possible, because the traditional use of the LOAEL or
NOAEL in determining the POD has long been recognized as having several limitations (and
dNote that the corresponding value for ingestion exposures is the benchmark dose (BMD). This
often is used as the general term for the BMC/BMD process.
April 2004 Page 12-13
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generally is not used in dose-response for cancer effects. In particular, the LOAEL-NOAEL
approach:
• Is limited to one of the doses in the study and thus is dependent on study design;
• Does not account for variability and uncertainty in the estimate of the dose-response
relationship;
• Does not account for the slope of the dose-response curve; and
• Cannot be applied, where there is no NOAEL, except through the application of an
uncertainty factor.
If the dose-response data are of high quality, a mathematical dose-response model maybe fitted
to the data to determine a more precise POD than the NOAEL or LOAEL. When a model is
used, the POD is calculated as the statistical lower confidence limit of the dose at which there is
a low toxic response (usually 5 or 10 percent incidence in populations with an effect or a change
in a physiological measurement indicating adversity).(6) The selection of the response percentage
is intended to coincide with the sensitivity limit of the experimental design or professional
judgment. This calculated POD is called the BMC.
The BMC approach is an alternate way of determining the point of departure for low-dose
extrapolation. It can be used in cancer and noncancer risk assessment as the starting point for
linear low-dose extrapolation, calculation of a margin of exposure, or application of uncertainty
factors for calculating RfCs or other dose-response values. BMC methods involve fitting various
mathematical models for dose-response to reported data and using the different results to select a
BMC that is associated with a predetermined benchmark response, such as a 10 percent increase
in the incidence of a particular lesion or a 10 percent decrease in body weight gain (Exhibit
12-8). EPA has developed the Benchmark Dose Software (BMDS) to facilitate these operations.
BMDS currently offers 16 different mathematical models that can be fit to the laboratory data.
EPA plans to continually improve and expand the BMDS system.6
It is likely that there will continue to be situations that are not amenable to BMC modeling and
for which a NOAEL or LOAEL approach should be used. In some cases, there may be a
combination of benchmark doses and NOAELs to be considered in the assessment of a particular
agent.
12.3.2 Derivation of the Human Equivalent Concentration
Because inhalation toxicity studies typically involve discontinuous exposures (e.g., animal
studies routinely involve inhalation exposures of 6 hours per day, 5 days per week), the POD will
usually need to be extrapolated to a continuous exposure scenario (as appropriate for the RfC and
IUR). This duration adjustment step is essential in interpreting inhalation studies, but is not
routinely necessary for the interpretation of oral exposures. Operationally, this is accomplished
April 2004 Page 12-14
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by applying a concentration-duration product, or C x t product(e) for both the number of hours
ina daily exposure period and the number of days per week that the exposures are performed.
For example, for a POD of 100 mg/m3 derived from an animal study in which animals are
exposed by inhalation for 6 hours per day, 5 days per week, the adjustment to a continuous
3
100 mg/m x — x -= IBmgfm
& 24 7 &
(Equation 12-1)
exposure concentration would consider both hours per day and days per week:
Thus, 18 mg/m3 is the POD concentration adjusted for continuous exposure versus 100 mg/m3
unadjusted. This approach assumes there is no dose-rate effect (i.e., that the same total inhaled
material produces the same effect regardless of the time over which this material was inhaled).
Exhibit 12-8. Example Derivation of Benchmark Dose Level
Log-Logistic Model with 0.95 Confidence Level
0.6
0.5
H 0.4
S
'•c
,2 0.2
0.1
0
Log-Logistic
1
r
BMDLI IBMD
10
20
30
dose
40
50
60
Illustration of the computation of a benchmark dose (BMD) and BMDL (a lower one-sided confidence
limit on the BMD) for an extra risk of 0.10 (as suggested by the BMDS guidance document), using a
one-sided 95 percent confidence interval. A number of models were fit to the data, and the log-logistic
model illustrated provides the best fit to the example data. The predicted curve comes well within the
confidence limits for each data point. Other data and models are illustrated in examples provided in
the BMDS guidance document/6'
e"C x t" is a component of Haber's Law that refers to the default assumption (in lieu of information to the contrary)
that effects observed are related to the cumulative exposure or "area under the curve" (quantified by concentration, C, multiplied
by duration, t). It is noted that when going from a discontinuous inhalation exposure regiment to a continuous exposure, the
result will always be a lower value for concentration, thus providing an automatic margin of protectiveness for chemicals for
which C alone (vs. C x t) may be appropriate, while providing the appropriate conversion for substances for which cumulative
exposure is the appropriate measure.'4'
April 2004
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Exposures documented from human occupational epidemiological studies are most often
reported as 8-hr time-weighted averages (TWAs) and therefore, also are discontinuous.
Adjustment of these exposures is usually done as part of the dosimetric adjustment to derive a
human equivalent concentration (HEC), rather than as a discrete step, and is explained below in
Section 12.3.3. The duration adjustment step also is explicitly incorporated into physiologically
based pharmacokinetic (PBPK) models used to extrapolate an animal or occupational
study-derived POD into an HEC.
After duration adjustment, the POD is converted into a human equivalent concentration
(HEC) from the experimental animal dose. This conversion may be done using default methods
specific to the particular chemical class of concern or more refined methods such as PBPK
modeling.
The Agency's inhalation dosimetry methodology(5) provides a recommended hierarchy, as well as
default generalized procedures for deriving dosimetric adjustment factors (DAFs) for this
extrapolation. Application of DAFs to an animal exposure value yields an estimate of the
corresponding concentration relevant to humans (i.e., the HEC) given differences in physiology
and in the form of the pollutant that influence how the chemical exerts its effect. The DAF
depends on the chemical category (i.e., gas or particle) and whether the adverse effect occurs in
the respiratory tract or outside of the respiratory tract. HECs are derived using DAFs for both
RfC development (noncancer effects) and IUR development (cancer).
/- x
Choice of a Default DAF for Extrapolation from Animal Data
Depends on the Physical and Chemical Properties of the Pollutant
Gases
• Category 1 (effect in respiratory system) - default DAF based on inhalation rate, and surface area
of target portion of respiratory tract
• Category 2 (some characteristics intermediate or common to category 1&3) - default DAF is the
more restrictive of the defaults for category 1 & 3
• Category 3 (systemic effect[s]) - default DAF based on blood:air partition coefficient
Particles
• Respiratory toxicant - default DAF based on fractional deposition, inhalation rate, and surface area
of target portion of respiratory tract
• Systemic toxicant - default DAF based on inhalation rate, body weight, and fractional deposition
Source: U.S. EPA. 1994. Methods for Derivation of Inhalation Reference Concentrations and
Application of Inhalation Dosimetry.(5)
When data are adequate to support it, the preferred EPA approach for calculating a HEC is to use
a chemical-specific PBPK model parameterized for the animal species and regions (e.g., of the
respiratory tract) involved in the toxicity (Exhibit 12-9).
April 2004 Page 12-16
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In PBPK models, the body is subdivided into a series of anatomical or physiological
"compartments" that represent specific organs or tissue and organ groups. The transfer of
chemicals between compartments is described by a set of differential equations. The parameters
of the model are of three types: physiological parameters (such as tissue perfusions or tissue
volumes), physicochemical parameters (such as partition coefficients that describe the degree of
partitioning of a given chemical to a given tissue), and biochemical parameters describing
metabolic processes. The structure of a PBPK model is determined by the intended use of the
model, the biochemical properties of the chemical studied, and the effect site of concern.
Exhibit 12-9. Extrapolation of Inhalation Exposure to Calculate the HEC
Inhalation Exposure
Chemical-specific
PBf K model
HEC
Inhalation Exposure
Exposure conditions
(e.g., mgAn3, hrs/day, days/wk)
Adjust to
continuous exposure
(24 hrs/day, 7 day/v*:)
Application of D AF
(fortoxicokinetics)
HEC
EPA employs a hierarchy of approaches for deriving the human equivalent concentration. Preference
is given to the use of a physiologically-based pharmacokinetic model, followed by intrermediate, less
detailed approaches, which are followed by the default approach, which utilizes a DAF specific to the
type of chemical and how it exerts its effect.
With sufficient data, a PBPK model is capable of calculating internal doses to a target organ in
an animal from any exposure scenario and then estimating what human exposure would result in
this same internal dose (i.e., the HEC). A formal DAF is not calculated in this process; rather,
the model itself serves as a DAF in estimating HECs. However, constructing a PBPK model is
an information-intensive process, requiring much chemical-specific data. Consequently, these
models are usually available for only a subset of chemicals. For example, EPA's IRIS toxicity
assessment for vinyl chloride relies on a PBPK model.
12.3.3 Extrapolation from POD to Derive Carcinogenic Potency Estimates
Observable cancer rates in laboratory or human occupational epidemiologic studies tend to be
several orders of magnitude higher than cancer risk levels that society is willing to tolerate from
involuntary chemical exposures. To obtain observable results, laboratory studies need to be
April 2004
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conducted at exposures usually well above environmentally relevant concentrations. Thus,
extrapolation from the POD-HEC to lower doses is usually necessary. This extrapolation is
performed consistent with the mode of action, if adequately supported. Where the mode of
action supports a biologically-based model and the data set is not rich enough to support a
biologically based model, a non-linear reference concentration approach is employed (see Section
12.4.2). When the data are insufficient to support a mode of action decision, or where the data
support a linear mode of action, a linear extrapolation is employed.
For linear extrapolation, a straight line is drawn from the point of departure expressed as a
human equivalent dose to the origin (i.e., zero incremental dose, zero incremental response) to
give an incremental probability dose unit. That is, the slope of the line expresses extra risk per
dose unit (e.g., the IUR, expressed as extra risk per ug/m3 of lifetime exposure). EPA's 1999
proposed guidelines'^ for carcinogen risk assessment recommend the use of the lowest effective
dose using a 10 percent response level (LED10) (as estimated by the lower one-sided confidence
limit on the benchmark concentration [or BMCL10]) as the POD for linear extrapolation. This
approach is to draw a straight line between the estimated point of departure, generally, as a
default, the LED10. The LED10 is the lower 95 percent limit on a dose that is estimated to cause a
10 percent response. The linear extrapolation approach to assessing risk is considered generally
conservative of public health, including sensitive subpopulations, in the absence of specific
information about the extent of human variability in sensitivity to effects.
The inhalation cancer dose-response value derived by linear extrapolation is the IUR. It is
presented as an upper-bound estimate of the excess cancer risk resulting from a lifetime
(assumed 70-year) of continuous exposure to an agent at a concentration of 1 ug/m3 in air. As
illustrated previously in Exhibit 12-2(A), risk is the product of the slope and the estimated
exposure. The IUR is a plausible upper-bound estimate of the risk (i.e., the risk is not likely to be
higher but may be lower and may be zero). When adequate human epidemiology data are
available, maximum likelihood estimates may be used instead of upper bounds to generate the
IUR. When only animal data are available and linear extrapolation is used, the IUR is derived
from the largest linear slope that is consistent with the data (within the upper 95 percent
confidence limit). In other words, the true risk to humans, while not identifiable, is not likely to
exceed the upper-bound estimate (the IUR), and is likely to be lower. This means that any
estimate of risk for air toxics using an IUR is likely to be protective of all potentially exposed
populations. In addition, this means that air toxics risk estimates are likely to be conservative,
that is, protective of public health.
The evidence for the carcinogenic mode of / „. , „„ TTTr> ,
° Risk = EC x IUR, where
action may lead to a conclusion that the
EC = lifetime estimate of continuous inhalation
exposure to an individual air toxic
IUR = the corresponding inhalation unit risk
estimate for that air toxic
dose-response relationship is nonlinear,
with response falling much more quickly
than linearly with dose, or may be most
influenced by individual differences in
sensitivity. In some cases this may be due N ^
to the mode of carcinogenic action being a
secondary effect of toxicity or of an induced physiological change that is itself a threshold
phenomenon. EPA does not generally try to distinguish between modes of action that might
imply a "true threshold" from those with a nonlinear dose-response relationship. Except in
unusual cases where extensive information is available, it is not possible to distinguish between
April 2004 Page 12-18
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these empirically. Therefore, as a matter of science policy, nonlinear probability functions are
only fitted to the response data to extrapolate quantitative low-dose risk estimates when the
carcinogenic mechanism of the toxicant is very well-understood. When the evidence indicates a
non-linear dose response function containing a significant change in slope, and alternate
nonlinear approach may be considered. For example, when carcinogenesis can be shown to be a
secondary effect of threshold toxicity, the EPA draft carcinogen guidelines recommend
derivation of a reference concentration.
12.4 Dose-Response Assessment for Derivation of a Reference Concentration
The reference concentration is defined as an estimate (with uncertainty spanning perhaps an order
of magnitude) of a continuous inhalation exposure to the human population (including sensitive
sub-populations) that is likely to be without an appreciable risk of deleterious effects during a
lifetime. The RfC is expressed as a chronic exposure level to the chemical in ambient air (in
units of milligrams of the substance per cubic meter of air, or mg/m3). This value is usually
derived for use with effects other than cancer. But when a chemical's carcinogenicity has been
shown to be associated with a nonlinear mode of action (see Agency's Cancer Guidelines)/4' a
reference concentration may be derived for use with all effects, including cancer.
Inherent in the derivation of a reference concentration is the recognition of an exposure level
likely to be without an appreciable risk of adverse effects (e.g., a sub-threshold level for adverse
effects). The objective of this type of dose-response assessment, then, is to estimate that
exposure level for humans. The RfC is derived after a thorough review of the health effects
database for an individual chemical and identification of the most sensitive and relevant endpoint
(the "critical effect") along with the principal study(ies) demonstrating that endpoint. In addition
to an analysis of the study data available for the chemical, risk assessors also use uncertainty
factors to account for differences in sensitivity between humans and laboratory animals, the
possibility of heightened sensitivity of some population groups (e.g., people with respiratory
disease, very young children, the aged), and any limitations of the database. The methodology
for derivation of an inhalation reference concentration is described in detail in EPA's Methods
for Derivation of Inhalation Reference Concentrations and Application of Inhalation
Dosimetry.^
The first part of this type of assessment, which involves a careful qualitative and quantitative
analysis of the study data, parallels that performed for linear cancer dose-response assessment
(i.e., derivation of the point of departure in terms of a human equivalent concentration
[PODHEC]). The qualitative analysis is described in Section 12.2.2, while the quantitative
analysis is described in Sections 12.3.1 and 12.3.2. The latter part of this type of assessment
involves the application of uncertainty factors to address limitations of the data used (e.g., the
factors raised above).
In IRIS, EPA includes with each RfC a statement of high, medium, or low confidence based on
the completeness of the database for that substance. High confidence RfCs are considered less
likely to change substantially with the collection of additional information, while low confidence
RfCs may be especially vulnerable to change.(5)
April 2004 Page 12-19
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12.4.1 Determination of the Point of Departure and Human Equivalent Concentration
In earlier sections (Section 12.2.2, 12.3.1 and 12.3.2) the analysis of the database and
identification of the critical effect, as well as the derivation of the POD in terms of human
equivalent concentrations are discussed.
In developing a dose-response assessment, toxicologists evaluate the available data for a
substance. Studies of high quality are selected, and the assessment is focused on the most
appropriate studies. As the RfC is a chronic value, preference is given to long-term studies over
short-term ones, to studies using animals that exhibit effects similar to those experienced by
humans, to studies using an appropriate exposure route (e.g., inhalation exposure for developing
an RfC), and to studies showing a clear pattern of increasing frequency or severity of response
with increasing dose. Toxicologists use the information to identify the critical effect (i.e., the
adverse effect that appears at the lowest dose). Afterwards, appropriate human data are chosen
as the basis for the RfC or, if human data are not adequate, data from the most appropriate
species are identified. If this is not known, the data from the most sensitive species is usually
chosen. This analysis is described in Section 12.2.2. The objective in identifying the critical
effect or effects is to identify the effect(s) - among all those associated with exposure to the
chemical of interest - that occur at the lowest exposure and would lead to derivation of the lowest
RfC (Exhibit 12-10).
Exhibit 12-10. Overview to Develop a Reference Concentration
O
TJ
O
Q.
w
0)
tt
n
s.
Liver Toxicity
(Critical Effect)
Tremors
_ Apply
Uncertainty
Factors
/ ....+ Enzyme
T" Change
Human NOEL NOAEL
RfC
LOAEL
Exposure Concentration
The LOAEL (HEC) and NOAEL (HEC) are illustrated with low-dose extrapolation with the
application of uncertainty or modifying factors to derive the human health-protective RfC. Note that
this figure represents data from appropriate animal species.
Using the dose-response relationship for the critical effect, toxicologists identify the POD from
the experimental data. This exposure concentration (in terms of its human equivalent) which
marks the boundary between the range of observation and that of extrapolation, is the point from
April 2004
Page 12-20
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which extrapolation begins for derivation of a RfC. The POD maybe derived from benchmark
modeling (see Section 12.3.1 regarding the derivation of a BMCL). If the data do not meet
requirements for benchmark modeling, the POD is derived by the use of a statistical analysis to
identify the no-observed-adverse-effect-level, or NOAEL, defined as the highest dose level
administered to laboratory animals that did not cause statistically or biologically significant
observable adverse effects after chronic (usually lifetime) exposure in the studied population. In
some cases, a LOAEL is used in the absence of a NOAEL. In either case, the POD is
transformed into a continuous inhalation exposure (e.g., from an intermittent animal exposure, 6
hours/day, 5 days/week) and then into a human equivalent concentration (as described in Section
12.3.2). In order for the appropriate critical effect to be identified, a comparison of PODs across
different endpoints is done in terms of human equivalent concentrations (or potential RfC values,
which incorporate the application of UFs, need to be compared).(5)
S N
Derivation of RfC Using BMC Methodology - 1,3-dichloropropene
A review of the available animal studies indicated changes to the surface cells of the nasal portion of
the respiratory tract as the critical effect for 1,3-dichloropropene. Benchmark modeling was
performed on the data demonstrating this effect. The seven statistical models for dichotomous data
from the Agency's benchmark dose modeling software (BMDS Version.lb) were applied to the
incidence data for the adjusted administered doses. The best model fit was determined by eliminating
all models that did not have a statistically significant goodness-of-fit (p<0.05). The remaining models
were then ranked by best visual fit of the data, especially for the lower doses, as observed in the
graphical output of the Benchmark Dose Software. The model with statistically significant goodness-
of-fit and best visual and statistical fit was used to estimate the BMC at 1 0 percent risk and the 95
percent lower confidence limit of the BMC (the BMCL). The gamma, logistic, multistage, Weibull,
and quantal-quadratic models provided statistically significant fits. The gamma model was the best fit
overall because it provided the best visual fit. This model yielded a BMC10 of 5.9 mg/m3 and a
! 0 of 3. 7 mg/m3.
The BMCL10 was identified as the POD and was adjusted from experimental conditions to a
continuous inhalation exposure value (PODadj). Because the critical target was the nasal mucosa,
algorithms for extrathoracic effects for Category 1 gases were used to adjust continuous animal
exposure concentration to HEC. The PODHEC for a Category 1 gas was derived by multiplying the
animal BMCL10 by an interspecies dosimetric adjustment for gas:respiratory effects in the
extrathoracic area of the respiratory tract. Using default values, the adjustment factor was equal to
0.2. For example, for 1,3-dichloropropene:
PODHEC = BMCL10(HEC) = BMCL10 (adj) x 0.2 = 3.7 x 0.2 = 0.7 mg/m3
The PODHEC was divided by uncertainty factors for interspecies extrapolation (UF of 3) and
intraspecies variation (UF of 1 0) and rounded to one significant figure to yield the RfC for 1,3-
dichloropropene :
RfC = PODHEC / 30 = 0.02 mg/m3
April 2004 Page 12-21
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12.4.2 Application of Uncertainty Factors
The RfC is an estimate derived from the PODHEC for the critical effect (based on either a
BMCLjjEC, NOAELjjEC or LOAELjjEC) by consistent application of UFs. The UFs are applied to
account for recognized uncertainties in the use of the available data to estimate an exposure
concentration appropriate to the assumed human scenario. The general formula for deriving an
RfC from a PODHEC is:
, _ . 10^
RfC (mg!mJ") = — (Equation 12-2)
J - & ^ UF
A UF of 10, 3, or 1 is applied for each of the following extrapolations used to derive the RfC (see
Exhibit 12-11):
• Animal to human;
• Human to sensitive human populations;
• Subchronic to chronic;
• LOAEL to NOAEL; and
• Incomplete to complete database.
The UFs are generally an order of magnitude (10), although incorporation of dosimetry
adjustments or other information may result in the use of reduced UFs for RfCs (3 or 1). The
composite UF applied to an RfC will vary in magnitude depending on the number of
uncertainties involved; however, an RfC will not be derived when use of the data involves more
than four areas of extrapolation. The composite UF when four factors are used generally is
reduced from 10,000 to 3,000 in recognition of the lack of independence and the conservatism of
these factors.
The 2002 Agency review of the reference dose (RfD)/reference concentration process(2)
encouraged the development of guidance in the area of chemical-specific adjustment factors
(CSAFs). These factors utilize specific data to replace the default UFs for interspecies or inter-
individual variation. The review panel noted, however, that the CSAF approach for any single
substance is determined principally by the availability of relevant data. For many substances
there are relatively few data available to serve as an adequate basis to replace defaults for
interspecies differences and human variability with more informative CSAFs.
Because of this procedure to address the lack of information on the translation from experimental
data to a human scenario, the resulting RfC for many HAPs is on the order of 100 to 300 times
lower than the NOAEL actually observed in the animal testing (see Exhibit 12-12). This reflects
the lowering of the RfC to address the uncertainties in the extrapolations mentioned above. For
those HAPs that have had their effects well documented in human studies, the RfC may be much
closer to the highest concentration at which an adverse effect was not observed (e.g., within a
factor of 3 to 10).
April 2004 Page 12-22
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Exhibit 12-11. Uncertainty Factors Used in the Derivation of an Inhalation RfC
Standard Uncertainty Factors
Processes Considered in UF Purview
A = Animal to human
Extrapolation from valid results of long-term studies
on laboratory animals when results of studies of
human exposure are not available or are inadequate.
Intended to account for the uncertainty in
extrapolating laboratory animal data to the case of
average healthy humans.
Pharmacokinetics/Pharmacodynamics
Relevance of laboratory animal model
Species sensitivity
H = Human to sensitive human
Extrapolation of valid experimental results for
studies using prolonged exposure to average healthy
humans. Intended to account for the variation in
sensitivity among the members of the human
population.
Pharmacokinetics/Pharmacodynamics
Sensitivity
Differences in mass (children, obese)
Concomitant exposures
Activity Pattern
Does not account for idiosyncrasies
S = Subchronic to chronic
Extrapolation from less than chronic exposure results
on laboratory animals or humans when there are no
useful long-term human data. Intended to account
for the uncertainty in extrapolating from less than
chronic NOAELs to chronic NOAELs.
Accumulation/Cumulative damage
Pharmacokinetics/Pharmacodynamics
Severity of effect
Recovery
Duration of study
Consistency of effect with duration
L = LOAEL to NOAEL
Derivation from a LOAEL instead of a NOAEL.
Intended to account for the uncertainty in
extrapolating from LOAELs to NOAELs.
Severity
Pharmacokinetics/Pharmacodynamics
Slope of dose-response curve
Trend, consistency of effect
Relationship of endpoints
Functional vs histopathological evidence
Exposure uncertainties
D = Incomplete to complete data
Extrapolation from valid results in laboratory animals
when the data are "incomplete". Intended to account
for the inability of any single laboratory animal study
to adequately address all possible adverse outcomes
in humans.
Quality of critical study
Data gaps
Power of critical study/supporting studies
Exposure uncertainties
Source: U.S. EPA. 1994. Methods for Derivation of Inhalation Reference Concentrations and
Application of Inhalation Dosimetry.(5>
April 2004
Page 12-23
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Exhibit 12-12. Examples of the Use of Uncertainty Factors in Deriving RfCs
RfC from NOAEL
Example: Diesel Engine Emissions
RfC from LOAEL
Example: Toluene
Toxicity data:
144 ug chemical/m3 air (NOAELjjEC from chronic
rodent study)
Uncertainty factors: 3 x 10 = 30
3 = animal-to-human extrapolation
10 = human to sensitive human subpopulations
RfC = 144/30 = 4.8 ng/m3 = 0.005 mg/m3
Toxicity data:
119 mg chemical/m3 air (LOAELjjEC from chronic
occupational study)
Uncertainty factors: lOx 10x3 = 300
10 = human to sensitive human subpopulations
10 = LOAEL-to-NOAEL extrapolation
3 = database deficiencies
RfC = 119/300 mg/m3 = 0.4 mg/m3
NOAELjjEC = No-Observed-Adverse-Effect Level (Human Equivalent Concentration)
LOAELjjEC = Lowest-Observed-Adverse-Effect Level (Human Equivalent Concentration)
Source: EPA's IRIS database http://www.epa.gov/IRIS/.
In some of the older IRIS assessments a "modifying factor" may have been applied in addition to
the traditional uncertainty factors. It had been used with professional judgement when it was
determined that another uncertainty factor was needed; its magnitude depended upon the
professional assessment of scientific uncertainties of the study and database not explicitly treated
via the other uncertainty factors.(5) The 2002 Agency review of the RfD/RfC process, however,
recommended against continued use of the modifying factor. It was felt that the traditional
factors could account for any remaining uncertainties/2'
12.5 Sources of Chronic Dose-Response Values
Appendix C provides a current listing of appropriate chronic dose-response values (i.e., RfCs or
comparable values and lURs) for HAPs.(f) References for acute exposure levels are provided
below in Exhibit 12-13. Hazard identification and dose-response assessment information for
chronic exposure, presented in Appendix C, was obtained from various sources and prioritized
according to (1) conceptual consistency with EPA risk assessment guidelines, and (2) level of
review received. The prioritization process was aimed at incorporating into our assessments the
best available science with respect to dose-response information. The sources listed below were
used, and provide this information for chemicals beyond the 188 Clean Air Act hazardous air
pollutants listed in Appendix C.
• U.S. Environmental Protection Agency (EPA). EPA has developed dose-response
assessments for chronic exposure to many pollutants. These assessments typically specify an
RfC (to protect against effects other than cancer) and/or IUR (to estimate the probability of
As noted earlier, see http://www.epa.gov/ttn/atw/toxsource/summary.html for a current listing of this
information.
April 2004
Page 12-24
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contracting cancer). Background documents, particularly for the more recent files, also
contain information on physical and chemical properties, toxicokinetics, and hazard
characterization. EPA disseminates dose-response assessment information in several forms,
based on the level of review. Dose-response assessments that have achieved full intra-agency
consensus are incorporated in the Integrated Risk Information System (IRIS), which is
regularly updated and available on-line (www.epa.gov/iris). All IRIS assessments since 1996
also have undergone independent external peer review. In the past, dose-response
assessments for some substances were prepared by the EPA Office of Research and
Development, but were never submitted for EPA consensus. EPA has assembled the results
of many such assessments in the Health Effects Assessment Summary Tables (HE AST).
Although the values in HEAST have undergone some review and have the concurrence of
individual Agency program offices, they have not had enough review to be recognized as
Agency-wide consensus information. In addition, since HEAST has not been updated since
1997, other sources described here are, for many chemicals, more reliable.
• Agency for Toxic Substances and Disease Registry (ATSDR). ATSDR, which is part of
the US Department of Health and Human Services, develops and publishes Minimum Risk
Levels (MRLs) for many toxic substances. The MRL is defined as an estimate of daily
human exposure to a substance that is likely to be without an appreciable risk of adverse
effects (other than cancer) over a specified duration of exposure. MRLs are derived for acute
(1-14 days), intermediate (>14-364 days), and chronic (365 days and longer) exposures by
inhalation and oral routes. ATSDR describes MRLs as substance-specific estimates to be
used by health assessors to select environmental contaminants for further evaluation. MRLs
are presented with only one significant figure and are considered to be levels below which
contaminants are unlikely to pose a health threat. Exposures above an MRL do not
necessarily represent a threat, and MRLs are therefore not intended for use as predictors of
adverse health effects or for setting cleanup levels. The MRL data undergo a rigorous review
process, including internal ATSDR review, peer reviews, and public comment periods.
Appendix C shows the ATSDR chronic MRL where no IRIS value is available, because the
MRL's concept, definition, and derivation are philosophically consistent (though not
identical) with EPA's guidelines for assessing noncancer effects. ATSDR publishes MRLs as
part of pollutant-specific toxicological profile documents, and also in regularly-updated
on-line tables.7
• California Environmental Protection Agency (CalEPA). The CalEPA Office of
Environmental Health Hazard Assessment (OEHHA) has developed dose-response
assessments for many substances, based both on carcinogenicity and health effects other than
cancer. The process for developing these assessments is similar to that used by EPA to
develop IRIS values and includes significant external scientific peer review. The non-cancer
information includes inhalation health risk guidance values expressed as chronic inhalation
reference exposure levels (RELs). CalEPA defines the REL as a concentration level at (or
below) which no health effects are anticipated, a concept that is substantially similar to
EPA's approach to non-cancer dose-response assessment. Appendix C shows the chronic
REL (including both final and proposed values) where no IRIS RfC/RfD or ATSDR MRL
exists. CalEPA's quantitative dose-response information on carcinogenicity by inhalation
exposure is expressed in terms of the IUR, defined similarly to EPA's IUR. Appendix C
shows specific CalEPA UREs where no IRIS values exist. CalEPA's dose response
assessments for carcinogens and noncarcinogens are available on-line.8
April 2004 Page 12-25
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• International Agency for Research on Cancer (IARC). The IARC, a branch of the World
Health Organization, coordinates and conducts research on the causes of human cancer and
develops scientific strategies for cancer control. The IARC sponsors both epidemiological
and laboratory research, and disseminates scientific information through meetings,
publications, courses and fellowships. As part of its mission, the IARC assembles evidence
that substances cause cancer in humans and issues judgments on the strength of evidence.
lARC's categories are Group 1 (carcinogenic in humans), Group 2A (probably carcinogenic),
Group 2B (possibly carcinogenic), Group 3 (not classifiable), and Group 4 (probably not
carcinogenic). The categorization scheme maybe applied to either single chemicals or
mixtures; however, IARC does not develop quantitative dose-response metrics such as
UREs,. IARC's categories for substances are included in Appendix C to support or augment
EPA's weight-of evidence (WOE) determinations, which do not cover all substances and in
some cases may be out-of-date. The list of IARC evaluations to date is available on-line
(http://l 93.51.164.11/monoeval/grlist.html).
Additionally, the EPA has compiled fact sheets for the 188 CAA hazardous air pollutants and
makes them available on the Air Toxics website (http://www.epa.gov/ttn/atw/hapindex.htmn.
This collection is called the Health Effects Notebook for Hazardous Air Pollutants, and
provides for each HAP a summary of available information in the following categories: hazard
summary, physical properties, uses, sources and potential exposure, and health hazard
information. These fact sheets are useful for describing hazards associated with the 188 HAPs.
12.6 Acute Exposure Reference Values
Many air pollutants can cause adverse health effects after acute or short-term exposures lasting
from a few minutes to several days. For some pollutants, acute exposures may be of greater
concern than chronic exposures. The severity of effects from acute exposures may vary widely.
Agency-wide guidance on how to assess toxic effects from short-term exposures is currently
being developed. This guidance for Acute Reference Exposure (ARE) levels is intended to assist
acute risk assessment activities. A variety of other short-term, acute exposure limits are also
described in Exhibit 12-12.9 Appendix C provides a current listing of acute dose-response values
for HAPs.
Methods for dose-response assessment of acute exposures are usually similar to the approach for
chronic exposure, with their derivation involving the identification of a "critical effect,"
determination of aNOAEL or comparable value for that effect, and application of uncertainty
factors (e.g., animal to human population). However, the process by which most acute inhalation
dose-response assessment values are derived differs from the chronic RfC methodology in two
important ways. First, "acute" may connote exposure times varying from a few minutes to two
weeks. The time frame for the value is critical, because the safe dose (or the dose that produces
some defined effect) may vary substantially with the length of exposure. Second, some acute
dose-response assessments include more than one level of severity. A typical assessment may
have values for level 1 (at which only mild, transient effects may occur), level 2 (above which
irreversible or other serious effects may occur), and level 3 (above which life-threatening effects
may occur). Therefore, many acute assessments present dose-response assessment values as a
matrix, with one dimension being length of exposure and the other a severity-of-effect category.
April 2004 Page 12-26
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Exhibit 12-13. Examples of Available Short-Term, Acute Exposure Levels
Acronym
Full Name
Group or
Agency
Purpose/Definition
Source/Website
AEGL
Acute
Exposure
Guideline
Level
National Research
Council (NRC)
National
Advisory
Committee
(NAC)
The AEGLs represent short-term threshold or ceiling exposure values
intended for the protection of the general public, including susceptible or
sensitive individuals, but not hypersusceptible or hypersensitive individuals.
The AEGLs represent biological reference values for this defined human
population and consist of three biological endpoints for four different single
emergency (accidental) exposure periods (30 minutes, 1 hour, 4 hours, and 8
hours). In some instances, AEGLs also are developed for 5 or 10 minutes.
The biological endpoints are defined as follows:
• AEGL-1 is the airborne concentration (expressed as parts per millions
[ppm] or milligrams [mg]/meters [m] ) of a substance at or above which it
is predicted that the general population, including "susceptible" but
excluding "hypersusceptible" individuals, could experience notable
discomfort. Airborne concentrations below AEGL-1 represent exposure
levels that could produce mild odor, taste, or other sensory irritations.
• AEGL-2 is the airborne concentration (expressed as ppm or mg/m ) of a
substance at or above which it is predicted that the general population,
including "susceptible" but excluding "hypersusceptible" individuals,
could experience irreversible or other serious, long-lasting effects or
impaired ability to escape. Airborne concentrations below the AEGL-2
but at or above AEGL-1 represent exposure levels that may cause notable
discomfort.
• AEGL-3 is the airborne concentration (expressed as ppm or mg/m ) of a
substance at or above which it is predicted that the general population,
including "susceptible" but excluding "hypersusceptible" individuals,
could experience life-threatening effects or death. Airborne
concentrations below AEGL-3 but at or above AEGL-2 represent
exposure levels that may cause irreversible or other serious, long-lasting
effects or impaired ability to escape.
http://search.nap.edu/books/
0309072948/html/
ARE
Acute
Reference
Exposure
U.S.
Environmental
Protection
Agency
The ARE is an informed estimate of the highest inhalation exposure
(concentration and duration) that is not likely to cause adverse effects in a
human population, including sensitive subgroups, exposed to that scenario,
even on an intermittent basis.10 For these purposes, acute exposures are
single continuous exposures lasting 24 hours or less; AREs may be derived
for any duration of interest within that period. "Intermittent" implies
sufficient time between exposures such that one exposure has no effect on the
health outcome produced by the next exposure. EPA is in the process of
finalizing the methodology for development of AREs.
April 2004
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Exhibit 12-13. Examples of Available Short-Term, Acute Exposure Levels
Acronym
Full Name
Group or
Agency
Purpose/Definition
Source/Website
BEI
Biological
Exposure
Indices
American
Conference of
Governmental
Industrial
Hygenists
BEIs® are health-based values for use by industrial hygienists in making
decisions regarding safe levels of exposure to various chemical and physical
agents found in the workplace.
http://www.acgih.org/TLV/
CEEL
Community
Emergency
Exposure
Level
National Research
Council (NRC)
National
Advisory
Committee
(NAC)
CEELs are ceiling exposure values for the public applicable to emergency
exposures of foreseeable magnitude and duration, usually not exceeding 1
hour. Three CEELs were established:
• CEEL-1: Concentration above which discomfort, for example eye and
nose irritation or headaches, becomes increasingly common;
• CEEL-2: Concentration above which disability, for example, severe eye
or respiratory irritation, becomes increasingly common;
• CEEL-3: Concentration above which death or life-threatening effects, for
example, pulmonary edema, cardiac failure, or cancer, become
increasingly common.
Guidelines for Developing
Community Emergency
Exposure Levels for
Hazardous Substances
(NRC, 1993)
EEGL
Emergency
Exposure
Guidance
Level
NAS Committee
on Toxicology
Exposure levels judged to be acceptable for military personnel performing
tasks during emergency situations. Not considered safe exposure level for
routine or normal operations.
ERPG
Emergency
Response
Planning
Guideline
American
Industrial
Hygiene
Association's
(AIHA)
Emergency
Response
Planning
Committee
These guidelines are intended for application by persons trained in
emergency response planning.
ERG-1: The maximum concentration in air below which it is believed nearly
all individuals could be exposed for up to one hour without experiencing
other than mild transient adverse health effects or perceiving a clearly defined
objectionable odor.
ERG-2: The maximum concentration in air below which it is believed nearly
all individuals could be exposed for up to one hour without experiencing or
developing irreversible or other serious health effects or symptoms that could
impair their abilities to take protective action.
ERG-3: The maximum concentration in air below which it is believed nearly
all individuals could be exposed for up to one hour without experiencing or
developing life-threatening health effects.
http://www.bnl.gov/scapa/er
pgpref.htm
http://www.bnl.gov/scapa/sc
apawl.htm
IDLH
Immediately
Dangerous to
Life or Health
Concentration
National Institute
for Occupational
Safety and Health
(NIOSH)
An immediately dangerous to life or health condition is one "that poses a
threat of exposure to airborne contaminants when that exposure is likely to
cause death or immediate or delayed permanent adverse health effects or
prevent escape from such an environment. The purpose of establishing an
IDLH is to ensure that the worker can escape from a given contaminated
environment in the event of failure of the respiratory protection equipment.
NIOSH Respirator Decision
Logic [NIOSH 1987],
http: //www. cdc. g o v/nio sh/id
Ih/intridl4 .html
April 2004
Page 12-28
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Exhibit 12-13. Examples of Available Short-Term, Acute Exposure Levels
Acronym
Full Name
Group or
Agency
Purpose/Definition
Source/Website
LOC
Level of
Concern
U.S.
Environmental
Protection
Agency, Federal
Emergency
Management
Agency, U.S.
Department of
Transportation
Defined by the Technical Guidance for Hazards Analysis (a guide developed
to assist in planning for accidental chemical releases). As the concentration
of an extremely hazardous substances in air above which there may be
serious irreversible health effects or death as a result of a single exposure for
a relatively short period of time. In the 1987 Technical Guidance for Hazards
Analysis document, an LOC was estimated by using one-tenth of the IDLH
level published by the National Institute for Occupational Safety and Health.
For the purposes of offsite consequence analysis performed as part of
accidental release requirements under Section 11 2(r) of the CAA, this value is
superceded by ERPG-2 values as available, and the Agency intends to
supercede those values with AEGL-2 values as they are developed and
adopted.
Technical Guidance for
Hazards Analysis.
Emergency Planning for
Extremely Hazardous
Substances. (USEPA,
FEMA, USDOT, 1987).
61 FR 31672;June 20,1996
MRL
Acute
Minimum
Risk Levels
U.S. Agency for
Toxic Substances
and Disease
Registry
(ATSDR)
The MRL is an estimate of human exposure to a substance that is likely to be
without an appreciable risk of adverse effects (other than cancer) over a
specified duration of exposure, and can be derived for acute exposures by the
inhalation and oral routes. Unlike the one-hour focus of most of the other
values listed here, acute MRLs are derived for exposures of 1 to 14 days
duration.
http://www.atsdr.cdc.gov/mr
ls.html
REL
Reference
Exposure
Level
California EPA
Office of
Environmental
Health Hazard
Assessment
(OEHHA)
The acute REL is an exposure that is not likely to cause adverse effects in a
human population, including sensitive sub-populations, exposed to that
concentration for one hour on an intermittent basis. RELs are based on the
most sensitive, relevant, adverse health effect reported in the medical and
toxicological literature. RELs are designed to protect the most sensitive
individuals in the population by the inclusion of margins of safety. Since
margins of safety are incorporated to address data gaps and uncertainties,
exceeding the REL does not automatically indicate an adverse health impact
OEHHA has defined the lowest available acute severity level as the REL.
http://www.oehha.ca.gov/air/
pdf/acuterel.pdf
SPEGL
Short-term
Public
Emergency
Exposure
Guidance
Level
National
Academy of
Sciences (NAS)
Committee on
Toxicology
The NAS develops short-term public emergency exposure guidance levels
(SPEGLs) to apply to the exposures of the general public to contaminants
during airborne chemical releases; SPEGLs are generally set at a level of 0.1
to 0.5 times the EEGL and are measured as 60 minute or 8 hour exposure
time frames.
Criteria and Methods for
Preparing Emergency
Exposure Guidance Level
(EEGL), Short-Term Public
Emergency Guidance Level
(SPEGL), and Continuous
Exposure Guidance Level
(CEGL) Documents. 1986.
National Academy Press,
National Academy of
Sciences ,Washington, D.C.
April 2004
Page 12-29
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Exhibit 12-13. Examples of Available Short-Term, Acute Exposure Levels
Acronym
Full Name
Group or
Agency
Purpose/Definition
Source/Website
STEL
Short-Term
Exposure
Limit
American
Conference of
Governmental
Industrial
Hygenists
(ACGIH)
STELs are time weighted average (TWA) guidelines for the control of short
term exposure in the workplace. These are important supplements to the
eight-hour TWA exposure standards which are more concerned with the total
intake over long periods of time. Generally, STELs are established to
minimize the risk of the occurrence in nearly all workers of: intolerable
irritation; chronic or irreversible tissue change; and narcosis to an extent that
could precipitate industrial accidents, provided the eight hour TWA exposure
standards are not exceeded. STELs are recommended for those substances
only when there is evidence either from human or animal studies that adverse
health effects can be caused by high short term exposure. STELs are
expressed as airborne concentrations of substances, averaged over a period of
15 minutes.
April 2004
Page 12-30
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12.7 Evaluating Chemicals Lacking Health Reference Values
12.7.1 Use of Available Data Sources
If EPA-derived IRIS assessments are available for the chemicals being examined, these values
should generally be used in the risk assessment. Use of IRIS or other EPA-derived dose-
response values prevents duplication of effort in toxicity assessment and ensures consistency in
the dose-response values among risk assessments. If EPA-derived dose-response values are not
available, the other sources described in Section 12.6 should be given next priority. Use of these
sources in a hierarchical manner has been implemented in tables developed for the 188 hazardous
air pollutants (see Appendix C and http://www.epa.gov/ttn/atw/toxsource/table 1 .pdf). The
Toxicology Excellence for Risk Assessment (TERA) maintains a database of international dose-
response values (see www.TERA.org/iter).
If those sources also lack inhalation dose-response values, then route-to-route extrapolation
(discussed below) may be considered. This approach, however, may be quite detailed, and
requires assistance from a professional toxicologist. If all sources and approaches have been
researched, and no dose-response value is available, the assessor should describe the effects of
the chemical qualitatively and discuss the implications of the absence of the chemical from the
risk estimate in the uncertainty section of the risk assessment.
12.7.2 Route-to-Route Extrapolation
For cases in which appropriate dose-response values are not available for the route of exposure
being considered, but are available for another route, it may be possible to use route-to-route
extrapolation. Route-to-route extrapolation is recommended only from oral to inhaled exposure
and only for carcinogens. The ability to perform quantitative route-to-route extrapolation is
critically dependent on the amount and type of data available. Regardless of the toxic endpoint
being considered, a minimum of information is required to construct plausible dosimetry for the
routes of interest. This information includes both the nature of the toxic effect and a description
of the relationship between exposure and the toxic effect.
Data from other routes of exposure may be useful ( R(mte to r(mte extrapolations should only
be done by qualified toxicologists.
to derive an RfC (for carcinogens only; discussed
below) only when respiratory tract effects and/or
"first pass" effects can be ruled out. First pass
effects are cases where metabolism takes place in the portal-of-entry tissues, prior to entry into
the systemic circulation. The respiratory tract can exhibit a first-pass effect after inhalation.
Unless the first-pass effect and dosimetry are adequately understood, there can be substantial
error introduced in route-to-route extrapolation that does not account for these considerations.
Oral toxicity data should not be used for route-to-route extrapolation in the following cases
(unless these effects can be accounted for in a PBPK model):
• When groups of chemicals have different toxicity by the two different routes (e.g., metals,
irritants, and sensitizers);
• When a first-pass effect by the respiratory tract is expected;
April 2004 Page 12-31
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• When a first-pass effect by the liver is expected;
• When a respiratory tract effect is established, but dosimetry comparison cannot be clearly
established between the two routes;
• When the respiratory tract is not adequately studied in the oral studies; and
• When short-term inhalation studies, dermal irritation, in vitro studies, or characteristics of the
chemical indicate potential for portal-of-entry effects at the respiratory tract, but studies
themselves are not adequate for an RfC development.
The actual impact of exposure by different routes can only be estimated by taking account of
factors that influence absorption at the portal of entry, such as (1) physicochemical characteristics
of the chemical; (2) exposure factors; and (3) physiologic parameters. The preferred method for
performing route-to-route extrapolation involves the development of a PBPK model that
describes the disposition of the chemical for the routes of interest. As previously discussed,
PBPK models account for fundamental physiologic and biochemical parameters and processes
such as blood flow, ventilatory parameters, metabolic capacities, and renal clearance, tailored by
the physicochemical and biochemical properties.
If appropriate toxicity information is not available, a qualitative rather than quantitative
evaluation of the chemical is recommended. The implications of the absence of the chemical
from the risk estimate should be discussed in the uncertainty section.
12.8 Dose-Response Assessment for Mixtures
The recommended approach for assessing risks from exposure to a mixture of pollutants (e.g.,
coke oven emissions, diesel exhaust, etc.) is to utilize a dose-response assessment developed for
that mixture or a mixture judged similar.1112 Where such an assessment is not available, a
component-by-component approach may be employed. There are several commonly used
approaches. Selection among the approaches involves consideration of the similarity of the
mixture components with regard to their toxicological activity. There are a few groups of
lexicologically similar chemicals for which the Agency recommends the use of relative potency
factors (RPFs) or toxicity equivalence factors (TEFs). These factors have been developed by
EPA and other organizations for two classes of compounds: PAHs and dioxins/furans. The
World Health Organization (WHO) has developed TEFs for polychlorinated biphenyls (PCBs) as
an extension of the factors for dioxins/furans (see Exhibit 12-14).
• Polycyclic Aromatic Hydrocarbons (PAHs). EPA has not developed lURs or CSFs for
carcinogenic PAHs other than benzo(a)pyrene. EPA recommends use of a RPF based on the
potency of each compound relative to that of benzo(a)pyrene.13 Although several references
may be found in the literature with proposed RPFs for PAHs, EPA recommends the
following RPF values for seven PAHs, which are classified as B2, probable human
carcinogens:(g)
gCalEPA has developed lURs based on RPFs for several additional PAHs that have been classified as
probably or possibly human carcinogens (e.g., IARC).
April 2004 Page 12-32
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PAH
Benzo(a)pyrene
Benzo(a)anthracene
Benzo(b)fluoranthene
Benzo(k)fluoranthene
Chrysene
Dibenz(a,h)anthracene
Indeno(l ,2,3-c,d)pyrene
RTF
1.0
0.1
0.1
0.01
0.001
1.0
0.1
Thus, for these seven PAHs, the IUR for benzo(a)pyrene is multiplied by the applicable RPF
to derive the IUR.
Dioxins, Furans, and PCBs. For carcinogenic dioxins and furans, the TEF approach has an
underlying assumption of additivity across mixture components. EPA currently recommends
TEFs for specific congeners, rather than isomeric groups (see Exhibit 12-13). TEFs were
determined by inspection of the available congener-specific data and an assignment of an
"order of magnitude" estimate of relative toxicity when compared to 2,3,7,8-TCDD. The
cancer potency of certain dioxin and furan congeners is estimated relative to 2,3,7,8-TCDD
based on other toxicity information that is available for the congeners. Scientific judgment
and expert opinion formed the basis for these TEF values. External review of the toxicity
and pharmacokinetic data utilized in setting these TEF values supported the basic approach
as a "reasonable estimate" of the relative toxicity of polychlorinated dibenzo-dioxins
(PCDDs) and polychlorinated dibenzo-furans (PCDFs).14 TEF values developed by scientific
groups over the past 15 years are provided in Exhibit 12-13. The most recent consensus of
the scientific community (including representation by EPA scientists) is represented by the
WHO 1997 values.
TEFs based on the relative cancer potencies are used to adjust the exposure concentrations of
mixture components, which are subsequently summed into a single exposure concentration
for the mixture. That exposure concentration based on TEFs is then used, along with the
2,3,7,8-TCDD IUR or noncancer reference value, to estimate cancer risks or other health
hazards for the mixture.
April 2004
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Exhibit 12-14. Toxicity Equivalence Factors for Dioxins, Furans and PCBs
Congener
EPA
(1987)15
NATO
(1989)16
WHO
(1994)17
WHO
(1997)18
TCDDs
2,3,7,8-TCDD
1,2,3,7,8-PeCDD
1,2,3,4,5,8-HxCDD
1,2,3,7,8,9-HxCDD
1,2,3,6,7,8-HxCDD
1,2,3,4,6,7,8-HpCDD
1,2,3,4,6,7,8,9-OCDD
1
0.5
0.04
0.04
0.04
0.001
0
1
0.5
0.1
0.1
0.1
0.1
0.001
1
1
0.1
0.1
0.1
0.01
0.0001
TCDFs
2,3,7,8-TCDF
1,2,3,7,8-PeCDF
2,3,4,7,8-HxCDF
1,2,3,4,7,8-HxCDF
1,2,3,7,8,9-HxCDF
1,2,3,6,7,8-HxCDF
2,3,4,6,7,8-HxCDF
1,2,3,4,6,7,8-HpCDF
1,2,3,4,7,8,9-HpCDF
1,2,3,4,6,7,8,9-OCDF
0.1
0.1
0.1
0.01
0.01
0.01
0.01
0.001
0.001
0
0.1
0.05
0.5
0.1
0.1
0.1
0.1
0.01
0.01
0.001
0.1
0.05
0.5
0.1
0.1
0.1
0.1
0.01
0.01
0.0001
PCBs
IUPAC # Structure
77 3,3',4,4'-TCB
81 3,4,4',5-TCB
105 2,3,3',4,4'-PeCB
114 2,3,4,4',5-PeCB
118 2,3',4,4',5-PeCB
123 2',3,4,4',5-PeCB
126 3,3',4,4',5-PeCB
156 2,3,3'4,4',5-HxCB
157 2,3,3',4,4',5'-HxCB
167 2,3',4,4',5,5'-HxCB
169 3,3'4,4'5,5'-HxCB
170 2,2',3,3',4,4',5-HpCB
180 2,2I,3,4,4I,5,5'-HpCB
189 2,3,3',4,4I,5,5I-HpCB
0.0005
-
0.0001
0.0005
0.0001
0.0001
0.1
0.0005
0.0005
0.00001
0.01
0.0001
0.00001
0.0001
0.0001
0.0001
0.0001
0.0005
0.0001
0.0001
0.1
0.0005
0.0005
0.00001
0.01
-
-
0.0001
Source: EPA's dioxin reassessment activities19
April 2004
Page 12-34
-------
References
1. U.S. Environmental Protection Agency. Air Toxics Website: Summary. Updated November
28, 2003. Available at: http://www.epa.gov/ttn/atw/toxsource/summary.html. (Last accessed
March 2004).
2. U.S. Environmental Protection Agency. 2002. A Review of the Reference Dose and
Reference Concentration Process. Risk Assessment Forum, Washington, B.C., 2002.
EPA/630/P-02/002F. Available at:
http://cfpub.epa. gov/ncea/raf/recordisplay.cfm?deid=55365
3. U.S. Environmental Protection Agency. 2002. Office of Research and Development,
National Center for Environmental Assessment. Risk Assessment Guidelines. Updated June
30, 2002. Available at: http://cfpub.epa.gov/ncea/raf/rafguid.htm. (Last accessed March
2004).
4. U.S. Environmental Protection Agency. 1999. Guidelines for Carcinogen Risk Assessment.
Review Draft. Risk Assessment Forum, Washington, D.C., July 1999. NCEA-F-0644.
Available at: http://cfpub.epa.gov/ncea/raf/rafguid.htm
U.S. Environmental Protection Agency. 1986. Guidelines for Carcinogen Risk Assessment.
Federal Register 51(185y33992-43QQ3, September 24, 1986. Available at:
http ://cfpub. epa. gov/ncea/raf/rafguid.htm
U.S. Environmental Protection Agency. 2003. Draft Final Guidelines for Carcinogen Risk
Assessment (External Review Draft), Risk Assessment Forum, Washington, B.C.
NCEA-F-0644A. Available at http://cfpub.epa.gov/ncea/raf/rafguid.htm
5. U.S. Environmental Protection Agency. 1994. Methods for Derivation of Inhalation
Reference Concentrations and Application of Inhalation Dosimetry. Washington, D.C.
U.S. Environmental Protection Agency. 2002. A Review of the Reference Dose and
Reference Concentration Process. Risk Assessment Forum, Washington, D.C. December
2002. EPA/630/P-02/002F. Available at:
http://www.epa.gov/iris/RFD FINAL%5B 1 %5D.pdf (Last accessed April 2004).
6. U.S. Environmental Protection Agency. 2002. Benchmark Dose Software (BMDS). Office
of Research and Development. Updated June 30, 2002. Available at
http://cfpub.epa.gov/ncea/cfm/bmds.cfm. (Last accessed March 2004).
U.S. Environmental Protection Agency. 1996. Benchmark Dose Technical Guidance
Document. Risk Assessment Forum, Washington, D.C., August 1996. EPA/600/P-96/002A.
Available at:
http://www.epa.gov/cgi-bin/claritgw?op-Display&document=clserv:ORD:0603:&rank=4&te
mplate=epa.
7. Agency for Toxic Substances and Disease Registry (ATSDR). 2004. Toxicological Profile
Information Sheet. Updated March 19, 2004. Available at:
http://www.atsdr.cdc.gov/toxpro2.html. (Last accessed March 2004).
April 2004 Page 12-35
-------
Agency for Toxic Substances and Disease Registry (ATSDR). 2004. Minimal Risk Levels
(MRLs) for Hazardous Substances. Updated March 22, 2004. Available at:
http ://www. atsdr. cdc. gov/mrls .html. (Last accessed March 2004).
8. State of California Office of Environmental Health Hazard Assessment. 2003. Air - Hot
Spots Guidelines. Available at: http://www.oehha.ca.gov/air/hot_spots/index.html. (Last
accessed March 2004).
9. Office of Response and Restoration, National Ocean Service, National Oceanic and
Atmospheric Administration. 2002. Occupational Exposure Limits. Updated March 26,
2002. Available at: http://response.restoration.noaa.gov/cameo/locs/worklims.html. (Last
accessed March 2004).
10. The ARE is described in http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=60983.
U.S. Environmental Protection Agency. 1998. An SAB Report: Development of the Acute
Reference Exposure. Science Advisory Board, Washington, B.C., EPA-SAB-EHC-99-005.
November 1998. Available at: http://www.epa.gov/sab/pdf/ehc9905.pdf.
11. U.S. Environmental Protection Agency. 1986. Guidelines for the Health Risk Assessment of
Chemical Mixtures. Risk Assessment Forum, Washington, D.C. EPA/630/R-98/002.
Federal Register 51(185):34014-34025, September 24, 1986.
12. U.S. Environmental Protection Agency. 2000. Supplementary Guidance for Conducting
Health Risk Assessment of Chemical Mixtures. Risk Assessment Forum, Washington, DC,
EPA/630/R-00/002. Available at:
http://www.epa.gov/ncea/raf/pdfs/chem_mix/chem_mix_08_2001 .pdf.
13. U.S. Environmental Protection Agency. 1993. Provisional Guidance for Quantitative Risk
Assessment ofPolycyclic Aromatic Hydrocarbons. EPA/600/R-93/089.
14. Olson, J.R., Bellin, J.S., Barnes, D.G., et al. 1989. Reexamination of data used for
establishing toxicity equivalency factors (TEFs) for chlorinated dibenzo-p-dioxins and
dibenzofurans (CDDs 45 and CDFs). Chemosphere 18(1-6):371-381.
15. U.S. Environmental Protection Agency. 1987. Interim Procedures for Estimating Risks
Associated with Exposures to Mixtures of Chlorinated dibenzo-p-dioxins and -dibenzofurans
(CDDs and CDFs). EPA/625/3-87/012.
16. NATO/CCMS. 1989. Scientific Basis for the Development of International Toxicity
Equivalent Factor (I-TEF) Method of Risk Assessment for Complex Mixtures ofDioxins and
Related Compounds. Report No. 178, December, 1998.
17. Ahlborg, U., Becking, G.C., Birnbaum, L.S., et al. 1994. Toxicity equivalence factors for
dioxin-like PCBs: Report on a WHO-ECEH and IPCS consultation, December 1993.
Chemosphere 28(6): 1049-1067.
18. van Leeuwen, F.X.R. 1997. Derivation of toxic equivalency factors (TEFs) for dioxin-like
compounds in humans and wildlife. Organohalogen Compounds 34:237.
April 2004 Page 12-36
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19. For more information on EPA's dioxin reassessment activities, see: http://cfpub.epa.gov/
ncea/cfm/recordisplav.cfm?deid=55264&CFID=12120688&CFTOKEN=95507561.
April 2004 Page 12-37
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Chapter 13 Inhalation Risk Characterization
Table of Contents
13.1 Introduction 1
13.2 Quantification of Cancer Risk and Noncancer Hazard 4
13.2.1 Cancer Risk Estimates 5
13.2.1.1 Characterization of Individual Pollutant Risk 5
13.2.1.2 Characterization of Cancer Risk from Exposure to Multiple Pollutants
6
13.2.2 Noncancer Hazard Estimates £
13.2.2.1 Characterizing Individual Pollutant Hazard for Chronic Exposures . . . £
13.2.2.2 Characterizing Multiple Pollutant Hazard for Chronic Exposures .... 9
13.2.2.3 Characterizing Hazard for Acute Exposures H
13.2.3 Quantifying Risk From Background Sources 12
13.3 Interpretation and Presentation of Inhalation Cancer Risks and Noncancer Hazards 13.
13.3.1 Presenting Risk and Hazard Estimates 1/7
13.3.2 Exposure Estimates and Assumptions 1/7
13.3.3 Toxicity Estimates and Assumptions 18
13.3.4 Assessment and Presentation of Uncertainty in Risk Characterization \9_
13.3.4.1 Practical Approaches to Uncertainty Assessment 20
13.3.4.2 Presentation of Uncertainty Assessment 23_
13.3.5 Additional Information 23_
References 25
-------
-------
13.1 Introduction
The last component of risk assessment, risk characterization, integrates the information from the
exposure assessment (Chapter 11) and toxicity assessment (Chapter 12), using a combination of
qualitative and quantitative information and including a discussion of uncertainty and
variability/1' The risk characterization and its components should be presented so that the details
of the analysis are transparent, clear, consistent with EPA guidance and policy, and will generally
support the conclusion that the analysis is reasonable for its intended purpose. Risk assessors
aim for the risk summary and risk conclusions to be complete, informative, and useful for
decision-makers. One way of accomplishing this is to make sure that major uncertainties
associated with determining the nature and extent of the risk are identified and discussed.
Risk = / (metric of exposure, metric of toxicity)
Risk characterization combines the information from the
exposure assessment and the toxicity assessment to
provide a quantitative estimate of potential cancer risk
and/or hazard for other adverse effects, along with a
statement of confidence about the data and methods used
EPA has developed several key
policies about how to characterize
and present risk assessment
information. EPA's Policy for Risk
Characterization^ specifies that a
risk characterization "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." The purpose of the memorandum was to ensure that
risk management decisions are well-supported and well-understood, both inside the EPA and
outside the Agency. The confidence in the data, science policy judgments, and the uncertainties
in the database should be clearly communicated. The 1995 Guidance for Risk Characterization
has been updated by the Handbook for Risk Characterization, which provides more background
and approaches to presenting the risk characterization results.(3) Risk assessors may want to
become familiar with the information provided in both the policy and handbook before beginning
a risk assessment.
A 1992 memorandum from EPA's Office of the Administrator provides guidance on describing
risk assessment results/4' This memorandum focuses on communicating the full range of
information used in developing the assessment, rather than providing only point estimates of risk
to the public. The risk characterization guidance and handbook^ recommends presenting a full
and complete picture of risk that includes: a statement of confidence about data and methods
used to develop the assessment; greater consistency and comparability in risk assessment across
EPA programs; and statement of the level of
scientific judgment inherent in risk
management decisions. Information should
be presented on the range of exposures
derived from exposure scenarios using
multiple risk descriptors (e.g., central-
tendency, high-end of individual risk,
population risk, important sub-populations, if
known). For risk management decisions, the
risk estimates are compared to legally
mandated or other risk objectives (see Part V
of this Reference Manual).
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 sub-populations, if
known) consistent with terminology in the
Guidance on Risk Characterization, Agency risk
assessment guidelines, and program-specific
guidance.
EPA Policy for Risk Characterization(2>
April 2004
Page 13-1
-------
Risks are often evaluated initially for (, .,. , r~,, ., xT ,. TZ ~ ... ,^
J Incidence is denned by the National Cancer Institute
individuals within the potentially
exposed population. Population risks for
the exposed population may also be
estimated, which may be useful in
estimating potential economic costs and
benefits from risk reduction. Sensitive
subpopulations should also be considered,
when possible. Estimates of incidence
as "The number of new cases of a disease diagnosed
each year." For example, a State's cancer registry
might report that the statewide 5-year average
incidence of lung cancer (i.e., the average number of
actual people that were diagnosed by a doctor over
the 5 year period) is 700 new cases per 100,000
people (5-year averages are often used to provide an
estimate that is more stable over time). In
also are possible (see Exhibit 13-1). comparison air toxics risk assessments provide only
a theoretical estimate ot the likelihood that an
individual in the exposed population will contract
cancer as a result of exposure over a period of time
(e.g., 50 or 100 years of a facility lifetime).
The potential risks calculated for specific
inhalation exposures are typically
incremental risks; that is, they are
potential risks that are in addition to those
risks already faced by the population under study for reasons other than exposure to air toxics
(e.g., hereditary, lifestyle risks such as smoking). The risk estimates are used to answer questions
concerning the general risks posed to the exposed population, the risk levels of various groups
within the population, and the potential range of risks across the population (e.g., central-
tendency (e.g., average) or high-end (e.g., maximum) risk for individuals within the populations
of interest).
/"N
Steps in an Inhalation Risk Characterization
1. Organize outputs of inhalation exposure and toxicity assessments.
2. Derive inhalation cancer risk estimates and noncancer hazard quotients for each pollutant in each
pathway for each type of receptor being studied.
3. Derive cumulative inhalation cancer risk estimates and noncancer hazards for each receptor for all
chemicals in a pathway and then across pathways.
4. Identify key features and assumptions of exposure and toxicity assessments.
5. Assess and characterize key uncertainties and variability associated with the assessment.
6. Consider additional relevant information (e.g., related studies).
Risk characterization should include a risk summary and risk conclusions that are complete,
informative, and useful for decision-makers, and which clearly identify and discuss the major
uncertainties associated with determining the nature and extent of risk. See references 2 and 3 at the
, end of this chapter for more information.
V. '
Estimated cancer risks and noncancer hazards are generally developed for each chemical to
which people are exposed in the study area and each exposure pathway through which exposure
can occur. The results are then summed in a specific way to provide total estimates of risk and
hazard. The general steps involved in risk characterization are:
• Quantify risks and hazards for each chemical through each pathway for each receptor;
• Review exposure estimates and assumptions;
• Review toxicity estimates and assumptions;
• Assess uncertainties and variability; and
• Consider additional relevant information (e.g., related studies).
April 2004 Page 13-2
-------
Exhibit 13-1. Estimates of Risk
Individual risk. Estimates of cancer risk are usually expressed as a statistical probability represented
in scientific notation as a negative exponent of 10. For example, an additional risk of contracting
cancer of one chance in 10,000 (or one additional person in 10,000) is written as IxlO"4 (or 1E-04).
This means that for every 10,000 people that are exposed, in the way that we have presumed, one of
those people may develop cancer over their lifetime. Likewise, a risk of one person in one million is
written 1 x 1 0"6 (or 1 E-06) and a risk or one in one hundred thousand is written 1 x 1 0"5 (or 1 E-05).
Population Risk. Estimates of cancer risk can be expressed as the number of people in the population
who may have the same risk level (e.g., 1,000,000 people in the exposed population under study may
have ariskof IxlO"6, 2,495 may have a risk of IxlO"5, and 300 may have a risk of IxlO"4).
Incidence. Estimates of cancer risk can be expressed as the incidence of cancer cases in a population.
For example, the estimated incidence of cancer in a population of 500,000 individuals where the
individual risk is IxlO"5 (based on a 100 year exposure scenario) is simply:
Individual Risk
Population Size x - x Exposure Duration; or
Averaging i'ime
Ix 10"5
500,000 Individuals x - x 1 00 Years = uptol New cancer cases
70 Years
Note that since the individual cancer risk value is a lifetime value, it is divided by 70 years (average
lifetime length) prior to multiplying by the exposure period duration (100 years). It is also important
to note the assumptions in this example calculation (e.g., average population size of 500,000
individuals and individual lifetime risk value of 1 x 1 0"5 for the 1 00 year period). Given these
assumptions, these possible seven new cases are the expected number of cases over the total exposure
duration of 1 00 years. If one wanted to estimate the number of new cases per year, simply use an
exposure duration of one year. In our example,
Ix 10"5
500,000 Individuals x - x 1 Year = up to 0.07 ne~w cancer cases
70 Years ^
This points out two problems with using risk estimates to derive incidence estimates. First, a fraction
of a cancer case (which often results from this exercise) is not a very helpful statistic when assessing a
potential air toxics problem. Second, people living in different areas with the same individual risks,
but with very different exposed population sizes can end up with very different incidence rates. For
example, if our population above only had 10,000 people, the incidence rate would have been
predicted to be no more than 0.1 (versus seven). While the first situation indicates a higher potential
population impact, the second situation nevertheless indicates identical individual risk predictions for
members of the population. Both metrics are informative to the risk manager, and reflect different
considerations which may have different weights in different decisions. Other ways of describing risk
to an exposed population are also possible.
April 2004 Page 13-3
-------
Risk estimates in screening-level (Tier 1) analyses typically are deterministic estimates based on
point estimates of exposure and toxicity. Deterministic estimates are useful screening tools in a
tiered analysis, but need to be qualified by transparent discussions of the nature and extent of
uncertainties in the input variables and the subsequent likely impact on the ultimate risk
characterization. Deterministic analyses with appropriate uncertainty characterization can be
used to identify situations of low incremental risk and to focus on areas where additional analysis
might improve the basis for selection of a risk management action. At higher tiers of analyses,
risk assessors commonly describe exposure (and less frequently, toxicity) by probability
distributions rather than by point values and propagate these distributions through the exposure
assessment and risk characterization process. This type of probabilistic analysis, which may
address uncertainty and variability as distinct issues, will result in an estimate of risk that is a
probability distribution rather than a point value. A more detailed discussion of the assessment
and presentation of uncertainty in the risk characterization process is provided in Section 13.3.4.
Probabilistic uncertainty analysis is discussed in Chapter 31.
13.2 Quantification of Cancer Risk and Noncancer Hazard
Quantification of risk and hazard is the / „. . „ , „,. ,, ,. ^.M „
x [ Risk versus Hazard—What's the Difference?
step where exposure concentrations in air
are combined with applicable inhalation
dose-response values. Predictive cancer
risk estimates are presented separately
from noncancer hazard quotients. Risks
are quantified for the pathways, receptors,
and exposure scenarios outlined in the
conceptual site model.
reference concentration associated with the
Information about the distribution of
Risk assessors purposefully use the term risk to mean
the statistical probability of developing cancer over a
lifetime (even if exposure only occurs over a portion
of that lifetime). Noncancer "risks," on the other
hand, are not expressed as a statistical probability of
developing a disease. Rather they are expressed as a
simple comparison of the exposure concentration to a
observable adverse health effects. To help make this
,.,.,, , . . distinction, the potential harm from exposure to
exposure and nsk for the population is an carcmogens 1S called «nsr and the potential harm
important component of risk
characterization. Distributions are often V. 1 _ J
more useful than point estimates.
However, since developing fully distributional estimates of risk is usually out of the scope of
most risk assessments, assessors can provide a sense of the range of risks by developing both
central tendency and high-end estimates.(5)
• Central tendency estimates are intended to give a characterization of risk for the typical
individual in the population. This is usually either based on the arithmetic mean risk
(average estimate) or the median risk (median estimate).
• High-end estimates are intended to estimate the risk that is expected to occur in the upper
range of the distribution (e.g., risk above about the 90th percentile of the population
distribution). For example, the maximum exposed individual (MEI) risk or maximum
individual risk (MIR) might be used to estimate high-end risks.
An evaluation of the uncertainty in the risk descriptors is an important component of the
uncertainty discussion in the assessment. Both quantitative and qualitative evaluations of
uncertainty can be useful to users of the assessment (see Section 13.3.4 and Chapter 31).
April 2004 Page 13-4
-------
13.2.1 Cancer Risk Estimates
Estimated individual cancer risk is expressed as the upper bound probability that a person may
develop cancer over the course of their lifetime as a result of the exposures under study. This
predicted risk is the incremental risk of cancer from the exposure being analyzed that is above
the risk that the individuals in the population have already (i.e., due to non-air toxics related
issues). Due to the nature of the assumptions in their derivation, inhalation unit risks (lURs) are
generally considered to be "plausible upper-bound" estimates of potency. As such, the calculated
risks are usually a conservative estimate (i.e., the true risk maybe lower).
As described above, risks may be estimated for both the central tendency (average exposure) case
and for the high-end (exposure that is expected to occur in the upper range of the distribution)
case. However, for both types of estimates, the same estimate of toxicity (i.e., an IUR or
reference concentration [RfC]) is generally used to calculate the risk. In other words, while the
estimate of exposure may be allowed to vary to derive a sense of the range of exposures in a
population, the same estimate of toxicity is used to calculate risk for both average and high-end
risks. With few exceptions, toxicity values are not currently presented as a range.
Cancer risk characterization typically is performed first for individual air toxics, then is summed
over all of the air toxics to which a person may be exposed at the same time. These steps are
described in separate subsections below.
13.2.1.1 Characterization of Individual Pollutant Risk
For inhalation exposures, chronic cancer risks for individual air toxics are typically estimated by
multiplying the estimate of long-term exposure concentration (EC) by the corresponding IUR for
each pollutant to estimate the potential incremental cancer risk for an individual:
Risk = ECL x IUR (Equation 13-1)
where:
Risk = Cancer risk to an individual (expressed as an upper-bound risk of contracting
cancer over a lifetime);
ECL = Estimate of long-term inhalation exposure concentration for a specific air toxic;
and
IUR = the corresponding inhalation unit risk estimate for that air toxic.
Performing the estimate in this way provides an estimate of the probability of developing cancer
over a lifetime due to the exposure in question. Because of the way this equation is written, the
underlying presumption is that a person is exposed continuously to the ECL for their full lifetime
(usually assumed to be 70 years).(a) The ECL is an estimate of this long-term exposure even
aEPA is currently reviewing methods for assessing cancer risk for less than lifetime exposures occurring in
childhood. EPA's Draft Document Supplemental Guidance for Assessing Cancer Susceptibility from Early-Life
Exposure to Carcinogens (http://www.epa.gov/sab/panels/sgacsrp.html) recommends a change to the current method
for strong mutagens. This document is undergoing public and Science Advisory Board review and will be completed
sometime in the future with consideration of that review. EPA's methods for air toxics assessments will be
consistent with the final document.
April 2004 Page 13-5
-------
though it is probably based on only one year's worth of monitoring data or a modeling run that
covers only one year's worth of time. (As noted in Chapter 11, exposure modeling can be used,
in some cases, to derive a better estimate of the amount of time people interact with
contaminated air. Nevertheless, the probability of developing cancer is still averaged out over
the full lifetime of the individual.)
Estimates of cancer risk are usually expressed as a statistical probability represented in scientific
notation as a negative exponent of 10. For example, an additional risk of contracting cancer of
one chance in 10,000 (or one additional person in 10,000) is written as IxlO"4 (or 1E-04). This
means that for every 10,000 people that are exposed, in the way that we have presumed, one of
those people may develop cancer over their lifetime. Likewise, a risk of one person in one
million is written 1 x 10"6 (or 1E-06) and a risk or one in one hundred thousand is written 1 xlO"5
(or 1E-05).
Because lURs are typically upper-bound estimates, actual risks may be lower than predicted (see
Chapter 12), and the true value of the risk is unknown and may be as low as zero.(5) These
statistical projections of hypothetical risk are intended as screening tools for risk managers and
cannot make realistic predictions of biological effects. Such risk estimates also cannot be used to
determine whether someone who already has cancer is ill because of a past exposure. Part VI of
this volume provides an overview of the Public Health Assessment process used to evaluate
whether past exposures resulted in current illness.
Risks for cancer are generally expressed as individual risks (i.e., the risk borne by an individual
in a larger exposed population). The number of people in the population who have the same risk
level may also be provided (e.g., 1,000,000 people in the exposed population under study have a
risk of 1 x lO'6, 2,495 have a risk of 1 x 10'5, and 300 have a risk of 1 x 10'4). It is also possible to
calculate the number of expected cases of cancer expected over a 70-year period by multiplying
the cancer risk to an individual by the number of individuals; however, even though the
calculation might yield an estimate of incidence, low predicted cancer incidence rates (even
vanishingly small) do not mean that individuals within the population will not get cancer because
of air toxics exposures.
13.2.1.2 Characterization of Cancer Risk from Exposure to Multiple Pollutants
People may receive exposure to multiple chemicals, rather than a single chemical, at the same
time. The concurrent exposure to multiple carcinogens may occur through the same pathway or
across several pathways. With a few exceptions (e.g., coke oven emissions), cancer dose-
response values (e.g., lURs) are usually available only for individual compounds within a
mixture.
The following equation estimates the predicted cumulative incremental individual cancer risk
from multiple substances, and assumes an additive effect from simultaneous exposures to several
carcinogens:
RJSkT = Risk., + Risk2 + .... + Risk; (Equation 13-2)
where:
April 2 004 Page 13-6
-------
RiskT = total cumulative individual pathway-specific cancer risk (expressed as an upper-
bound risk of contracting cancer over a lifetime); and
Risk; = individual risk estimate for the ith substance in the inhalation pathway.
In screening-level assessments of carcinogens for which there is an assumption of a linear dose-
response, the cancer risks predicted for individual chemicals may be added to estimate
cumulative cancer risk. This approach assumes that the risks associated with individual
chemicals in the mixture are additive. In more refined assessments, the chemicals under
assessment may be evaluated to determine whether effects from multiple chemicals are
synergistic (greater than additive) or antagonistic (less than additive), although sufficient data for
this evaluation are usually lacking. In those cases where lURs are available for a chemical
mixture of concern, risk characterization can be conducted on the mixture using the same
procedures used for a single compound. When more than one pathway is involved, the pathway
specific risks are generally summed first, and then summed across pathways. This process is
described in Part IE of this reference manual. Note that for carcinogens being assessed based on
the assumption of nonlinear dose-response, for which an RfC considering cancer as well as other
effects has been derived, the hazard quotient approach will be appropriate (see Section 13.2.2).
Example Calculation to Estimate Cancer Risk (Hypothetical)
A Tier 1 modeling analysis was performed to estimate risk to the maximum exposed individual,
assumed to reside at the point of maximum concentration for ABC Factory. Four FIAPs were
potentially of concern: benzene, dichloroethyl ether, formaldehyde, and cadmium compounds.
Cancer risk estimates were obtained for each HAP by multiplying the estimated annual average EC by
the IUR for each HAP. The resulting upper bound cancer risk estimates ranged from 2xlO"6 (benzene,
formaldehyde) to 8><10"4 (dichloroethyl ether). The cancer risk estimates for each HAP were summed
to obtain an estimate of total inhalation cancer risk (9><10"4). Note that 97 percent of the estimated
total risk results from dichloroethyl ether, and that more than 99 percent results from dichloroethyl
ether and cadmium compounds. In this hypothetical example, the risk assessor would need to decide
which HAPs to carry to higher tiers by weighing the small proportion of risk posed by benzene and
formaldehyde against the fact that these risks nevertheless exceeded one in one million.
HAP
Benzene
Dichloroethyl ether
Formaldehyde
Cadmium compounds
Total
EC
Hg/m3
0.3
2.5
0.2
0.01
IUR
l/(Hg/m3)
7.8 x lO'6
3.3 x 1Q-4
1.3 x ID'4
1.8 x ID'3
Cancer Risk
Estimate*"'
2 x lO'6
8 x ID'4
2 x lO'6
1 x lO'5
9 x ID'4
Percent of
Total Risk
<1%
97%
<1 %
2%
(a) Standard rules for rounding apply which will commonly lead to an answer of one significant figure
in both risk and hazard estimates. For presentation purposes, hazard quotients (and hazard indices)
and cancer risk estimates are usually reported as one significant figure.
April 2004
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13.2.2 Noncancer Hazard Estimates
For noncancer effects (as well as carcinogens being assessed based on the assumption of
nonlinear dose-response), exposure concentrations are compared to RfCs, which are estimates
(with uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposure to
the human population (including sensitive sub-populations) that is likely to be without an
appreciable risk of deleterious noncancer effects during a lifetime (see Chapter 12).
13.2.2.1 Characterizing Individual Pollutant Hazard for Chronic Exposures
For inhalation exposures, noncancer hazards are estimated by dividing the estimate of the chronic
inhalation EC by the RfC to yield a hazard quotient (HQ) for individual chemicals:
HQ = ECC •*• RfC (Equation 13-3)
where:
HQ = the hazard quotient for an individual air toxic;
ECC = estimate of chronic inhalation exposure to that air toxic; and
RfC = the corresponding reference concentration for that air toxic.
In screening inhalation risk assessments, which are routinely built around a particular year's
estimate of emissions, the exposure estimate is usually based on an assumption of continuous
long-term exposure using an annual average as the estimate of exposure concentration. A more
refined assessment (e.g., by use of an exposure model) may generate an estimate of a more
realistic exposure (e.g., by the application of an exposure model or refined emissions estimates
over the longer time period).
Based on the definition of the RfC, an HQ less than or equal to one indicates that adverse
noncancer effects are not likely to occur, and thus can be considered to have negligible hazard.
Unlike cancer risks, however, HQs greater than one are not statistical probabilities of harm
occurring. Instead, they are a simple statement of whether (and by how much) an exposure
concentration exceeds the RfC. Moreover, the level of concern does not increase linearly or to
the same extent as HQs increase above one for different chemicals because RfCs do not generally
have equal accuracy or precision and are generally not based on the same severity of effect.
Thus, we can only say that with exposures increasingly greater than the RfC, (i.e., HQs
increasingly greater than 1), the potential for adverse effects increases, but we do not know by
how much. An HQ of 100 does not mean that the hazard is 10 times greater than an HQ of 10.
Also an HQ of 10 for one substance may not have the same meaning (in terms of hazard) as
another substance resulting in the same HQ.
April 2004 Pagel3-i
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Example Calculation to Estimate Chronic Noncancer Hazard (Hypothetical)
A Tier 1 modeling analysis was performed to estimate chronic noncancer hazard to the maximum
exposed individual, assumed to reside at the point of maximum concentration for ABC Factory. Four
HAPs were potentially of concern: benzene, dichloroethyl ether, formaldehyde, and cadmium
compounds. Noncancer hazard estimates were obtained for each HAP by dividing the estimated
Exposure Concentration (EC) by the Inhalation Reference Concentration (RfC) for each HAP (note
that the EC is expressed in units of mg/m3 for this analysis). The resulting Hazard quotient (HQ)
estimates ranged from 1 x 10"3 (formaldehyde) to 1 (cadmium compounds). Note that no RfC was
available for dichloroethyl ether. The HQs for each HAP were summed to obtain an estimate of the
Hazard Index (HI) of 1. Note that cadmium compounds account for 95 percent of the HI, suggesting
that the other HAPs may not need further consideration (although this determination should be made
in consideration of all relevant information, including uncertainties such as confidence in the exposure
concentration and uncertainty factors used to derive each RfC).
HAP
Benzene
Dichloroethyl ether*3'
Formaldehyde
Cadmium compounds
Hazard Index (HI)
EC
mg/m3
6 x ID'4
5 x ID'3
4 x IQ-4
2 x IQ-5
RfC
(mg/m3)
6 x ID'2
—
1 x IQ-2
2 x IQ-5
HQ(b)
1 x IQ-2
—
1 x IQ-3
1
1
Percent of
HI
1 %
—
4%
95%
(a) note that the absence of an RfC value means that we cannot quantitatively assess a HAP.
(b) Standard rules for rounding apply which will commonly lead to an answer of one significant figure
in both risk and hazard estimates. For presentation purposes, hazard quotients (and hazard indices)
and cancer risk estimates are usually reported as one significant figure.
13.2.2.2 Characterizing Multiple Pollutant Hazard for Chronic Exposures
Noncancer health effects data are usually available only for individual compounds within a
mixture. In these cases, the individual HQs can be summed together to calculate a multiple-
pollutant hazard index (HI):
where
HQ+ ...
(Equation 13-4)
HI = hazard index; and
HQ = hazard quotient for the ith air toxic.
For screening-level assessments, a simple HI may first be calculated for all chemicals of concern
within the inhalation pathway (adding hazards across pathways is discussed in Part in). If the HI
is less than your decision criterion, a more refined analysis is usually not performed. Adding
HQs in this fashion is based on the assumption that even when individual pollutant levels are
April 2004
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lower than the corresponding reference levels, some pollutants may work together such that their
potential for harm is additive and the combined exposure to the group of chemicals poses greater
likelihood of harm. Some groups of chemicals can also behave antagonistically, such that
combined exposure poses less likelihood of harm, or synergistically, such that combined
exposure poses harm in greater than additive manner. Where this type of HI exceeds the
criterion of interest, a more refined analysis is warranted.
Although the HI approach encompassing all chemicals in a mixture is commonly used for a
screening-level study, it is important to note that application of the HI equation to compounds
that may produce different effects, or that act by different toxicological mechanisms, could
overestimate the potential for effects. Consequently, it is more appropriate to calculate a separate
HI for each endpoint of concern for which mechanisms of action are known to be similar.
Because the assumption of dose additivity is most appropriate for compounds that induce the
same effect by similar modes of action, EPA's Guidance for Conducting Health Risk
Assessment of Chemical Mixtures and Supplementary Guidance^ suggest subgrouping pollutant-
specific HQs by toxicological similarity of the pollutants for subsequent calculations; that is, to
calculate a target-organ-specific-hazard index (TOSHI) for each subgrouping of pollutants.
This calculation allows for a more appropriate estimate of overall hazard.
Segregation of hazard indices by effect
and mechanism of action can be complex
and time-consuming because it is
necessary to identify all the major effects
and target organism for each chemical and
then to classify the chemicals according to
target organ(s) or mechanism of action.
This analysis is not simple and a
toxicologist with familiarity in developing
TOSHIs is best suited to perform this
function. If the segregation is not
carefully done, an underestimate of true
hazard could result.
Procedure for Segregation of His by Effect
Segregation of His requires identification of the
major effects of each chemical, including those seen
at higher doses than the critical effect (e.g., the
chemical may cause liver damage at an EC of 20
(ig/m3 and neurotoxicity at an EC of 50 (ig/m3).
Major effect categories include neurotoxicity,
developmental toxicity, reproductive toxicity,
immunotoxicity, and adverse effects by target organ
(i.e., hepatic, renal, respiratory, cardiovascular,
gastrointestinal, hematological, musculoskeletal, and
dermal/ocular effects).
Acute HQs are developed in the same manner as chronic HQs, with the caveat that the exposure
duration associated with the exposure concentration should match the exposure duration
embodied in the acute toxicity value. Whereas summing chronic HQs to a total hazard index is a
relatively straightforward exercise, the issues related to developing acute HI are more subtle and
complex. A toxicologist familiar with acute exposure and risk analysis should be consulted to
perform this process.
April 2004
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13.2.2.3 Characterizing Hazard for Acute Exposures
Risk assessors can derive estimates of acute noncancer hazard for each HAP by combining the
applicable short-term exposure concentration (EC) and acute dose-response value (AV) for the
HAP to obtain the acute Hazard Quotient (HQ) for the HAP using the following equation:
HQA = ECST + AV
where:
HQA = the acute hazard quotient for an individual HAP;
ECST = estimate of short-term inhalation exposure to that HAP; and
AV = the corresponding acute dose-response value for that HAP.
Note that ambient air concentrations are calculated for an exposure duration compatible with the
acute dose-response value used.
Available acute dose-response values are more diverse than chronic values, because they were
developed for different purposes and considering different exposure durations. The most
effective characterization of acute risk often is to compare the maximum estimated hourly
concentrations with a range of acute dose-response values from sources described in Chapter 12.
If the ambient concentration is lower than all the acute benchmarks, it is generally reasonable to
conclude that the potential for significant acute hazard is negligible. If the concentration exceeds
some benchmarks but not others, the assessment should include a discussion of the implications
for the chemical of interest, with attention to the details of both the exposure scenario and the
benchmarks included in the analysis.
Acute noncancer health effects data are usually available only for individual HAPs within a
mixture. In these cases, it maybe possible to combine the individual acute HQs to calculate a
multi-pollutant acute hazard index (HI) using the following formula:
HIA=HQA1 + HQA2+...+ HQAi
where
HIA = acute hazard index; and
HQAi = acute hazard quotient for the ith HAP.
Although this appears similar to the process for combining chronic HQs, the summing of acute
HQs is complicated by several issues that do not pertain to chronic HQs. First, acute dose-
response values have been developed for purposes that vary more widely than chronic values.
Some sources of acute values define exposures at which adverse effects actually occur, while
other sources develop only no-effect acute values. Second, some acute values are expressed as
concentration-time matrices, while others are expressed as single concentrations for a set
exposure duration. Third, some acute values may specifically consider multiple exposures,
whereas others consider exposure as a one-time event. Fourth, some sources of acute values are
intended to regulate workplace exposures, assuming a population of healthy workers (i.e.,
without children, seniors, or other sensitive individuals). Such occupational values may also
consider cost and feasibility, factors that EPA considers the province of the risk manager rather
than the risk assessor.
April 2004 Page 13-11
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Given these differences among acute values with regard to their purposes, and the different types
of acute exposure characterization that maybe performed, the acute HI analysis is most
informative when limited to acute values from the same source, the same level of effects, and the
same duration. Analyses that mix sources, effects levels, and durations are likely to be
misleading.
Risk assessors commonly evaluate acute noncancer hazard using a variety of different acute
values from different sources, and discuss the resulting hazard estimates considering the purpose
for which each of value was developed. This kind of evaluation should only be done by an
experienced toxicologist. The significance of these HQs and His would need to be
considered in the context of the purpose of the risk assessment and the characteristics of
the dose-response values, such as their purpose, averaging time, and health endpoints. EPA
is working to provide more comprehensive guidance on what benchmarks to rely upon and plans
to develop a relevant acute benchmark methodology.
13.2.3 Quantifying Risk From Background Sources
In some cases, it may be appropriate to quantify background concentrations of the air toxics of
concern. For example, background concentrations may be a critical element in determining the
need for further reductions of emissions from a particular source. Background concentrations are
the levels of contaminants that would be present in the absence of contaminant releases from the
source(s) under evaluation. Background concentrations may occur naturally in the environment
or originate from other human sources (e.g., an industrial area upwind from the sources of
concern).
The general approach in risk assessments and risk management decisions has often been to
assess the incremental risk posed by emissions from a particular source or group of sources.
Various EPA programs, however, have taken specific approaches to considering background
risks, some of which are summarized in EPA's Residual Risk Report to Congress.m
A detailed analysis of background concentrations typically would require extensive data
gathering and modeling beyond that required for the incremental risk analysis. For example,
numerous nearby (and possibly distant) air toxics sources of varying types would need to be
characterized in sufficient detail to support release and exposure modeling. The data needs for
assessment of background concentrations may differ depending on what will be done with the
data. For example, if the question is simply "what is the risk to the population in a specific
place," then an assessment of background may be unnecessary (monitoring data in the study area
may be all that is required). On the other hand, if the question is "what is the risk and what can
we do about it," then a knowledge of how much risk is contributed from both local and
background sources may be necessary. If the risk is unacceptably high, but most of the risk is
background in nature, there may be no appropriate risk reduction strategy (especially in regard to
local sources).
Interpreting background concentrations may be difficult for anthropogenic chemicals and for
chemicals formed through chemical reactions. For example, when trying to estimate background
formaldehyde concentrations, it is difficult to screen out the reactive precursors which change in
the study area from those that change before entering the study area. Also, if a source of nitrogen
oxides (NOX) is not present, secondary formation of formaldehyde may be slowed.
April 2004 Page 13-12
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The presence of high background concentrations of anthropogenic chemicals could increase
public concerns in some situations (see Part V of this reference manual for discussion of risk
communication). On the other hand, knowledge of background risks could help place the air
risks from a particular source or source area in better perspective.
In general, the most appropriate way to evaluate the contribution of background concentrations to
the risk estimate is to simply compare the risk attributable to known or estimated (e.g., through
monitoring) background concentrations in a bar chart against the risk attributable to the source(s)
being evaluated (see Exhibit 13-3). Note that the study-specific risk estimate will be based on a
metric of total exposure (when monitoring data are available) or incremental exposure (when
modeling data are available. It generally is not appropriate to subtract background concentrations
from monitored values.
Exhibit 13-3. Example Comparison of Risk Estimates from Study-specific
and Background Sources
3.1E-D5 -
2.6E-K -
2.1E-IE -
1.6E-DS -
1.1E-05 -
6.DE-D6 -
Bttnatd Rtfc iron Slt-ep>cltfc
Sointss
Kth; torn Bacfcgrcnd
In this example, the estimated risk from the specific sources being evaluated (2.8x10"5) and the
estimated risk from background sources (l.OxlO"5) are compared side-by-side. This places the risk
estimates from the sources of concern in an appropriate regional context.
13.3 Interpretation and Presentation of Inhalation Cancer Risks and Noncancer Hazards
In the final part of the risk characterization, risk assessors commonly present estimates of health
risk in the context of uncertainties and limitations in the data and methodology. Exposure
estimates and assumptions, toxicity estimates and assumptions, and the assessment of uncertainty
are usually discussed. Additionally, information relevant to the public health context of the
estimated risks is presented.
EPA's Policy for Risk Characterization^ describes a philosophy of transparency, clarity,
consistency, and reasonableness (TCCR), and provides detailed approaches to achieving TCCR.
Exhibit 13-4 provides an overview of EPA's TCCR principles.
April 2004
Page 13-13
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Exhibit 13-4. Transparency, Clarity, Consistency, and Reasonableness Principles
Principle
Transparency
Clarity
Consistency
Reasonableness
Definition
Explicitness in the risk
assessment process
The assessment itself is free
from obscure language and is
easy to understand
The conclusions of the risk
assessment are characterized
in harmony with EPA actions
The risk assessment is based
on sound judgment
Criteria for a Good Risk Characterization
• Describe assessment approach, assumptions,
extrapolations, and use of models
• Describe plausible alternative assumptions
• Identify data gaps
• Distinguish science from policy
• Describe uncertainty
• Describe relative strength of assessment
• Employ brevity
• Use plain English
• Avoid technical terms
• Use simple tables, graphics, and equations
• Follow statutes
• Follow Agency guidance
• Use Agency information systems
• Place assessment in context with similar risks
• Define level of effort
• Use review by peers
• Use review by peers
• Use best available scientific information
• Use good judgment
• Use plausible alternatives
Source: EPA Risk Characterization Guidance^
The risk characterization document should allow the risk manager, and the public, to know why
risk was assessed the way it was, by clearly summarizing the available data and its analysis,
uncertainties, alternative analyses, and the choices made. A good risk characterization will state
the scope of the assessment, express results clearly, articulate major assumptions and
uncertainties, identify reasonable alternative interpretations, and separate scientific conclusions
from science policy judgments. The Policy for Risk Characterization calls for the explanation of
the choices made to be highly visible.
The goal of risk characterization is to clearly communicate the key findings and their strengths
and limitations so that decision-makers can put the risk results into context with other
information critical to evaluating risk management options (e.g., economics, social values, public
perception, policies). The risk characterization will provide a means of placing the numerical
estimates of risk and hazard in the context of what is known and what is not about the potential
exposures and should include the elements listed in Exhibit 13-5. Exhibit 13-6 provides
examples of graphical presentations of risk estimates.
April 2004
Page 13-14
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Exhibit 13-5. Elements Commonly Included in the Risk Characterization Discussion
Agreement that the key contaminants were identified
A discussion of modeled or measured air concentrations relative to background
The magnitude of the estimated cancer risks and noncancer hazard indices, and a description of the
types of health risks potentially present, distinguishing between known effects in humans and those
found only in experimental animals
The level of confidence in the toxicity data used to estimate risks
A presentation of qualitative information about the toxicity of substances not included in the
quantitative risk assessment
Level of confidence in the exposure estimates for key exposure pathways and related exposure
parameter assumptions
The major factors driving the risks (e.g., substances, pathways)
The major factors reducing the certainty in the results and the significance of these uncertainties
(e.g., a change in the assumption for a certain parameter could increase/decrease the risk estimate).
The exposed population characteristics
A comparison with location-specific health studies, if available
April 2004 Page 13-15
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Exhibit 13-6. Example Comparison of Risk Results for a Hypothetical Risk Assessment
Nearby Resident Population
ExcessLifetimeCancerRisk<3E-04
I.OOE + 00
n
(J
1.00E-01 -
| 1 .OOE-02 -
~ 1 .OOE-03 -
& 1.00E-04 -
x
u
B 1 .OOE-OS -
o
_a
oi
1 .OOE-07
- I I I I
-
-
-I - ^-B - , - ^-B - , - ^ - 1 -
Benzene (A) 1,2-DCE(B2)
Total
The risk of developing cancer is plotted as shown. A risk of 1 x 10"4 (1 E-04) indicates a probability of
one chance or less in 10,000 of an individual developing cancer. Risks of 1 x 10"5 (1 E-05) and 1 x 10"6
(1 E-06) correspond to probabilities of one chance or less in 100,000 and one million, respectively.
Values in parentheses represent EPA's Weight-of-Evidence classification of the agent as a potential
human carcinogen: A = human carcinogen; B2 = probable human carcinogen (with sufficient evidence
in animals and inadequate or no evidence in humans).
Nearby Residential Population
Chronic Hazard Index = 1.0
QAjetalderryde
n Formaldehyde
Ajpolein
The hazard index is equal to the sum of the hazard quotients (i.e., exposure concentration/RfC) for
each chemical. It is not a probability. A hazard index < 1 indicates that it is unlikely for even
sensitive populations to experience adverse health effects. Thus, hazard is negligible.
April 2004
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13.3.1 Presenting Risk and Hazard Estimates
Risk and hazard estimates will usually be presented both to risk managers and to the public.
Depending on the audience, risk characterizations can present information with different amounts
of technical detail as required, although avoiding the use of technical terms generally improves
clarity. Presentations may include the assumptions the risk assessment used, as well as the
distribution of risks estimated for the assessment. Multiple point estimates and risk ranges could
be discussed in both narrative and tabular forms. The discussion of results may include items
such as:
• The range of risks estimated within specified distances from the source(s) of concern;
• An estimate of population size associated with different risk levels; and/or
• A comparison of the magnitude of the risk estimate to background risks.
Key issues and conclusions should be clearly highlighted in any summary. Exhibit 13-7
identifies several summary products that can facilitate risk communication. (See also Part V of
this Reference Manual for a description of various techniques for communicating risk.)
Exhibit 13-7. Summary Products to Facilitate Risk Communication
Executive summary - a summary 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.
Bulleted list - a list highlighting the key issues and conclusions culled from the technical risk
characterization with little or no technical detail; for audiences with little or no technical
knowledge (e.g., higher-level managers, decision makers).
Briefing packages - written products that describe key issues and conclusions for managers,
decision makers, and other public officials.
Fact sheets, press releases, and public relations notices - written products that describe key
issues and conclusions for non-technical audiences (e.g., affected or interested public).
Slide shows, speeches, and talks - visual presentations (perhaps accompanied by audio
presentations) and transcripts of oral presentations of key issues and their context; for mostly
non-technical audiences.
13.3.2 Exposure Estimates and Assumptions
For each exposure pathway evaluated in the risk assessment, check that all information needed to
characterize exposure is available. For each exposure pathway evaluated, exposure estimates and
assumptions should be reviewed to assure the consistency and validity of key assumptions.
These assumptions may include, for example, the period of exposure and the modeling
assumptions.
April 2004 Page 13-17
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The risk characterization section on exposure may summarize the following exposure
information:
• Estimated exposures (chronic, subchronic, and shorter-term, as appropriate); and
• Important exposure modeling assumptions, including:
- Chemical concentration at the exposure points; and
- Frequency and duration of exposure.
Other items that could be addressed in the risk characterization summary of the exposure
assessment include:
• The most significant sources of environmental exposure:
- Data on sources of exposure from different media (when multimedia analyses are
performed);
- Estimates of the relative contribution of different sources of exposure; and
- Identification of the most significant environmental pathways for exposure (when
multimedia analyses are performed);
• Descriptions of the populations that were assessed, including the general population, highly
exposed groups, and highly susceptible groups;
• Description of the basis for the exposure assessment, including any monitoring, modeling, or
other analyses of exposure distributions (e.g., probabilistic techniques - see Part VII of this
Reference Manual); and
• Key descriptors of exposure:
- Description and illustration of the (range of) exposures to: "average" individuals, "high-
end" individuals, the general population, and special subpopulations such as children and
the elderly;
- Description of how the central tendency estimate was developed, including the factors
and/or methods used in developing this estimate;
- Description of how the high-end estimate was developed;
- Description of how population estimates of risk were developed; and
- Description of how any incidence calculations were performed.
13.3.3 Toxicity Estimates and Assumptions
During the risk characterization step, the risk assessor usually reviews whether all toxicity
information needed to characterize risk is available. The risk characterization section on toxicity
often summarizes the following information:
• lURs for all carcinogenic chemicals;
• Discussion of weight of evidence and classifications for all carcinogenic chemicals;
• Type of human cancer for Class A carcinogens;
• Chronic and subchronic dose-response values and shorter-term (acute) dose-response values
(if appropriate) for all chemicals (including carcinogens and developmental toxicants);
• Critical effect associated with each dose-response value;
April 2004 Page 13-18
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• Discussion of uncertainties, uncertainty factors, and modifying factors used in deriving each
dose-response value and degree of confidence in dose-response values;
• Whether the dose-response values are expressed as absorbed or administered doses (applies
primarily to ingestion exposures - See Chapter 22);
• Pharmacokinetic data that may affect the extrapolation from animals to humans for dose-
response values; and
• Uncertainties in any route-to-route extrapolation.
13.3.4 Assessment and Presentation of Uncertainty in Risk Characterization
The risk estimates used in air toxics risk assessments usually are not fully probabilistic estimates
of risk but conditional estimates given a considerable number of assumptions about exposure and
toxicity. Air toxics risk assessments make use of many different kinds of scientific concepts and
data (e.g., exposure, toxicity, epidemiology), all of which are used to characterize the expected
risk 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
inherent in the risk assessment process, and risk managers almost always must make decisions
using assessments that are not as definitive in all important areas as would be desirable. Risk
assessments also incorporate a variety of professional and science policy judgements (e.g., which
models to use, where to locate monitors, which toxicity studies to use as the basis of developing
dose-response values). Risk managers therefore need to understand the strengths and the
limitations of each assessment, and to communicate this information to all participants and the
public.(2) A critical part of the risk characterization process, therefore, is an evaluation of the
assumptions and uncertainties inherent in the risk assessment in order to place the risk estimates
in proper perspective.
One of the key purposes of uncertainty analysis is to provide an understanding of where the
estimate of exposure, dose, or risk is likely to fall within the range of possible values. Often this
is expressed as a subjective confidence interval within which there is a high probability that the
estimate will fall. A related analysis, termed "sensitivity analysis" or "analysis of uncertainty
importance," is often performed to identify the relative contribution of the uncertainty in a given
parameter value (e.g., emission rate, ingestion rate) or model component to the total uncertainty
in the exposure or risk estimate/8' Often this is used either to identify which parameter values
should be varied to provide high-end vs. central-tendency risk estimates, or to identify parameter
values where additional data collection (or modeling effort) can increase the confidence in the
resulting risk estimate.
The Presidential/Congressional Commission on Risk Assessment and Risk Management
(CRARM) recommends that risk assessors respect the objective scientific basis of risks and
procedures for making inferences in the absence of adequate data.(9) Risk assessors should
provide risk managers and other stakeholders with plausible conclusions about risk that can be
made on the basis of the available information, along with evaluations of the scientific weight of
evidence supporting those conclusions and descriptions of major sources of uncertainty and
alternative views.
April 2004 Page 13-19
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The risk characterization typically should address the following:
• Considering the hazard and the exposure, what is the nature and likelihood of the health risk?
• Which individuals or groups are at risk? Are some people more likely to be at risk than
others?
• How severe are the anticipated adverse impacts or effects?
• Are the effects reversible?
• What scientific evidence supports the conclusions about risk? How strong is the evidence?
• What is uncertain about the nature or magnitude of the risk?
• What is the range of informed views about the nature and probability of the risk?
• How confident are the risk analysts about their predictions of risk?
• What other sources cause the same type of effects or risks?
• What contribution does the particular source make to the overall risk of this kind of effect in
the affected community? To the overall health of the community?
• How is the risk distributed in relation to other risks to the community?
• Does the risk have impacts besides those on health or the environment, such as social or
cultural consequences?
• The level of detail considered in a risk assessment and included in a risk characterization
should be commensurate with the problem's importance, expected health or environmental
impact, expected economic or social impact, urgency, and level of controversy, as well as
with the expected impact and cost of protective measures.
Risk characterizations should include sufficient information to enable:
• Risk managers to make a useful risk management decision, and
• Stakeholders to understand the importance and context of that decision.
13.3.4.1 Practical Approaches to Uncertainty Assessment
There are numerous sources of ( I 77^ , . , ^
[ Sources of Uncertainty
uncertainties in air toxics risk
assessments, and each merits
consideration. The degree to which these
sources of uncertainty need to be
quantified, and the amount of uncertainty
that is acceptable, varies considerably on
a study-specific basis. For a screening-
level (Tier 1) analysis, a high degree of
uncertainty is often acceptable, provided
that conservative assumptions are used to
,. , , • i , j , , • \ influence risk estimates
bias potential error toward protecting
Scenario uncertainty. Information to fully
define exposure or risk is missing or incomplete
Model uncertainty. Algorithms or assumptions
used in models may not adequately represent
reality
Parameter uncertainty. Values for model
parameters cannot be estimated precisely
Decision-rule uncertainty. Policy and other
choices made during the risk assessment may
human health. The use of conservative
assumptions is intended to result in a situation where the risk assessor is confident that the risk
estimate is unlikely to be greater than the point estimate of risk. In other words, the point
estimate of risk is expected to be at the high-end of the range of possible values. The uncertainty
characterization for a Tier 1 analysis commonly is limited to a qualitative discussion of the major
sources of uncertainty and their potential impact on the risk estimate. At higher tiers of analysis,
sensitivity analysis to quantify the impact of varying input parameter values (or model
April 2004 Page 13-20
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algorithms) on the risk estimate, or more complete quantitative uncertainty analysis, commonly
are performed to more fully describe the range of possible or plausible values.
Practical approaches to the assessment and presentation of the principal sources of uncertainty in
risk assessments are summarized below.(10)
Characterize Scenario Uncertainty. There are uncertainties associated with the estimate of the
magnitude and extent of chemical exposure or toxicity, the spatial and temporal aggregation of
chemical concentrations to calculate the exposure concentration used in the risk characterization,
the completeness of the analysis (e.g., important exposure pathways may not have been
evaluated), and the manner in which the exposed population and/or exposure scenario were
specified for the analysis. Ideally, the key scenario uncertainties have been discussed during
planning, scoping, and problem formulation, and the analysis plan has been developed to address
these uncertainties. A limited sensitivity analysis (e.g., on key assumptions associated with
exposure) may indicate the magnitude of uncertainty associated with specific aspects of the
scenario. At a minimum, the analysis of uncertainty should identify the key scenario
uncertainties and indicate the potential impact of each on the direction and magnitude of the risk
estimate.
Characterize Model Uncertainty. There are uncertainties associated with the selection of
scientific models; these include dose-response models, models of environmental fate and
transport, and exposure models. There is always some doubt as to how well an exposure model
or its mathematical expression approximates
the true relationships between site-specific f ~ " '. ._ , 1TT , . ,. ^
, ,. . TI 11 11 Characterize Model Uncertainties
environmental conditions. Ideally one would
List/summarize key model assumptions
Indicate the potential impact of each
assumption on the exposure and risk estimate
- Direction
- Magnitude
like to use a fully validated model that
accounts for all the known complexities in the
parameter interrelationships for each
assessment. Often, however, only partially
validated models are available. As a
consequence, it is important to identify key ^'
model assumptions (e.g., linearity,
homogeneity, steady-state conditions, equilibrium) and their potential impact on the risk
estimates. In the absence of field data for model validation, the risk assessor could perform a
limited sensitivity analysis (i.e., vary assumptions about functional relationships) to indicate the
magnitude of uncertainty that might be associated with model form. At a minimum, the analysis
of uncertainty should list key model assumptions and indicate the potential impact of each on the
direction and magnitude of the risk estimate.
Characterize Parameter Uncertainty. During the course of a risk assessment, numerous
parameter values are included in the calculations of chemical fate and transport and human
intake. Significant data gaps might have required that certain parameter values be assumed for
the risk assessment. For example, no information on the time spent outdoors may be available
for a specific population, and a national average may be used instead. Even if data on the
parameter of interest are available, they will be uncertain because the parameter estimates are
derived from a sample of the potentially exposed population. A first step in characterizing
parameter value uncertainty is to identify the key parameters influencing the risk estimate. This
usually can be accomplished by expert opinion or by an explicit sensitivity analysis. In a
April 2004 Page 13-21
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sensitivity analysis, the values of parameters suspected of driving the risk estimates are varied,
and the degree to which changes in the input variables result in changes in the risk estimates are
summarized and compared. It may be possible to reduce parameter uncertainty in the most
sensitive parameters by additional, selective data gathering.
Characterize Decision-Rule Uncertainty. There are uncertainties associated with policy and
other choices made during the risk assessment. For example, the exposure assessment might
have evaluated an exposure duration (e.g., a subchronic exposure) for which no appropriate dose-
response value was available. Uncertainty would be associated with the choice of value to use in
the hazard characterization (e.g., an acute versus chronic value). In this situation, it might be
possible to assess hazard twice, once with the acute value, and once with the chronic value, to
may indicate the magnitude of uncertainty associated with this decision. At a minimum, the
analysis of uncertainty should identify the key decision-rule uncertainties and indicate the
potential impact of each on the direction and magnitude of the risk estimate.
Tracking Uncertainty. Ideally, one would like to quantitatively carry through the risk
assessment the uncertainty associated with each parameter in order to characterize the uncertainty
associated with the final risk estimates. However, this process can be highly complex and
resource intensive and the more practical approach for air toxics risk assessments may be to
describe qualitatively how the uncertainties might be propagated through the risk analysis. Three
different approaches to tracking uncertainty are described below:
• Qualitative Approach. This approach involves developing a quantitative or qualitative
description of the uncertainty for each parameter and indicating the possible influence of
these uncertainties on the final risk estimates given knowledge of the models used.
• Semi-Quantitative Approach. This approach involves: (1) using available data to describe
the potential range of values that the parameters might assume; (2) performing sensitivity
analysis to identify the parameters with the most impact on the risk estimate; and (3)
performing sensitivity analysis to compute the range of exposure or risk estimates that result
from combinations of minimum and maximum values for some parameters and mid-range
values for others.
• Quantitative Approach. Probabilistic techniques such as Monte Carlo simulation analysis
can explicitly characterize the extent of uncertainty and variability in risk assessment,
especially in the exposure assessment step. Using these techniques, important variables in
the exposure assessment, as well as in the other parts of the risk assessment, are specified as
distributions (rather than as single values) according to what can be expressed about their
underlying variability and/or uncertainty. Values are sampled repeatedly from these
distributions and combined in the analysis to provide a range of possible outcomes. While
this technique can offer a useful summary of complex information, it must be noted that the
analysis is only as certain as the underlying data (and assumed forms of the distribution of
data values in the population). It is important that the risk assessor clearly expresses
individual modeled variables in a way that is consistent with the best information available.
Highly quantitative statistical uncertainty analysis is usually not practical or necessary for
most air toxics risk assessments. The general quantitative approach to propagating or
tracking uncertainty through probabilistic modeling is described in Chapter 31.
April 2004 Page 13-22
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13.3.4.2 Presentation of Uncertainty Assessment
The final discussion of the risk characterization results must place the numerical estimates of risk
in the context of the uncertainties inherent in the analysis/2' The discussion should include:
• Level of confidence in the quantitative toxicity information used to estimate risks;
• Presentation of qualitative information on the toxicity of substances not included in the
quantitative assessment;
• Level of confidence in the exposure estimates for key exposure pathways and related
exposure parameter assumptions;
• Major factors reducing certainty in the results and the significance of these uncertainties (e.g.,
adding individual risk estimates for several substances or across multiple exposure
pathways); and
• Possible graphical presentation of key parameter and risk uncertainties.
13.3.5 Additional Information
Other studies relevant to the risk assessment being performed may be available, such as
community health studies or previous risk assessments. For example, the Agency for Toxic
Substances and Diseases Registry (ATSDR) may conduct public health assessments, health
consultations, and other activities resulting in evaluations, assessments, and recommendations on
specific public health issues related to actual or potential human exposure to hazardous materials
(see Chapter 30). ATSDR's recommendations may include additional hazard characterization or
risk reduction activities. In addition, these activities can initiate other activities within ATSDR
such as exposure investigations, health studies, and health education.
If health or exposure studies have been identified and evaluated as adequate, the study findings
maybe incorporated into the risk characterization to strengthen the conclusions of the risk
assessment. In general, a qualitative comparison of the results of available studies will usually be
sufficient.
April 2004 Page 13-23
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Additional References Related to Uncertainty Analysis
Hattis. D.B. andD.E. Burmaster. 1994. Assessment of variability and uncertainty distributions for
practical risk analyses. Risk Analysis 14(5):713-730.
U.S. Environmental Protection Agency. 1997. Guiding Principles for Monte Carlo Analysis. Risk
Assessment Forum, Washington, DC. March 1997. EPA-630/R-97-001.
U.S. Environmental Protection Agency. 1988. National Emission Standards for Hazardous Air
Pollutants. Federal Register 53(145):28496-28056, Proposed Rule and Notice of Public Hearing. July
28, 1988.
Finkel, A.M. 1990. Confronting Uncertainty in Risk Management: A Guide for Decision-Makers.
Center for Risk Management, Resources for the Future. Washington, DC.
U.S. Environmental Protection Agency. 1997. Policy for Use of Probabilistic Analysis in Risk
Assessment. Office of the Administrator, Washington, DC. May 15, 1997.
National Council on Radiation Protection and Measurements. 1996. A Guide for Uncertainty Analysis
in Dose and Risk Assessments Related to Environmental Contamination. NCRP Commentary No. 14;
. available at http://www.ncrp.com/comml 4.html.
V. '
April 2004 Page 13-24
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Information Quality Guidelines
The U.S. Office of Management and Budget (OMB) has directed all federal agencies to develop
information quality guidelines for risk-related and other information; EPA has developed draft
guidelines pursuant to the OMB directive. While these guidelines do not apply to S/L/T governments,
they provide useful principles for developing and communicating the information developed for the
risk characterization.
The OMB guidelines denote four substantive qualifiers for information disseminated by federal
agencies. Quality is defined as the encompassing term, of which utility, objectivity, and integrity are
the constituents. Utility refers to the usefulness of the information to the intended users. Objectivity
focuses on whether the disseminated information is being presented in an accurate, clear, complete,
and unbiased manner, and as a matter of substance, is accurate, reliable, and unbiased. Integrity
refers to security - the protection of information from unauthorized access or revision, to ensure that
the information is not compromised through corruption or falsification.
The guidelines provide some basic principles for agencies to consider when developing their own
guidelines, including:
• Guidelines should be flexible enough to address all communication media and variety of scope and
importance of information products.
• Some agency information may need to meet higher or more specific expectations for objectivity,
utility, and integrity.
• Ensuring and maximizing quality, objectivity, utility, and integrity comes at a cost, so agencies
should consider using a cost-benefit approach.
• Agencies should adopt a common-sense approach that builds on existing processes and procedures.
It is important that agency guidelines do not impose unnecessary administrative burdens.
EPA developed draft information quality guidelines in response to the OMB directive
(www.epa.gov/oei/qualityguidelines). EPA's guidelines include two components of particular
relevance to air toxics risk management: (1) guidelines to ensure and maximize the quality of
"influential" information; and (2) guidelines to ensure and maximize the quality of "influential"
scientific risk assessment information.
Source: Office of Management and Budget. 2002. Guidelines for Ensuring and Maximizing the
Quality, Objectivity, Utility, and Integrity of Information Disseminated by Federal Agencies. 67
Federal Register 36:8451. February22, 2002 (www.whitehouse. go v/omb/fedr eg/r epro ducible .html).
References
1. U.S. Environmental Protection Agency. 2003. Framework for Cumulative Risk Assessment
(External Review Draft). Office of Research and Development, National Center for
Environmental Assessment, Washington, D.C., April 23, 2002. EPA/630/P-02/001F.
Available at: http://cfpub.epa.gov/ncea/raf/recordisplay.cfm?deid=54944.
U.S. Environmental Protection Agency. 1997. Guidance on Cumulative Risk Assessment,
Part 1, Planning and Scoping. Science Policy Council, Washington, B.C.
U.S. Environmental Protection Agency. 1984. Risk Assessment and Management:
Framework for Decision Making, Washington, D.C. EPA 600/9-85-002.
April 2004 Page 13-25
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2. U.S. Environmental Protection Agency. 1995. Policy for Risk Characterization ("Browner
Memorandum"). Science Policy Council, Washington, B.C., March 1995. Available at:
http://64.2.134.196/committees/aqph/rcpolicy.pdf.
3. U.S. Environmental Protection Agency. 1995. Guidance for Risk Characterization. Science
Policy Council, Washington, B.C., February 1995. Available at:
http://www.epa.gov/osa/spc/htm/rcguide.htm.
4. U.S. Environmental Protection Agency. 1992. Guidance on Risk Characterization for Risk
Managers and Risk Assessment. Memorandum. Office of the Administrator, Washington,
B.C.
5. U.S. Environmental Protection Agency. 1986. Guidance Mutagenicity Risk Assessment of
Chemical Mixtures. Risk Assessment Forum, Washington, B.C., September 1986.
EPA/630/R-98/003. (Published in the Federal Register 51: 33997-8, Sept 24, 1986).
Available at: http://cfpub.epa.gov/ncea/raf/pdfs/mutagen2.pdf.
6. U.S. Environmental Protection Agency. 1986. Guidance for Conducting Health Risk
Assessment of Chemical Mixtures. Risk Assessment Forum, Washington, B.C.
EPA/630/R-98/002. Available at:
http ://cfpub. epa. gov/ncea/raf/recordisplay .cfm?deid=2053 3.
U.S. Environmental Protection Agency. 2000. Supplementary Guidance for Conducting
Health Risk Assessment of Chemical Mixtures. Risk Assessment Forum, Washington, B.C.
EPA/630/R-00/002. Available at:
http ://cfpub. epa. gov/ncea/raf/recordisplay .cfm?deid=2053 3.
7. U.S. Environmental Protection Agency. 1999. Residual Risk Report to Congress. Office of
Air Quality Planning and Standards, Research Triangle Park, NC, March 1999. EPA-45/R-
99/001. Available at: http://www.epa.gov/ttn/oarpg/t3/reports/risk_rep.pdf.
8. Morgan, G. and Henrrion. M. 1990. Uncertainty: A Guide to Dealing with Uncertainty in
Quantitative Risk and Policy Analysis. Cambridge University Press, Cambridge, U.K.
9. Commission on Risk Assessment and Risk Management (CRARM). 1996. Risk Assessment
and Risk Management in Regulatory Decision-Making (The "White Book"). Braft Report,
Washington, B.C.
CRARM. 1997. Framework for Environmental Health Risk Management. Final Report,
Volume 1. Washington, B.C.
CRARM. 1997. Risk Assessment and Risk Management in Regulatory Decision-Making.
Final Report, Volume 2. Washington, B.C.
10. U.S. Environmental Protection Agency. 1989. Risk Assessment Guidance for Superfund:
Volume I. Human Health Evaluation Manual (Part A). Office of Emergency and Remedial
Response. Washington, B.C., Becember 1989. EPA/541/1-89/002. Available at:
http ://www. epa. go v/superfund/programs/risk/ragsa/index .htm.
April 2004 Page 13-26
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PART III
HUMAN HEALTH RISK ASSESSMENT:
MULTIPATHWAY
-------
-------
Chapter 14 Overview and Getting Started: Planning
and Scoping the Multipathway Risk
Assessment
Table of Contents
14. 1 Introduction
14.2 Overview of Multipathway Air Toxics Risk Assessment .............................. 3.
14.2.1 Planning, Scoping, and Problem Formulation ................................. 3_
14.2.2 Analysis [[[ 4
14.2.3 Risk Characterization [[[ 5
14.3 Overview of Multipathway Exposure Assessment .................................... 5
14.4 Planning and Scoping [[[ 9
14.4. 1 Identifying the Concern .................................................. 9
14.4.2 Identifying The Participants .............................................. 9
14.4.3 Determining the Scope of the Risk Assessment ............................... 9
14.4.4 Describing the Problem ................................................. K)
14.4.5 Determining How Risk Managers Will Evaluate the Concern ................... K)
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14.1 Introduction
Part II of this Reference Manual discussed how to plan for and conduct a human health risk
assessment via the direct inhalation pathway. Part IE provides the same general discussion of the
various aspects of the risk assessment process; however, the discussion is focused specifically on
multipathway human health risk assessment. As noted earlier, all air toxics risk assessments
evaluate the direct inhalation pathway. In addition, multipathway risk assessment may be
appropriate generally when air toxics that persist and which also may bioaccumulate and/or
biomagnify are present in releases. These generally will focus on the persistent
bioaccumulative hazardous air pollutant (PB-HAP) compounds (Exhibit 14-1), but specific
risk assessments may need to consider additional chemicals that persist and which also may
bioaccumulate and/or biomagnify. For these compounds, the risk assessment generally will
need to consider exposure pathways other than inhalation - in particular, pathways that involve
deposition of air toxics onto soil and plants and into water, subsequent uptake by biota, and
potential human exposures via consumption of contaminated soils, surface waters, and foods.
Substances that persist and bioaccumulate readily transfer between the air, water, and land.
Some may travel great distances, and linger for long periods of time in the environment.
The discussion of multipathway risk assessment follows the same general framework presented
in Part II. This chapter presents an overview of multipathway risk assessment and discusses the
initial planning, scoping and problem formulation activities. The remaining chapters of this Part
focus on Exposure Assessment (Chapters 14 to 20), Toxicity Assessment (Chapter 21), and Risk
Characterization (Chapter 22). The discussions presented here supplement the information
provided earlier - readers are encouraged to refer back to the corresponding Chapters in Part II
for additional background materials.
Bioconcentration is the net accumulation of a substance by an organism as a result of uptake directly
from an environmental medium (e.g., net accumulation by an aquatic organism as a result of uptake
directly from ambient water, through gill membranes or other external body surfaces).
Bioaccumulation is the net accumulation (storage in tissue and/or organs) of a substance by an
organism as a result of uptake from all environmental sources - the medium in which they live, the
water they drink, and the diet they consume - over a period of time.
Biomagnification or Biological Magnification is the process whereby certain substances, such as
pesticides or heavy metals, transfer up the food chain and increase in concentration. A biomagnifying
chemical deposited in rivers or lakes absorbs to algae, which are ingested by aquatic organisms, such
as small fish, which are in turn eaten by larger fish, fish-eating birds, terrestrial wildlife, or humans.
The chemical tends to accumulates to higher concentration levels with each successive food chain
level. Biomagnification is illustrated in Chapter 23.
\ s
April 2004 Page 14-1
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Exhibit 14-1. PB-HAP Compounds
PB-HAP Compound
Cadmium compounds
Chlordane
Chlorinated dibenzodioxins and furans
DDE
Heptachlor
Hexachlorobenzene
Hexachlorocyclohexane (all isomers)
Lead compounds
Mercury compounds
Methoxychlor
Polychlorinated biphenyls
Polycyclic organic matter
Toxaphene
Trifluralin
Pollution
Prevention
Priority PBTs
X
X(a)
X
X
xe)
X
X
X(d)
X
Great Waters
Pollutants of
Concern
X
X
X
X
X
X
X
X
X
X
X
TRI PBT
Chemicals
X
X(b)
X
X
X
X
X
X
X(e)
X
X
(a) "Dioxins and furans" ("" denotes the phraseology of the source list)
^ "Dioxin and dioxin-like compounds"
(c) Alkyl lead
(d) Benzo[a]pyrene
(e) "Polycyclic aromatic compounds" and benzo[g,h,i]perylene
See Appendix D for a discussion of the derivation of this list of PB-HAPs.
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14.2 Overview of Multipathway Air Toxics Risk Assessment
The multipathway risk assessment is organized in the same way as the direct inhalation risk
assessment into three general phases:
1. Planning, scoping, and problem formulation;
2. Analysis, consisting of exposure assessment and toxicity assessment; and
3. Risk characterization.
14.2.1 Planning, Scoping, and Problem Formulation
The planning, scoping, and problem formulation phase of multimedia risk assessment focuses on
developing a common understanding of what needs to be added to the risk assessment (beyond
the direct inhalation assessment) to assess risks associated with pathways involving deposition
(i.e., transfer of the compounds to soil, water, sediment, and biota) and subsequent ingestion
exposure. The scope of the multimedia risk assessment generally is more extensive than that for
inhalation assessment, and therefore significant additional effort is likely.
" "
For purposes of this Reference Manual, we discuss planning, scoping, and problem formulation
for multipathway human health risk assessment separately from the corresponding phase for
inhalation risk assessment. In reality, the planning, scoping, and problem formulation phase for
the multipathway assessment would be integrated with the inhalation analysis as early as feasible.
It may be necessary to include on the planning and scoping team experts in multimedia
modeling, bioaccumulation, human exposure factors, and ingestion toxicology. The focus on
additional exposure pathways may influence many aspects of the risk assessment, including the
size of the study area; emission sources to be considered; the temporal and spatial resolution
required; the appropriate level of detail and documentation; trade-offs between depth and breadth
in the analysis; QA/QC requirements; analytical approaches to be used; and the staff and
monetary resources to commit. The study-specific conceptual model would also reflect the
specific concerns of air toxics that persist and which also may bioaccumulate. As with the
inhalation risk assessment, the planning, scoping, and problem formulation process is an iterative
process that reflects changing information and concerns as the multimedia risk assessment
unfolds.
The reader should become familiar with Part n of this manual before reading this Part, since Part
IE focuses primarily on those aspects of the risk assessment that are unique to multipathway
analyses, including:
• How the study area is defined;
• Potentially exposed populations;
• Exposure pathways and exposure routes;
• How exposure is assessed;
• Dose-response values for non-inhalation pathways; and
• How risks are characterized.
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14.2.2 Analysis
The analysis phase of the multipathway assessment is divided into two components: exposure
assessment and toxicity assessment. Exposure assessment is likely to be considerably more
complicated than the corresponding inhalation exposure assessment for several reasons:
• People can be exposed to air toxics in many more ways, including in the food they eat, the
milk they drink, and the soils on which they play.
• Time is a critical variable. Air toxics that persist and which also may bioaccumulate can
slowly build up in soils, sediments, and biota over time. With sufficient time, even relatively
small releases have the potential to result in high exposures.
• The spatial distribution of the air toxics can be complex. Chemicals can move away from
deposition points due to runoff, erosion, and the movement of contaminated animals.
Chemicals deposited over a wide area (e.g., a watershed) can concentrate in smaller areas
(e.g., a pond).
• Multimedia models often use more extensive input variables.
• Sampling and analysis may involve a wider range of media (e.g., soil, sediment) and different
types of biota (e.g., fish, shellfish, plants). Each type of sampling and analysis has its own
methods, protocols, and QA/QC procedures.
• Whereas the exposure concentration in air is the quantitative metric of exposure for
inhalation, intake is the quantitative metric of ingestion exposure in multipathway analyses.
To quantify intake, it is necessary to (1) estimate the concentrations of chemicals of potential
concern (COPC) in water, soil, sediment, and/or food items; (2) determine how much water,
soil, sediment, and food are ingested; (3) determine the duration and temporal patterns over
which ingestion occurs; and (4) adjust for body weight, to account for the different types of
people in the population who interact with the contaminated media. Multimedia exposure
assessment uses a number of different exposure factors that provide quantitative estimates of
the physical and behavioral attributes of potentially exposed populations (e.g., how much fish
a person eats per day). Exposure factors can be treated as either constants or variables in the
exposure assessment, depending on whether a deterministic or probabilistic analysis is being
performed.
The multipathway toxicity assessment is similar to the toxicity assessment for inhalation. It
considers the same general information: (1) the types of potential adverse health effects
associated with chemical exposures; (2) dose-response relationships; and (3) related uncertainties
such as the weight of evidence for carcinogenic effects. There are two primary differences:
• A chemical's toxicity is influenced by the route of exposure. That is, the same chemical can
result in different toxic effects (and have different dose-response values) depending on
whether the chemical is inhaled or ingested. There are a number of reasons why this may
occur. For example, when a chemical is inhaled into the respiratory tract, the primary toxic
effect may occur in the respiratory tract as a result of the inhaled chemical (a portal of entry
effect). When swallowed, on the other hand, many chemicals are absorbed into the
April 2004 Page 14-4
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bloodstream through the gastrointestinal tract where they are carried directly to the liver.
Chemicals in the liver are often metabolized extensively (either to more or less toxic
substances) before being transported by the bloodstream to other parts of the body.
• The specific dose-response values used for the ingestion pathway - reference doses (RfDs)
for non-cancer effects and oral cancer slope factors (CSFs) - differ in form and derivation
from those used for inhalation assessments. Specifically, RfDs and CSFs are developed to
match the metric of exposure for ingestion and are expressed (usually) in terms of amount of
chemical ingested per unit of body weight per day (i.e., mg/kg-d for RfDs) and risk per
amount of chemical ingested per unit body weight per day (i.e., (mg/kg-d)"1 for CSFs).
14.2.3 Risk Characterization
The risk characterization for multipathway assessments also may be more complicated than that
for the inhalation risk assessment.
• Ingestion risk estimates are first added across all ingestion pathways and then added to
inhalation risk estimates to calculate total (i.e., cumulative) risk. Although the summation
process is relatively simple for screening-level analyses, it can become complex for more
advanced tiers of risk assessment.
• The uncertainty analysis for multipathway risk assessments may be considerably more
complex if multiple pathways are important because many more exposure factors and
variables will be involved in the quantification of risk. As noted earlier, many more specific
exposure factors can be treated as variables for probabilistic multipathway risk assessments.
• The uncertainty analysis for multipathway analysis is also much more complex due to the
larger number of pathways assessed and the larger number of measurement and modeling
inputs that are needed.
14.3 Overview of Multipathway Exposure Assessment
As with inhalation risk assessments, the exposure assessment for multipathway risk assessments
includes identifying sources, characterizing releases to the air, estimating concentrations of air
toxics in the environment, characterizing potentially exposed populations, and developing
metrics of exposure. This section provides an overview of exposure assessment for
multipathway risk assessments. Familiarity with EPA's Guidelines for Exposure Assessment
prior to beginning the multipathway exposure assessment would be helpful.
The multipathway exposure assessment covers a broader scope and may be more complex than
direct inhalation exposure assessment.
• Exposure pathways to be evaluated include multiple media (soil, water, sediment, biota) and
exposure routes in addition to inhalation (e.g., ingestion). Therefore, the exposure setting
may need additional characterization (e.g., the location and nature of water bodies and/or
agricultural crops).
April 2004 Page 14-5
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Overview of Multipathway Exposure Pathways/Routes
L^.pY^-;"
L,M>f-&U
_i4r.s'.BB.ai|8f»K'
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The evaluation of chemical fate and transport accounts for the transfer of contaminants from
air to soil and water and subsequent transport and transfer to other media. For example, air
toxics that persist and which also may bioaccumulate are deposited onto soils and can enter
surface waters via runoff; some of the compounds that deposit into water predominantly
partition into sediments. Bioaccumulation - a concentration of contaminants in biological
tissues - and subsequent transfer to humans via ingestion often play a major role in the
exposure assessment. Multimedia models can be used to describe contaminant fate and
transport through the use of partition coefficients and mass-balance techniques (see Chapter
6). Different monitoring methods (e.g., sediment or fish tissue sampling and analysis) may
be included to augment or assist in the evaluation of modeling outputs.
In contrast to the direct inhalation assessment, in which the quantitative metric of exposure is
the ambient air concentration at the exposure point, ingestion exposures are quantified using
the chemical intake rate - the amount of chemical ingested per unit time - generally
expressed in units of milligrams of chemical per kilogram of body weight per day.
Calculation of chemical intake rate requires information on COPC concentrations in items
ingested as well as information about the type and amount of different items eaten each day,
body weight, and exposure durations for the sub-populations of interest. Intake rate is
simply the amount of food (or other media), containing the contaminant of interest, that an
individual ingests during some specific time period (units of mass/time). Intake rate can be
expressed as a total amount (e.g., mg); as a dose rate (e.g., mg/day); or as a rate normalized to
body mass (e.g., mg/kg-day). For most chemicals, the dose-response value (e.g., reference
dose, or RfD) is based on the potential dose (i.e., the amount of chemical taken in), with no
April 2004
Page 14-6
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explicit correction for the fraction absorbed. For some chemicals, it may be necessary to
adjust for such differences using physiologically based pharmacokinetic (PB-PK) models,
mathematical dosimetry models, and/or adjustment factors (see Chapter 8).
Because exposure is quantified using chemical intake rate, different types of people within a
population (e.g., childhood exposures) may need to be considered explicitly. Consumption rates,
dietary preferences, and body weight vary with age and would be accounted for in the risk
assessment. (Note that not only age, but sex, ethnicity, cultural and religious practices may also
strongly influence the exposure patterns of people within a potentially exposed population.)
Although it is possible to evaluate acute exposures for the ingestion pathway, EPA does not
generally perform acute exposure assessments, because it is unlikely that PB-HAP compounds
would concentrate to acutely toxic levels under any typical release scenario that did not pose a
much more substantial chronic risk. However, each assessment would consider the available
evidence in making this judgement. At a minimum, the risk characterization would state the
reasons why an analysis of acute health effects for non-inhalation pathways was not performed.
The multipathway exposure assessment focuses on two general categories of ingestion pathways:
incidental ingestion and food chain (Exhibit 14-2). Incidental ingestion pathways consider
exposures that may occur from ingestion of soils or surface water while an individual is engaged
in other activities (e.g., ingestion of soil while gardening or playing outside; ingestion of surface
water while swimming). Food chain pathways consider exposures that may occur if PB-HAP
compounds accumulate in the food and water people consume.
Exhibit 14-2. Human Exposure Pathways Considered for Multipathway
Air Toxics Assessments
soil —> human
surface water •
air —¥ water —¥ human
air —> soil —> water —> human
air —> vegetation —> human
air —> animal —> human
air —> vegetation —> animal —> human
air —> soil —> vegetation —> human
air —K soil —K animal —K human
air —> soil —^ water —> animal —> human
air —> soil —> water —> fish —> human
air —> soil —> water —> sediment —> fish —> human
air —> water —> animal —> human
air —> water —> fish —> human
air —> water —> sediment —> fish —> human
April 2004
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As Exhibit 14-2 suggests, the focus of the multipathway assessment is on ingestion pathways.
Other exposure pathways may be important for particular risk assessments, including dermal
exposures (i.e., direct contact with contaminated soils, surface waters, or surface water sediments
during outside activities such as gardening or swimming); resuspension of dust (e.g., from wind
blowing across contaminated soils, or agricultural activities such as tilling) and subsequent
inhalation of the dust particles; and ingestion of contaminated groundwater. However, EPA does
not have sufficient experience with multipathway air toxics risk assessments to identify the
circumstances for which exposures via these additional pathways may represent a potential
concern.
• If site-specific circumstances suggest that dermal pathways may be of concern, EPA's Risk
Assessment Guidance for Superfund (RAGS), Part D, Standardized Planning, Reporting and
Review of Superfund Risk Assessments,^ includes a relatively straightforward methodology
for dermal exposure and risk assessment, starting with soil concentrations. The Planning
Tables in the document are simple to use and incorporate into the multipathway analysis.
• Relative to the direct inhalation pathway, inhalation of soil resulting from dust resuspension
by wind erosion generally is not thought to be a significant pathway of concern for air toxics
risk assessments. If site-specific circumstances suggest that resuspension of dust may
represent a potential concern, EPA's Methodology for Assessing Health Risks Associated
with Multiple Pathways of Exposure to Combuster Emissions (MPE) (Chapter 5 Dust
Resuspension) discusses the methods for evaluating this pathway.(3)
/N
Analysis of Groundwater Pathways
EPA's Office of Solid Waste has considerable experience in modeling and monitoring the movement
of contaminants in groundwater. Much of that experience is based on exposure assessments
associated with land-based disposal units (i.e., where the source of contamination is in the
subsurface). For example, EPA's Center for Exposure Assessment Modeling (CEAM) distributes
multimedia models designed to quantify the movement and concentration of contaminants (from
land-based releases at hazardous waste sites) traveling through groundwater, surface water, and food
chain media (available at http ://www. epa. gov/ceampubl/). In these models, releases to the atmosphere
from the subsurface may be considered, but transfer from the air through the subsurface are not.
EPA does not have sufficent experience with air toxics multipathway analysis to identify situations in
which the groundwater may be contaminated. EPA's Methodology for Assessing Health Risks
Associated with Multiple Pathways of Exposure^ identifies three site-specific conditions that might
lead to greater groundwater impacts:
• Deposition rates that are several times greater than the average;
• The existence of more soluble HAPs in emissions; and
• Higher recharge rates such as would occur in areas with very permeable soil and bedrock near the
. surface. ,
• If site-specific circumstances suggest that groundwater may represent a potential concern
(e.g., the presence of extremely shallow aquifers used for drinking water purposes or a karst
environment in which the local surface water significantly affects the quality of ground water
used as a drinking water source), Total Risk Integrated Methodology - Fate, Transport, and
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Ecological Exposure Module (TRIM.FaTE) has the ability to assess chemicals moving into
the groundwater pathway. EPA's Human Health Risk Assessment Protocol for Hazardous
Waste Combustion Facilities^ and EPA's Draft Technical Background Document for Soil
Screening Guidance discusses methods for evaluating the groundwater pathway.
14.4 Planning and Scoping
As with inhalation analyses, the key steps in the planning and scoping process include (1)
identifying the concern; (2) identifying who will be involved; (3) determining the scope of the
risk assessment; (4) describing why there may be a problem; and (5) determining how the
concern will be evaluated. The planning and scoping process for multipathway risk assessment
focuses on developing a common understanding of what needs to be evaluated to assess risks via
deposition and transfer of the air toxics to soil, water, and biota, and subsequent ingestion. More
detailed discussions of the planning and scoping process can be found in Part II of this Volume
and in guidance documents developed by EPA.(4)
14.4.1 Identifying the Concern
The driving concern for the multipathway risk assessment generally would be the same as that for
the inhalation risk assessment (e.g., regulatory requirement, community need, health concern).
However, a number of additional specific concerns may arise. For example, the potential for
bioaccumulation in food and subsequent ingestion may raise specific concerns about areas where
people farm, economic issues such as recreational fishing, or additional exposure pathways of
potential concern (e.g., infants ingesting mother's milk).
14.4.2 Identifying the Participants
The participants for the multipathway risk assessment generally would be the same as those for
the inhalation risk assessment. However,
• A broader range of risk managers would be involved. For example, if there is a potential for
a fishery or farm crops to become contaminated with air toxics, different persons or groups
may have the authority to make the risk management decisions - the state, local, or tribal
(S/L/T) fish and game department or the agriculture department may become involved.
• The risk assessment technical team would include additional experts (e.g., in the areas of
multimedia modeling, bioaccumulation, soil chemistry).
• The specific set of interested or affected parties may change or expand (e.g., farmers and
fishermen may be more concerned/involved).
14.4.3 Determining the Scope of the Risk Assessment
At a minimum, the scope of the risk assessment will include additional exposure pathways,
exposure routes, and potentially exposed populations or sub-populations. The details of scope
are developed during the problem formulation step (see Chapter 15).
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14.4.4 Describing the Problem
As with inhalation, participants would develop a problem statement that clearly articulates the
perceived problem to be evaluated. The problem statement may also provide statements of what
is and is not included in the multipathway risk assessment and why. (Note that, in general, only
one problem statement is necessary to describe all exposure pathways, including inhalation. A
separate problem statement for each exposure pathway is not usually necessary.)
14.4.5 Determining How Risk Managers Will Evaluate the Concern
As with inhalation, the multipathway risk assessment would be designed to provide input to risk
managers to help inform the decisions they must make. Part of the planning and scoping process
is developing an understanding of the types of information needed by the risk managers and the
level of uncertainty in that information that can be tolerated.
S N
Example Multipathway Problem Statement
Air toxics emissions may be causing increased long-term health risk to people who eat fish in Puffer
Pond that may be contaminated with mercury compound releases from the Big Air Manufacturing
Company. A multipathway risk assessment will be performed to evaluate potential long-term human
health impacts associated with consumption of contaminated fish. Ingestion risks will be assessed for
recreational fishers who eat fish caught in Puffer Pond. In addition, a modeling risk assessment using
air dispersion modeling will be conducted to estimate inhalation risks for populations within 50 km of
the Acme property boundary using residential exposure conditions.
\ /
14.5 Tiered Multipathway Risk Assessments
EPA guidance generally recommends that a tiered approach to risk assessments be taken to
identify the key chemicals, sources, and pathways that contribute most to the risk being
evaluated/5' A tiered approach can be particularly valuable for multipathway risk assessments
because of the potential complexity commonly associated with such analyses. Often, screening-
level analyses assume relatively high exposure factors (e.g., all of the fish a person eats comes
from a potentially contaminated pond) to determine whether risk associated with a specific
pathway appears to be significant enough to warrant more robust analysis. Subsequent tiers of
analysis, using more realistic exposure factors and perhaps involving more complex modeling
and perhaps sampling and analysis, are generally undertaken only if lower-tier analyses continue
to indicate the potential for risk. As with inhalation risk assessments, an iterative process of
evaluation, deliberation, data collection, work planning and communication is used to decide:
• Whether or not the risk assessment, in its current state, is sufficient to support the risk
management decision(s); and
• If the assessment is determined to be insufficient, whether or not progression to a higher tier
of complexity (or refinement of the current tier) would provide a sufficient benefit to warrant
the additional effort.
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References
1. U.S. Environmental Protection Agency. 1992. Guidelines for Exposure Assessment. Federal
Register 57:22888-22938, May 29, 1992. Available at
http ://cfpub. epa. gov/ncea/raf/recordisplay .cfm?deid= 15263
2. U.S. Environmental Protection Agency. 2001. Risk Assessment Guidance for Superfund
(RAGS): Volume I - Human Health Evaluation Manual (Part D, Standardized Planning,
Reporting and Review of Superfund Risk Assessments), Final. Office of Emergency and
Remedial Response, Washington, D.C., December 2001. EPA 9285.7-47.
3. U.S. Environmental Protection Agency. 1998. Human Health Risk Assessment Protocol for
Hazardous Waste Combustion Facilities, Peer Review Draft. Office of Solid Waste and
Emergency Response, July 1998. EPA/530/D-98/001 A, B, and C and subsequent Errata
(EPA Memo, July 1999). Available at:
http ://www. epa. gov/earth 1 r6/6pd/rcra_c/pd-o/comb_risk.htm
4. U.S. Environmental Protection Agency. 1997. Guidance on Cumulative Risk Assessment.
Part 1. Planning and Scoping. Science Policy Council, Washington, B.C., July 3, 1997.
Available at: http://www.epa.gov/osp/spc/cumrisk2.htm
U.S. Environmental Protection Agency. 2003. Framework for Cumulative Risk Assessment.
Office of Research and Development, National Center for Environmental Assessment,
Washington, D.C., 2003. EPA/600/P-02/001F. Available at:
http ://cfpub. epa. gov/ncea/raf/recordisplay .cfm?deid=54944
U.S. Environmental Protection Agency. 2001. Risk Assessment Guidance for Superfund
(RAGS): Volume I - Human Health Evaluation Manual (Part D, Standardized Planning,
Reporting and Review of Superfund Risk Assessments) Final. Office of Emergency and
Remedial Response, Washington, B.C., December 2001. Publication 9285.7-47. Available at:
http://www.epa.gov/superfund/programs/risk/ragsd/index.htm
5. U.S. Environmental Protection Agency. 2001. Risk Assessment Guidance for Superfund
(RAGS). Volume III - Part A. Process for Conducting Probabilistic Risk Assessment. Office
of Emergency and Remedial Response, Washington, B.C., December 2001.
EPA/540/R-02/002. Available at:
http ://www. epa. gov/superfund/programs/risk/rags3 a/index.htm
April 2004 Page 14-11
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Chapter 15 Problem Formulation: Multipathway
Risk Assessment
Table of Contents
15.1 Introduction 1
15.2 Developing the Multipathway Conceptual Model 1
15.3 Developing the Multipathway Analysis Plan 2
15.3.1 Identification of the Sources 3_
15.3.2 Identification of the Chemicals of Potential Concern 3_
15.3.3 Identification of the Exposure Pathways/Routes 3_
15.3.3.1 Characteristics of the Assessment Area 4
15.3.3.2 Scale of the Assessment Area 5
15.3.3.3 Use of Modeling vs. Monitoring 5
15.3.3.4 Quantitation of Exposure 6
15.3.3.5 Evaluation ofUncertainty 7
15.3.3.6 Preparation of the Documentation 7
15.3.4 Identification of the Exposed Population 7
15.3.5 Identification of Endpoints and Metrics 7
15.4 Exposure Assessment Approach 7
15.4.1 Scenario Approach £
15.4.2 Population-Based Approach 1J_
References 12
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15.1 Introduction
This chapter discusses the problem formulation step of the multipathway risk assessment, which
takes the results of the planning and scoping process and translates them into two critical
products: the conceptual model, and the analysis plan.
15.2 Developing the Multipathway Conceptual Model
As with inhalation analyses, the conceptual model (Exhibit 15-1) focuses the multipathway risk
assessment on several key elements, including sources, chemicals released, fate and transport
mechanisms, potentially exposed populations, potential exposure pathways and routes of
exposure, and potential adverse effects. Although discussed separately here, as noted in Chapter
6, the elements of the conceptual model that are unique to the multipathway human health
risk assessment should be integrated with those for the inhalation assessment as early as
feasible.
Exhibit 15-1. Generalized Conceptual Model for Multipathway Analyses
Sources
Sfressors
Pathways/
Media
Routes
Subpopulations
End points
(Specific non-cancer
target organ
endpoints shown for
example purposes)
Metrics
HAP-spedlic and
cumulative (e.g.. by
cancer type, weight of
evidence: by target-organ-
specific hazard index), by
Srate by county fatso ail
counties and all urban
counties}
Extrinsic "background"
in other media
33 Priority Urban HAPs
(including PET
— 1 — — 1 —
ante
White AAfrlMn
American
General
Population
Asian American
i
1,
! 1
(leukemia" lung" otters) Res'ira""V
Young
Children
Blood (including
marrow & spleen)
CNS
Adoles-
cents
.
Adults
Liver &
kidney
Cardio-
vascular
Elderly
Othe
et
effects
Possible Csranogers
Probable Carcinogens
Known Carcinogens
Distribution of
high-end cancer
risk estimates
Estimated percent of
population within specified
cancer risk ranges
Estimated
number of
cancer cases
Cardiovascular Hazard Index
Liver and Kldntay Hazard Index
CNS Hazard Index
Blood Hazard Index
Respiratory System Hazard Irdex
Distribution of
estimated
index values
Estimated percent of
population within specified
ranges of index values
This figure highlights the multipathway components of the general air toxics risk assessment
conceptual model introduced in Chapter 6. The conceptual model for a specific multipathway risk
assessment may consider only part of this general model, or may focus more closely on specific sub-
populations of concern.
April 2004
Page 15-1
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Elements of the conceptual model that maybe unique to the multipathway assessment include:
• Sources. The specific sources included in the analysis maybe focused on the subset of all
sources that release most or all of the identified air toxics that persist and which also may
bioaccumulate.
• Chemicals of potential concern. The specific COPC will focus on those air toxics that
persist and which also may bioaccumulate (i.e., persistent bioaccumulative hazardous air
pollutants (PB-HAPs) and other non-HAP chemicals that maybe of concern for persistence
and bioaccumulation).
• How the COPC move through the environment. The conceptual model will need to
consider the mechanisms by which PB-HAPs move through the environment, which include
dispersion in the air; deposition (including vapor phase transfer) to soils, surface waters, and
plant surfaces; erosion and other runoff phenomena; and uptake and bioconcentration by
biota. The physical boundaries of the study area may need to include geographic areas where
COPC may be transported after deposition (e.g., PB-HAPs may have the potential to be
deposited in a watershed and be carried out of the geographic area defined for the inhalation
pathway modeling).
• The exposure pathways/media of concern. The potential exposure pathways will include a
number of different ingestion pathways and, in some cases, dermal absorption pathways.
• The human populations potentially receiving exposure. The potentially exposed
populations may need to include persons who do not live within the study area but consume
food products that have the potential to become contaminated (e.g., recreational fisher).
Additionally, different sensitive sub-populations may be identified (e.g., people who consume
large amounts of locally-caught fish because of cultural reasons).
• The potential adverse health effects (endpoints) that may result from exposure. The
general types of chronic health risks (cancer, non-cancer) may or may not change, depending
on the specific COPC being evaluated. However, acute exposures generally are not a concern
for multipathway analyses because it would be unlikely for air toxics to accumulate in soil,
sediment, or food items to concentrations that would pose, in the absence of a chronic hazard,
an acute hazard through the ingestion or dermal pathway.
• Metrics. The metrics used to characterize exposure and estimate risk may or may not be
different from those used in the inhalation risk assessment. For example, the inhalation
assessment may stop at a Tier 1 analysis, while the multipathway assessment may go all the
way to a Tier 3 analysis.
15.3 Developing the Multipathway Analysis Plan
As noted in Chapter 6, the analysis plan matches each element of the conceptual model with the
analytical approach that the assessor will use to develop data about that element. This section
describes the elements of the analysis plan that are unique to the multipathway assessment,
including (1) identification of sources; (2) identification of COPC; (3); identification of exposure
April 2004 Page 15-2
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pathways/routes; (4) identification of exposed populations; and (5) identification of endpoints
and metrics.
15.3.1 Identification of the Sources
This part of the analysis plan identifies the sources to be included in the risk assessment. As
noted earlier, the focus of multipathway analysis is on sources of the air toxics that persist and
which also may bioaccumulate. Within that subset, certain sources may be most important for a
specific risk assessment. A tiered approach is recommended for focusing the risk assessment
from the initial set of sources to the sources that will drive risk management decisions. The
initial tier of analysis generally includes all sources of PB-HAPs. In subsequent tiers of analysis,
it may be possible to remove specific sources from the analysis that contribute a very small
fraction to the total risk estimate.
15.3.2 Identification of the Chemicals of Potential Concern
This part of the analysis plan identifies the chemicals that will be evaluated in the risk
assessment. As noted earlier, the focus of multipathway analysis is on the subset of air toxics
that persist and which may also bioaccumulate. Within that subset, certain chemicals may be
most important for a specific risk assessment. A tiered approach is recommended for focusing
the risk assessment from the initial list of COPC to the set of contaminants that will drive risk
management decisions. The initial tier of analysis generally includes all of the air toxics released
from the identified important sources. In subsequent tiers of analysis, it maybe possible to
remove specific chemicals from the analysis if they contribute a very small fraction to the total
risk estimate.
15.3.3 Identification of the Exposure Pathways/Routes
This part of the analysis plan identifies the exposure pathways/routes to be evaluated. As noted
in Chapter 6, an exposure pathway consists of four elements:
• A source and mechanism of chemical release;
• One or more environmental media (i.e., air, water, soil) in which the chemical is transported
from the source;
• A point of potential human contact with the contaminated medium (referred to as the
exposure point); and
• An exposure route (e.g., inhalation, ingestion) at the contact or exposure point. The route
maybe actual or potential, depending on the purpose of the assessment.
The exposure pathway is complete if all four elements can be identified; otherwise the exposure
pathway is incomplete and not considered further (see Exhibit 14-2, which presents the potential
exposure pathways considered for multipathway assessments).
The exposure points selected for the multipathway risk assessment also will depend on the choice
of multipathway assessment approach and may or may not be identical to those used in the
inhalation risk assessment. In the example presented in Chapter 11, Mr. McDonald's house was
selected as the point of maximum inhalation concentration at a receptor location. The
multipathway assessment would likely also evaluate potential exposures via crops, meat, milk,
April 2004 Page 15-3
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and other foods. However, the focus would be on other exposure points or areas within the farm
(e.g., the area where forage fed to dairy cows is grown or where vegetable crops are planted), not
on the farmer's house.
15.3.3.1 Characteristics of the Assessment Area
The physical setting is important both in developing the study-specific conceptual model and
selecting and providing input parameters for the appropriate multimedia models. As described
earlier, the physical setting includes information such as urban vs. rural setting, simple vs.
complex terrain, climate and meteorology, and other important geographic features (see Chapter
6). The most important additional information required for multipathway analyses is information
on land use, soils, and surface water bodies within the assessment area.(a) Many of the general
physical characteristics of the setting will influence the scope of multimedia modeling required.
For example, if the sources being evaluated are located in heavily industrialized area, there may
be few, if any, agricultural areas or water bodies close enough to receive significant deposition.
In this example, deposition to soils in nearby residential areas and subsequent exposure pathways
may be the most significant exposure pathways to examine.
• Land use. Information on land use is an important part of the physical characteristics of the
assessment area discussed in Chapter 6. For multipathway analyses, it is important to
identify specific types of land uses that may lead to exposures via ingestion pathways,
especially agriculture, fishing, recreation, and residential (indoor and outdoor, including
gardening), as well as the location of particular areas where exposures via soil may be of
concern (e.g., playgrounds, schools, day care centers). Sources for land use data are
discussed in Chapter 6.
• Soils. The type and characteristics of soils (e.g., sandy, organic, acidic, alkaline) in the
assessment area affects physical phenomena such as soil erosion rates, the types and density
of plants supported by the soils, and the physical and chemical characteristics that govern
contaminant fate and transport. For example, the bioavailability of a compound may depend
partially on soil pH. The specific information needed will depend in part on the input
requirements of the multimedia fate and transport models selected for the analysis (see
Chapter 19).(b)
• Water bodies and their associated watersheds. Water bodies and their associated
watersheds are important factors in evaluating some of the major exposure pathways/routes
considered in multipathway analyses. For example, the identification of surface water bodies
at locations in the assessment area receiving deposition from emission sources indicates the
potential for exposures to contaminants from ingestion of fish, and possibly drinking water
(drinking water is usually evaluated only if the local population obtains drinking water from
Maps, aerial photos, and tools such as Geographic Information Systems (GIS) can be very helpful tools for
characterizing the exposure setting (see Part VI of this Reference Manual).
Sources of this information may include any existing site descriptions, preliminary risk assessments, county
soil surveys, wetlands maps, aerial photographs, U.S. Geological Survey topographic maps, U.S. Department of
Agriculture Soil Conservation Service reports, and information from state natural resources agencies.
April 2004 Page 15-4
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surface water sources) .(c) Information on fishing activity will also be useful in characterizing
the potentially exposed population.
Land use and human activities should be characterized in much the same way as Chapter 6
described, except that a broader range of activities/uses needs to be considered. It is important to
identify all activities within the assessment area that could result in exposure to contaminants via
non-inhalation pathways. These would include hunting, fishing, growing crops (e.g.,
commercially, as animal feed, or for private consumption), and incidental ingestion of soils. As
noted earlier, the multipathway assessment may need to specifically address special populations
that are located in impacted areas because of unique characteristics of the exposure setting or to
address particular community concerns. For example, a day care center or traditional Tribal
fishing/hunting area may be located in an area that is impacted by releases from a facility or
source area. Consequently, due to the site-specific exposure characteristics, exposure to children
at the day care center or tribal members may need to be addressed, because they may be
especially sensitive to the adverse effects and/or the exposure setting maybe particularly
conducive to exposure. EPA has developed a policy focused on consistently and explicitly
evaluating environmental health risks to infants and children in all risk assessments.0'
15.3.3.2 Scale of the Assessment Area
For inhalation assessments, the study area generally is limited to a 50-km radius from the
emissions sources (based on the dispersion models being used). The study area for the
multipathway risk assessment generally will be limited similarly to the area in which deposition
is modeled. However, certain potential exposure scenarios may require expansion of the study
area beyond the modeled deposition area. Examples include:
• The watershed for a lake or pond is within the modeled deposition area, but the lake or pond
(where contaminants may accumulate) is outside the deposition area.
• A commercial farm is within the deposition area, and a portion of the crops are consumed by
persons living outside the deposition area.
A popular fishing area is located within the
deposition area, and people from outside
the deposition area come there to fish.
15.3.3.3 Use of Modeling vs. Monitoring
As this document has previously noted, risk
assessors can base estimates of current
exposure concentrations on either actual
Multimedia Assessments: Modeling vs. Monitoring
Most multimedia air toxics risk assessments will
develop estimates of exposure concentration for non-
inhalation pathways primarily through modeling. In
some instances, analysts may use monitoring to evaluate
the model. In more rare instances, however, analysts
will use monitoring to develop exposure concentrations.
°Use, area, and location of water bodies and their associated watersheds can typically be identified by
reviewing the same land-use land classification maps, topographic maps, and aerial photographs used in
identification of land use discussed in Part II of this Reference Manual. Additional information on water body use
can also be obtained through discussions with local authorities (e.g., state environmental agencies, fish and wildlife
agencies, or local water control districts) about viability to support fish populations and drinking water sources, or
current postings offish advisories.
April 2004
Page 15-5
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measurements (i.e., monitoring data) or modeling (in this case, multimedia models). In many
cases, monitoring can be helpful in reducing uncertainties in the exposure assessment, because
multimedia modeling is more complex and involves more uncertainties. Note, however, that the
scope of potential monitoring for multipathway analysis is considerably greater than that for
inhalation analyses. A wide range of types of sampling and analysis could be conducted,
including sampling of soils, surface waters, sediments, and biota (human food items). Each type
of sample has its own methods, protocols, and QA/QC requirements (see Chapter 19).
Multimedia sampling and analysis may require additional expertise and effort. The analysis plan,
including the quality assurance protection plan (QAPP), will need to be modified accordingly.
15.3.3.4 Quantitation of Exposure
In contrast to the inhalation assessment, in which the quantitative metric of exposure is the
ambient air concentration at the exposure point, ingestion exposures are quantified using the
chemical intake rate - the amount of chemical ingested per unit time - generally expressed in
units of milligrams of chemical per kilogram of body weight per day. The fundamental equation
for dietary intake and ingestion pathways in general is given as:
CR EF x ED
I = x (Equation 15-1)
BW AT
where
/ = Chemical intake rate, expressed in units of mg/kg-day. For evaluating exposure to
non-carcinogens, the intake is referred to as average daily dose (ADD}; for evaluating
exposure to carcinogenic compounds, the intake is referred to as lifetime average
daily dose (LADD).
EC = Exposure concentration of the chemical in the medium of concern for the time period
being analyzed, expressed in units of mg/kg for soil and food or mg/L for surface
water or beverages (including milk).
CR = Consumption rate, the amount of contaminated medium consumed per unit of time,
event, or other measure, (e.g., kg/day for soil and food; L/day for water).
EF = Exposure frequency (number of days exposed per year).
ED = Exposure duration (number of years exposed ).
B W = Average body weight of the receptor over the exposure period (kg).
AT = Averaging time, the period over which exposure is averaged (days). For carcinogens,
the averaging time is usually 25,550 days, based on an assumed lifetime exposure of
70 years; for non-carcinogens, averaging time equals ED (years) multiplied by 365
days per year.
As noted above, modeling and/or monitoring (sampling and analysis) can be used to determine
the exposure concentration (EC) at specified exposure points. However, a variety of approaches
and assumptions can be used to determine the remaining variables in the equation, as will be
discussed in subsequent chapters. For example, calculation of the intake rate requires
assumptions about diet (i.e., how much the exposed individual eats and drinks each day) and
body weight (how much the individual weighs). Dietary assumptions need to be specific to the
type of food consumed (e.g., fish, milk, beef).
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As noted in Section 6.3.3.4, the exposure duration (ED) used to calculate chemical intake rate (I)
will have an impact on the choice of toxicity values (e.g., acute vs. chronic) used to characterize
risk and hazard. As a general rule, the ED values should match the exposure assumptions used in
developing the dose-response values.
15.3.3.5 Evaluation of Uncertainty
As with the inhalation assessment, the evaluation of uncertainty includes both a summary of the
values used to estimate exposure, including their range, midpoint,and other values; and a
qualitative or quantitative discussion that evaluates which variables or assumptions have the
greatest potential to affect the overall uncertainty in the exposure assessment.
15.3.3.6 Preparation of the Documentation
The analysis plan needs to specify the approach used to document the multipathway exposure
assessment, as discussed in Chapter 20.
15.3.4 Identification of the Exposed Population
This part of the analysis plan identifies the exposed population that will be evaluated in the risk
assessment. The procedure for characterizing the potentially exposed population generally will
be similar to that described for the inhalation pathway (Chapter 6). As noted previously, it may
be necessary to include individuals who live outside the modeled deposition area. The manner in
which potentially exposed populations are characterized depends on the general approach used
for the multipathway assessment (see Section 15.4 below).
15.3.5 Identification of Endpoints and Metrics
This part of the analysis plan identifies the specific human health endpoints that will be evaluated
in the risk assessment and the metrics used to quantify exposure and risk. The multimedia
assessment uses the same general endpoints (i.e., cancer and non-cancer) and presents the central
tendency and high-end tendency descriptors required as the range of risk estimates of the
distribution. Risk characterization is discussed in more detail in Chapter 22.
15.4 Exposure Assessment Approach
A variety of approaches are available for multipathway exposure assessments. This section
describes two representative approaches that range from a relatively simple approach based on
scenarios to a very complex and data-driven approach based on mass-balance models. This
discussion is intended to illustrate some of the potential approaches available for multipathway
exposure assessment. A given risk assessment might incorporate features of either of the two
approaches outlined below, or might feature a different approach.
Regardless of the specific approach taken, EPA recommends a tiered approach to multipathway
exposure assessment, in which the exposure assessment moves from relatively simple to more
complex as warranted by the quality of available information and its ability to be used to support
the risk management decision(s). Chapter 3 provides an overview of tiered approaches to risk
assessment.
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Childhood exposures need to be considered explicitly in any non-inhalation scenario. This can
be done with a separate scenario (e.g., a "resident child") or by incorporating changes in
consumption rates, dietary preferences, and body weight with age in the exposure factors
incorporated into the scenario. EPA's Risk Assessment Forum recently published guidance on
selecting appropriate age groups for assessing childhood exposures.(2)
15.4.1 Scenario Approach
Multipathway exposures may be evaluated by developing a number of scenarios that describe the
potential human exposures that might occur via each of the potential exposure pathways
identified in the conceptual model. An exposure scenario is a combination of exposure
pathways by which a single defined human receptor might be exposed to air toxics that persist
and which also may bioaccumulate. The specific exposure scenarios defined for a given risk
assessment would be based on the characteristics of the exposure setting, potential exposure
pathways, potential exposure points or areas, and predominant land uses and activities associated
with the potentially exposed population. For example, if the study area included a small lake
where fishing might occur, the assessment might include a "fisher" scenario that included
ingestion offish caught in the lake.
The scenario approach generally involves relatively simple modeling and fewer data
requirements as modeling inputs. This can be performed by using "linked modeling systems"
which can either be relatively simple or incorporate highly sophisticated single-medium models
into a single multimedia system. However, these types of models do not assure conservation of
mass and therefore may under- or over-estimate exposure concentrations for particular scenarios.
The general scenario approach involves:
• Identifying the potential exposure pathways that may be important, including the areas where
contaminants have the potential to accumulate in soils, surface waters, sediments, and biota;
and specific activities that may result in ingestion of these contaminants (either via incidental
ingestion of soil while in the contaminated areas or by consuming the contaminated plants,
animals, or surface water).
• Developing a set of scenarios that describe reasonable sets of potential exposure pathways,
given the types of people and activities that occur within the study area. The scenarios would
include specific exposure factors (e.g., body weight, fish consumption) based on the
particular activities identified above. The exposure scenarios should consider children, either
as a separate scenarios (e.g., a "resident child") or as part of an overall scenario (e.g.,
someone who is born in the exposure area and lives there for 30 years, and thus experiences
exposure both during childhood and as an adult). The exposure factors could be set initially
at conservative levels for screening-level assessments and then at more site-specific levels for
higher tiers of analysis. Each exposure scenario also should appropriately consider study-
specific sub-populations that may experience different exposure conditions (e.g., because
they eat different foods or parts of foods at different rates than the general population).
• Using relatively simple multimedia modeling techniques (e.g., "linked modeling systems"
described in Chapter 18) to estimate exposure concentrations in the media and biota of
interest to each scenario. Monitoring (sampling or analysis) could be used to augment the
modeling effort. For screening-level analyses, the scenarios can be based on the locations
April 2004 Page 15-8
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with the highest modeled concentrations or deposition rates. For example, a scenario
involving consumption offish could be based on the same location as a residential scenario.
In some cases, it may be appropriate to evaluate an exposure scenario assuming exposure
through ingestion of fish from one water body and drinking water from a different water
body. Such assumptions may need to be refined in subsequent modeling tiers.
• Quantifying the dietary intake for each scenario based on the modeled or estimated exposure
concentrations and the specific exposure factors for each scenario.
Several exposure scenarios are commonly used in multipathway risk assessments (Exhibit 15-4).
A recent description of several scenarios is provided in EPA's risk assessment guidance for
hazardous waste incinerators .(3) In addition to the commonly assessed scenarios provided in
Exhibit 15-4, other scenarios may be appropriate, depending on study-specific conditions. For
example, if a contaminated surface water body is used for bathing and swimming, incidental
ingestion, and dermal exposure from these activities may need to be considered. As another
example, the resuspension of contaminated soils (i.e., windblown dust) maybe important in
some study areas. Note also that exposure of an infant to chlorinated dioxins/furans (and other
lipophilic contaminants) via the ingestion of breast milk may be evaluated as an additional
exposure pathway, separately from adult exposures, in each of the scenarios outlined below.
Note also that in each of these scenarios, the risk assessment needs to look at both an adult
and child (for example, the "farmer" includes both an adult farmer and a farmer child).
Farmer. The farmer scenario is commonly evaluated to account for the combination of exposure
pathways to which a person may be exposed in a farm or ranch exposure setting. As indicated in
Exhibit 15-4, the farmer is commonly assumed to be exposed to air toxics through one or more of
the following exposure pathways:
• Direct inhalation of vapors and particles;
• Incidental ingestion of soil;
• Ingestion of drinking water from surface water sources;
• Ingestion of homegrown produce;
• Ingestion of homegrown beef;
• Ingestion of dairy products from homegrown livestock;
• Ingestion of homegrown chicken;
• Ingestion of eggs from homegrown chickens;
• Ingestion of homegrown pork; and
• Ingestion of breast milk (evaluated separately for an infant [for PCBs, dioxins, and furans]).
In a Tier 1 assessment, the farmer commonly is assumed to consume a certain amount daily (e.g.,
grams/day) of each food group (beef, pork, poultry, eggs, and milk) to make up a total
consumption rate, and amounts consumed are assumed to be homegrown. If site-specific
information is available that demonstrates that a farmer does not raise beef, poultry, or pork, and
that raising any of these livestock would not occur for a reasonable potential future farmer at a
location, then elimination of one or more of these exposure pathways could be justified. The
farmer scenario often does not include the fish ingestion exposure pathway. However, in some
areas of the country, it is common for farms to also have stock ponds which are fished on a
regular basis for the farmer's consumption. Also, ingestion rates (e.g., food, incidental soil
ingestion) often are age-dependent.
April 2004 Page 15-9
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Exhibit 15-4. Common Exposure Scenarios Used in Multipathway Exposure Assessments
Exposure Pathways
Scenarios"
OJ
OJ
e2
s
e
V
V §
•«
o
El
(S 5£
u S3
o o
J U
Inhalation of Vapors and Particulatesb
Incidental Ingestion of Soil
Ingestion of Drinking Water from Surface Water Sources
Ingestion of Homegrown Produce
Ingestion of Homegrown Beef
Ingestion of Milk from Homegrown Cows
Ingestion of Homegrown Chicken
Ingestion of Eggs from Homegrown Chickens
Ingestion of Homegrown Pork
Ingestion of Fish
Ingestion of Breast Milk
Notes:
• Pathway is included in exposure scenario.
- Pathway is not included in exposure scenario.
a Exposure scenarios are defined as a combination of exposure pathways evaluated for a receptor at
a specific exposure scenario location. Note that these scenarios are not exhaustive (i.e., additional
or other scenarios may be relevant to a particular exposure assessment). Note also that within
each scenario, the quantitative exposure estimates will vary across age groups.
b Note that inhalation is included in the overall exposure assessment, but the inhalation exposure
assessment is performed separately (as described in Part n of this Reference Library).
c Infant exposure to dioxins and/or furans via the ingestion of their mother's breast milk is evaluated
for infants as an additional, separate exposure pathway.
d
Regional specific exposure setting characteristics (e.g., presence of ponds on farms or within
semi-rural residential areas, presence of livestock within semi-rural residential areas) may warrant
inclusion of this exposure pathway when evaluating a recommended exposure scenario.
Resident. The resident scenario is commonly evaluated to account for the combination of
exposure pathways to which a person may be exposed in an urban or rural (non-farm) setting. As
indicated in Exhibit 15-4, the resident is commonly assumed to be exposed to air toxics through
the following exposure pathways:
• Direct inhalation of vapors and particles;
• Incidental ingestion of soil;
• Ingestion of drinking water from treated surface water sources; and
• Ingestion of breast milk (evaluated separately for an infant [for PCBs, dioxins, and furans]).
April 2004
Page IS-10
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The resident scenario often does not include the fish ingestion exposure pathway. However, in
some areas of the country, ponds within semi-rural residential areas support fish for human
consumption.
Resident with Garden. The resident with garden scenario is commonly evaluated to account for
people who maybe exposed while gardening or through the consumption of produce grown in
their garden in an urban or rural (non-farm) setting. As indicated in Exhibit 15-4, the resident
with garden is commonly assumed to be exposed to air toxics through the same exposure
pathways as the resident scenario, with one additional exposure pathway:
• Ingestion of homegrown produce.
Local Fish Consumer. The local fish consumer scenario is evaluated to account for the
combination of exposure pathways to which a receptor may be exposed in an urban or rural
setting where fish is the main component of the person's diet. As indicated in Exhibit 15-4, the
local fish consumer is commonly assumed to be exposed to air toxics through the following
exposure pathways:
• Direct inhalation of vapors and particles;
• Incidental ingestion of soil;
• Ingestion of drinking water from surface water sources;
• Ingestion of homegrown produce;
• Ingestion of fish; and
• Ingestion of breast milk (evaluated separately for an infant [for PCBs, dioxins, and furans]).
In many cases, local fish consumers are assumed to grow some of their own produce, but this
may or may not be relevant to a particular risk assessment. Also note that in some parts of the
country, a primary reliance on fishing as a source or dietary protein is common - a circumstance
known as "subsistence fishing." Subsistence hunting may also be important for some groups.
15.4.2 Population-Based Approach
Multipathway exposures may be evaluated by tracking individual members of a population and
their inhalation and ingestion through time and space. Such analyses may incorporate a user-
specified number of simulated individuals or population groups (cohorts) to represent the
population in the study area. A cohort is defined here as a group of people within a population
with the same demographic variables who are assumed to have similar exposures. In this
approach, the exposure analysis process consists of relating chemical concentrations in
environmental media (e.g., air, soil, water) to chemical concentrations in the exposure media
with which a person or population has contact (e.g., soil, food, household dust). Exposure is
estimated by tracking the movement of a population cohort through locations where chemical
exposure can occur according to a specific activity pattern.(4) Models such as the Stochastic
Human Exposure and Dose Simulation Model (SHEDS), Calendex, the Hazardous Air Pollution
Exposure Model (HAPEM), and the Total Risk Integrated Methodology, Exposure Event Model
(TRIM.Expo) incorporate this approach (see Chapter 19). The general approach, which is
analogous to the inhalation exposure modeling techniques described in Chapter 9, involves:
April 2004 Page 15-11
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• Defining exposure districts - geographic locations within the study area where there is
potential contact between humans and a pollutant - and estimating chemical concentrations
within each exposure district (through modeling and/or measurement).
• Preparing inventories of chemical concentrations in each microenvironment in each exposure
district at selected time intervals (e.g., days, hours). These inventories maybe developed
using mass-balance approaches that predict the partitioning of chemicals throughout the
environment or through the use of microenvironment factors.
• Identifying the characteristics and activity patterns of each population cohort or set of
representative individuals (e.g., the demographic characteristics of the individual; the
locations where the individual lives, works, etc.; the amount of time spent in each location,
and the individual's activities within a location). These activity patterns should be
representative of the exposed population of concern. For representative individuals or
cohorts, each simulated person/cohort is represented by a "personal profile" or "activity
pattern" developed by selecting from a set of variables that include:
- Demographic variables (e.g. age, sex), which are generated based on census data;
- Residential variables (e.g., where the person lives, works, etc., which are generated based
on sets of distribution data;
- Daily varying variables (e.g., how long a person works in a garden), which are generated
based on distribution data that change daily during the simulation period;
- Physiological variables (e.g., height, weight), which are generated based on age group-
specific distribution data; and
- Dietary variables (e.g., amount and type of food consumed), which are generated based
on sets of distribution data.
Profiles or activity patterns may be developed using probability density functions, allowing
the analysis to incorporate probabilistic techniques such as Monte Carlo analysis (see Part VII
of this reference manual).
• Summing the exposures for each exposure event over the assumed duration of exposure (e.g.,
lifetime or portion of a lifetime).
The primary advantage of the population-based approach is that it is a more realistic exposure
assessment that simulates how people actually live and work within the study area. It therefore
can provide a more complete characterization of the spatial and temporal patterns of exposure.
The primary disadvantage of the cohort approach is the time and resources it requires, including
significant input data requirements.
References
1. U.S. Environmental Protection Agency. 1995. New Policy on Evaluating Health Risks to
Children. Memorandum to Assistant Administrators, General Counsel, Inspector General,
Associate Administrators, Regional Administrators. From Carol M. Browner, Administrator,
and Fred Hansen, Deputy Administrator. Washington, DC., October 20, 1995.
April 2004 Page 15-12
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2. U.S. Environmental Protection Agency. 2003. Guidance on Selecting the Appropriate Age
Groups for Assessing Childhood Exposures to Environmental Contaminants (External
Review Draft). Risk Assessment Forum, Washington, B.C., February 1, 2003.
EPA/630/P-03/003A. Available at: http://cfpub.epa.gov/ncea/cfm/
recordisplay.cfm?deid=55887
3. U.S. Environmental Protection Agency. 1998. Human Health Risk Assessment Protocol for
Hazardous Waste Combustion Facilities, Volume 1. Peer Review Draft. Office of Solid
Waste and Emergency Response, Washington, D.C., July 1998. EPA/530/D-98/001A.
Available at: http://www.epa.gov/combustion/risk.htm.
4. See the Human Exposure Modeling page of EPA's Fate, Exposure and Risk Analysis
(FERA) website: http://www.epa.gov/ttn/fera/human_gen.html.
See the TRIM.Expo web page at: http://www.epa.gov/ttn/fera/human_apex.html.
U.S. Environmental Protection Agency. 1999. Total Risk Integrated Methodology.
TRIM.Expo Technical Support Document. External Review Draft. Office of Air Quality
Planning and Standards, Research Triangle Park, NC, November 1999. EPA/453/D-99/001.
Available at http://www.epa.gov/ttn/fera/trim fate.html# 1999historical.
April 2004 Page 15-13
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Chapter 16 Quantification of Exposure:
Development of the Emissions Inventory
for the Multipathway Risk Assessment
Table of Contents
16.1 Introduction
16.2 Developing the Emissions Inventory
-------
-------
16.1 Introduction
Chapter 7 provides an overview of the process used to develop an emissions inventory for an air
toxics risk assessment. As noted in that chapter:
• Emissions data are a source term for the risk assessment, primarily as a key input for
computer models that estimate the transport of chemicals in the atmosphere; if and how they
will be transformed by chemical or physical processes; how and where they will be
deposited; and how they will continue to partition and move through environmental media
following deposition.
• Developing the emissions inventory involves identifying the specific air toxics released from
the source and quantifying release characteristics (e.g., release rates, temperature, release
velocity).
• Local enhancements of existing air toxics emissions inventories may be advantageous to a
particular air toxics assessment effort as a very critical initial step, because air toxics
inventories are not always at the quality that would provide the results desired in a modeling
assessment.
16.2 Developing the Emissions Inventory
The process used to develop the emissions inventory for the multipathway risk assessment is
similar to the process for inhalation analyses (see Chapter 7 for a description of this process).
However, there are a few additional considerations that may apply to a given multipathway
analysis (e.g., information on particulate/particle-bound/vapor fractions if ISCST3 is used). See
Chapter 18 for more discussion on inputs for models used in multimedia assessment.
April 2004 Page 16-1
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Chapter 17 Quantification of Exposure: Chemical
and Physical Properties Affecting
Multimedia Fate and Transport
Table of Contents
17.1 Introduction 1
17.1.1 Measures of Persistence 1
17.1.2 Metrics of Bioaccumulation 5
17.2 Chemical and Physical Properties that Affect Persistence and Bioaccumulation £
17.3 Evaluating Persistence and Bioaccumulation in Exposure Assessments K)
References 11
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17.1 Introduction
This chapter provides both an overview of the physical and chemical properties of chemicals that
persist in the environment long enough to be of potential concern for multimedia exposure and
information on their potential to bioaccumulate in biological tissues to levels that may result in
significant exposures. This chapter also provides a brief discussion of various approaches for
evaluating persistence and bioaccumulation in an air toxics exposure assessment.
• The term persistence refers to air toxics that are slow to degrade in the atmosphere or in the
soils, water, and/or sediments onto which they deposit and partition. Under certain
circumstances, persistent chemicals can increase in concentration over time. In addition,
some of these pollutants can bind tightly to soils and sediment and move from place to place
by erosion. Examples of persistent chemicals are metals (which never degrade) and
poly chlorinated biphenyls (which degrade, but only over very long periods of time).
Measures of persistence are described in Section 17.1.1.
• The term bioaccumulation refers to persistent chemicals that build up in the tissues of living
organisms to concentrations that are higher than in the surrounding environment. These
pollutants are often lipophilic in nature, which allows them to be taken up in and stored by fat
tissues. As an example, the group of chemicals known collectively as dioxins (usually some
mixture of chlorinated dioxins and furans) persists for long periods of time in the
environment and is strongly lipophilic. Repeated exposure to dioxin in food can lead to
increased body burdens in fat tissue and human milk. Measures of bioaccumulation are
discussed in 17.1.2.
• The term biomagnification refers to persistent chemicals that increase in concentration as
they transfer up the food chain so that they accumulate to higher concentration levels with
each successive food chain level (see Section 17.1.2).
The air pollutant's physical and chemical properties and the characteristics of the environment to
which the pollutant is emitted affect its potential to persist and bioaccumulate. One of the most
important determinants in predicting persistence and accumulation in biota and other
environmental media is the partitioning behavior of the pollutant. Partitioning refers to where in
the environment a chemical will tend to reside and in what relative quantities. When released to
the air, chemicals may partition to air, water, soils, sediments, or biota, depending on a number
of chemical and site-specific factors. Section 17.2 highlights measures of partitioning and other
chemical and physical properties. Section 17.3 discusses how measures of persistence,
bioaccumulation, and partitioning are used in exposure assessment.
17.1.1 Measures of Persistence
Estimating the persistence of chemicals in the environment is a challenging exercise. Persistence
depends on basic processes such as how the chemicals are released (i.e., which environmental
media they are released to initially, in this case, air); how they move in the environment (i.e., to
which environmental media they tend to partition); and their tendency to degrade within those
specific media (i.e., their persistence in air vs. in water). These basic processes, in turn, depend
on a number of chemical-specific properties and site-specific conditions. However, despite the
April 2004 Page 1 7-1
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complexity of the overall process, some general screening methods are available to get a sense of
persistence of chemicals in certain media.
Within each environmental medium, several different degradation processes can influence the
persistence of chemicals. However, regardless of the specific degradation process, what
generally occurs is that organic chemicals (or organo-metallic compounds) are reduced in size
and complexity, and, if complete degradation occurs, converted to carbon dioxide, methane,
ammonia, water, sulfates, phosphates, nitrates, and other end products. Explanations of the
specific degradation processes and their applications within different environmental media are
summarized below and in Exhibit 17-1:
• Aerobic biodegradation is the breakdown of chemicals by microorganisms that utilize
oxygen;
• Hydrolysis is the breakdown of chemicals by reaction with water;
• Photolysis or photodegradation is the process by which chemicals can be degraded by the
energy in artificial light or sunlight;
• Oxidation or reduction (or redox)
reactions involving the exchange of
electrons between the pollutant and reactive
compounds found in the environment;
• Photooxidation is a process by which
oxidation and photolysis work jointly to
break down chemicals and refers to a
reaction with oxygen in the presence of light
(usually sunlight); and
• Anaerobic biodegradation is the
breakdown of chemicals by microorganisms
without the use oxygen (for example, in
sediments).
Persistence is usually described using a term
called half-life, which is the time required for
one-half of the original mass of the chemical to
be degraded, transformed, or destroyed in a
given medium. Half-life values may be
measured directly or estimated (e.g., with
computer models that predict half-life based on
chemical structure). Alternatively, the literature
may report a degradation or transformation rate
constant in units such as I/day or day1. Assuming the reaction is first-order, the rate constant
can be converted to the half-life and vice versa using the equation t/2 = 0.693/k, where t/2 is the
half-life (days) and k is the first-order rate constant (day1). Exhibit 17-2 provides a list of data
sources for degradation half-life or rate constant values.
Exhibit 17-1. Degradation Processes in
Environmental Media
Environmental
Medium
Air
Surface water
Soils
Sediments
Applicable Degradation
Process(es)
Photolysis
Photooxidation
Aerobic biodegradation
Hydrolysis
Photolysis
Photooxidation
Aerobic biodegradation
Hydrolysis
Photolysis (surface soil)
Oxidation - reduction
reactions
Anaerobic biodegradation
April 2004
Page 1 7-2
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Exhibit 17-2. Data Sources for Half-Life and Rate Constant Values
Data Source
Data Elements
Comments
Howard et al.
Handbook
High and low compartment
half-life values for soil, air,
surface water, and
sediment/ground water
based on measurements and
modeling estimations; and
High and low measured and
estimated process-specific
half-life values, including
hydrolysis, reduction,
photolysis, photooxidation
(in water and air), and
biodegradation.
Howard et al.(1) compiled measured and estimated
environmental degradation rates for organic
chemicals, including polycyclic aromatic
hydrocarbons (PAHs), pesticides, and solvents.
Mackay et al
Handbooks
Measured and estimated
half-life and rate constant
data for air, water, soil, and
sediment.
Mackay et al.(2) compiled measured and estimated
environmental degradation rates for organic
chemicals, including monoaromatic
hydrocarbons, chlorobenzenes, polychlorinated
biphenyls, polynuclear aromatic hydrocarbons,
polychlorinated dioxins and dibenzofurans,
volatile organic compounds (VOCs), pesticides,
and oxygen, nitrogen, and sulfur organic
compounds.
Verschuren
Measured and estimated
half-life values in surface
water, ground water,
sediment, soil, and biota.
Verschuren(3) compiled measured and estimated
degradation rates for organic chemicals.
Mercury Study
Report to
Congress
Measured demethylation
rate constants converted to
half-life data for mercury
(water, soil, sediment).
The Mercury Study Report to Congress^ was
developed for a rulemaking and has undergone
extensive Agency peer review.
HYDROWIN
Estimated hydrolysis rate for
water.
HYDROWIN, the hydrolysis estimation program,
is part of EPA's Estimation Program Interface
(EPI) Suite/5' HYDRO WIN uses a chemical's
structure to estimate the acid- and base-catalyzed
rate constants for certain chemical classes (esters,
carbamates, epoxides, halomethanes, and certain
alkyl halides). Chemicals can be catalyzed
(broken down) by acids (hydronium) or bases
(hydroxide ions). The rate constants are used to
calculate hydrolysis half-lives at selected pHs.
April 2004
Page 1 7-3
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Half-life values for the same substance in different media, and for different substances in the
same medium, can differ by several orders of magnitude. This is illustrated in Exhibit 17-3.
Exhibit 17-3. Example Illustrating Ranges of Half-life Values in Different Environmental Media
HAP
acrolein
benzene
chlorobenzene
formaldehyde
methyl bromide
2,3,7,8-TCDD
Measured or Estimated Half-life Value (Hours)(a)
Air
19
276
401
4
8,980
200
Water
672
252
2,616
192
420
768
Soil
672
252
50
96
420
12,096
Sediment
1,776
9,984
1,800
384
1,680
14,400
Note: Values are for Illustrative Purposes Only
(a) Values represent the maximum measured or estimated values from the references cited in Exhibit 17-2.
The fate and transport models used for characterizing multipathway exposure use metrics of
persistence to account for loss of the chemical through degradation or transformation processes
described above. Typically, for each modeled media compartment, the fate and transport models
require an overall metric of persistence for that media compartment (e.g., a half-life value for air,
a half-life value for soil, a half-life value for surface water). The media compartment half-life is
the half-life associated with the most important or fastest degradation process or reaction. That
is, the process-specific half-life of the fastest degradation process is usually selected as the
overall media compartment half-life.
Metals may transform among different compounds or species (e.g., divalent mercury can undergo
methylation to yield methyl mercury, and it can be reduced to form elemental mercury). Some
metal species are more persistent and/or maybe more toxic than others. Transformation half-life
values in different media are more useful for evaluating the persistence of metal pollutants of
concern. The speciation of metals is highly dependent on geochemical environment (and in some
cases, the presence of certain microbes). One species may dominate in water of one pH, Eh,
DOC concentration, etc., and an entirely different species may dominate in water of different
geochemistry. [Also note that a further complicating factor is that analytical laboratories often
report the total amount of a metal present in a sample, rather than the amount of the various
individual metal species present (e.g., Cr6+ versus Cr3+), which usually have different toxicities
and different persistence values. An understanding of the concentrations of various metal species
is therefore desirable; however, it is often not analytically achievable.](6) There are a number of
concerns regarding the assessment of risks posed by metals in the environment. Information on
this subject can be found at the following website:
http ://cfpub. epa. gov/ncea/raf/recordisplay.cfm?deid=51736.
April 2004
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What is a Persistent Chemical?
Because environmental persistence is a complicated phenomenon, no single value is universally
accepted as indicating a "persistent" chemical. EPA has used a half-life value of two months (1,440
hours) in the Toxics Release Inventory (TRI) PBT final rule and the Premanufacturing Notice
evaluation process/7' Other authors have suggested a half-life value of one month (720 hours), using
the following logic: Assuming that a chemical will degrade in approximately six half lives (when less
than two percent of the mass remains), a chemical with a half-life of one month would persist in the
environment for six months. This six month period would be long enough to encompass the sensitive
developmental life stages of many organisms/8'
Note that the use of any single threshold value to define "persistent" chemicals may be
misleading. An important consideration is data quality (e.g., whether the half-life value is measured
or predicted and the overall quality of the experimental study or computer algorithm used to develop
the value). Assessors must consider other factors including the tendency of the chemical to partition
into various media. For example, vinyl chloride has a half-life of six months in surface water and two
years in sediment - values that might suggest this chemical is "persistent." However, its half-life in air
is 53.4 hours and in soil is 10 days. Thus, depending on its relative tendency to partition between air,
soil, water, and sediment, a significant amount of the mass in air emissions might be degraded (in the
air and/or soil) prior to the chemical reaching surface water and sediment.
Ultimately, it is often difficult to select a single and reliable half-life because the half-life of a
chemical depends not only on its physical properties (see section 16.4), but also on the
environmental conditions of the site to which the chemical is emitted. Temperature, sunlight
intensity, the nature of the microbial community, and concentrations of reactive species such as
oxygen radicals can all affect the reactivity of a compound.(3)
17.1.2 Metrics of Bioaccumulation
Several chemical-specific metrics can be
used to evaluate the potential for a chemical
to bioaccumulate in plants and animals and
biomagnify in food webs.(9) These values
may be measured in laboratory tests or
estimated with computer models based on
chemical structure. These metrics include:
Note that BAFs and BCFs are not calculated for
humans; rather, they are sometimes used to
estimate air toxics concentrations in the food items
eaten by people.
• Bioaccumulation Factor (BAF). The concentration of a substance in tissue of an organism
divided by its concentration in an environmental medium in situations where the organism
and its food are exposed (i.e., accounting for food chain exposure as well as direct chemical
uptake). Such values are often used to characterize the transfer of pollutants through
consumption offish, beef, or dairy products.(10)
• Bioconcentration Factor (BCF). The concentration of a substance in the tissue of an
organism divided by the concentration in an environmental medium (e.g., the concentration
of a substance in an aquatic organism [ug/kg body weight] divided by the concentration in
the ambient water [ug/L water], in situations where the organism is exposed through the
water only). The most commonly given value is an estimate of the relative concentrations in
water and whole fish (or, in some cases, fish fillets, since most people in the U.S. do not eat
April 2004 Page 1 7-5
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whole fish), but BCFs for other organisms are also available. For plants, the Root
Concentration Factor (RCF) indicates how readily pollutants are taken up from soil into
underground tissues.
• Octanol/water partition coefficient. The ratio of a chemical's solubility in n-octanol to its
solubility in water at equilibrium (in this test, n-octanol is used as a surrogate for lipophilic
tissue). This metric, usually expressed as a logarithm (log Kow or log P), is often used as a
surrogate for (and is an important basis for estimating) BAF or BCF.
As with persistence, bioaccumulation is a complicated phenomenon, and no single value is
universally accepted as indicating that a chemical has a high tendency to bioaccumulate, although
EPA's Office of Pollution Prevention and Toxics has used a threshold BCF value of 1,000 in
evaluating new and existing chemicals.(11) Exhibit 17-4 provides a list of sources for
bioaccumulation data.
Importance of Trophic Levels in Evaluating
Bioaccumulation in Aquatic Food Chains
An organism's trophic position in the aquatic food web can have an important effect on the magnitude
of bioaccumulation of certain chemicals. Certain pollutants have the potential to biomagnify, or
increase in concentration at successive trophic levels through a series of predator-prey associations.
Chapter 5 (Bioaccumulation) of EPA's Methodology for Deriving Ambient Water Quality Criteria for
the Protection of Human Health provides guidance about deriving trophic level-specific
bioaccumulation factors/17'
Trophic level 4
predatory fish
(e.g., bass)
Trophic level 3
forage fish (e.g., bluegill)
Trophic level 2
zooplanhton
Trophic level 1
phytoplankton
April 2004
Page 17-6
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Exhibit 17-4. Sources of BCF and BAF Values
Data Source
Data Element
Comments
HWIR Technical
Support Document
Measured BAF
Measured BCF
Predicted BAF
Predicted BCF
The Hazardous Waste Identification Rule (HWIR)
Technical Support Document02' data were developed for
a rulemaking. Estimates are available for different
classes of organisms (fish and invertebrates).
Mercury Study
Report to Congress
Measured BAF for
mercury
The Mercury Study Report to Congress(4) was developed
for a rulemaking and has undergone extensive Agency
peer review.
Ambient Water
Quality Criteria
documents
Measured BCF
Ambient Water Quality Criteria documents03' are
developed for rulemakings that establish concentration
limits for chemicals in the surface waters of the United
States. They have undergone extensive Agency peer
review.
AQUIRE Database
Measured BCF
EPA's Office of Research and Development,
Environmental Research Laboratory in Duluth, MN,
maintains a database of citations and aquatic bioassay
data including residue measures.04'
BCFWIN
Predicted BCF
BCFWIN, the Bioconcentration Factor Estimation
Program, is part of EPA's EPI Suite/5' This program
estimates BCFs based on log Kow data using the
estimation methodology presented in a 1997 study
prepared for EPA by Meylan et al.°5' The methodology
was formulated using a training set of 694 compounds
with measured BCF values for fish. In order of
preference, the program uses (1) the log Kow entered by
the user, (2) the experimental log Kow from the
experimental log Kow database for KOWWIN, and (3)
the KOWWIN estimated log Kow value.
BAF or BCF values are used in some fate and transport models to calculate how much of the
chemical will partition into organisms, such as fish or shellfish, that are consumed by humans or
ecological receptors of concern. The concentrations in these biota can then be used to calculate
the intake of the chemical by humans or ecological receptors of interest. It is recommended that
BAFs be derived separately for species of different trophic levels to account for different levels
of accumulation for members of different trophic levels.(16) EPA presents specific guidelines for
deriving BAF values, including how to estimate BAFs using BCF values in its revised
methodology for developing Ambient Water Quality Criteria.(17) National-level BAFs developed
by the Office of Water can be used in screening analyses. These can be refined based on site-
specific characteristics in subsequent tiers of the assessment, if necessary.
As with half-life values, BCF values vary significantly among air toxics. Exhibit 17-5 presents a
few representative BCF values for several HAPs. Note that these represent the highest values
identified in the references cited in Exhibit 17-4 and are meant for illustrative purposes only.
April 2004
Page 17-7
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Exhibit 17-5. Example BCF Values
HAP
acrolein
carbon tetrachloride
chloroform
pentachlorophenol
2,3,7,8-TCDD
BCF Value(a)
3
30
6
776
5,754
Note: values are for illustrative purposes only
(a) Values represent the maximum measured or estimated values
from the references cited in Exhibit 17-4.
Note that the use of any single threshold value to define "bioaccumulative" chemicals may
be misleading. As with persistence, data quality is an important consideration (e.g., measured
vs. predicted values; quality of the underlying study/algorithm used to develop the value).
Moreover, the specific organisms and tissues in which bioaccumulation is measured or predicted
are important determinants of the relevance of a given BCF or BAF value for the exposure
assessment. Many substances that bioaccumulate tend to accumulate in lipid tissues (e.g., fat,
organs), which may not be the tissues that most people eat (e.g., fish fillet). Therefore, a high
BCF may not actually result in high exposures to humans.
17.2 Chemical and Physical Properties that Affect Persistence and Bioaccumulation
Exhibit 17-6 identifies both direct metrics of persistence (i.e., half-life values), as well as the
physical and chemical properties that are most important in determining persistence and
bioaccumulation.
In Exhibit 17-6, solubility and vapor pressure determine the propensity for pollutants to
dissolve in water and volatilize into the air, respectively. The Henry's Law constant, which is
simply the ratio of the chemical's water solubility to its vapor pressure, indicates whether a
compound will partition into air or water at equilibrium. The speed with which the equilibrium
occurs is affected by the diffusion constants in air and water.
The coefficients that are abbreviated with a capital "K" (e.g., the octanol-water partition
coefficient, Kow) in Exhibit 17-6 provide information on how strongly organic and inorganic
compounds are likely to bind to soil or sediment particles, or to partition into lipid versus
aqueous phase liquids. Strong binding indicates a high potential to persist and accumulate in
soils and sediments; soil/sediment binding also tends to be correlated with the potential to
bioaccumulate.
The 1998 Peer Review Draft of EPA'sHuman Health Risk Assessment Protocol for Hazardous
Waste Combustion Facilities (HHRAP) provides (Appendix A) tables of recommended rate
constants and chemical/physical parameters for a large number of air toxics.(18) Also, the user's
guide for EPA's Risk Screening Environmental Indicators (RSEI) tool includes physicochemical
properties for TRI chemicals and chemical categories/19' Note, however, the values in these
sources may need to be updated.
April 2004
Page 1 7-8
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Exhibit 17-6. Chemical and Physical Property Definitions
Property
Name
CAS No.
MW
VP
S
H
Da
Dw
Kow
KOC
Kdsoll
Kdsed
1 1/2 soil
tl/2sed
tl/2sw
BAF
BCF
RCF
B
Definition
Unique identifier
Unique identifier
Molecular weight
Vapor pressure
Solubility
Henry's Law constant
Diffusion coefficient in air
Diffusion coefficient in water
Octanol-water partition
coefficient (log Kow is
frequently tabulated)
Organic carbon partition
coefficient (log Koc often
tabulated)
Soil dissociation constant
Sediment dissociation constant
Half-life in soil
Half-life in sediment
Half-life in surface water
Bioaccumulation factor
Bioconcentration factor
Root concentration factor
Biotransfer factors
Significance/Comments
Not always reliable (many synonyms)
Much more reliable than the chemical name; some chemicals
have no CAS number; some CAS numbers refer to mixtures
In absence of data, can be used to calculate Da, Dw, etc.
Indicates volatility
Indicates maximum concentration of a chemical that will
dissolve in water
Ratio of vapor phase concentration to the liquid phase
concentration of a gas; high values indicate tendency to
volatilize from water solution
Used to calculate rate of volatilization from air
Used to calculate rate of volatilization from water
High value (> 1000, log Kow > 3) indicates strong tendency to
bioconcentrate
High value indicates strong tendency to bind to soil/sediment;
Koc, Kow can be estimated from each other
Indicates potential of inorganic ions/compounds to bind to soil;
varies for different ionic species, pH, soil types
Indicates potential of inorganic ions/compounds to bind to
sediment (similar to Kd^])
Indicates persistence in soil; generally soil type, conditions,
and degradation pathway(s) must be specified
Indicates persistence in sediment; same considerations as for
1 1/2 soil
Indicates persistence in surface water; for moderate to
high-vapor pressure compounds
Indicates accumulation of a compound into tissues of an
organism from contact with contaminated water, contaminated
sediments, and ingestion of contaminated food
Indicates accumulation of a compound into tissues of an
organism from contact with a contaminated medium.
Ratio of root to soil concentration, measures propensity to take
up pollutant from soil for defined plant species
Describes propensity of pollutant to be transferred through
food chain; defined for specific crops and consuming
organisms (e.g., alfalfa => dairy cattle); generally correlates
with BCF, Kow; used primarily for detailed pathway modeling
April 2004
Page 1 7-9
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Fugacity as a Determinant in the Fate and Transport of a Pollutant
Once a contaminant is emitted from its source, the fate of the contaminant is determined by a number
of factors (e.g., molecular weight, solubility, partition coefficients). In order to characterize the fate
of the pollutant, modelers have developed the concept of fugacity*20' to define the tendency of the gas
to escape to another phase in order to reach a steady-state equilibrium. This tendency to migrate then
leads to partitioning of the pollutant across environmental media based on its chemical and physical
characteristics. Fugacity models are distribution-based models incorporating all environmental
compartments (media) and are used to quantify steady-state fluxes of pollutants across compartment
interfaces. There exist three levels at which fugacity may be modeled. The Level I model depicts the
distribution of a known quantity of a chemical in a closed environment at equilibrium, in which no
degrading reaction occurs and no advective gain or loss is attained. A Level II model describes a
situation in which a chemical is continuously discharged at a constant rate and achieves steady-state
equilibrium, at which the input and output rates are equal. In Level n models, reaction and advection
may occur. A Level in model is similar to a Level n model in that the modeled chemical is
continuously discharged at a constant rate and achieves a steady state condition, in which the input
rate equals the output rate. Yet, a Level HI model differs in that fugacity for the given chemical is
equal within a single compartment for all defined subcompartments, but is not equal between
compartments. Therefore, individual inputs for each medium must be defined separately in order to
determine appropriate pollutant partitioning among environmental compartments.
^^_ ^j
17.3 Evaluating Persistence and Bioaccumulation in Exposure Assessments
Characterizing the movements of air toxics that persist and which also may bioaccumulate
through various environmental media such as air, soils, water, sediments, and biota can be a
highly complex task, and generally available methods for evaluating these fate and transport
pathways have only recently been developed. Specifically, EPA and other regulatory agencies
have developed a number of models that estimate the concentrations of persistent and
bioaccumulative compounds over time in the various environmental "compartments" subsequent
to defined patterns of deposition. These models simulate both physical and chemical processes
such as air deposition to soil, runoff, leaching (dissolution), soil/sediment adsorption, and
chemical speciation (oxidation/reduction, precipitation reactions). Some models also evaluate
the biodegradation of organic pollutants by bacteria and other organisms in soil, sediment, and
surface water. These models require a large number of site-specific inputs and many measures of
the physical and chemical properties of pollutants. It is beyond the scope of this chapter to
discuss in detail all the processes that maybe modeled in the assessment of indirect exposure
pathways; however, Mackay and his colleagues provide a good overview of the multimedia fate
and transport(20) and Conell and Emlay describe the principles governing the bioaccumulation of
pollutants in the environment/21' Also, Chapter 18 provides a description of available
multimedia models that are generally recommended for use in air toxics risk assessment. The
documentation for these models provides detailed descriptions of the specific processes and
methods used in each model.
April 2004 Page 17-10
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References
1. Howard, P., Boethling, R., Jarvis, W.F., Meylan, W. 1990. Handbook of Environmental
Degradation Rates. Lewis Publishers, Michigan.
2. Mackay D., Shiu W.Y., and Ma K.C. 1991-1997. Illustrated Handbook of Physical-
Chemical Properties and Environmental Fate for Organic Chemicals, (5 volumes). Lewis
Publishers Inc., Boca Raton, Florida.
3. Verschueren, K. 1996. Handbook of Environmental Data on Organic Chemicals. 3rd ed. Van
Nostrand Reinhold Co., New York, NY.
4. U.S. Environmental Protection Agency. 1997. Mercury Study Report to Congress. Office of
Air Quality Planning and Standards; Office of Research and Development, Washington,
D.C., December 1997. EPA/452/R-976/003. Available at:
http://www.epa.gOv/ttn/atw/l 12nmerc/volumel .pdf.
5. U.S. Environmental Protection Agency. 2002. The Estimations Programs Interface for
Windows (EPIWIN) and SMILES. Updated June 20, 2002. Available at: http://www.epa.gov
/oppt/p2framework/docs/epiwin.htm. (Last accessed April, 2004).
6. Stumm, W. and Morgan, J.J. 1996. Aquatic Chemistry, 3rd Ed. John Wiley & Sons, Inc.,
New York.
Langmuir, D. and Klusman, R.L. 1997. Natural Background Concentrations of Metals That
Exceed Drinking Water Standards: Defining Background and the Effect of Sample Filtration.
Abstract. Geol. Soc. Am. Annual Meetings. Oct. 20-23. Salt Lake City UT: A-435.
Langmuir, D., Chrostowski, P., Chaney, R., and Vigneault, C. 2003. Draft Issue Paper on
the Environmental Chemistry of Metals. Submitted to EPA's Risk Assessment Forum by
ERG, Lexington, MA. August, 2003.
7. U.S. Environmental Protection Agency. 1999. Persistent Bioaccumulative Toxic (PBT)
Chemicals (40 CFR Part 372). Final Rule. Federal Register 64:58665, October 29, 1999.
U.S. Environmental Protection Agency. 1999. Notice of Receipt of Requests for Amendments
to Delete Uses in Certain Pesticide Registrations. Federal Register 64:60193, November 4,
1999.
8. Boethling, R.S., P.H. Howard, W. Meylan, W. Stiteler, J. Beauman, andN. Tirado. 1994.
Group contribution method for predicting probability and rate of aerobic biodegradation.
Environmental Science and Technology. 28:459-465.
9. U.S. Environmental Protection Agency. 1995. Great Lakes Water Quality Initiative
Technical Support Document for the Procedure to Determine Bioaccumulation Factors.
Office of Water, Washington, D.C., March 1995. EPA-820-B-95-005.
April 2004 Page 17-11
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10. U.S. EPA. 1990. Interim Final Methodology for Assessing Health Risks Associated with
Indirect Exposure to Combustor Emissions. Environmental Criteria and Assessment Office,
Office of Research and Development, Washington, D.C., January 1990. EPA-600-90-003.
11. U.S. Environmental Protection Agency. 1992. Classification Criteria for Environmental
Toxicity and Fate of Industrial Chemicals. Office of Pollution Prevention and Toxics,
Washington, D.C.
12. U.S. Environmental Protection Agency. 1995. Technical Support Document for the
Hazardous Waste Identification Rule: Risk Assessment for Human and Ecological Receptors.
Volume I. Office of Solid Waste, Washington, DC, August, 1995.
13. U.S. Environmental Protection Agency. 2003. Office of Water Shopping Cart Home Page.
Available at: http://yosemite.epa.gov/water/owrccatalog.nsf/.
14. U.S. Environmental Protection Agency. 2003. AQUatic Information REtrieval (AQUIRE)
database, apart of the ECOTOX database. Version 3.0. Office of Research and
Development, National Health and Environmental Effects Laboratory, Mid-Continent
Ecology Division, Duluth, MN. Available at: http://www.epa.gov/ecotox/
15. Meylan, W. M., P. H. Howard, D. Aronson, H. Printup, and S. Gouchie. 1997. Improved
Method for Estimating Bioconcentration Factor (BCF)from Octanol-Water Partition
Coefficient. Third Update Report - August 1997. SRC-TR-97-006 (EPA Contract No. 68-
D5-0012). Prepared for Robert S. Boethling, U.S. EPA, OPPT, Washington, D.C.; Prepared
by SRC, Environmental Science Center, North Syracuse, NY 13212.
16. U.S. Environmental Protection Agency. 1998. Methodology for Assessing Health Risks
Associated with Multiple Pathways of Exposure to Combustor Emissions. Office of Research
and Development, National Center for Environmental Assessment, Cincinnati, OH. EPA
600/R-98/137.
17. U.S. Environmental Protection Agency. 2000. Methodology for Deriving Ambient Water
Quality Criteria for the Protection of Human Health. Office of Water, Washington, D.C.,
October 2000. EPA/822/B-00/004. Available at:
http ://www. epa. go v/waterscience/humanhealth/method/me thod.html
18. U.S. Environmental Protection Agency. 1998. Human Health Risk Assessment Protocol for
Hazardous Waste Combustion Facilities, Peer Review Draft. Office of Solid Waste and
Emergency Response, Washington, D.C., July 1998. EOA/30/D-98/001A. Available at:
http://www.epa.gov/epaoswer/hazwaste/combust/risk.htm.
19. U.S. Environmental Protection Agency. 2002. Risk-Screening Environmental Indicators
User's Manual RSEI Version 2.1 [1988-2000 TRI Data]. Office of Pollution Prevention and
Toxics, Washington, D.C., December, 2002. Available at:
http://www.epa.gov/opptintr/rsei/docs/users manual.pdf.
April 2004 Page 17-12
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20. Mackay, D. 1991. Multimedia Environmental Models. The Fugacity Approach. Lewis
Publishers, Chelsea, MI.
Mackay D, Paterson S, and WY Shiu. 1992. Generic models for evaluating the regional fate
of chemicals. Chemosphere 24(6):695-717.
Mackay D, DiGuardo A, Paterson S, and CE Cowan. 1996. Evaluating the environmental fate
of a variety of types of chemicals using the EQC Model. Environmental Toxicology and
Chemistry 15(9): 1627-1637.
21. Connell, D.W. and D. Emlay. 1989. Bioaccumulation ofXenobiotic Compounds. CRC
Press.
April 2004 Page 17-13
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Chapter 18 Quantification of Exposure: Multimedia
Modeling
Table of Contents
18.1 Introduction
18.2 Multimedia Fate and Transport Modeling .......................................... 1
18.2.1 Basis of Multimedia Models .............................................. I
18.2.2 Multimedia Exposure Models ............................................. 2
18.3 Key Parameters/Inputs for Multimedia Models ...................................... 5
18.4 Examples of Multimedia Modeling ............................................... £
-------
-------
18.1 Introduction
This chapter summarizes the concepts and tools available for multimedia modeling to support a
multipathway human health risk assessment. The discussion is divided into three sections:
• Section 18.2 discusses multimedia fate and transport modeling used to estimate chemical
concentrations in abiotic and biotic media that indirectly result from air emissions;
• Section 18.3 discusses key parameters used as inputs to multimedia models; and
• Section 18.4 presents examples of the use of multimedia models in air toxics risk
assessments.
18.2 Multimedia Fate and Transport Modeling
Although the primary route of exposure to many air toxics is via inhalation, non-inhalation
exposure through soil, water, and food pathways can be a potential health concern for those air
toxics that persist and which also may bioaccumulate (see Chapter 4 for the list of persistent
bioaccumulative hazardous air pollutants (PB-HAP) chemicals). Therefore, risk assessments for
these substances often include multimedia modeling to predict the movement of these air toxics
in the environment. This section provides an overview of the multimedia fate and transport
models commonly used by EPA.
18.2.1 Basis of Multimedia Models
Multimedia fate and transport models take into account various physical and chemical processes
to predict the movement of pollutants within and between environmental media. Multimedia
models can be grouped into the following basic categories.
• Linked modeling systems are composed of several independent single-medium models.
These systems typically consist of a "one-way" process through a series of linked single-
medium models or algorithms; that is, they calculate fate and transport by running a single-
medium model (e.g., an atmospheric model) and using the output as the input for the next
single-medium model (e.g., a soil or surface water model). One of the primary advantages of
linked modeling systems is that they can incorporate several highly sophisticated single-
medium models into a single modeling system. The primary drawbacks of these types of
models are (1) they do not always assure conservation of mass; (2) they lack dynamic
"feedback" loops; and (3) secondary pollutant transfers are not treated in a fully coupled
manner.
• Fully coupled, mass-conserving models estimate the fate and transport of pollutants
between and within media and are able to fully account for the distribution of pollutant mass
within a defined modeling region. In these types of models, each of the included media (e.g.,
soil, air, biota) are modeled simultaneously (i.e., fully coupled), and thus these models can
simulate dynamic "feedback" loops and secondary pollutant transfers. The primary drawback
of these types of models is that they typically involve some simplification relative to
sophisticated single-medium models due to the computational demands associated with
modeling multiple media simultaneously.
April 2004 Page 18-1
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18.2.2 Multimedia Exposure Models
To date, EPA has used primarily the Multiple Pathways of Exposure (MPE) model and variations
of the MPE approach to conduct multimedia fate and transport modeling for air toxics. More
recently, EPA developed the Fate, Transport, and Ecological Exposure (TRIM.FaTE) model as a
component of the Total Risk Integrated Methodology (TRIM).(1) This section provides a
summary of the MPE model, the variations of the MPE approach, and the TRIM.FaTE model.
During the development of the TRIM.FaTE model, EPA conducted a comprehensive review of
those multimedia fate and transport models that estimate exposures and risks from emissions of
air toxics that EPA and other organizations in the United States use. Exhibit 18-1 provides a
summary of the models included in this review, with models grouped into the two basic
categories described in the previous section. The TRIM.FaTE documentation provides a
description of each of these models. Also presented at the end of this section is a multimedia
model developed by the State of California called CalTOX.(2)
Exhibit 18-1. Multimedia Models Reviewed During TRIM.FaTE Development
Linked Modeling Systems
Fully Coupled, Mass-Conserving Models
Indirect Exposure Methodology
(IEM)/Multiple Pathways of Exposure (MPE),
developed by EPA's National Center for
Environmental Assessment
Multimedia Environmental Pollutant
Assessment System (MEPAS), developed by
the U.S. Department of Energy
CalTOX, California Department of Toxic
Substance Control's Multimedia Risk
Computerized Model
SimpleBOX, developed by the Netherlands
National Institute of Public Health and the
Environment
Modeling Multimedia Environmental
Distribution for Toxics (Mend-Tox)/ISMCM),
developed by EPA's Office of Research and
Development
Multiple Pathways of Exposure Model (MPE)
The Multiple Pathways of Exposure model, formerly known as the Indirect Exposure
Methodology (IBM), primarily consists of a set of multimedia fate and exposure algorithms
developed by EPA's Office of Research and Development (ORD).(a) ORD issued an interim
document describing this methodology in 1990, a major addendum was issued in 1993, and an
updated guidance document was issued in 1999 in response to comments it received during a
1994 Science Advisory Board review of the addendum.(3) The MPE documentation describes
fate and transport algorithms, exposure pathways, receptor scenarios, and dose algorithms.
The MPE approach includes procedures for estimating human exposures and health risks
resulting from the transfer of emitted pollutants from air to soil and surface water bodies and the
Note that the MPE model and many of its variations are conceptual models used to describe fate and
transport, not "ready-to-run" computer models. Typically, users incorporate these conceptual models into
spreadsheets or other computer frameworks to create a usable model.
April 2004
Page 18-2
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subsequent uptake by vegetation, animals, and humans. The methodology specifically addresses
exposures via inhalation; ingestion of food, water, and soil; and dermal contact. The MPE model
was designed to predict long-term, steady-state impacts from continuous sources, rather than
short-term, time-series estimates. It consists of a "one-way process" through a series of linked
models and algorithms, beginning with the modeling of the transport of pollutant emissions in air
and the subsequent deposition to soil and surface water and culminating in the uptake of the
emitted pollutant(s) into biota. The aspects of the MPE model that address exposure estimation
are described in more detail in Section 18.4 below.
EPA designed the MPE model to assess /I, „ ft ^ ., tj r, , . ^ , ..
°^ The £)rq/f Guidance on the Development, Evaluation,
human exposures to air toxics emitted
from stationary combustors, although
analysts can apply most aspects of the
approach to other types of stationary
sources. One can apply this model to one
or more sources at a single facility
simultaneously to estimate exposures
within 50 kilometers of the facility. The
MPE model will allow modeling of only
and Application of Regulatory Environmental
Models recommends best practices to help determine
when a model, despite its uncertainties, can be
appropriately used to inform a decision. The
Knowledge Base (KBase) is a web-accessible
database of information on some of EPA's most
frequently used models. The draft guidance
recommends what information about models to
document, while the Knowledge Base is the
one chemical at a time, and there is no repository where this information is documented.
Both products are available at the CRbM internet site
at http://www.epa.gov/crem.
tracking (i.e., carry through the analysis)
of transformation products of the modeled
chemical. To apply the MPE approach,
users must provide a significant number of site-specific inputs, such as source emission rate,
wind speed and direction, soil loss constant, and pollutant degradation rate.
EPA modified the MPE approach to multimedia fate and transport modeling for use in two
additional EPA models and modeling approaches. These models and approaches are as follows.
• IEM2M. In 1997, Office of Air Quality Planning and Standards (OAQPS) modified the
then-current version of the IBM model to create IEM2M. This revised version of IBM added
the functionality necessary to model transformation between the three key species of mercury
and track the concentrations throughout the modeled system for each of these species. This
model was applied to estimate nationwide exposures to mercury for the Mercury Study
Report to Congress.^
• Human Health Risk Assessment Protocol (HHRAP). EPA's Office of Solid Waste and
Emergency Response (OSWER) developed the HHRAP to provide guidance for conducting
multipathway exposure and risk assessments of emissions of air toxics from hazardous waste
combustion facilities. The suggested protocol for assessing multipathway exposures was
adapted from the MPE approach and the documentation of this protocol(5) compiles detailed
information on many of MPE's input parameters and algorithms.
Two additional models and approaches used by EPA to assess multipathway exposures to air
toxics use many of the same fate and exposure algorithms and methodologies used in the MPE
model.
April 2 004 Page 18-3
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• Dioxin Reassessment Methodology. Many of the algorithms used in the MPE model have
been used for ongoing EPA efforts to characterize exposure and risks from dioxins,
particularly chlorinated dibenzodioxins and dibenzofurans, as part of the Dioxin
Reassessment project.(6)
• Multimedia, Multipathway, Multi-receptor Exposure and Risk Assessment Model
(3MRA). The 3MRA model is currently being developed by EPA's Office of Solid Waste
and Emergency Response to support their Hazardous Waste Identification Rule (HWIR).
Many of the fate and exposure algorithms used in 3MRA are similar to those used in MPE.
TRIM.FaTE
EPA developed the TRIM Fate, Transport, and Ecological Exposure (TRIM.FaTE) model(7) to
describe the movement and transformation of pollutants over time, through a user-defined,
bounded system of environmental compartments (i.e., abiotic media and organisms). The design
of the compartment system can encompass spatial interconnections (with some similarities to
grid-type Eulerian models) and ecological exposure-related relationships. TRIM.FaTE is
designed to generate both media concentrations relevant to human pollutant exposures and
exposure estimates relevant to ecological risk assessment primarily for air pollutants for which
non-inhalation exposures are important.
In contrast to the IEM/MPE approach, TRIM.FaTE is a fully coupled multimedia model that
estimates the flow of pollutant through time among environmental compartments. TRIM.FaTE
offers the following important features that are not available using IEM/MPE.
• TRIM.FaTE is able to model mass-balanced "feedback" loops between media as well as
secondary emissions (e.g., re-emission of deposited pollutants).
• TRIM.FaTE has the ability to provide detailed time-series estimates of pollutant
concentrations in the environmental compartments.
• TRIM.FaTE maintains a full mass balance of the pollutant mass in the system (i.e., all the
pollutant introduced into the system is accounted for among all the environmental
compartments).
• TRIM.FaTE can model sensitivity of model results to variations in input parameters and
perform probabilistic modeling such that uncertainty and variability in model results can be
characterized.
• TRIM.FaTE is designed with the flexibility to allow for implementation of nearly limitless
configurations (e.g., spatial resolution, types of biota), algorithms, and approaches.
Simulations can range from quite simple analyses of pollutant distribution across abiotic
media and biota to more complex, spatially-refined assessments, with associated implications
with regard to user requirements.
TRIM.FaTE can model multimedia fate and transport of air toxics from any type of stationary
source. It can be applied to multiple facilities, sources, and chemicals simultaneously to track the
fate and transport of emitted pollutants as well as transformation products of the emitted
April 2004 Page 18-4
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pollutants. The amount of input data required by TRIM.FaTE is directly related to the
complexity of the user-specified modeling system; however, TRIM.FaTE analyses typically
require more input data than similar analyses conducted using the MPE approach. As noted in
Exhibit 18-2, TRIM.Expo is the exposure component of the TRIM modeling system (see Section
18.2.2.2).
California Total Exposure Model for Hazardous Waste Sites (CalTOX)
The Department of Toxic Substances Control (DTSC), within the California Environmental
Protection Agency, has the responsibility for managing the State's hazardous-waste program. As
part of this program, the DTSC funded the development of the CalTOX program.(2) CalTOX has
been developed as a set of spreadsheet models and spreadsheet data sets to assist assessing
human exposures and defining soil clean-up levels at uncontrolled hazardous wastes sites. More
recently, CalTOX has been modified for use in establishing waste classification for landfills and
hazardous waste facilities in California. CalTOX addresses contaminated soils and the
contamination of adjacent air, surface water, sediments, and ground water. The modeling
components of CalTOX include a multimedia transport and transformation model, exposure
scenario models, and add-ins to quantify uncertainty and variability. The multimedia transport
and transformation model is a dynamic model that can assess time-varying concentrations of
pollutants introduced initially to soil layers or for pollutants released continuously to air, soil, or
water. This model assists the user in examining how chemical and landscape properties impact
both the ultimate route and quantity of human contact. Multimedia, multiple pathway exposure
models are used in CalTOX to estimate average daily doses within a human population. The
exposure modeling part of CalTOX is described further in Chapter 20.
18.3 Key Parameters/Inputs for Multimedia Models
For most air risk applications, multimedia modeling results are strongly dependent on the
emission rate of pollutants emitted to the air from the facility. For the MPE framework and
TRIM.FaTE model, transport of modeled pollutants and accumulation in media of interest result
directly from the emission of the chemical into the air from the facility, the dispersion or
advection of chemical through the air, and the subsequent deposition of the chemical onto land,
water, or other surfaces in the modeled region. In addition to emission rate, several other types
of data are often required by multimedia models to characterize the pollutants and site being
modeled. Generally, the data requirements for multimedia fate and transport models fall into the
following categories.
• Source characteristics for the sources that are modeled, such as location, emission rates for
the modeled pollutant(s), stack height, exit gas velocity, and exit gas temperature.
• Environmental setting characteristics for the abiotic media included in the modeling
scenario, such as water body dimensions, surface soil characteristics (e.g., organic carbon
content, porosity), and data related to local meteorology and hydrology (e.g., precipitation,
erosion, runoff rates).
• Abiotic chemical/physical data for the chemicals included in the modeling scenario, such as
Henry's law constant and soil-water partition coefficients. EPA's draft HHRAP provides
default values for many of these parameters/5'
April 2004 Page 18-5
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Exhibit 18-2. Role of the TRIM Modeling System
----- AIR-only IMPACTS •
. -— MULTI-MEDIA IMPACTS-—
AQ Model
Or
AQ Data
Inputs:
e.g.; ActMtydata..
population data..
indoorioutdoor
concentrations, etc)
Alternative
Exposure Model
(e.g., HAPEM)
TRIM.FaTE
(Fate, Transport 8t
Ecological Exposure)
I Farm I
Food Oiain |
TRIM. Expo,
I (Hum an E xppsune E vent)
HHToi Database -
Inputs:
Human uadtn
g, RfC HUE)
TRIM. Risk
Characterization)
Ecc
[Inhalation Risk] [Ingestion Risk] [Eco Risk]
Quantitative risk & exposure characterization, U/V, assumptions, limitations.
The Total Risk Integrated Methodology (TRIM) modeling system can be used to assess human
inhalation, human ingestion, and ecological risks. TRIM.FaTE accounts for movement of a chemical
through a comprehensive system of discrete compartments (e.g., media and biota) that represent
possible locations of the chemical in the physical and biological environments of the modeled
ecosystem and provides an inventory, over time, of a chemical throughout the entire system. In
addition to providing exposure estimates relevant to ecological risk assessment, TRIM.FaTE generates
media concentrations relevant to human ingestion exposures that can be used as input to the ingestion
component of the Exposure-Event module, TRIM.Expo. Measured concentrations also can be used as
inputs to TRIM.Expo. In the inhalation component of TRIM.Expo, human exposures are evaluated by
tracking randomly selected individuals that represent an area's population and their inhalation and
ingestion through time and space. TRIM.ExpoInhalation can accept ambient air concentration estimates
from an external air quality model or monitoring data. In the Risk Characterization module,
TRIM.Risk, estimates of human exposures or doses are characterized with regard to potential risk
using the corresponding exposure- or dose-response relationships. The TRIM.Risk module is also
designed to characterize ecological risks from multimedia exposures. The output from TRIM.Risk is
intended to include documentation of the input data, assumptions in the analysis, and measures of
uncertainty/variability, as well as the results of risk calculations and exposure analysis. Information
on TRIM can be accessed at: http://www.epa.gov/ttn/fera/.
Non-chemical-specific characteristics of biota for any organisms included in the modeling
scenario, such as feeding rates, body weight, and population density.
Biotic chemical-specific data for any organisms included in the modeling scenario, such as
bioaccumulation and/or bioconcentration factors or assimilation efficiency values.
April 2004
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The Multiple Pathways of Exposure (MPE) model,(8) a commonly used model for multipathway
analyses, requires air concentrations, deposition rates, which are typically obtained via Industrial
Source Complex (e.g., ISCST3) modeling (see Chapter 9 for descriptions of these models). Risk
assessors would execute the ISCST3 modeling for multipathway in a similar fashion to how they
executed the modeling for inhalation. Specifically, the sources would be characterized in the
same way (e.g., vent height and diameter, release temperature and velocity, flow rate). The user
would provide the inputs necessary to calculate the deposition rates properly (e.g., particle size
distribution, scavenging coefficient). However, for multipathway analyses, the user should
execute the ISCST3 model with the "depletion option" (i.e., telling the model to subtract out the
mass of chemical deposited).
The user would need to know the particulate/particle-bound/vapor fractions of the emissions for
ISCST3 to calculate wet and dry deposition of vapors and particles. These would probably be
considered source-related, since although they are chemical-dependent, they also vary by source
(i.e., the industrial process affects the emissions profile).
For dry deposition of particles, the user would supply the following inputs (in addition to the
normal ISC inputs), including the:
• Array of particle diameters of the emissions;
• Array of mass fractions corresponding to the different particle diameters; and
• Array of particle densities corresponding to the different particle diameters.
For wet deposition of particles, the user would supply the following inputs (in addition to the
normal ISC inputs), including the:
• Particle scavenging coefficients for liquid precipitation corresponding to the different particle
diameters; and
• Particle scavenging coefficients for frozen precipitation corresponding to the different
particle diameters.
For wet deposition of gases, the user would supply the following inputs (in addition to the
normal ISC inputs), including the:
• Gaseous scavenging coefficient for liquid precipitation; and
• Gaseous scavenging coefficient for frozen precipitation.
The ISC user's guide(9) provides more detailed information on the deposition algorithms and
required input data. There also is guidance for application of ISC for multipathway assessment
in the latest MPE documentation.^
The only facility-related/source term data points used by the TRIM Fate, Transport, and
Ecological Exposure (TRIM.FaTE) model are chemical emission rate, location (lat/long,
UTM), and emission height, which are available from the inhalation modeling. TRIM.FaTE
calculates all values internally for determining vapor/particle fractions and deposition rates based
on chemical-specific (not source-specific) properties.
April 2004 Page 18-7
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Other multimedia models may require specific source characterization data and other
documentation that were not obtained for the inhalation analysis (the various user's guides for
these models should be consulted for appropriate inputs).
It is important to note that the number and refinement of inputs to a multimedia model may vary
depending on the outputs of interest and level of detail entailed in the modeling.
18.4 Examples of Multimedia Modeling
TRIM.FaTE Test Case Application. As a test case application, the TRIM.FaTE model was
used to predict multimedia concentrations of mercury at a chlor-alkali facility in the northeastern
United States. Speciated mercury concentrations were calculated for various abiotic media (e.g.,
surface soil, surface water, lake sediment) and biota (e.g., fish for various trophic levels, birds,
mammalian predators) for the ecosystem surrounding the facility. A sensitivity and uncertainty
analysis using TRIM.FaTE tools and a model comparison involving the 3MRA modeling system
were also performed. The complete report on the test case will be available at the TRIM.FaTE
page of EPA's Fate, Exposure, and Risk Analysis (FERA) website:
http://www. epa.gov/ttn/fer a/trim_fate.html.
Paints Hazardous Waste Listing Determination Analysis. On April 4, 2002, EPA issued a
final determination not to list as hazardous certain wastes generated from the production of paint.
EPA made this determination pursuant to the Resource Conservation and Recovery Act (RCRA),
which directs EPA to determine whether certain wastes from the paint production industry may
present a substantial hazard to human health or the environment. EPA proposed
concentration-based listings for certain paint waste solids (K179) and liquids (K180) on February
13, 2001 (66 Federal Register 10060). However, following a review of the public comments and
supplemental analyses based on public comments, EPA determined that the paint wastes
identified in the February 13, 2001, proposal did not present a substantial hazard to human health
or the environment. EPA conducted a multipathway risk assessment in support of this
determination/10' EPA used a series of models to estimate concentrations of Chemicals of
Potential Concern (COPCs) in the environment with which human and ecological receptors may
come into contact. The analysis used a source partioning model to estimate environmental
releases of each COPC from a waste management unit for each waste stream, as appropriate.
These estimated environmental releases provided input to the fate and transport models to
estimate media concentrations in air, soil, surface water, and groundwater. A farm food chain
model was used to estimate COPC concentrations in produce, beef, and dairy products. Aquatic
bioconcentration factors were used to estimate concentrations in fish.
Chlorinated Aliphatics Hazardous Waste Listing Determination. In support of a hazardous
waste listing determination for wastewaters and wastewater treatment sludges generated from the
production of certain chlorinated aliphatic chemicals, EPA conducted a multipathway human
health risk assessment/11' EPA used the ISCST3 model to estimate dispersion and deposition of
vapors emitted from wastewater treatment tanks and landfills, and vapors and particulates
emitted from sludge land treatment units. EPA used a series of indirect exposure equations based
on the MPE approach to quantify the concentrations of contaminants that pass from contaminated
environmental media to the receptor indirectly. For example, EPA examined risks associated
with contaminant transport in air; deposition onto plants and soil; accumulation in forage, grain,
April 2004 Pagel8-i
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silage, and soil; subsequent ingestion by beef cattle and dairy cattle; and human ingestion of
contaminated beef and dairy products.
Hazardous Waste Combustor MACT Standard Analysis. A human health and ecological risk
assessment was performed in support of developing a Maximum Achievable Control Technology
(MACT) standard for hazardous waste combustor facilities/12' The risk analysis included a
multimedia, multipathway assessment that addressed direct exposures to constituents released
into the atmosphere by hazardous waste combustor units and indirect exposures due to the
movement of air toxics in the food chain. The risk assessment addressed both human health risks
(cancer effects and noncancer effects) as well as ecological risks. Constituents assessed were
seven congeners of chlorinated dioxin and 10 congeners of chlorinated furan; three species of
mercury; 14 metals (antimony, chromium IE, chromium VI, arsenic, lead, barium, nickel,
beryllium, selenium, cadmium, silver, thallium, cobalt, copper, and manganese); particulate
matter; hydrochloric acid; and chlorine gas. To the maximum extent possible, this risk
assessment followed the latest risk guidelines adopted by EPA and used the most recent data
available.
Columbus Waste-to-Energy Study. A risk assessment study using fate modeling was
performed by EPA's NCEA for dioxin emissions at the Columbus, Ohio, Waste-to-Energy
incinerator facility/13' In 1994, EPA headquarters, the Office of Research and Development, and
Region 5 conducted a screening assessment of indirect impacts, leading to the conclusion that
continued emissions "may pose an imminent endangerment to public health and the
environment." Fate modeling used to support EPA's position utilized the air-to-beef model
described in the draft Dioxin Exposure document (i.e., based on the principles included in the
MPE framework) and assumed a subsistence farming family scenario. Exposure pathways
considered beef, milk and vegetable ingestion; soil dermal contact and childhood soil ingestion;
and breast milk ingestion. The exposure duration for adults was assumed to be seventy years.
Air concentrations used were the average from nine dairy farms located between five and twelve
miles from the incinerator. Overall exposure and cancer risk were estimated for each of the
exposure pathways, with cancer risk being highest for beef consumption (2x10~4) and lowest for
soil dermal contact (9X 10~9). Exposure from breast milk ingestion was determined to be higher
by one order of magnitude than exposure from beef and milk consumption, and higher by two
orders of magnitude than exposure from inhalation. Breast milk exposure near the incinerator
site ranged between two and more than seven times the background dioxin levels. A
TRIM.FaTE case study has been developed based on this analysis, including a direct model
comparison component on the air-soil outputs, and will be available at:
http://www.epa.gov/ttn/fera/trim fate.html.
April 2004 Page 18-9
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References
1. A summary of this review can be found in: U.S. Environmental Protection Agency.
TRIM.FaTE Technical Support Document, Volume I (Chapter 2). Office of Air Quality
Planning and Standards, Research Triangle Park, NC, September 2002. EPA/453/R-02/01 la.
Available at: http://www.epa.gov/ttnatw01/urban/trim/trimpg.html
2. McKone, T.E. 1993. CalTOX, a Multimedia Total-Exposure Model for Hazardous wastes
Sites Part I: Executive Summary. UCRL-CR-11456, Pt. I. 1993b. CalTOX, a Multimedia
Total-Exposure Model for Hazardous Wastes Sites Part II: the Dynamic Multimedia
Transport and Transformation Model. UCRL-CR-111456, Pt. II. 1993c. CalTOX, a
Multimedia Total-Exposure Model for Hazardous Wastes Sites Part III: The Multiple-
Pathway Exposure Model. UCRL-CR-111456, Pt. in. Livermore, CA: Lawrence Livermore
National Laboratory.
3. U.S. Environmental Protection Agency. 1990. Methodology for Asses sing Health Risks
Associated with Indirect Exposure to Combustor Emissions. Interim Final. Office of Health
and Environmental Assessment, Washington, B.C., EPA/600/6-90/003.
U.S. Environmental Protection Agency. 1998. Methodology for Assessing Health Risks
Associated with Multiple Pathways of Exposure to Combustor Emissions. National Center for
Environmental Assessment, Washington, B.C. EPA 600/R-98/137. Both are available at:
http://cfpub.epa. gov/ncea/cfm/recordisplay.cfm?deid=55525
4. U.S. Environmental Protection Agency. 1997. Mercury Study Report to Congress. Office of
Air Quality Planning and Standards, Research Triangle Park, NC and Office of Research and
Bevelopment, Washington, BC. EPA/452/R97/003. Available at:
http ://www. epa. gov/ttn/atw/112nmerc/mercury.html
5. U.S. Environmental Protection Agency. 1998. Human Health Risk Assessment Protocol for
Hazardous Waste Combustion Facilities, Peer Review Braft. Office of Solid Waste,
Washington, B.C. EPA-530-B-98-001A. Available at:
http://www.epa.gov/epaoswer/hazwaste/combust/risk.htm.
6. EPA is progressing toward completion of its comprehensive reassessment of dioxin exposure
and human health effects entitled, Exposure and Human Health Reassessment of
2,3,7,8-Tetrachlorodibenzo-p-Dioxin (TCDD) and Related Compounds. The latest
information on the status of the reassessment is available at:
http://cfpub.epa.gov/ncea/cfm/dioxreass.cfm?ActType=default.
7. U. S. Environmental Protection Agency. 2002. Total Risk Integrated Methodology.
TRIM.FaTE Technical Support Document. Volume 1: Description of Module. EPA-453/R-
02-01 la; Volume 2: Description of Chemical Transport and Transformation Algorithms.
EPA/453/R-02/011b. Evaluation of TRIM.FaTE. Volume 1: Approach and Initial Findings.
EPA/453/R-02/012; TRIM.FaTE User's Guide. Office of Air Quality Planning and
Standards, Research Triangle Park, NC. These documents and information are available at:
http://www.epa.gov/ttn/fera/trim fate.html#current user.
April 2004 Page 18-10
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8. U.S. Environmental Protection Agency. 1998. Methodology for Assessing Health Risks
Associated with Multiple Pathways of Exposure to Combustor Emissions. Office of Research
and Development, National Center for Environmental Assessment, Cincinnati, OH, 1998.
EPA/600/R-98/137. Available at:
http://cfpub.epa. gov/ncea/cfm/recordisplay.cfm?deid=55525.
9. U.S. Environmental Protection Agency. 1995. User's Guide for the Industrial Source
Complex (ISC) Dispersion Models. Volume 1 - User Instructions. Office of Air Quality
Planning and Standards, Research Triangle Park, NC, September 1995. EPA/454/B-95/003a.
Available at: http://www.epa.gov/scramOOl/userg/regmod/isc3vl .pdf
10. U.S. Environmental Protection Agency. 2001. Risk Assessment Technical Background
Document for the Paint and Coatings Hazardous Waste Listing Determination. Office of
Solid Waste, Washington D.C., January 2001. (see also the February 28, 2002 addendum).
Available at http://www.epa.gov/epaoswer/hazwaste/id/paint/index.htm.
11. U.S. Environmental Protection Agency. 1999. Risk Assessment Technical Background
Document for the Chlorinated Aliphatics Listing Determination. Office of Solid Waste,
Washington, D.C., July 1999. Available at:
http://www.epa.gov/epaoswer/hazwaste/id/chlorali/clordoc 1 .htm, (see also the September 29,
2000 addendum to the risk assessment. Available at:
http ://www.epa. gov/epaoswer/hazwaste/id/chlorali/ca_risk.pdf).
12. U.S. Environmental Protection Agency. 1999. Human Health and Ecological Risk
Assessment Support to the Development of Technical Standards for Emissions from
Combustion Units Burning Hazardous Wastes: Background Document, Final Report. Office
of Solid Waste, Washington, D.C., July 1999. Available at:
http://www.epa.gov/epaoswer/hazwaste/combust/riskdocl.htm.
13. Lorber, M. 2002. Comments on the Columbus Waste-to-Energy Site. Presentation at EPA
Regional/ORD Workshop on Air Toxics Exposure Assessment. June 25 - 27, 2002. San
Francisco, CA. National Center for Environmental Assessment. U.S. Environmental
Protection Agency.
April 2004 Page 18-11
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Chapter 19 Quantification of Exposure: Multimedia
Monitoring
Table of Contents
19.1 Introduction 1
19.2 Why Monitor? I
19.3 Planning and Implementing Issues 1
19.4 Monitoring and Sampling Methods, Technologies and Costs 3_
19.4.1 Method Selection 3
19.4.2 Available Methods 7
References 12
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19.1 Introduction
As noted earlier, modeling is generally the recommended approach for estimating exposure
concentrations for air toxics risk assessments (for both inhalation and other pathways). However,
there may be circumstances in which monitoring is requested or recommended for a particular
multipathway risk assessment. This chapter provides an overview of multimedia monitoring,
including the reasons for monitoring (Section 19.2), planning and implementation issues (Section
19.3), and available monitoring methods (Section 19.4).
19.2 Why Monitor?
The reasons for monitoring for a
multipathway risk assessment are identical to
those noted earlier for inhalation risk
assessments (Chapter 10):
• Measuring existing concentrations of air
toxics in specific locations (e.g., soils in a
schoolyard) and/or food items (e.g., fish
from a lake within the study area) for
purposes of developing estimates of
exposure;
• Developing or refining values for specific
parameters needed by multimedia models;
Monitoring for Evaluation of Multimedia
Modeling
For multipathway risk assessments, monitoring is
a valuable tool for evaluating model predictions
because multimedia modeling is more
complicated and involves more uncertainties than
does air quality modeling. When using samples
to evaluate model predictions, however, it is
important to realize that monitored
concentrations may be greater than model
predictions because sources other than those
being modeled may have contributed to the
contamination.
> s
• Evaluating the predictions of a model in specified circumstances (e.g., estimates of sediment
concentrations resulting from deposition and runoff);
• Closing gaps that might be present in existing data (e.g., gaps in emissions inventory); and
• Providing compliance/enforcement information as to whether a given facility or set of
sources is meeting regulatory or permit requirements.
19.3 Planning and Implementing Issues
The planning and implementation processes for multipathway risk assessment monitoring
programs are similar to those for air monitoring programs discussed in Chapter 10. The planning
process involves a step-wise integration of data quality and data sampling and analysis processes
that are consistent with the study-specific conceptual model (CM), quality assurance project plan
(QAPP), and data quality objectives (DQO) process. Many of the general planning and
implementation issues for air monitoring programs also apply to multimedia modeling. Some
additional considerations arise because the sampling and analysis program might include soils,
surface waters, sediments, fish, meat, vegetables, milk, and other human food items. The scale
and scope of monitoring could be much greater (e.g., multiple media could be sampled), and
issues specific to ingestion need to be considered (e.g., what parts of plants and animals do
people eat?).
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Monitoring or sampling methods should be appropriate for the compounds and
environmental media to be measured. They must have the sensitivity needed to monitor at
the levels likely to be of health and/or regulatory concern.
Monitoring sites and frequency of monitoring should be appropriate for the spatial and
temporal variation of the chemical being measured and the monitoring objective.
Typically, an exposure location (e.g., a water body, a property, an agricultural field) or source
(e.g., milk from cows on a specific farm) is defined for the risk assessment. The monitoring
program should be adequate to represent the spatial and temporal variation within the
location or source, given the particular measure(s) used to support the risk management
decision to be made (e.g., average exposure, maximum exposure). However, several aspects
of spatial and temporal variation are unique to air toxics that persist and which also may
bioaccumulate. For example:
- The temporal patterns of releases from sources may be less important because the
chemicals may slowly accumulate in media and biota over time;
- Spatial "hot spots" of contamination may occur (for example, if soils erode and collect in
low-lying areas);
- Chemicals generally accumulate in different tissues at different rates; therefore,
concentrations may be higher in certain parts of the plant or animal (which may or may
not be the parts that people tend to eat, and vice versa);
- Certain seasonal effects (e.g., growing season for plants, migratory movements in
animals) may be important sources of variation; and
- Age of the plant or animal being sampled may be important if it takes many months or
years for contaminants to reach equilibrium in biological tissues (or if equilibrium is
never reached). For example, mercury concentrations in fish tend to be higher in older,
larger fish.
The monitoring effort should consider the relative contributions of the four main
sources of variability in measurements. As noted in Chapter 10, these are analytical,
sampling, temporal, and spatial.
Standard operating procedures should be defined and followed both in the field (during
sample collection) and in the laboratory (during sample analysis). These include procedures
related to sample collection, sample transport and storage (including prevention of sample
degradation), sample analysis, "chain of custody," audits, data validation, and data reporting.
These procedures may be quite varied due to the range of possible media and biota that could
be sampled.
Limits of quantitation or detection should be determined and compared against relevant
decision needs, including health benchmarks and likely environmental levels.
Measurement processes should be properly calibrated to ensure the accuracy of the
method.
Results must be adequately recorded and archived. The best monitoring program can be
compromised by a failure to keep proper records that can be made part of the public record.
April 2004 Page 19-2
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A periodic, random check of the archived records (e.g. computer files) should be made
against "hard copies" to ensure the integrity of the process of recording the data.
Soil Depth: Issues for Sampling
The depth over which surface soils are sampled should reflect the type of exposure expected in the
study area, the type of receptors expected in the study area, the depth of biological activity and the
depth of potential contamination. Careful consideration of the size, shape, and orientation of sampling
volume is important since they have an effect on the reported measured contaminant concentration
values.0' Selection of sampling design and methods can be accomplished by use of the Data Quality
Objectives (DQO) process discussed in Chapter 6. Additional soil sampling guidance that may be
consulted includes EPA's Preparation of Soil Sampling Protocols: Sampling Techniques and
Strategies and Guidance for Data Usability in Risk Assessment and Soil Screening Guidance,
available at: http://www.epa.gov/superfund/programs/risk/tooltrad.hrmffdbhh/2'
19.4 Monitoring and Sampling Methods, Technologies and Costs
19.4.1 Method Selection
Method selection for sample collection and analysis programs that are applicable to
multipathway human health risk assessments are dependent on numerous aspects of the project.
Factors such as media, sample types, sample program designs, lead regulatory authority, and
concentration ranges of concern all can impact the selection of the appropriate methods. While it
is not possible for this chapter to review all of the monitoring methods available for this broad
range of applications, several of the more important factors that generally influence decisions on
methods selected are discussed below.
The primary determining factor in selection of sample collection and analysis methodologies is
the sample media to be evaluated. Exhibit 19-1 presents several examples of the types of media
that might be sampled for a multipathway human health risk assessment.(a) Other factors that
affect selection of sample collection methods are sample type and sample program design.
Specific factors in selection of sample collection methods may also be construction material of
the sampling devices, its design, decontamination, and proper use, site-specific conditions,
relative cost, and data quality limitations.
Sample collection methods may be categorized by sample type as discussed in Chapter 10.
However, the distinction is not always clear (e.g., a single fish tissue sample might be considered
a grab sample because it is collected at a single location and time; however, because the
contaminant concentrations in its tissues accumulate over time, the sample could also be
considered a time-integrated sample). The more common types of samples used for non-air
sampling are provided below:
• Grab samples (also known as discrete samples) are collected at a specific location (and
generally instantaneous) time. Any technique where the sampling container is filled to
represent a snapshot of the concentration of target contaminants at a single specific time is
Air sampling also may be conducted; however, that is discussed in Chapter 10.
April 2004 Page 19-3
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considered a grab sample. Where the population to be represented is demonstrated to be
homogenous or consistent, grab samples provide the maximum information.
Time-integrated samples are collected at a single location but over an extended period of
time. Similar to grab samples, analysis of time-integrated samples provides a snapshot of
that range of time and location as a single value. Only the total pollutant collected is
measured, and so only the average concentration during the sampling period can be
determined.
Exhibit 19-1. Examples of Environmental Media that May be Sampled for
Multipathway Human Health Risk Assessment
-------
analyzed. Depending on the application, maximum, median, time-weighted average, or
distribution curves may be applied to reduce the large amount of results obtained from true
continuous data to usable results which can be compared to decision criteria.
Sample collection methods may also be determined by the sample collection design methodology
(Exhibit 19-2). Sample design impacts method selection often by determining the number of
samples being collected.
Exhibit 19-2. Common Types of Sampling
Purposive
sampling
Are a estimated to
have highest
concentration
Grid
sampling
n
Random
sampling
ff
0
0
0
Purposive sampling focuses the sampling effort in specific locations (in this example, the area
estimated to have the highest concentration). Grid sampling consists of regularly-spaced
samples in a predetermined grid. Random sampling consists of samples in locations selected
by chance.
Purposive sampling involves focused sample collection based on previous knowledge of
release event locations. Purposive (also called biased) sampling is named such because the
person taking the sample willfully takes that sample at a time or place where, based on prior
knowledge, it is expected that concentrations will generally be biased high. Purposive
sampling may be desired in programs looking to verify expected model results. Purposive
sampling often targets maximum contaminant conditions to evaluate maximally impacted
areas. However, it maybe used for reasons such as targeting specific species to calibrate
bioaccumulation models or defining the spatial extent of contamination.
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• Systematic sampling consists of collecting samples at locations and times according to
specific patterns (e.g., grid sampling). Systematic sampling may use previous knowledge to
set frequency, density, or coverage of sampling.
• Random sampling involves collecting samples from locations in a manner such that each
location has an equal probability of being sampled and analyzed. Random sample collection
designs are an important aspect of certain statistical data evaluations.
The factors which primarily affect selection of preparation and analysis methods include target
contaminants, required reporting limits (i.e., concentration range of decision criteria), number of
samples, data quality limitations, method/instrument portability, previous data comparability,
acceptance/approval by regulators and stakeholders, and relative cost and availability.
• Target contaminants. The specific contaminants being sampled may have a significant
impact on both budget and overall approach. For example, sampling and analytical
procedures for metals are different than those for organic chemicals. Careful evaluation
before inclusion of unwarranted parameters and establishment of a procedure for
identification and removal of chemicals of potential concern (COPCs) is critical to an
effective monitoring program.
• Required reporting limits. Assessors should select analytical methods so that the reporting
limits (usually the estimated quantitation limits) are less than the effects concentrations of
interest. If the assessor does not select an adequately sensitive analytical method, the
quantitation limit for a given chemical could exceed the chemical's effects benchmark
concentration of interest; in that case, monitoring information would not provide meaningful
input to the risk assessment.
• Number of samples. A sampling program that involves screening-level assessment of a
large number of samples may drive selection of certain methods for the bulk of samples in
order to allocate limited resources. In the opposite case, determination of low heterogeneity
of sample media, and extremely low risk-based concentrations of interest as decision criteria
may require fewer samples and more highly sophisticated methodologies.
• Data quality limitations. High data quality requirements imposed by high uncertainty or
other factors may influence the choice of sampling methods such as procedures that are more
stringent and more costly than usual procedures.
• Method/instrument portability. In-field or on-site analysis has begun to replace laboratory-
based analysis in many monitoring programs. Certain preparation and analysis
methodologies are more portable than others, in part because of the sensitivity of the
instrumentation. However, considerable expertise in sampling and analysis is needed to
decide whether in-field or laboratory-based analysis is appropriate for the study.
• Previous data comparability. Previous data sets can affect selection of appropriate
methods. All other factors being equal, data comparability goals and objectives are more
easily met by use of consistent methods.
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• Stakeholder input. Stakeholder preferences may influence method selection.
• Relative Cost/Availability. The reality of limited resources often impacts method selection.
Certain monitoring methods are commonly performed and available at numerous laboratories
or by readily available field instrumentation. Other more obscure methods may better meet
the needs of the project but are only available from highly specialized laboratories. In
addition to cost impact, low availability of some specific monitoring methods can impact data
quality due to lack of practice, market competition, appropriate standards, or certifications.
19.4.2 Available Methods
Hundreds of specific sampling, test, analysis, and quality assurance methods and procedures exist
for soil, water, sediment, and biota. The list of available methods changes frequently as new
methods are introduced and older methods are retired. It is not possible for this chapter to review
all of the monitoring methods available. Instead, this section provides an overview of several
key EPA resources and provides a listing of web sites that serve as sources of additional
information. Key EPA resources include the EPA Test Methods Index; the Contract Laboratory
Program (CLP); and the Fish and Wildlife Advisories Program.
• EPA Test Methods Index (http://www.epa.gov/epahome/Standards.html). EPA has
developed hundreds of specific sampling, test, analysis, and quality assurance methods and
procedures. In response to frequent requests for agency test methods, Region 1 Library staff
developed a methods index as a tool to help locate copies. Confirming that there was no
single volume containing all agency methods and no comprehensive list of them, the project
commenced and in 1988 printed the first EPA Test Methods Index.^ It has been updated
periodically to reflect new procedures and revoked methods, and the current edition includes
about 1,600 method references. The index includes only EPA methods, and its primary goal
remains as a reference tool to identify a source from which the actual method can be
obtained, either free or for a fee.
• EPA Contract Laboratory Program. The Contract Laboratory Program (CLP) is a national
network of EPA personnel, commercial laboratories, and support contractors whose
fundamental mission is to provide data of known and documented quality, primarily for the
Superfund program (http://www.epa.gov/superfund/programs/clp/about.htm). The Analytical
Operations/Data Quality Center (AOC) provides several tools to assist CLP clients,
laboratories, and samplers (http://www.epa.gov/superfund/programs/clp/tools.htm). These
tools were designed to use the Internet to facilitate many of the essential functions of the
CLP.
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Available Guidance from EPA's Contract Laboratory Program
Contract Laboratory Program National Functional Guidelines for Low Concentration Organic Data
Review EPA-540-R-00-006 June 2001
Contract Laboratory Program National Functional Guidelines for Organic Data Review
EPA-540/R-99-008 (PB99-963506) October 1999
Contract Laboratory Program National Functional Guidelines for Inorganic Data Review
EPA 540-R-01-008 July 2002
Contract Laboratory Program National Functional Guidelines for Chlorinated Dioxin/Furan Data
Review EPA-540-R-02-003 August 2002
Contract Laboratory Program Guidance for Field Samplers (Draft-Final) EPA-540-R-00-003 April
2003
This information, as well as methodology information is available from the CLP at:
http ://www. epa. gov/superfund/programs/clp/services .htm
• EPA's Fish and Wildlife Advisories Program (http://www.epa.gov/waterscience/fish/).
EPA's Office of Science and Technology provides technical and outreach material that
support efforts by state, local, and tribal (S/L/T) governments to protect their residents from
the health risks of consuming contaminated noncommercially caught fish. S/L/T
governments do this by issuing consumption advisories for the general population as well as
for specific vulnerable sub-populations. These advisories tell the public when high
concentrations of chemical contaminants have been found in local fish. They also include
recommendations to limit or avoid eating certain fish species from specific water bodies or
water body types. The program also provides Guidance for Assessing Chemical Contaminant
Data for Use in Fish Advisories (http://www.epa.gov/waterscience/fish/guidance.html). a set
of four volumes that provides guidance for assessing health risks associated with the
consumption of chemically contaminated non-commercial fish and wildlife. The set includes
Third Editions of Volume 1: Fish Sampling and Analysis and Volume 2: Risk Assessment
and Fish Consumption Limits.
Exhibit 19-3 provides links to information on specific sampling and analysis methods,
summarized from key EPA compendia of methods. Methods are divided into four categories
(General, Analytical Method Index, Sample Collection, and Quality Assurance). Keywords are
added to help readers get to the area they are concerned with. Additional effort may be required
to "drill into" each site to view the relevant information. These links generally are limited to
government sites. Some non-EPA sites are included (e.g., Occupational Safety and Health
Administration (OSHA), National Institute of Standards and Technology (NIST), and National
Institute for Occupational Safety and Health (NIOSH)) to help fill specific information gaps.
April 2004 Page 19-i
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Exhibit 19-3. Sources for Information on Specific Sampling and Analysis Methods
Keywords
Description and URL Link
General References
Sample collection, analysis
method, criteria, water
Analysis methods
Sample collection, analysis
methods, reference
Sample collection, analysis
methods, reference
Sample collection, analysis
methods, reference
General EPA Water page with links to analytical methods,
sampling guidance, and criteria for assessment of contamination.
http ://www. epa. 2ov/waterscience/
EPA' s Office of Ground Water and Drinking Water (OGWDW)
links to analysis methods.
http://www.epa.20v/OGWDW/methods/methods.html
NIOSH pocket guide to chemical hazards contains information by
analyte which can support field sample collection, analysis, and
determination of relevant criteria.
http://www.cdc .2ov/niosh/np 2/np 2.html
NIST web book contains information by analyte which can
support field sample collection, analysis, and basic chemical
parameters from thermodynamic constants to reference mass
spectra, http://webbook.nist.2ov/chemistrv/
General EPA environmental test methods and guidelines page
with numerous links to other areas of information throughout EPA
web sites. http://www.epa.20V/epahome/Standards.html
Analysis Method Index
Analysis methods, sample
collection
Analysis methods, sample
collection
Analysis methods, sample
collection
Region I list of methods available as hardcopy and partial links to
analysis methods, http://www.epa.2ov/epahome/index/
Searchable online database of analysis methods. NEMI is a
project of the National Methods and Data Comparability Board, a
partnership of water quality experts from Federal agencies, States,
Tribes, municipalities, industry, and private organizations
supported by EPA and the U.S. Geological Survey.
http ://www.nemi. 2ov
National Exposure Research Laboratory (NERL) formerly EMSL,
Manual of Manuals links to information about analysis methods;
summaries and ordering information for eight laboratory
analytical chemistry methods manuals published by the former
Environmental Monitoring Systems Laboratory-Cincinnati
(EMSL-Cincinnati) between 1988 and 1995.
http ://www . epa . 2ov/nerl cwww/methmans .html
Analysis Methods
Analysis methods, water
Analysis methods, water, 601,
602, 603, 604, 605, 606, 607,
608,609,610,611,612,613,
624, 625, 1624, 1625
EPA's Office of Water link to analysis methods. Laboratory
analytical methods that are used by industries and municipalities
to analyze the chemical and biological components of wastewater,
drinking water, sediment, and other environmental samples that
are required by regulations under the authority of the Clean Water
Act (CWA) and the Safe Drinking Water Act (SDWA).
http ://www. epa. 2ov/waterscience/methods/
Methods for organic chemical analysis under the authority of the
Clean Water Act (CWA) and the Safe Drinking Water Act
(SDWA).
http ://www . epa . 2ov/ostwater/methods/2uide/methods .html
April 2004
Page 19-9
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Exhibit 19-3. Sources for Information on Specific Sampling and Analysis Methods
Keywords
Analysis methods, drinking water
Organic, analysis methods,
drinking water
Inorganic, metal, analysis
methods, drinking water
Analysis methods, drinking
water, radionuclides
Analysis methods, drinking
water,
Analysis methods, drinking
water,
Analysis methods, immunoassay
Analysis methods, CLP, organic,
dioxin, inorganic, water, soil
Analysis methods, air
Analysis methods, pesticide, soil,
water
Analysis methods, water, soil,
sediment, waste, air
Sample collection, analysis
methods, air
Sample collection, analysis
methods, air
Description and URL Link
Recent drinking water methods from EPA's Office of Research
and Development, National Exposure Research Laboratory
(NERL), formerly the Environmental Monitoring Systems
Laboratory (EMSL). http://www.epa.2ov/nerlcwww/ordmeth.htm
Organic method index with hyperlink to method by analyte in
drinking water as maintained by Office of Ground Water and
Drinking Water.
http://www.epa.20V/OGWDW/methods/orch tbl.html
Inorganic and metal analysis methods in drinking water as
maintained by Office of Ground Water and Drinking Water.
http ://www . epa . 20V/OGWD W/method s/inch tbl .html
Radionuclides in drinking water as maintained by Office of
Ground Water and Drinking Water.
http://www.epa.20V/OGWDW/methods/rads.html (EPA)
http://www.epa.20V/OGWDW/methods/indrads.html (non-EPA)
Approved methods for unregulated contaminants in drinking
water as maintained by Office of Ground Water and Drinking
Water, http ://www . epa . 20V/OGWD W/method s/unre2tbl .html
Secondary contaminants in drinking water as maintained by
Office of Ground Water and Drinking Water.
http://www.epa.20V/OGWDW/methods/2nd tbl.html
Region 1 guidance on immunoassay methods.
http://www.epa.2ov/re2ionl/measure/ia/ia2uide.html
Contract Laboratory Program (CLP) methods for organics,
inorganics, and dioxins/furans.
http://www.epa.2ov/superfund/pro2rams/clp/methods.htm
EPA Emissions Measurement Center (EMC) for methods related
to determination of airborne pollutants.
http ://www. epa. 2ov/ttn/emc/
EPA' Office of Pesticide Programs (OPP) database of
environmental chemistry, residual, and antimicrobial analysis
methods, http://www.epa.2ov/oppbeadl/methods/
EPA's OSWER provides online updated SW-846 waste sampling
and analysis methods manual which is the source of many related
methods used in environmental sampling and analysis.
http://www.epa.2ov/epaoswer/hazwaste/test/main.htm
Occupational Safety and Health index of sampling and analysis
methods alphabetically by parameter and general information on
selection of methods and laboratories, http://www.osha-
slc.gov/dts/sltc/methods/index.html
EPA's Organic (TO) Compendium of methods for air toxics and
EPA's Inorganic (IO) Compendium methods.
http ://www . epa . 2ov/ttn/amtic/airtox. html
Sample Collection
Sample collection, analysis, fish,
shellfish, biota
Methods for sampling and analyzing contaminants in fish and
shellfish tissue.
http://www.epa.2ov/waterscience/fishadvice/volumel/index.html
April 2004
Page 19-10
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Exhibit 19-3. Sources for Information on Specific Sampling and Analysis Methods
Keywords
Sample collection
Sample collection, monitoring
wells, low stress
Sample collection, monitoring
wells, low stress
Sample collection, field analysis
Sample collection, field analysis,
program design
Description and URL Link
Current manuals and protocols prepared by NERL-Cincinnati
scientists. NERL is the EPA's scientific lead for the following
stream and source monitoring indicators: fish, macro invertebrates,
periphyton, zooplankton, functional ecosystem indicators, water
and sediment toxicity and fish tissue contaminants. As part of
their indicator lead responsibilities NERL-Cincinnati scientists
prepare and update field and laboratory protocol and methods
manuals for these indicators.
http ://www. epa. 2ov/nerleerd/methman.htm
Guidance for RCRA/Superfund groundwater sample collection
methodologies and the logical process for determining an
approach fit to site specifics.
http://www.epa.2ov/tio/tsp/download/2w samplin2 2uide.pdf
Generally well accepted low stress (low flow) ground water
sample collection guidance from EPA Region I. Several versions
exist across EPA regions and within other governmental and State
guidelines.
http://www.epa.2ov/re2ionl/measure/well/wellmon.html
EPA Environmental Response Team provides numerous sampling
and field analysis Standard Operating Procedures (SOPs) often
encountered in environmental responses including otherwise
atypical sample collections SOPs such as drum, wipe, and waste
pile sampling techniques, http://www.ertresponse.com/sops.asp
EPA's Office of Technology Innovation provides a web site with
information on proper sampling program design, QA/QC
concerns, and use of field methodologies to expedite information
collection without loss of data quality, http://clu-in.or2
Quality Assurance
Quality assurance
Quality assurance
EPA Agency-wide quality system documents for EPA and non-
EPA organizations plus general guidance. Documents are
available as PDFs. http://www.epa.2ov/qualitv/aa docs.html
Region I guidance includes quality assurance documents.
http://www.epa.2ov/re2ionl/lab/qa/qualsvs.html
April 2004
Page 19-11
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References
1. U.S. Environmental Protection Agency. 2000. Draft Ecological Soil Screening Level
Guidance. Office of Emergency and Remedial Response. July 10, 2000.
2. U.S. Environmental Protection Agency 1992. Guidance for Data Useability in Risk
Assessment (Part A). Office of Emergency and Remedial Response, Washington, B.C., April
1992. Publication 9285.7-09A, PB92-963356. Available at:
http ://www. epa. gov/superfund/programs/risk/datause/parta.htm
U.S. Environmental Protection Agency 1992. Preparation of Soil Sampling Protocols:
Sampling Techniques and Strategies. Office of Research and Development.
EPA/600/R-92/128. Available at:
http://www.epa.gov/superfund/programs/riskytooltrad.htmfabh
U.S. Environmental Protection Agency 1996. Soil Screening Guidance: User's Guide. Office
of Solid Waste and Emergency Response. Washington, D.C., July 1996. EPA540/R-96/018.
See especially Attachment B, Soil Screening DQOs for Surface Soils and Subsurface Soils.
Available at: http://www.epa.gov/superfund/resources/soil/index.htmfaser
U.S. Environmental Protection Agency. 2002. Supplemental Guidance For Developing Soil
Screening Levels for Superfund Sites. Office of Solid Waste and Emergency Response,
Washington, D.C., December 2002. OSWER 9355.4-24. Available at:
http://www.epa.gov/superfund/programs/riskytooltrad.htmfabh
3. U.S. Environmental Protection Agency. 1988. EPA Test Methods Index. EPA 901/388/001.
April 2004 Page 19-12
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Chapter 20 Exposure Metrics for Multimedia
Assessment
Table of Contents
20.1 Introduction 1
20.2 Generic Equation for Dietary Intake 3.
20.3 Estimating Exposure Concentrations 4
20.4 Calculating Intake Variable Values 6
20.4.1 Consumption Rate 7
20.4.2 Exposure Frequency K)
20.4.3 Exposure Duration K)
20.4.4 Body Weight 12
20.5 Calculating Averaging Time Value 12
20.6 Combining Exposure Estimates Across Pathways 13.
20.7 Exposure Models 14
References 16
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20.1 Introduction
This chapter concludes the exposure assessment component of the multipathway risk assessment
by describing how to develop estimates of intake (i.e., the metric of exposure) for the ingestion
pathways selected for analysis. Estimates of chemical intake via the inhalation pathway were
presented in Chapter 11. Exhibits 14-2 and 20-1 provide an overview of the potential
multimedia exposure pathways by which air toxics that persist and potentially bioaccumulate
may reach ecological and human receptors, respectively. Determination of chemical intake via
the ingestion exposure route combines the estimates of chemical of potential concern (COPC)
levels in food items and drinking water (discussed in Chapter 7) with estimates of consumption
rates (food, water), exposure frequency and duration, averaging time, and body weight to derive
estimates of the chemical intake rate (expressed generally as mg/kg-day).(1)
Exhibit 20-1. Potential Multimedia Exposure Pathways of Concern
Dispersal
Atmospheric
Deposition
Dispersal
/ . Atmospheric / /
/ , / Deposition / /
l,li - • •
I I '
Inhalation of
Contaminated
Air
1
Dermal
Absorptio
Consumption of
Contaminated Fish
Absorption
and Settling
Ingestion by
Livestock
Transfer Up Consumption of Livestock
Aquatic Food Web j1 ^ and Dairy Products
Consumption of
Contaminated
Water and Plants
Uptake by Plants
This graphic illustrates many of the potential multimedia pathways of concern for air toxics. Air
toxics released from a source disperse through the air and eventually fall to the earth (atmospheric
deposition) via settling and/or precipitation. Air toxics deposited to soil may be absorbed by plants
that are then harvested for human consumption. Humans may be exposed via ingestion of
contaminated plants and soils, or by consuming contaminated terrestrial animals (e.g., beef, for those
air toxics that bioaccumulate and transfer up the terrestrial food web). Air toxics deposited to water
may be dissolved in the water column and/or may settle and be absorbed into aquatic sediments. Air
toxics in sediments and the water column may be absorbed by aquatic plants (uptake). Aquatic
organisms (e.g., fish) may be exposed directly to air toxics in the water column and/or by consuming
other contaminated aquatic organisms (for those air toxics that bioaccumulate and transfer up the
aquatic food web) or sediments. People may be exposed to air toxics by eating contaminated aquatic
plants, fish, or shellfish and/or by drinking contaminated water. Note also that, while in the
atmosphere, air toxics may also have direct impacts to humans via inhalation.
April 2004
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Chapter 7 described two general approaches for deriving the exposure concentration (EC) for an
inhalation risk assessment: (1) use of ambient air concentrations as a surrogate for the EC, and
(2) exposure modeling that combines estimates of ambient air concentrations with information
about the population of interest, including the types of people present (e.g., ethnicity, age, sex),
time spent in different microenvironments, and microenvironment concentrations. The first
approach (i.e., use of ambient concentrations in abiotic media such as soil, water, or
sediments) generally is not used for multipathway air toxics risk assessments. Instead, a
multipathway exposure assessment must involve some type of exposure modeling (e.g., at a
minimum simple scenarios to characterize persons who are exposed and the amount and duration
of their contact with the abiotic and bio tic media).
Note that EPA has derived some human health screening-level concentration benchmarks for
surface water and soil (i.e., the Office of Water's Ambient Water Quality Criteria for the
Protection of Human Health,(2) and the Superfund Program's soil screening levels(3)). However,
these human health benchmarks are based on specific scenarios (e.g., how much water a person
drinks each day, how much they weigh) that were selected to meet different programmatic goals
and statutory requirements. Therefore, the scenarios on which these benchmarks are based may
not be appropriate for a specific air toxics risk assessment.
The way a chemical enters the body and eventually reaches the target organ is a complex process
(see box below). For most chemicals, however, it is not necessary to quantify anything beyond
the chemical intake rate, because the dose-response value (e.g., Reference Dose [RfD] or
Cancer Slope Factor [CSF]) is also based only on the amount of chemical ingested and not the
amount of chemical that has been absorbed into the bloodstream.
Exposure and Intake via Ingestion
The process of a chemical entering the body can be described in two steps: exposure (contact),
followed by entry (crossing the boundary). Intake involves physically moving the chemical in
question through an opening in the outer boundary (usually the mouth), typically via eating or
drinking. Normally the chemical is contained in a medium that comes into contact with the body,
such as food or water, and the concentration of the chemical at this point of contact is called the
exposure concentration. The estimate of how much of the chemical enters into the body is based on
how much of the carrier medium enters the body. The chemical intake rate is the amount of
chemical crossing the outer boundary per unit time, and is the product of the exposure concentration
times the ingestion rate. Ingestion rate is the amount of the carrier medium crossing the boundary
per unit time, such as the number of kilograms of food ingested/day or liters of water consumed/day.
Ingestion rates typically are not constant over time (they can vary over time and among individuals)
and are usually given (for deterministic analyses) as an average intake rate over some period of time.
In addition, the intake rates are usually normalized to body weight. Thus, a common intake rate
would take the form of milligrams of pollutant ingested per kilogram of body weight per day (or
mg/kg-d). A different ingestion rate would be developed for each type of person in the population
under study. For example, one intake rate could be developed to represent the average adult (male
and female) while a separate intake rate could be developed to represent children between the ages of
birth to four years old.
x^ ^
The remainder of this chapter focuses on how to quantify ingestion exposure (intake) for
multipathway air toxics risk assessments. The corresponding chapter for inhalation analyses
April 2004 Page 20-2
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(Chapter 11) discusses how to evaluate uncertainty in the exposure assessment and how to
present the exposure assessment results; this applies to all exposure evaluations (i.e., inhalation
and ingestion).
20.2 Generic Equation for Dietary Intake
Equation 20-1 is the generic equation used to calculate dietary chemical intake:(4)
EC x C8 EF* ED (Equation 20-1)
/ = x
BW AT
where
/ = Chemical intake rate, or the amount of pollutant ingested per unit time per body
weight (mass), expressed in units of mg/kg-day. For evaluating exposure to
noncarcinogens, the intake is referred to as Average Daily Dose (ADD); for evaluating
exposure to carcinogenic compounds, the intake is referred to as Lifetime Average
Daily Dose (LADD).
Chemical-related variable:
EC = Exposure concentration of the chemical in the medium of concern for the time
period being analyzed, expressed in units of mg/kg for soil and food or mg/L for
surface water or beverages (including milk).
Variables that describe the exposed population (also termed "intake variables"):
CR = Consumption rate, the amount of contaminated medium consumed per unit of time or
event (e.g., kg/day for soil and L/day for water).
EF = Exposure frequency (number of days exposed per year).
ED = Exposure duration (number of years exposed).
B W = Average body weight of the receptor over the exposure period (kg).
Assessment-determined variable:
AT = Averaging time, the period over which exposure is averaged (days). For carcinogens,
the averaging time is 25,550 days, based on an assumed lifetime exposure of 70 years;
for noncarcinogens, averaging time equals ED (years) multiplied by 365 days per
year.
The values of some exposure factors depend on site conditions as well as the characteristics of
the potentially exposed population (e.g., child vs. adult). Because of differences in physiology
and behavior, exposures among children are expected to be different than exposures among
adults. For example, body weight and consumption rate differ for children and adults. For the
evaluation of non-carcinogenic effects, intakes for children generally are estimated separately
(often for ages 0-6) than for adults (often from ages 6-beyond). For the evaluation of
carcinogenic effects, intake estimates are averaged over the assumed lifetime (70 years).
April 2004 Page 20-3
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20.3 Estimating Exposure Concentrations
The exposure concentration for a chemical is calculated separately for each food item and
environmental medium of concern. The value of these variables may be determined by modeling
(Chapter 18), monitoring (Chapter 19), or a combination of both. The specific algorithms for
determining these concentrations will depend on the specific models and/or sampling and
analysis techniques used. For example, EPA has developed methodologies for estimating EC
values in soil, water, sediment, and various food items for releases from hazardous waste
combustion facilities (see Appendix L).(5)
For ingestion pathways, the specific media concentration values obtained from a multimedia
modeling simulation for use in deriving exposure concentrations depends on several important
decisions made during problem formulation, including:
• Choice of modeling duration for a model run;
• Choice of the year or years of the model run on which to base the EC; and
• Choice of a specific ED.
Exhibit 20-2 presents several different examples relevant to different purposes/objectives for an
assessment.
Exhibit 20-2. Example Decisions in Assessing Exposures Resulting From
Distribution of Air Toxics into Other Media
Concentration in Fish Tissue
1DDDD
1000 -
100 H
10 -
0 10 20 30 40 50 60 70 80 SO 100
time (years)
In this hypothetical example, a modeling analysis was used to predict the concentrations of a persistent
bioaccumulative hazardous air pollutant (PB-HAP) in fish tissue during a 100-year emissions scenario
(annual average was estimated each year and is plotted here using a logarithmic scale). As discussed
below, the exposure scenario assessed will reflect several key choices including:
(1) choice of modeling duration for model run;
(2) choice of year or years of model run on which to base EC (i.e., the model outputs); and
(3) choice of specific ED.
April 2004
Page 20-4
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Exhibit 20-2 (continued)
The modeling duration is a separate decision from the ED and is not related to the average human
lifespan,
Note that in this example, the analyst assumed that the starting concentration was zero (i.e., the tissue
concentrations reflect only the sources being modeled). Some multimedia models (e.g., TRIM.FaTE)
can start with an initial concentration.
Modeling Duration. The analyst can choose to run a multimedia model for any period of time.
Duration will usually be chosen to reflect the expected duration of emissions from the source(s) being
evaluated or, perhaps, that duration expected in order to reach steady-state conditions. A common
duration is 30 or 40 years (e.g., the expected lifespan of many facilities or processes). For this
example, a 100-year duration was selected.
Selection of Model Outputs. Usually the modeling duration will have been chosen with
consideration of the model outputs on which the exposure scenario is to be based and the exposure
duration. Some common examples follow:
• Year of maximum concentration. Screening-level analyses often use the maximum
concentration reached during the modeling period which, for a constant emissions scenario, will
usually be the final year of the modeling simulation. For this example (see figure), it would be the
100th year (at such time as the fish concentration was approximately 2,000 ng/kg).
- Exposure Duration. With use of the maximum model result, the analysis presumes no change
in fish concentration over the exposure duration (i.e., in this example EC = 2,000 ng/kg
throughout the exposure period).
• Initial years of simulation. In this case the exposure being assessed is that beginning with
initiation of emissions and extending through the duration selected for assessment.
- 30-year Exposure Duration. In this case, the analyst is basing the exposure duration near
the 95 percentile of how long people live in the same home.(6) If the analyst chose to examine
changing concentrations over time, the ECs would vary, reflecting the concentration outputs
from the first 30 years of the modeling duration.
- 70-year Exposure Duration. In this case, the analyst is using a lifetime exposure
assumption. The exposure scenario then may be based on the model outputs from the first 70
years of the modeling duration.
• Last years of simulation. In this case, the exposure being assessed is that which occurs during
the ending years of the simulation, with the number of years involved equal to the exposure
duration selected for assessment.
- 30 -year Exposure Duration. For this ED, the ECs would vary reflecting the predicted
concentrations from the last 30 years of the model simulation.
- 70-year Exposure Duration. In this case, the analyst is using a lifetime exposure
assumption. The exposure scenario may then employ varying ECs reflecting the predicted
concentrations from the last 70 years of the model simulation.
Note: When using varying exposure concentrations for the exposure scenario, other variables included
in the calculation of ingestion exposure estimates (pollutant intake, mg/kg-day) for the population(s)
of interest may also vary. For example, if the exposure scenario includes exposure for cohorts aging
from birth - 30 years, other exposure factors (e.g., body weight, consumption rate) will also vary over
time.
April 2004 Page 20-5
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20.4 Calculating Intake Variable Values
Each intake variable in Equation 20-1 (e.g., consumption rate, body weight) has a range of
potential values. Intake variable values for a given pathway may be selected so that the
combination of all intake variables results in an estimate for an individual at the "high-end" of
potential exposure levels. Alternatively, the intake variables maybe selected to represent a
"central tendency" individual expected to receive an average exposure. In doing this, the
assessor needs to avoid combinations of parameter values that are inconsistent (e.g., low body
weight used in combination with high dietary intake rates), and must keep in mind the ultimate
objective of being within the distribution of actual expected exposures and doses, and not beyond
it. Commonly, both the central tendency and high end intakes are quantified. In some cases, the
distribution of intake rates in the population may be described using probabilistic risk assessment
methods (discussed in Part VI).
EPA recommends values for intake variables for the U.S. population in the Exposure Factors
Handbook,^ the Child-Specific Exposure Factors Handbook,^ and the Consolidated Human
Activity Database..(9)(a) EPA also recently published draft guidance on selecting the appropriate
age groups for assessing childhood exposures.(10) Note, however, that there are likely to be
differences between recommended default, and regional and site-specific, exposure parameter
values. This may be especially true for consumption rate (see below).
For central tendency estimates, risk assessors commonly set all of the exposure factors in the
Equation 20-1 at central tendency values. If only limited information on the distribution of the
exposure or dose factors is available, risk assessors commonly approach the high-end estimates
by identifying the most sensitive variables and using high-end values for a subset of these
variables, leaving others at their central values. As mentioned earlier, the assessor needs to avoid
combinations of parameter values that are inconsistent (e.g., low body weight with high dietary
intake rates) and must keep in mind the ultimate objective of being within the distribution of
actual expected exposures and doses.
Maximizing all variables will in virtually all cases result in an estimate that is above the actual
values seen in the population. When the principal parameters of the dose equation (e.g.,
concentration [appropriately integrated over time], intake rate, and duration) are broken out into
sub-components, it may be necessary to use maximum values for more than two of these
sub-component parameters, depending on a sensitivity analysis.
For probabilistic analyses, values for exposure factors are commonly allowed to vary according
to specific assumed distributions of potential values.
Note that the high-end intake estimate is a plausible estimate of intake for those persons at the
upper end of the exposure distribution. This descriptor is intended to estimate the exposures
that are expected to occur in small but definable high-end segments of the subject population
aNCEA recently published a new compilation of consumption data from the 1994-1 996 CSFII. This data
updates CSFII data in the 1997 Exposure Factors Handbook.
See: http://cfbub.epa.gov/ncea/cfm/recordisplay.cfm?deid=56610.
April 2004 Page 20-6
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(but not higher than the highest person in the population), but may not be appropriate for
estimating exposure for the population as a whole.m
20.4.1 Consumption Rate
Consumption rate is the amount of contaminated food or medium consumed per event or unit of
time (e.g., amount offish consumed per meal or per day). The consumption rate is multiplied by
a fraction of the total dietary intake for this type of food or medium, representing the amount
consumed from the study area. The specific fraction applied depends on the analysis.
• For screening-level analyses, it is common to assume that the person obtains 100 percent of
the food type from the study area (e.g., farm, water body) being evaluated. This assumption
also might be used for a subsistence-type receptor (e.g., a local fish consumer who only eats
fish caught from the study area).
• For higher tiers of analyses, it is common to assume that the person obtains some of the food
type from the study area (i.e., the contaminated fraction) and some of the food type from
other sources (e.g., at the grocery store). This latter fraction generally is assumed to be
uncontaminated by the source(s) under assessment. Thus, if a person is assumed to eat x/2
pound of fish per day, but only 25 percent is caught within the study area, the assumed
consumption of contaminated fish would be 1/8 pound per day.
The following pathway-specific considerations are important for estimating consumption rate.
• Food Ingestion. Plants and animals may accumulate COPCs that were deposited onto soil or
water. Humans may be exposed to these compounds via the food chain when they consume
these plants (and animals that consume these plants) as a food source. Human intake of
COPCs is quantified on the basis of the concentration of COPC in the food (Section 20.3)
and:
- The types of foods consumed, which vary with age (e.g., children and adults often eat
different things), geographical region, and sociocultural factors (e.g., ethnicity, cultural
factors);
- The amount of food consumed per day, which can vary with age, sex, and geographic
region, and also within these categories;
- The fraction of the diet contaminated by COPCs (which can vary by food type); and
- The effect of food preparation techniques on concentrations of COPCs in the food itself.
• Soil Ingestion. Children and adults may receive direct exposure to COPCs in soil when they
consume soil that has adhered to their hands (called incidental soil ingestion). Factors that
influence exposure by soil ingestion include concentration of the COPC in soil, the rate of
soil ingestion during the time of exposure, and the length of time spent in the vicinity of
contaminated soil. Soil ingestion rates in children are based on studies that measure the
quantities of nonabsorbable tracer minerals in the feces of young children. Ingestion rates for
adults are based on assumptions about exposed surface area and frequency of hand-to-mouth
transfer. Indoor dust and outdoor soil may both contribute to the total daily incidental
ingestion of soil (indoor dust is partially made up of outdoor soil that has been tracked
inside).
April 2004 Page 20-7
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In addition, some young children - referred to as "pica" children - may intentionally eat soil.
The typical medical and scientific use of the term "pica" refers to the ingestion of nonfood
items, such as soil, chalk, and crayons.(10) Such behavior is considered a temporary part of a
child's development. For risk assessment purposes, pica is typically defined as "an
abnormally high soil ingestion rate" and is believed to be uncommon in the general
population. If available information indicates that there are children exhibiting pica behavior
in the assessment area, it may be appropriate to include these children as a separate group in
the exposure assessment. EPA's Exposure Factors Handbook provides quantitative data on
soil ingestion rates related to pica.(11)
Inhalation of soil resulting from dust resuspension by wind erosion generally is not a
significant pathway of concern for air toxics .(5) However, it may be an issue for locations at
which there is little vegetative cover. Methodologies have been developed to assess the
exposure to pollutants resuspended by wind erosion for landfills and Superfund sites.(12) The
exposure estimate from resuspended soil would depend on moisture content of the soil,
fraction of vegetation cover, wind velocity, soil particle size, COPC concentration in the soil,
and size of the contaminated area.
Depth of Contaminated Soils: A Key Variable
When exposures to COPCs in soils are modeled for human health risk assessment, an important factor
affecting the exposure estimate is the depth of contaminated soils used to calculate soil concentrations.
The same deposition rate will result in different soil concentrations depending on how deeply the
COPCs are assumed to mix or migrate into the soil. Mixing depth also may affect exposure estimates
via specific pathways. For example, in calculations of exposures resulting from uptake through plant
roots, the average concentration of COPCs over the depth of the plant root determines plant uptake.
However, calculations that assess soil ingestion through hand-to-mouth activity commonly focus on
only the top few centimeters of soil.
COPCs deposited onto undisturbed soils generally are assumed to remain in the shallow, upper soil
layer. However, COPCs deposited onto soil surfaces may be moved into lower soil profiles by tilling,
whether manually in a garden or mechanically in a large field. Other factors such as soil disturbance
by domestic animals (e.g., cattle in an enclosure) also may need to be considered. Some chemicals are
also highly soluble in water and may be carried deeper into soil along with infiltrating rainwater. The
key questions to ask therefore include:
• Are soils tilled, or is it reasonable to assume they are undisturbed?
• If soils are tilled, what mixing depth is reasonable to assume?
• What other factors might affect how deeply COPCs will be moved into soils?
EPA guidance and other references'5'03' provide a more detailed discussion of depth of contaminated
soils, along with recommended values.
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Ingestion of Drinking Water. In air toxics assessments, assessors only evaluate the
ingestion of drinking water when an affected surface water body or collected precipitation
(e.g., a cistern) is used as a drinking water source.(b) Important factors affecting the
concentration of COPCs in a surface water body include the location of the surface water
body or precipitation collection apparatus relative to emissions sources; concentrations of
COPCs in and characteristics of the soils (which affects runoff and leachate concentrations);
and the size and location of the watershed. For drinking water, the exposure estimate is
affected by:
- The concentration of the COPC in the water;
- The daily amount of drinkable water ingested; and
- The fraction of time that the individual spends in the area serviced by that water supply
system. (Note that for screening level analyses, 100% of drinking water maybe
presumed to come from the contaminated source.)
Note that in estimated exposures associated with drinking water supplies, risk assessors
commonly assume that the drinking water undergoes at least a minimum level of treatment to
remove solids (i.e., particles in the water which are PB-HAPs or onto which PB-HAPs may
be absorbed). Therefore, the risk assessment commonly focuses on the dissolved
concentrations of PB-HAPs in drinking water sources.
Groundwater as a Source of Drinking Water
If site-specific circumstances suggest that groundwater may represent a potential concern (e.g., the
presence of extremely shallow aquifers used for drinking water purposes or a karst environment in
which the local surface water significantly affects the quality of ground water used as a drinking water
source), the TRIM.FaTE library includes a groundwater compartment that can be used to assess the
groundwater pathway. EPA's Human Health Risk Assessment Protocol for Hazardous Waste
Combustion Facilities(U) and Draft Technical Background Document for Soil Screening Guidance(l5}
discuss the methods for evaluating the groundwater pathway.
Ingestion of Fish. Factors that affect human exposure by ingestion of fish from a surface
water body include:
- Sediment and water COPC concentrations;
- The types of fish and shellfish consumed;
- The portion offish eaten (e.g., fillet only, fillet plus skin, whole body);
- The effect of food preparation techniques on concentrations of COPCs in the fish;
- Ingestion rates for the various fish and shellfish groups; and
- The fraction of dietary fish caught in the surface water body or bodies being evaluated.
(Note that for screening level analyses, 100 percent offish/shellfish is presumed to come
from the contaminated water body.)
Note that ingestion of contaminated groundwater generally is not a significant pathway of concern for air
toxics risk assessments because most air toxics that persist and may bioaccumulate tend to get bound up in soil and,
therefore, tend not to move readily into groundwater. However, if the groundwater pathway were a concern for a
specific study, it would be evaluated in generally the same way as the ingestion of surface water pathway (i.e., as a
drinking water source; however, depending on the circumstances, groundwater may or may not be treated to remove
particles prior to consumption).
April 2004 Page 20-9
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The types offish consumed will affect exposure because different types offish and shellfish
accumulate COPCs at different rates. For example, fatty fish tend to accumulate lipophilic
organic compounds more readily than lean fish. The amount offish consumed also affects
exposure because people who eat large amounts offish will tend to have higher exposures.
Fish consumption rates and the parts of the fish that are consumed can vary greatly,
depending on geographic region and social or cultural factors. Also, because all of a person's
dietary fish may not originate from the surface water body near the source of the PB-HAP,
the fraction of locally caught fish is also a variable for exposure.
20.4.2 Exposure Frequency
The specific exposure frequency will depend on how the exposure analysis is set up. For
example, a scenario-based analysis would specify one or more exposure frequencies for each
defined scenario. A typical screening-level exposure frequency is 350 days per year; this number
is based on the assumption that all people spend a minimum of two weeks at a location other
than the exposure scenario location selected for analysis (e.g., on vacation)/1'(5) However, many
activities vary on a weekly and/or seasonal basis. For example, recreational fishing is more
likely to occur on weekends than on weekdays, and most areas in the U.S. have limited fishing
and hunting seasons.
20.4.3 Exposure Duration
Exposure duration is the length of time over which exposure occurs (e.g., a lifetime or a
particular residence time). As noted in Section 20.3 above, choice of ED will depend on many
factors, including the purpose of the assessment or risk management decision, the tier of analysis,
and the particular effect(s) of concern. There are no universally established ED values for risk
assessments because different EDs may be appropriate in different situations. Some commonly
used EDs include:
• Lifetime (70 years) - generally used for screening-level analyses;
• High-end number of years a person resides in a single location (about 30 years);
• Median number of years a person resides in a single location (about 9-10 years); and
• Seven years (ten percent of an assumed lifetime) - sometimes used for noncancer effects.
Although a source may remain in the same location for more than 70 years, and a person may
have a lifetime of exposure to emissions from that source, U.S. Bureau of the Census data on
population mobility indicate that many Americans do not always remain in the same area for
their assumed 70-year lifetime.(16) An estimate of the number of years that a person is likely to
spend in one area can be derived from information about mobility rate and median time in a
residence.
Analysts may use long EDs when conducting simple screening analyses performed to determine
if more complex analyses are necessary. The rationale for use of such EDs is that if risks are not
of concern when the exposure duration is long, then they would not be of concern given other,
shorter, exposure durations. (Typically analysts also make other conservative or "health-
protective" assumptions when conducting this type of screening analysis.) Analysts may use
specific EDs particular to the legal framework for the assessment. For example, the residual risk
section of the Clean Air Act (CAA) references an Agency rulemaking for which one prominent
April 2004 Page 20-10
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risk metric considered a 70-year exposure duration (see CAA section 1 12(f)(2) and 54 Federal
Register 38044).
The type of risk metric being derived also influences the consideration of exposure duration. For
example, when the analyst wants to describe central tendency risk based on a deterministic
analysis, s/he typically will use mean or median exposure assumptions to calculate risk.(c)
Similarly, when the analyst wants to describe high-end risk based on a deterministic analysis,
s/he may use high-end exposure assumptions or a combination of central tendency and high-end
exposure assumptions that provide a reasonable estimate of the individual risk for those persons
at the upper end of the risk distribution. As explained in EPA's Policy on Risk
Characterization:^ "Conceptually, high-end exposure means exposure above about the 90th
percentile of the population distribution, but not higher than the individual in the population who
has the highest exposure. "(d) When the analyst wants to conduct a probabilistic analysis of risk,
s/he typically will use or develop a distribution of exposure durations from the available data
(e.g., see EP 'A' 's Exposure Factors Handbook, Part III; Tables 15-164, 15-166, 15-167, and 15-
The areal extent of the impacted area(s) may also be a consideration. If a source of concern
occurs in the majority of communities, then it is possible that individuals may be exposed to the
source for a longer period of time than one might predict using standard estimates of exposure
duration. In this case, the analyst might assume that even though an individual changes
residence, the individual still would be exposed to the source of concern, and thus the
individual's exposure duration would be greater than typically anticipated. Such an analysis
must consider whether the concentration of the pollutant at the multiple locations of exposure
would be equivalent. Because location-specific parameters such as meteorological conditions,
distance from the source, and the presence of certain pathways of exposure (e.g., surface water,
home-grown produce) may vary considerably by geographic area, the analyst likely will have to
estimate exposure concentrations for each geographic location or community of interest.
Similarly, if a single source impacts a large geographic area, then it is possible that national
estimates of population mobility will not adequately capture an individual's potential duration of
exposure. That is, an individual may move from one point of exposure associated with a
particular source to another point of exposure associated with that same source. For example,
data indicate 29 percent of home buyers move less than five miles to a new home (Table 15-171
in EPA's Exposure Factors Handbook, Part 7//10)). Similar to the caution expressed above, the
concentrations of pollutants within an area impacted by a single source may vary considerably.
The analysis should reasonably account for such situations.
The central tendency estimate of adult exposure duration commonly used in risk assessments is 9 years
(Section 15.4.3 and Table 15-174 in EPA's Exposure Factors Handbook, Part HI). This estimate is a median
value based on national residential occupancy data for the general population. This estimate may not be appropriate
in certain situations, such as when population-specific data exist or when the analyst is evaluating a specific sub-
population that is expected to differ from the general population (e.g., farm families).
As described in Section 20.4, estimation of high-end exposure will sometimes involve setting exposure
duration at its high-end value. The high-end estimate of adult exposure duration typically used in risk assessments is
30 years (Section 15.4.3 and Table 15-174 in EPA's Exposure Factors Handbook, Part HI), although this may
vary for specific sub-populations.
April 2004 Page 20-11
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The persistence of the source-associated contamination may also be an important consideration
in the exposure duration for ingestion pathway exposure assessment. For example, the analyst
should not automatically assume that the exposure duration can be no greater than the operating
life of the source. Persistent pollutants may remain in the environment (e.g., soils and sediments)
for years after the primary source is discontinued. Nevertheless, in certain cases, once the source
of exposure stops, the pollutant concentrations in the affected media may diminish. Particularly
in more refined assessments, the exposure concentration may reflect any expected variations in
media or food concentrations over time.
When evaluating the risk of noncancer health effects from ingestion exposures (i.e., calculating
hazard quotients for ingestion exposures), we do not average pollutant dose over the lifetime of
an individual as we do when calculating carcinogenic risk. Rather, when calculating hazard
quotients for ingestion exposures, we average the dose over an averaging time equivalent to only
the period of exposure (i.e., we calculate an average daily dose rather than a lifetime average
daily dose). Consequently, the values for exposure duration and averaging time are the same,
and mathematically cancel each other out. Nevertheless, when calculating average daily dose,
the analyst must still consider exposure duration when selecting and computing food and media
intakes for use in the dose equation. EPA typically considers exposures of seven years or greater
as chronic exposures. Food and media intakes that represent time-weighted averages over a
seven-year period are reasonable for evaluating chronic non-cancer health effects. Durations as
short as one year are also commonly used, particularly in screening assessments, and for
childhood evaluations where intake on a per body weight basis may rapidly change from
year to year.
20.4.4 Body Weight
The choice of body weight for use in the exposure assessment depends on the definition of the
population group at potential risk. Because children have lower body weights, typical ingestion
exposures per unit of body weight, such as for soil, milk, and fruits, tend to be higher for
children. If a lifetime exposure duration (or an exposure duration over the childhood and adult
years) is being evaluated, it needs to be based on differing values for the different age groups. If
a less than a lifetime exposure estimate is being evaluated, it is important to include the
children's age group in the specific scenarios or cohorts used. EPA's Exposure Factors
Handbook and Child-Specific Exposure Factors Handbook provide age-specific values for
body weight and consumption rate per unit body weight.
20.5 Calculating Averaging Time Value
When evaluating exposure for the purposes of assessing hazard (vs. predicting cancer risk),
intakes are calculated by averaging intakes over the period of exposure (i.e., subchronic or
chronic durations) and result in average daily doses or ADDs for the duration of interest. For
evaluation of cancer risks, potential dose is calculated as the average daily dose over a lifetime
(i.e., chronic daily intakes, also called lifetime average daily doses or LADDs). The approach for
carcinogens is based on the premise that risk is proportional to total lifetime dose (i.e., a high
dose received over a short period of time is equivalent to a corresponding low dose spread over a
lifetime)/18' The basis for this approach becomes less strong as the exposures in question
become more intense but less frequent, especially when there is evidence that the agent has
shown age-related variations in carcinogenic potency, or a nonlinear dose-response relationship.
April 2004 Page 20-12
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In some cases, therefore, it may be necessary to consult a toxicologist to assess the level of
uncertainty associated with the exposure assessment for carcinogens.
Note that, even when the exposure of interest is a full lifetime, chronic hazards are generally
calculated separately for chronic exposures to age groups that differ substantially with regard to
pertinent exposure factors (e.g., ingestion rate or body weight) and are not combined (i.e., usually
the oral route hazards calculated for children are not added to the hazards posed to adults to
represent a "lifetime hazard"). Rather, both hazard quotients/indices are presented as chronic
hazard metrics relevant to the two groups. When assessing carcinogenic risks for a lifetime
exposure, on the other hand, cancer risk estimates are usually added across different age groups,
since the risk received over discrete periods of time (e.g., as a child, as a young adult, as an older
adult) are each considered to be fractions of the risk associated with a full lifetime of exposure.
Note that in calculating LADDs, it is essential to account for differences in the values of different
intake variables (e.g., body weight, consumption rate) at different ages.
20.6 Combining Exposure Estimates Across Pathways
A given population may receive exposure to an individual chemical from several different
exposure pathways. For example, individuals may receive exposure via inhalation of the
chemical in the air and via ingestion of surface water and fish that have become contaminated
through deposition. The specific exposure scenarios or cohorts defined for the analysis may
include more than one pathway. The corresponding intake variables used in the analysis may
need to account for the number of pathways over which exposure will be combined. For
example, to develop a high-end estimate for a scenario that includes inhalation, ingestion of soil,
and ingestion offish, it may be necessary to combine high-end exposure assumptions for all
pathways. In other cases, it maybe more appropriate combine high-end exposure assumptions
for particular pathways with more central-tendency assumptions for others. Otherwise, the
estimate may represent an extreme situation in which the simulated behavior is assumed to result
in high exposures via all pathways.
Two steps are required to determine whether intake estimates should be combined for a single
scenario:
• Identify reasonable exposure pathway combinations. Identify exposure pathways that
have the potential to expose the same individual, cohort, or subpopulation at the key exposure
areas evaluated in the exposure assessment, making sure to consider areas of highest
exposure for each pathway. For each pathway, the intake estimates have been developed for
a particular exposure area and time period; they do not necessarily apply to other locations or
time periods. Hence, if two pathways do not affect the same individual, cohort, or
subpopulation, neither pathway's exposure estimate affects the other, and exposures should
not be combined.
• Examine whether it is likely that the same individuals would consistently face a
reasonable central tendency or high-end exposure by more than one pathway. Once
reasonable exposure pathway combinations have been identified, it is necessary to examine
whether it is likely that the same individuals would consistently face central tendency or high-
end exposure conditions. As noted in Section 20.4 above, the exposure estimate for each
exposure pathway includes many conservative estimates. Also, some of the exposure
April 2004 Page 20-13
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parameters are not completely predictable in space and/or time (e.g., the maximum
downwind concentration may shift compass direction). For real-world situations in which
contaminant concentrations vary over time and space, the same individual or cohort may or
may not experience central-tendency or high-end exposure conditions for more than one
pathway over the same period of time. Thus, it is important to clearly explain why the key
assumptions chosen for more than one pathway for an individual, subpopulation, or cohort
are set at central tendency and/or high-end exposure estimates. (Note that an important goal
in the analysis of high-end receptors is to identify exposures that are in the high-end of the
range - usually higher than the 90th percentile exposure - but not higher than the highest
exposure in the population.)
20.7 Exposure Models
Exposure models have been developed that automate the calculation of chemical intake. They
may simply calculate exposure for a set of individual scenarios, or they may draw upon activity
pattern and/or dietary survey databases to characterize cohort exposure within a population.
Three exposure models are described below.
California Total Exposure Model for Hazardous Waste Sites (CalTOX)
As described previously in Part II, Chapter 9, the California Environmental Protection Agency
funded the development of the CalTOX program.(19) CalTOX has been developed as a set of
spreadsheet models and spreadsheet data sets to assist in assessing human exposures and defining
soil clean-up levels at uncontrolled hazardous wastes sites. CalTOX addresses contaminated
soils and the contamination of adjacent air, surface water, sediments, and ground water. The
modeling components of CalTOX include exposure scenario models. The exposure models
encompass twenty-three exposure pathways. The exposure assessment process consists of
relating pollutant concentrations in the multimedia model compartments to pollutant
concentrations in the media with which a human population has contact (e.g., personal air, tap
water, foods, household dusts, soils). The temporal resolution is either daily for inhalation and
dermal exposure or annual for ingestion. The aggregation period is variable, depending on the
duration of residence at a single location. The spatial resolution and modeling domain are user-
specified, but generally encompass some vicinity around the waste site of interest. Activity data,
such as inhalation, ingestion, and dermal contact rates, are derived from EPA's Exposure Factors
Handbook.^
TRIM.Expo
As discussed in Chapter 18, TRIM.Expo is the exposure component of the TRIM modeling
system. The ingestion component of TRIM.Expo (TRIM.ExpoIngestion) is designed to take input
values from TRIM.FaTE, but may also be operated independently with inputs from measurement
studies or alternative models. TRIM.ExpoIngestion will employ a scenario-based approach, based
on that used in the 3MRA modeling system, in its initial version. Information about the ingestion
component of TRIM.Expo is available on EPA's Fate, Exposure and Risk Analysis (FERA) web
site: http://www.epa.gov/ttn/fera.
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Stochastic Human Exposure and Dose Simulation Model (SHEDS)
The Stochastic Human Exposure and Dose Simulation (SHEDS) Model(20) is a probabilistic,
physically-based model that simulates aggregate exposure and dose for population cohorts and
multimedia pollutants of interest. It is being developed by EPA's National Exposure Research
Laboratory (http://www.epa.gov/nerlpage/). At present the model is applied to assess children's
exposures to pesticides (SHEDS-Pesticides) and population exposures to particulate matter
(SHEDS-PM).
SHEDS-Pesticides focuses on children's aggregate population exposure to pesticides. Activity
data are selected from daily sequential time/location/activity diaries from surveys contained in
EPA's Consolidated Human Activity Database (CHAD).(8) For each individual, SHEDS-
Pesticides constructs daily exposure and dose time profiles for the inhalation, dietary and non-
dietary ingestion, and dermal contact exposure routes, and then aggregates the dose profiles
across routes. A pharmacokinetic component has been incorporated to predict pollutant or
metabolite concentrations in the blood compartment or eliminated urine. Exposure and dose
metrics of interest (e.g., peak, time-averaged, time-integrated) are extracted from the individual's
profiles. Two-stage Monte-Carlo sampling is applied to predict the range and distribution of
aggregate doses within the specified population and identify the uncertainties associated with
percentiles of interest.
SHEDS-Pesticides is currently being refined to characterize both aggregate and cumulative dose
associated with human exposure (i.e., for both adults and children) to a variety of environmental
pollutants in addition to pesticides. SHEDS-Pesticides will eventually be expanded to include
source-to-concentration (i.e., fate and transport) models and more complete exposure-to-dose
models (i.e., pharmacokinetic or dosimetric models).
SHEDS-PM estimates the population distribution of particulate matter (PM) exposure by
sampling from distributions of ambient PM concentrations, distributions of emission strengths
for indoor sources of PM (e.g., cigarette smoking and cooking), and distributions of mass-
balance parameters (e.g., air exchange rate, penetration rate, deposition rate). A steady-state
mass balance equation is used to calculate PM concentrations for the residential and other
microenvironments. Additional model inputs include demographic and human activity pattern
data from the National Human Activity Pattern Survey (NHAPS). Output from the SHEDS-PM
model includes distributions of PM exposures in various microenvironments (e.g., in the home,
in vehicles, outdoors) and the relative contributions of these various microenvironments to the
total exposure.
April 2004 Page 20-15
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Sites Part I: Executive Summary. UCRL-CR-11456, Pt. I. 1993b. CalTOX, a Multimedia
Total-Exposure Model for Hazardous Wastes Sites Part II: the Dynamic Multimedia
Transport and Transformation Model. UCRL-CR-111456, Pt. II. 1993c. CalTOX, a
Multimedia Total-Exposure Model for Hazardous Wastes Sites Part III: The Multiple-
Pathway Exposure Model. UCRL-CR-111456, Pt. in. Livermore, CA: Lawrence Livermore
National Laboratory.
20. Zartarian V.G., Ozkaynak H., Burke J.M., Zufall M.J., Rigas M.L., and Furtaw Jr. E.J. 2000.
A modeling framework for estimating children's residential exposure and dose to
chlorpyrifos via dermal residue contact and non-dietary ingestion. Environmental Health
Perspectives 108:505-514.
April 2004 Page 20-18
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Chapter 21 Ingestion Toxicity Assessment
Table of Contents
21.1 Introduction 1
21.2 Hazard Identification 2
21.3 Predictive Approach for Cancer Effects 2
21.3.1 Determining the Point of Departure (POD) 2
21.3.2 Deriving the Human Equivalent Dose 2
21.3.3 Extrapolating from POD to Derive the Oral Cancer Slope Factor 3_
21.4 Dose-response Assessment for Derivation of a Reference Dose 3_
21.5 Sources of Human Health Reference Values for Risk Assessment 4
References 5
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21.1 Introduction
As described previously in Chapter 12, the purpose of the toxicity assessment is to weigh
available evidence regarding the potential for toxicity in exposed individuals (hazard
identification) and to quantify the
toxicity by deriving an appropriate
dose-response value (dose-
response assessment). Toxicity
assessment is the second part of
the general risk equation. The
Risk = / (metric of exposure, measure of toxicity)
Toxicity Assessment is a Two-Step Process:
Hazard Identification -What types of effects does the
chemical cause? Under what circumstances?
toxicity assessment is 0 _. . , TT , , . ,, , . ,
,. 2. Dose-response Assessment - How potent is the chemical
accomplished in two steps: as a carcinogen and/or for noncancer effects?
hazard identification and dose- v s
response assessment. Although
the toxicity assessment is an integral and important part of the overall air toxics risk assessment,
this is usually accomplished prior to the risk assessment. EPA has completed the toxicity
assessment for all HAPs and has made available the resulting toxicity information and dose-
response values, which have undergone extensive peer review (see Appendix C).(a)
This chapter focuses on toxicity assessment for the ingestion (oral) pathway. Dermal toxicity
assessment is described in detail in several EPA guidance documents.0' The ingestion pathway
uses the same general types of studies, hazard and dose-response information, and dose-response
methods to assess toxicity as those used for the inhalation pathway (see Chapter 12). The
discussion in this chapter focuses on the unique features of toxicity assessment for the oral
pathway.
/" "\
Ingestion Dose-Response Values(a)
Oral Cancer Slope Factor (CSF): An upper bound, approximating a 95 percent confidence limit, on
the increased cancer risk from a lifetime exposure to an agent For ingestion, this estimate is usually
expressed in units of amount of risk per amount of intake and is written as risk per mg/kg-day or
simply (mg/kg-d)"1.
Reference Dose (RfD): An estimate (with uncertainty spanning perhaps an order of magnitude) of a
daily oral exposure to the human population (including sensitive sub-populations) that is likely to be
without an appreciable risk of deleterious effects during a lifetime. Generally used in EPA's
noncancer health assessments. RfDs are usually given in units of intake per day on a body weight
basis (written as mg/kg-d).
(a)The phrase "dose-response" is used generally here and elsewhere in the document. EPA's values for ingestion,
however, are related to oral intake rather than dose. Consideration of the relationship between exposure
concentration, dose, and dosimetry (what happens to a chemical in the body once it is ingested) may be
considered, depending on data availability in the derivation of these values. /
See http://www.epa.gov/ttn/atw/toxsource/summary.html for an up-to-date list of dose-response values.
April 2004 Page 21-1
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21.2 Hazard Identification
The hazard identification process for the ingestion pathway is identical to that for the inhalation
pathway, although the specific toxic effects of concern and details of the toxicity studies are
derived from feeding a chemical to animals (either in food or drinking water) rather than on
having the animals inhale the chemical. As with inhalation, the hazard identification step
includes consideration of various types of studies (e.g., feeding, in vitro, etc.) and the resulting
weight of evidence with regard to potential for carcinogenicity and identification of critical
effects. See Part n, Chapter 12, for information on the hazard identification step.
21.3 Predictive Approach for Cancer Effects
The approach to dose-response assessment for cancer effects is identical to that for the inhalation
pathway discussed in Chapter 12, including:
• Determination of the point of departure (POD);
• Duration adjustment of the POD to a continuous exposure;
• Extrapolation of an animal study POD into its corresponding Human Equivalent Dose
(PODHED); and
• Low-dose extrapolation from the PODHED to lower doses for the purposes of deriving the
oral cancer risk estimate.
As with inhalation, the first three steps are also performed in the derivation of reference values
for ingestion, such as the oral RfD. In addition to the steps shown above, the derivation of RfDs
are followed by the application of uncertainty factors (see Section 21.4). Additionally, the use of
tools such as pharmacokinetic modeling, which go beyond these default approaches, may
facilitate the accomplishment of several of these steps.
21.3.1 Determining the Point of Departure (POD)
The process for determining the POD for ingestion exposures is identical to that for inhalation
exposures. The POD may be the no-observed-adverse-effect level (NOAEL) or lowest-observed-
adverse-effect level (LOAEL), or it may be a benchmark dose (BMD) for noncancer effects.(b)
21.3.2 Deriving the Human Equivalent Dose
The optimal approach for extrapolating from an animal study to a human dose-response
relationship is to use Physiologically Based Pharmacokinetic (PBPK)(c) modeling. When such a
model us used, the duration adjustment step is incorporated into that model. Otherwise, any
duration adjustment, if necessary (e.g., when the exposure is not via daily feed), would be
accomplished by deriving an average daily dose for the exposure period (e.g., two years in an
animal cancer bioassay).
Note that the corresponding value for inhalation exposures is the benchmark concentration (BMC).
°A model that estimates the dose to a target tissue or organ by taking into account the rate of absorption into
the body, distribution among target organs and tissues, metabolism, and excretion.
April 2004 Page 21-2
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For purposes of cancer assessment, an animal to human body weight-based scaling factor is
applied to the oral study POD (duration-adjusted if applicable) to extrapolate to a human
equivalent oral exposure/2' The default scaling factor is based on the body mass raised to the 3/4
power of the test animals relative to humans. This step stems from the consideration of various
studies of the species differences in toxicity of certain compounds, including data collected on
chemotherapeutic agents.(3) These data served as the principal basis for the use of a body surface
area or metabolic rate scaling as the default method in cancer risk assessments. Empirically, the
best estimate of surface area scaling is BW2/3 and for metabolic rate scaling is BW3/4.(4) These
findings reflect general expectations of more rapid distribution, clearance, and metabolism by
smaller animals.
In the case of the RfD, a scaling factor is not currently applied. Instead, the interspecies
uncertainty factor is intended to account for potential differences in sensitivity of humans
compared to the test animal, including this consideration.(d)
A PBPK model can accommodate adjustments for metabolic rate as well as other species-related
dosimetric variables such as liver perfusion rates. The model therefore provides a more accurate
estimate of steady-state target site concentrations than use of default methods. EPA's preferred
approach for calculating a HED for oral exposures is to use a chemical-specific PBPK model
parameterized for the animal species and body regions (e.g., of the gastrointestinal tract) involved
in the toxicity.
21.3.3 Extrapolating from POD to Derive the Oral Cancer Slope Factor
As with inhalation, extrapolation from the PODHED to lower doses is usually necessary and, in the
absence of a data set rich enough to support a biologically based model (e.g., a PBPK model), is
conducted using linear extrapolation or a nonlinear extrapolation using a Reference Dose
approach.
The Cancer Slope Factor (CSF) for oral exposures is derived in a similar way as the unit risk
estimate for inhalation (URE) (see Chapter 12). The CSF is derived using the upper bound
estimate of risk. In other words, the true risk to humans, while not identifiable, is not likely to
exceed the upper-bound estimate (the CSF). The CSF is presented as the risk of cancer per mg of
intake of the substance per kg body weight per day ([mg/kg-day]^).
21.4 Dose-response Assessment for Derivation of a Reference Dose
The oral reference dose is expressed as a chronic dietary intake level (in units of mg of the
substance per kilogram body weight per day, or mg/kg-day) for the human population (including
sensitive sub-populations) that is likely to be without an appreciable risk of deleterious effects
during a lifetime. In other words, exposures at or below the RfD will probably not cause adverse
health effects, even to sensitive sub-populations. While the RfD is routinely employed for
At the time of publication, an Agency activity is underway to "harmonize" the cancer assessment and RfD
development methods with regard to the method employed for interspecies scaling, which may result in the use of
body weight scaling in the development of the RfD.
April 2004 Page 21-3
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noncancer effects, it maybe inclusive of cancer for those pollutants for which a nonlinear (e.g.,
threshold) mode of action has been demonstrated consistent with the Cancer Guidelines.
As with the derivation of an inhalation reference concentration, the reference dose is derived by
dividing the POD by one or more uncertainty factors (UFs). EPA includes with each RfD a
statement of high, medium, or low confidence based on the completeness of the database for that
substance. High confidence RfDs are considered less likely to change substantially with the
collection of additional information, while low confidence RfDs may be especially vulnerable to
change .(5)
The UFs are applied to account for recognized uncertainties in the extrapolations from the
experimental data conditions to an estimate appropriate to the assumed human scenario. As with
the derivation of RfCs, a UF of 10, 3, or 1 is applied for each of the following extrapolations:
• Animal to human;
• Human to exposed sensitive human populations;
• Subchronic to chronic;
• LOAEL to NOAEL; and
• Incomplete to complete database.
The UFs are generally an order of magnitude (10), although consideration of available
information on the chemical may result in the use of reduced UFs for RfDs (3 or 1). It is noted
that as there is currently no default dosimetric adjustment for the oral route. The uncertainty
factor for extrapolation from animal to human data is usually the full 10, as compared to the
reduced factor of 3, routinely used for RfCs which employs an interspecies dosimetric
adjustment. Additional discussion on the application of uncertainty factors is provided in Section
12.4.3.
21.5 Sources of Human Health Reference Values for Risk Assessment
Appendix C provides a current listing of chronic oral dose-response values (i.e., RfDs and CSFs)
for HAPs. Chapter 12 describes additional sources of human health reference values for risk
assessment for the ingestion route.
April 2004 Page 21-4
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References
1. U.S. Environmental Protection Agency. 2001. Risk Assessment Guidance for Superfund
Volume I: Human Health Evaluation Manual (Part E, Supplemental Guidance for Dermal
Risk Assessment) Interim Review Draft - For Public Comment, Office of Emergency and
Remedial Response, Washington, D.C. EPA/540/R/99/005, available at:
http ://www. epa. gov/superfund/programs/risk/ragse/index .htm.
U.S. Environmental Protection Agency. 1992. Dermal Exposure Assessment: Principles and
Applications. Office of Health and Environmental Assessment. EPA/600/6-88/005C.
2. U.S. Environmental Protection Agency. 1999. Guidelines for Carcinogen Risk Assessment.
Review Draft. Risk Assessment Forum, Washington, DC. NCEA-F-0644.
U.S. Environmental Protection Agency. 1986. Guidelines for Carcinogen Risk Assessment.
Federal Register 51(185):33992-43003.
U.S. Environmental Protection Agency. 2003. Draft Final Guidelines for Carcinogen Risk
Assessment (External Review Draft), Risk Assessment Forum, Washington, DC,
NCEA-F-0644A.
These documents are available at http://cfpub.epa.gov/ncea/raf/rafguid.htm.
3. Freireich, E.J., Gehan, E.A., Rail, D.P., et al. 1966. "Quantitative comparison of toxicity
anticancer agents in mouse, rat, hamster, dog, monkey, and man." Cancer Chemother Report
50:210:244.
4. U.S. Environmental Protection Agency. 1992. Request for Comments on Draft Report of
Cross-species Scaling Factor for Cancer Risk Assessment. Federal Register 57:24152.
5. U.S. Environmental Protection Agency. 2002. A Review of the Reference Dose and
Reference Concentration Process. Risk Assessment Forum, Washington, DC.
EPA/630/P-02/002F. Available at:
http ://cfpub. epa. gov/ncea/raf/recordisplay.cfm?deid=553 65.
April 2004 Page 21-5
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Chapter 22 Multipathway Risk Characterization
Table of Contents
22.1 Introduction I
22.2 Cancer Risk Estimates 2
22.2.1 Characterizing Individual Pollutant Ingestion Risk - Scenario Approach 2
22.2.2 Characterizing Risk from Exposure to Multiple Pollutants - Scenario Approach 3.
22.2.3 Combining Risk Estimates across Multiple Ingestion Pathways - Scenario Approach . . 4
22.2.4 Evaluating Risk Estimates from Inhalation and Ingestion Exposures 4
22.3 Noncancer Hazard 4
22.3.1 Characterizing Individual Pollutant Hazard - Scenario Approach 5
22.3.2 Multiple Pollutant Hazard 6
22.3.3 Evaluating Hazard Estimates From Inhalation and Ingestion Exposures 6
22.4 Interpretation and Presentation of Risks/Hazards 7
References 8
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22.1 Introduction
The last component of risk assessment, Risk Characterization, integrates the information from
the exposure assessment (Chapter 20) and toxicity assessment (Chapter 21), using a combination
of qualitative information, quantitative information, and a discussion of uncertainty/1' Risk
assessors should present the risk characterization and its components so that they are transparent,
clear, and consistent with EPA guidance and policy, and thus components should support the
conclusion that the analysis is reasonably conservative enough for its intended purpose. The risk
summary and risk conclusions must be complete, informative, and useful for decision-makers.
Major uncertainties associated with determining the nature and extent of the risk should be
identified and discussed.
Risk characterization for the multipathway risk assessment is performed using the same approach
as described for the inhalation pathway (Chapter 13), except that risks for both inhalation and
ingestion are considered. As for inhalation-only analyses, most multipathway risk assessments
for air toxics will focus on estimating individual risk and hazard. This chapter focuses on the
unique features of risk characterization for multipathway analyses. This chapter also assumes
that the inhalation risk characterization has been completed, as described in Chapter 13.
/"x
Steps in a Multipathway Risk Characterization
1. Organize outputs of the ingestion exposure and toxicity assessments.
2. Derive cancer risk estimates and noncancer hazard quotients for each pollutant in each pathway.
3. Derive multiple pollutant cancer risk estimates and noncancer hazard indices for each pathway.
4. In consideration of target organ, develop target organ specific hazard indices, if appropriate.
5. As appropriate, combine information on cancer risk and noncancer hazard from the ingestion
analysis with appropriate risk information from the inhalation analysis to derive a total estimate of
cancer risk and noncancer hazard.
6. Identify key features and assumptions of exposure and toxicity assessments.
7. Assess and characterize key uncertainties associated with the assessment.
8. Consider additional relevant information (e.g., related studies).
The risk characterization should be written consistent with EPA guidance and policy, including a risk
summary and risk conclusions that are complete, informative, and useful for decision-makers, and
which clearly identify and discuss the major uncertainties associated with determining the nature and
.extent of the risk.
The general process for characterizing cancer risks and noncancer hazards for multipathway
analyses can be thought of as developing information to fill in a matrix similar to that shown in
Exhibit 22-1 (which presents cancer risks for a group of chemicals; a similar matrix can be
developed to present noncancer hazards [see Exhibit 22-2]). A table like this would be
developed for each of the types of receptors being evaluated in the study area (e.g., adult farmer -
high-end exposure; adult farmer - central tendency exposures; child resident - high-end
exposure). This type of presentation format shows the total risk by chemical, pathway, and
across all pathways. In addition, this format allows one to quickly identify both the individual
chemicals and pathways that contribute most to the total risk estimate. The following sections
describe how to develop the numbers to fill in such a table for both multipathway cancer risk
estimates (Section 22.2) and multipathway noncancer hazards (Section 22.3). The focus of this
April 2004 Page 22-1
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chapter is on developing risks and hazards for the ingestion pathways; procedures for developing
inhalation risk estimates have previously been provided in Chapter 13.
Exhibit 22-1. Example Matrix for Estimating Excess Cancer Risks for Multiple Chemical
Exposure through Multiple Ingestion Pathways for a Particular Exposure Scenario
Chemical 1
Chemical 2
Chemical 3
Chemical 4
Cumulative
Ingestion
Pathway
Risk
Estimate (a)
Pathway 1
(Vegetable
Ingestion Risk
Estimate)(a)
1 x IQ-6
4 x lO'7
4 x lO'9
9 x lO'7
3 x lO'6
Pathway 2
(Fish
Ingestion Risk
Estimate)(a)
3 x lO'4
4 x lO'6
7 x lO'7
1 x lO'6
3 x lO'4
Pathway 3
(Egg Ingestion
Risk
Estimate)(a)
9 x lO'8
4 x lO'8
3 x lO'8
6 x lO'7
7 x lO'7
Pathway 4
(Beef
Ingestion Risk
Estimate)(a)
8 x lO'5
4 x lO'7
9 x lO'9
6 x lO'7
8 x lO'5
Aggregate
Chemical
Ingestion
Risk Estimate (a)
4 x lO'4
5 x lO'6
8 x lO'7
3 x lO'6
4 x lO'4
(a) Standard rules for rounding apply which will commonly lead to an answer of one significant figure
in both risk and hazard estimates. For presentation purposes, hazard quotients (and hazard indices)
and cancer risk estimates are usually reported as one significant figure.
22.2 Cancer Risk Estimates
As discussed in detail in Chapter 13, estimated individual cancer risk is expressed as the
probability that a person will develop cancer as a result of the estimated exposure over a lifetime.
This predicted risk is the incremental risk of cancer from the exposure being analyzed, which
are in addition to other risks due to any other factors (e.g., smoking). Due to default assumptions
in their derivation, cancer slope factors (CSFs) are generally considered to be "plausible upper-
bound" estimates, regardless of whether they are based on statistical upper bounds or best fits.
As noted in Chapter 13, risks may be estimated for both the central tendency (average exposure)
case and for the high-end (exposure that is expected to occur in the upper range of the
distribution) case, or probabilistic techniques can be used to develop a distribution of estimated
risks.
22.2.1 Characterizing Individual Pollutant Ingestion Risk - Scenario Approach
The first step in characterizing individual pollutant risk for an exposure scenario (e.g., a
recreational fisher) is to quantify risk for each ingestion exposure pathway being evaluated. In
this step, cancer risks for individual pollutants are estimated by multiplying the estimate of the
lifetime average daily dose (LADD) for each ingestion exposure pathway by the appropriate CSF
to estimate the potential incremental cancer risk:
Risk= LADD x CSF
(Equation 22-1)
April 2004
Page 22-2
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where:
Risk = Individual cancer risk (expressed as an upper-bound risk of contracting cancer
over a lifetime) for each pollutant via the ingestion pathway being evaluated
(unitless);
LADD = Lifetime Average Daily Dose for the pollutant via the ingestion pathway being
evaluated (mg/kg-d); and
CSF = Cancer Slope Factor for the pollutant via the ingestion pathway being
evaluated [(mg/kg-d)"1]
Estimates of cancer risk are usually expressed as a probability represented in scientific notation
as a negative exponent of 10. For example, an additional risk of contracting cancer of 1 chance
in 10,000 (or one additional person in 10,000) is written as IxlO"4. Because CSFs are typically
upper-bound estimates, actual risks maybe lower than predicted (see Chapter 12) - note that the
true value of the risk is unknown and may be as low as zero.(2) These statistical projections of
hypothetical risk are intended as screening tools for risk managers and cannot be used to make
realistic predictions of biological effects.
Risks are generally evaluated initially for individuals within the potentially exposed population.
Population risks for the exposed population may also be estimated, which may be useful in
estimating potential economic costs and benefits from risk reduction. Sensitive subpopulations
should also be considered, when possible. Estimates of incidence also are possible, although
there are some caveats associated with these measures (see Chapter 13).
For carcinogens being assessed based on the assumption of nonlinear dose-response, for which a
reference dose (RfD) was derived that considers cancer as well as other effects, the hazard
quotient approach will be appropriate for risk characterization (see Section 22.3).
22.2.2 Characterizing Risk from Exposure to Multiple Pollutants - Scenario Approach
For each exposure pathway of a scenario, exposure maybe to multiple chemicals at the same
time rather than a single chemical; however, CSFs are usually available only for individual
compounds within a mixture. Consequently, a component-by-component approach is usually
employed.(3) The following equation estimates the predicted cumulative incremental individual
cancer risk from multiple substances for a single exposure pathway, assuming additive effects
from simultaneous exposures to several carcinogens:
RJSkT = Risk., + Risk2 + .... + Risk; (Equation 22-2)
where:
RiskT = Cumulative individual ingestion cancer risk (expressed as an upper-bound risk of
contracting cancer over a lifetime); and
Risk; = Individual ingestion risk estimate for the ith substance.
In screening-level assessments of carcinogens for which there is an assumption of a linear dose-
response relationship, the cancer risks predicted for individual chemicals may be added to
estimate cumulative cancer risk for each pathway. This approach is based on an assumption that
April 2004 Page 22-3
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the risks associated with individual chemicals in the mixture are additive. In more refined
assessments, the chemicals being assessed may be evaluated to determine whether effects from
multiple chemicals are synergistic (greater than additive) or antagonistic (less than additive),
although sufficient data for this evaluation are usually lacking. In those cases where CSFs are
available for a chemical mixture of concern, risk characterization can be conducted on the
mixture using the same procedures used for a single compound.
For carcinogens being assessed based on the
assumption of nonlinear dose-response, for which an
RfD considering cancer as well as other effects has
been derived, the hazard quotient approach will be
appropriate (see Section 22.3).
22.2.3 Combining Risk Estimates across Multiple
Ingestion Pathways - Scenario Approach
Aggregate vs. Cumulative Risk
Aggregate risk refers to risk attributed to a
single chemical across multiple pathways/routes
Cumulative risk refers to risk attributed to
simultaneous exposure to multiple chemicals via
, a single or multiple pathways/routes
To evaluate risks associated with the aggregate
exposure across multiple pathways of a given scenario, the individual pollutant cancer risk
estimates may be summed for each chemical across the multiple ingestion pathways assessed.
Additionally, a cumulative multi-pathway risk estimate may be derived by summing cumulative
(multiple pollutant) cancer risk estimates across the multiple ingestion pathways.
22.2.4 Evaluating Risk Estimates from Inhalation and Ingestion Exposures
Depending on the ingestion scenario, the inhalation pathway will also have been assessed. In
such cases, the inhalation exposures must be presented along with the ingestion exposures to
provide an overall estimate of risk across the multiple pathways. When there is a compatibility
in the exposure scenarios, inhalation and ingestion risk estimates can be combined. Essentially,
an additional column for inhalation can be added to Exhibit 22-1 to achieve this result.
Regardless, when both routes are assessed, risk estimates for both routes of exposure should be
presented, along with descriptions regarding the populations assessed for all pathways and routes,
thereby clarifying any differences in populations.
It is important to note, however, that the methods and assumptions used to derive the inhalation
and ingestion risks may not always yield compatible exposure scenarios. This is particularly
important when population-level (versus individual) risk estimates are being developed. For
example, a scenario-based ingestion exposure assessment will not be easily amenable to
producing estimates of numbers of people at different risk levels, while a population-based
inhalation assessment may be more appropriate. In addition, it would generally not be
appropriate to add an inhalation risk that presumes a 70-year exposure duration with an ingestion
pathway that presumes a 30-year exposure duration. Any matching of exposure durations among
pathways in a multipathway assessment should be carefully considered.
22.3 Noncancer Hazard
For noncancer effects (as well as carcinogens being assessed based on the assumption of
nonlinear dose-response), ingestion exposure concentrations are compared to RfDs, which are
estimates (with uncertainty spanning perhaps an order of magnitude) of a daily oral exposure to
April 2004
Page 22-4
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the human population (including sensitive sub-populations) that is likely to be without an
appreciable risk of deleterious noncancer effects during a lifetime (see Chapter 21).
As with carcinogens, the development of hazard quotients (HQs) for ingestion typically is
performed first for individual air toxics. Then, hazard indices (His) may be developed for
multiple pollutant exposures and summed across pathways to develop multiple pathway
cumulative hazard estimates. An additional step in the multipathway analysis is to evaluate
combining both ingestion and inhalation hazard estimates. These steps are described in separate
subsections below.
22.3.1 Characterizing Individual Pollutant Hazard - Scenario Approach
The first step in characterizing individual pollutant hazard for an exposure scenario (e.g., a
recreational fisher) is to quantify hazard for each pollutant being evaluated. For ingestion
exposures, noncancer hazards are estimated by dividing the estimate of the Average Daily Dose
(ADD) by the chronic oral RfD to yield an HQ for individual chemicals:
HQ = ADD •*• RfD (Equation 22-3)
where:
HQ = Hazard Quotient for the pollutant via each ingestion pathway being evaluated
(unitless);
ADD = Estimate of the Average Daily Dose for the pollutant via the ingestion pathway
being evaluated (mg/kg-d); and
RfD = Corresponding reference dose for the pollutant via the ingestion pathway being
evaluated (mg/kg-d).
In screening assessments, the chronic exposure estimate is commonly based on a simplifying
assumption of continued similar conditions for a long-term period (for example, that the
maximum annual average modeled concentration remains constant during the full course of the
exposure duration). A more refined assessment might consider how concentration changes with
time over the exposure duration. In both cases, it is important to match the type of RfD value to
the specific exposure scenario. For example, for childhood scenarios (e.g., ages 0-6), risk
assessors commonly use chronic RfDs (rather than subchronic). Subchronic RfDs(a) are more
commonly used to evaluate exposure scenarios that last a year or less (e.g., a construction worker
who is exposed for 6 months). For exposure durations of a few years, both chronic and
subchronic values may be considered, with chronic values commonly being used, particularly in
screening assessments, with explicit recognition of the decision and its basis. Acute toxicity
values are for exposures that are much shorter in duration (usually 24 hours or less); however,
such exposures generally are not evaluated in a multipathway air toxics risk assessment.
Based on the definition of the RfD, an HQ less than or equal to one indicates that adverse
noncancer effects are not likely to occur. With exposures increasingly greater than the RfD (i.e.,
Although subchronic RfDs are not routinely developed by EPA, ATSDR develops MRLs for
"intermediate" exposures and describes them as being relevant to exposure durations on the order of weeks to
months (i.e., >14 days to 364 days).
April 2004 Page 22-5
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HQs increasingly greater than one), the potential for adverse effects increases, but we do not
know by how much. An HQ of 100 does not mean that the hazard is 10 times greater than an HQ
of 10. Also an HQ of 10 for one substance may not have the same meaning (in terms of hazard)
as another substance resulting in the same HQ.
22.3.2 Multiple Pollutant Hazard
Noncancer health effects data are usually available only for individual compounds within a
mixture. In these cases, the individual HQs can be summed together to calculate a multi-
pollutant HI:
HI = HQ., + HQ2 + ...+ HQi (Equation 22-4)
where
HI = Hazard index; and
= Hazard quotient for the ith air toxic.
For screening-level assessments, a simple HI may first be calculated for all chemicals of potential
concern (COPCs) (Exhibit 22-2). This approach is based on the assumption that even when
individual pollutant levels are lower than the corresponding reference levels, some pollutants
may work together such that their potential for harm is additive and the combined exposure to the
group of chemicals poses greater likelihood of harm. Some groups of chemicals can also behave
antagonistically, such that combined exposure poses less likelihood of harm, or synergistically,
such that combined exposure poses harm in a greater than additive manner, although information
needed to perform such an analysis is generally not available. Where this type of HI exceeds the
criterion of interest, a more refined analysis is warranted.
The assumption of dose additivity is most appropriate to compounds that induce the same effect
by similar modes of action. Thus, EPA guidance for chemical mixtures(3) suggests subgrouping
pollutant-specific HQs by toxicological similarity of the pollutants for subsequent calculations;
that is, calculating a target-organ-specific-hazard index (TOSHI) for each subgrouping of
pollutants. This calculation allows for a more appropriate estimate of overall hazard.
The HI approach encompassing all chemicals in a mixture may be appropriate for a screening-
level study. However, it is important to note that applying the HI equation to compounds that
may produce different effects, or that act by different mechanisms, could overestimate the
potential for effects. Consequently, in a refined assessment, it is more appropriate to calculate a
separate HI for each noncancer endpoint of concern when target organs or modes of action are
known to be similar. Refined assessments also may employ techniques more complex than the
HI derived using RfDs.(4)
22.3.3 Evaluating Hazard Estimates From Inhalation and Ingestion Exposures
As with carcinogenic assessments, inhalation hazards must be combined with ingestion hazards
to provide total hazard across all exposure pathways for a receptor. Similar to Exhibit 22-1,
inhalation and ingestion risk estimates can be combined either by chemical across pathways or
across chemicals within a pathway. Essentially, an additional column for inhalation can be added
to Exhibit 22-2 to achieve this result.
April 2004 Page 2 2-6
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Exhibit 22-2. Example Matrix for Characterizing Hazard for Multiple Chemical Exposure
through Multiple Ingestion Pathways for a Particular Exposure Scenario
Chemical 1
Chemical 2
Chemical 3
Chemical 4
Cumulative
Ingestion
Pathway HI (a)
Pathway 1
(Vegetable
Ingestion HQ
Estimate)00
2 x ID'1
3 x ID'1
1 x 10'1
9 x ID'2
7 x 10'1
Pathway 2
(Fish
Ingestion HQ
Estimate)00
2 x ID'1
7 x ID'1
4 x ID'1
1 x 1Q-2
1
Pathway 3
(Egg Ingestion
HQ Estimate)(a)
4 x ID'2
3 x 1Q-2
2 x ID'1
1 x IQ-1
4 x ID'1
Pathway 4
(Beef
Ingestion HQ
Estimate)00
2 x ID'1
2 x ID'1
4 x ID'1
2 x ID'2
9 x ID'1
Aggregate
Chemical
Ingestion
HQ Estimate00
7 x 10'1
1
1
3 x ID'1
3
(a) Standard rules for rounding apply which will commonly lead to an answer of one significant figure
in both risk and hazard estimates. For presentation purposes, hazard quotients (and hazard indices)
and cancer risk estimates are usually reported as one significant figure.
22.4 Interpretation and Presentation of Risks/Hazards
In the final part of the risk characterization, estimates of cancer risk and noncancer hazard should
be presented in the context of uncertainties and limitations in the data and methodology.
Exposure estimates and assumptions, toxicity estimates and assumptions, and the assessment of
uncertainty should be discussed. Chapter 13 provides more detailed information and examples.
Part VI of this reference manual discusses risk communication and other elements of the risk-
based decision-making process.
Estimating Risk for Drinking Water Sources
In evaluating potential risks associated with drinking water supplies, risk assessors commonly assume
that the drinking water undergoes at least a minimum level of treatment to remove solids (i.e.,
particles in the water which are persistent bioaccumulative hazardous air pollutants [PB-HAPs] or
onto which PB-HAPs may be absorbed). Therefore, the risk assessment commonly focuses on the
dissolved concentrations of PB-HAPs in drinking water sources. In addition, if the drinking water
source is part of a public drinking water system, the risk assessment may also assume that the water is
treated to meet applicable drinking water standards (i.e., treated to maximum contaminant levels or
MCLs, unless study-specific information indicates otherwise) for chemicals regulated under the
drinking water program. National Primary Drinking Water Regulations are enforceable standards that
apply to public water systems. The MCLs are the highest level of a specific list of contaminants
allowed in drinking water (see http://www.epa.gov/safewater/mcl.html).
Note that multipathway air toxics risk assessments are subject to additional sources of
uncertainty as compared to inhalation risk assessments. The multimedia modeling effort is both
more complex and less certain due to many factors. For example: (1) there are many more
chemical-dependent and chemical-independent variables involved as input values to the models;
April 2004
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(2) the models involve analysis of the transfer of air toxics from the air to other media (e.g., soil,
sediment, water), the subsequent movement of the air toxics between these media (e.g., soil
runoff to surface water), and uptake and metabolism by biota; and (3) many variables affect the
ingestion of food, water, and other media by humans and wildlife, and the exposure and risk
estimates may differ considerably as a consequence of the assumptions used to derive intake
estimates. Sampling of biota and abiotic media also may be more complex. Additional
uncertainties are incorporated in the risk assessment when exposure estimates to multiple
substances across multiple pathways are summed.
References
1. U.S. Environmental Protection Agency. 2002. Framework for Cumulative Risk Assessment
(External Review Draft). Risk Assessment Forum, Washington, DC, April 2002, available
at: http://oaspub.epa.gov/eims/eimsapi.dispdetail?deid=29570
U.S. Environmental Protection Agency. 1997. Guidance on Cumulative Risk Assessment,
Part 1, Planning and Scoping. Science Policy Council, Washington, DC.
U.S. Environmental Protection Agency. 1984. Risk Assessment and Management:
Framework for Decision Making, Washington, D.C. EPA 600/9-85-002.
2. U.S. Environmental Protection Agency. 1986. Guidelines for Mutagenicity Risk Assessment.
Risk Assessment Forum, Washington, DC. EPA/630/R-98/003; published in the Federal
Register 51:(1185): 34006-34012, Sept 24, 1986, available at:
http ://cfpub. epa. gov/ncea/raf/pdfs/mutagen2 .pdf.
3. U.S. Environmental Protection Agency. 2000. Supplementary Guidance for Conducting
Health Risk Assessment of Chemical Mixtures. Risk Assessment Forum, Washington, D.C.
EPA/630/R-00/002, available at
http://www.epa.gov/ncea/raf/pdfs/chem_mix/chem_mix_08_2001 .pdf.
U.S. Environmental Protection Agency. 1986. Guidelines for the Health Risk Assessment of
Chemical Mixtures. EPA/630/R-98/002; published in the Federal Register 51 (185):34014-
34025, Sept 24, 1986, available at
http://www.epa.gov/ncea/raf/pdfs/chem_mix/chem_mix_08_2001 .pdf.
4. U.S. Environmental Protection Agency. 2002. Guidance on Cumulative Risk Assessment for
Pesticide Chemicals that have a Common Mechanism of Action. Office of Pesticides
Programs, Washington, D.C., January 2002. Available at:
http://www.epa.gov/pesticides/trac/science/.
U.S. Environmental Protection Agency. 2003. National Center for Environmental
Assessment. Developing Approaches to Estimate Cumulative Risks of Drinking Water
Contaminants. Updated December 30, 2003. Available at: http://cfpub.epa.gov/ncea/cfm/
recordisplay.cfm?deid=l 8494. (Last accessed April, 2004.)
April 2004 Page 22-i
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PART IV
ECOLOGICAL RISK ASSESSMENT
-------
-------
Chapter 23 Overview and Getting Started: Problem
Formulation
Table of Contents
23.1 Introduction 1
23.2 Overview of Air Toxics Ecological Risk Assessment 4
23.2.1 Problem Formulation 6
23.2.2 Analysis 8
23.2.3 Evaluation of Ecological Effects 9
23.2.4 Ecological Risk Characterization 9
23.3 Planning and Scoping 9
23.3.1 What is the Concern? K)
23.3.2 Identifying The Participants H
23.3.3 Determining the Scope of the Risk Assessment 1_2
23.3.4 Study-Specific Conceptual Model 12
23.3.4.1 Identifying Receptors of Concern 13
23.3.4.2 Identifying Assessment Endpoints and Measures of Effects 15
23.3.5 Analysis Plan and Quality Assurance Program Plan (QAPP) 16_
23.4 Tiered Ecological Risk Assessments 2J_
References 23
-------
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23.1 Introduction
Part IV constitutes a snapshot of EPA's current thinking and approach to the adaptation of the
evolving methods of ecological risk assessment to the context of Federal and state control of air
toxics. While inhalation risk assessment has been increasingly used in regulatory contexts over the
last several years, ecological risk assessment tools are less well developed and field tested in a
regulatory context. Part IV should be considered a living document for review and input. By
publishing Part IV in its current state of development, EPA is soliciting the involvement of persons
with experience in this field to help improve these assessment methods for use in a regulatory
context EPA anticipates revisions to this draft section of Part IV on the basis of this input.
Part IE of this Reference Manual discusses how to plan for and conduct a multipathway human
health risk assessment when air toxics that persist and may also bioaccumulate (e.g., the
persistent bioaccumulative hazardous air pollutant compounds, or PB-HAPs) in media other than
air and/or biomagnify in food chains are present in releases. For these compounds, the risk
assessment generally will need to include consideration of exposure pathways that involve
deposition of air toxics onto soil and plants and into water, subsequent uptake by biota, and
potential human exposures via consumption of contaminated soils, sediments, surface waters,
and foods. These substances may also pose risks to ecological receptors from direct exposure to
contaminated media or through indirect exposure via aquatic and terrestrial food chains (see
Exhibit 23-1). The preliminary list of PB-HAPs was derived primarily on the basis of exposure
and risk/hazard once HAPs are deposited onto soils, into surface waters, etc. Its derivation did
not consider direct exposures of ecological receptors to air toxics while they are in the air (e.g.,
phytotoxic effects on plants; inhalation by animals). Additional HAPs of potential concern for
ecological risk may be identified as EPA gains more familiarity with ecological risk assessments
for air toxics. Appendix D describes the process by which EPA identified the PB-HAP
compounds.
Trophic Levels and Biomagnification
The trophic level is a way to describe where an
organism may be located within an aquatic or
terrestrial food web. The lowest trophic level consists
of primary producers, the green plants that convert
sunlight into carbohydrates via photosynthesis. The
next trophic level generally consists of primary
consumers, or the organisms that feed directly on
green plants. The next level up, often termed
secondary consumers, represents animals that feed on
primary consumers. The highest trophic level
consists of the top predators in the food web. For
some chemicals, the concentration in biological tissue
can increase as it moves up the food chain, a process
called biomagnification.
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Exhibit 23-1. Air Toxics Exposure Pathways of Potential Concern for Ecological Receptors
Dispersal
Dispersal
"
Inhalation
Atmospheric Contaminated
Deposition Air
Consumption
of Fish
itionof / / Atmospheric , ,
linated / / / Deposition , /
irv€ ////I'1// '
j* i /7v
Absorption
and Settling
_
i
Transfer Up
Aquatic Food Web
Dermal Uptake
by Soil Organism
Uptake by
Benthic Organisms
Consumption of
Contaminated
Water
Ingestion of
Contaminated
Plants and Soil
This graphic illustrates some of the potential multimedia pathways of concern for air toxics exposure
to ecological receptors. Air toxics released from a source disperse through the air and eventually fall
to the earth (atmospheric deposition) via settling and/or precipitation. Air toxics deposited to soil may
be absorbed or ingested by plants and soil invertebrates (uptake). Terrestrial animals may be exposed
to air toxics via ingestion of contaminated plants and soil, or by consuming contaminated terrestrial
animals (for those air toxics that bioaccumulate and transfer up the terrestrial food web). Air toxics
deposited to water may be dissolved in the water column and/or may settle and be absorbed into
aquatic sediments. Air toxics in sediments may be absorbed or ingested by benthic organisms
(uptake); those in sediments and the water column may be absorbed by aquatic plants (uptake).
Aquatic organisms (e.g., fish) may be exposed directly to air toxics in the water column and/or by
consuming contaminated aquatic organisms (for those air toxics that bioaccumulate and transfer up the
aquatic food web). Terrestrial animals may be exposed to air toxics by eating contaminated fish or
shellfish and/or by drinking contaminated water. Note also that, while in the atmosphere, air toxics
may also have direct impacts on plants (direct exposure) and terrestrial animals (inhalation).
This part (Part IV) of this reference manual introduces the basic concepts of ecological risk
assessment and describes their application to air toxics. Several differences of particular
importance are highlighted in a text box on page 23-3. The discussion of ecological risk
assessment follows the same general framework as that presented in Part IE since the overall
concept is the same; namely that certain air toxics may move from the air into other media where
exposures to organisms (in this case, non-human organisms) can occur with potentially adverse
outcomes. Readers are strongly encouraged to become familiar with the information provided in
Part IE before reading this Part. However, although there are many similarities between
April 2004
Page 23-2
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multimedia human health risk assessment and ecological risk assessment (e.g., they may use
the same multimedia monitoring and modeling tools), professional expertise will always be
required to apply the ecological risk assessment principles and tools identified in this
document to specific assessment areas or problems. This document is not a substitute for a
working familiarity with ecological principles, their application, and the field of ecological
risk assessment.
X *
Air toxics may have adverse effects on ecological receptors through direct exposures (e.g.,
inhalation by animals; direct deposition onto plants). However, EPA does not have sufficient
experience with multipathway air toxics risk assessments to identify the circumstances for which
these exposures would represent a potential concern. This reference manual therefore does not
address these additional exposure pathways. The methods for conducting such an analysis are
described in greater detail in EPA's Guidelines for Ecological Risk Assessment.^
\ x-
This chapter presents an overview of ecological risk assessment and discusses the initial planning
and scoping activities. The remaining chapters of this part focus on Characterization of
Exposure (Chapter 24), Characterization of Ecological Effects (Chapter 25), and Risk
Characterization (Chapter 26). The discussion presented here is based largely on EPA's
Guidelines for Ecological Risk Assessment and the Residual Risk Report to Congress.(2) The
Guidelines for Ecological Risk Assessment were developed especially for evaluating ecological
risk. Readers are also strongly encouraged to become familiar with that document for a more
complete understanding of EPA's recommended approach to ecological risk assessment.
Interested readers are also referred to EPA 's Ecological Risk and Decision Making Workshop
materials which provide detailed information on the definition of ecological risk assessment, how
it relates to human health assessment, the ecosystem protection place-based approach, and the
bases for ecological protection and risk assessment at EPA.(3)
X N
Key Ecological Risk Assessment Resources
NCEA's Ecological Risk Assessment webpage http://cfpub.epa.gov/ncea/cfm/ecologic.cfm
The Oak Ridge National Laboratory Ecological Risk Assessment webpage on tools, guidance, and
applications http://www.esd.ornl. gov/programs/ec orisk/ecorisk.html
The Superfund Ecological Risk Assessment Program
http://epa.gov/superfund/programs/risk/ecolgc.htm
Navy Guidance for Conducting Ecological Risk Assessments http: //web.ead. anl. gov/ecorisk/
EPA's Watershed Ecological Risk Assessment program
http://cfbub.epa.gov/ncea/cfm/weracs.cfm7ActT ype=default
April 2004 Page 23-3
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Some Important Differences Between Ecological Risk Assessment and
Multipathway Human Health Risk Assessment
Planning and scoping. The ecological risk assessment requires more preliminary analysis and
deliberation regarding endpoints to be assessed and toxicity reference values to be used because
ecological systems are more complex and are not as well understood biologically as human health
systems. The planning and scoping team should include individuals with specific expertise in
ecological risk assessment.
Assessment area. It may be necessary to evaluate additional portions of the assessment area that
are not of concern from a human health perspective.
Potentially exposed populations. The focus shifts from potentially exposed individual humans to
potentially exposed populations and species of ecological receptors of concern. In many cases, the
exposure assessment may need to address multiple species and life-stages, many of which have
physiological and biochemical processes that differ significantly from humans. (When threatened
or endangered species are present, the assessment may also include an evaluation of those
organisms as individuals).
Exposure pathways and exposure routes. It may be necessary to assess different exposure
pathways and routes that are not of concern for human health.
Ecological effects assessment. Ecological systems have traits and properties that are different
from humans and, thus, the ecological effects assessment (comparable to hazard assessment for
human health) may consider a wider range of potential causal relationships.
Risk characterization. While risks may be assessed at multiple levels of ecological organization
(i.e., organism, population, community, and ecosystem), they generally are assessed at the
population level in air toxics assessments. (Nevertheless, when appropriate, consideration should
be given to assessments at high levels of ecological organization, such as at the landscape level).
23.2 Overview of Air Toxics Ecological Risk Assessment
The ecological risk assessment process has three main steps that broadly correspond to the four
basic steps in human health risk assessment methodology (Exhibit 23-2):(1)
• Problem formulation, which corresponds to the problem formulation step of the human
health risk assessment methodology (planning and scoping activities similar to human health
risk assessment are also integrated with this step; however, they are discussed separately
below to maintain the operational structure of the ecological risk assessment as described in
EPA's ecological risk assessment guidelines);
• Analysis, which corresponds to the exposure assessment and toxicity assessment steps of the
human health risk assessment methodology; and
• Risk characterization, which corresponds to the risk characterization step of the human
health risk assessment methodology.
April 2004 Page 23-4
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Exhibit 23-2. Ecological Risk Assessment Framework
•^Integrate Aura liable Information^1
Cha-acterizdionof Exposure
Characterization of Ecological
Effects
Ecological Response
Analysis
ID
O
W.
ju
7*
ID
ID
RISK
CHARACTERIZATION
Communicating Results to the Risk Manager
Risk Management and Communicating
R esufts to Interested Parties
Source: EPA Guidelines for Ecological Risk Assessment1
April 2004
Page 23-5
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23.2.1 Problem Formulation
Problem formulation provides the foundation for the entire ecological risk assessment. This step
includes:
• Identifying risk management goals from an ecological perspective, ecological receptors of
concern (e.g., wetlands, fish populations, keystone species that impact the overall ecosystem),
and assessment endpoints (explicit expression of the environmental value that is to be
protected, operationally defined by an ecological entity and its attributes);
• Developing the ecological risk part of the conceptual model as necessary to account for
ecological exposure pathways and receptors; and
• If necessary, developing the Sampling and Analysis Plan and associated Quality Assurance
Project Plan to collect data on exposures and measures of effects that are needed to support
the ecological risk assessment.
As with human health risk assessments, problem formulation is often an iterative process, in
which substantial re-evaluation may occur as new information and data become available. Data
collection in subsequent iterations often is triggered by identification of major data gaps and
uncertainties in the risk characterization that prevent confident decision-making by risk
managers.
The problem formulation process for ecological risk assessment for air toxics focuses on
developing a common understanding of what needs to be done to assess ecological risks
associated with pathways involving deposition; the transfer of compounds to soil, water,
sediment, and biota, and subsequent exposure. While the ecological risk assessment may build
on the foundation of the human health multipathway assessment (e.g., using the same emissions
data and multimedia models), the problem formulation step is particularly critical for the
ecological risk assessment because of the effort needed to understand and identify ecological
receptors, exposure pathways, endpoints, and management goals. The ecological risk assessment
is not simply an "add-on" to the human health multipathway risk assessment. The problem
formulation effort will need to consider a wide variety of possible ecological receptors that are
not similar to humans. For example:
• Different species (and life stages) may have very different responses to the same exposure.
Therefore, knowledge of the exposure-response of many species, including those that maybe
particularly sensitive to the air toxic, is needed.
• Ecosystems may show adverse effects at lower exposures than most individual species do
because species that are important in terms of ecosystem function (e.g., energy flow, nutrient
recycling) may also be sensitive to toxic effects. Ecosystem-level metrics such as species
diversity indices may be more sensitive indicators of adverse effects than are toxicological
studies.
• There may be many different types of ecosystems present in the assessment area, and
sensitivity likely varies among them. Therefore, the particular features of the ecosystem(s)
that occur in areas where high exposures are predicted may be particularly important.
April 2004 Page 23-6
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An Ecological Risk Assessment Case Study: Ozone Risks To Agroecosystems
The case study summarized here provides an example of how EPA has assessed environmental risks from an air
pollutant (ozone) as part of EPA's effort to promulgate National Ambient Air Quality Standards (NAAQS) for
criteria air pollutants (see Chapter 2). Note that this example is for ozone, a criteria air pollutant; however, the
concepts presented here are relevant to air toxics risk assessment. In addition, an agroecosystem, such as the
system discussed here, is more of a human construct than a natural ecosystem and is provided here only for
illustration of general principles. An actual air toxics ecological risk assessment of a natural system would have
to consider site-specific characteristics of the system in question.
Problem Formulation. Pursuant to the Clean Air Act (CAA), EPA is required to set NAAQS for "any pollutant
which, if present in the air, may reasonably be anticipated to endanger public health or welfare and whose
presence in the air results from numerous or diverse mobile and/or stationary sources." EPA develops public
health (primary) and welfare (secondary) NAAQS. According to section 302 of the CAA, the term welfare
"includes ... effects on soils, water, crops, vegetation, manmade materials, animals, wildlife, weather, visibility,
and climate, damage to and deterioration of property, and hazards to transportation, as well as effects on
economic values ...." A secondary standard, as defined in section 109(b)(2) of the CAA, must "specify a level of
air quality the attainment and maintenance of which in the judgment of the Administrator, based on such criteria,
is requisite to protect the public welfare from any known or anticipated adverse effects associated with the
presence of such air pollutant in the ambient air."
This case study focuses on an assessment endpoint for agricultural crops (e.g., the prevention of an economically
adverse reduction in crop yields). Yield loss is defined as an impairment of, or decrease in, the value of the
intended use of the plant. This concept includes a decrease in the weight of the marketable plant organ, reduction
in aesthetic values, changes in crop quality, and/or occurrence of foliar injury when foliage is the marketable part
of the plant. These types of yield loss can be directly measured as changes in crop growth, foliar injury, or
productivity, so they also serve as the measures of effect for the assessment.
Exposure Analysis. EPA used ambient ozone monitoring data across the U.S. and a Geographic Information
System (GIS) model to project national cumulative, seasonal ozone for the maximum three month period during
the summer ozone season. This allowed EPA to project ozone concentrations for some rural parts of the country
where no monitoring data were available but where crops were grown, and to estimate the attainment of
alternative NAAQS scenarios. The U.S. Department of Agriculture's (USDA's) national crop inventory data
were used to identify where ozone-sensitive crop species were being grown and in what quantities. This
information allowed the Agency to estimate the extent of exposure of ozone-sensitive species under the different
scenarios.
Ecological Effects Analysis. Stressor-response profiles describing the relationship between ozone and growth
and productivity for 15 crop species representative of major production crops in the U.S. (e.g., crops that are
economically valuable to the U.S., of regional importance, and representative of a number of crop types) had
already been developed from field studies conducted from 1 980 to 1986 under the National Crop Loss
Assessment Network (NCLAN) program. The NCLAN studies also included secondary stressors (e.g., low soil
moisture and co-exposure with other pollutants like sulfur dioxide), which helped EPA interpret the
environmental effects data for ozone.
Risk Characterization. Under the different NAAQS scenarios, the Agency estimated the increased protection
from ozone-related effects on vegetation associated with attainment of the different NAAQS scenarios.
Monetized estimates of increased protection associated with several alternative standards for economically
important crops were also developed. This analysis focused on ozone effects on vegetation since these public
welfare effects are of most concern at ozone concentrations typically occurring in the U.S. By affecting
commercial crops and natural vegetation, ozone may also indirectly affect natural ecosystem components such as
soils, water, animals, and wildlife.
Source: U.S. Environmental Protection Agency. 1999. Residual Risk Report to Congress. Office of Air Quality
.Planning and Standards, Research Triangle, NC, March 1999. EPA-453/R-99-011. ,
April 2004 Page 23-7
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23.2.2 Analysis
Analysis includes two principal steps. Characterization of exposures includes identifying the
contaminants of potential ecological concern (COPECs) that may affect ecological receptors,
characterizing the spatial and/or temporal pattern of stressor concentrations in environmental
media (including certain body burden levels), and analyzing the level of contact or co-occurrence
(exposure) between the stressors and the ecological receptors. This often is done using the
multimedia models identified in Chapter 18; however, different models or approaches may be
appropriate. Characterization of ecological effects includes identifying the types of effects that
different stressors may have on ecological receptors, along with characterizing the stressor-
response relationship (the relationship between the level of exposure to the stressor and the
expected biological or ecological response). A common result is the identification of ecological
toxicity reference values (TRVs), which are concentrations of chemicals in environmental
media (including biota such as fish tissues) below which no significant ecological effects are
anticipated. TRVs are similar, in concept, to RfDs (reference doses) and RfCs (reference
concentrations) for human health noncancer evaluations. TRVs may be screening level (i.e.,
conservative, generic values) or more refined values for use in higher levels of analysis. They
may be point values, ranges, or developed using more advanced probabilistic methods (such as
Monte Carlo techniques). The ecological exposure characterization also is likely to differ
significantly from the corresponding multipathway exposure assessment for human health. For
example:
• In addition to food chain (ingestion) exposures, many ecological receptors can be exposed to
air toxics via direct contact with contaminated soils (e.g., earthworms) or sediments (e.g.,
sediment-dwelling invertebrates, bottom-feeding fish); direct exposure to surface water (e.g.,
free-swimming invertebrates and fish); or direct exposure to contaminated air via inhalation
(e.g., birds), dermal contact (e.g., amphibians), deposition to plant surfaces, etc.
• Particular geographic areas of concern may differ because ecological receptors may occur in
areas rarely used by human populations (e.g., large wetland areas, ponds where people rarely
fish).
• Sampling and analysis may involve a wider range of media (e.g., sediment) and different
types of biota (e.g., earthworms, aquatic invertebrates). Each type of sampling and analysis
has its own methods, protocols, and Quality Assurance/Quality Control (QA/QC) procedures.
• Quantitative metrics of exposure may include both direct and indirect exposures for
ecological receptors. Quantification of direct exposure is similar to human health inhalation
analyses, in which ambient concentrations of COPECs in soil, water, and/or sediment are
compared to corresponding TRVs. Quantification of indirect exposure via ingestion is
similar to that for human health ingestion analyses, except that different food items may be
involved, and the appropriate ecological exposure factors (e.g., diet, body weight) will be
different. As with human health analyses, many exposure factors can be treated either as
constants or as distributions in the exposure assessment. Ecological exposure assessments
for ingestion pathways frequently use bioenergetic models to more explicitly relate intake to
adverse effects.(4)
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23.2.3 Evaluation of Ecological Effects
The characterization of ecological effects is similar to a toxicity assessment for human health. It
considers the types of adverse effects associated with chemical exposures, stressor-response
relationships, and related uncertainties. There are two primary differences:
• Adverse effects of concern generally focus at the population, community, or ecosystem level.
With rare exceptions (e.g., threatened or endangered species), effects to individual organisms
are not the primary concern. Note, however, that ecological risk assessments often use
estimates of impacts to individual organisms (e.g., mortality, reproductive effects) to infer
impacts at higher levels of organization because exposure-response data for populations,
communities, or ecosystems often are lacking. Some approaches are available, however, for
incorporating population-level analysis in ecological risk assessments/5'
• A distinction is made between assessment endpoints, which are the environmental values to
be protected, and measures of effects, which are the specific measures used to evaluate risk
to the assessment endpoints (assessment endpoints and measures of effects are defined in
Section 23.3.4.2).
23.2.4 Ecological Risk Characterization
Similar to human health risk characterization, ecological risk characterization combines
information concerning exposure to chemicals with information regarding effects of chemicals to
estimate risks. Human health risk assessments consider health effects in the bodies of individual
people. Ecological risk assessments consider various "health" issues that can range from actual
health effects in the bodies of individual ecological receptors to something more attuned to the
"health" of the ecosystem as measured by species richness and diversity.
23.3 Planning and Scoping
To ensure that the ecological risk assessment will
provide information useful to the risk managers
who will be making the risk management
decisions, EPA's Guidelines for Ecological Risk
Assessment recommends a planning and scoping
dialogue occur between the risk assessors, risk
managers, and where appropriate, interested
stakeholders at the very start of the risk
assessment process. The outcome of the planning
and scoping phase is an agreement on the basic
goals, scope, and timing of the risk assessment.
Important goals of the dialogue are the
identification of the risk management goals and
risk management options that the risk assessment
will be designed to inform (see accompanying
text box). This 'kick-off dialogue sets the stage for
plans for the ecological risk assessment are finalized
f .\
Planning and Scoping the Ecological
Risk Assessment
The planning phase is complete when
agreements are reached on:
• The management goals for ecological
values;
• The range of management options the
risk assessment is to support;
• Objectives for the risk assessment,
including criteria for success; and
• The focus and scope of the assessment,
and resource availability.
the problem formulation phase, when the
April 2004
Page 23-9
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When actually performing the problem formulation phase of an ecological risk assessment, the
five-step planning and scoping process identified for human health risk assessments is a helpful
tool to get the right people involved and the risk questions, expectations, and plans in place to
make the overall assessment go smoothly and in a scientifically responsible manner. Similar to
the human health evaluation process, the risk assessment and management team should be
assembled to start identifying the concern, identifying who needs to be involved in the risk
assessment process, determining the scope of the risk assessment, describing why there may be a
problem, and determining how the concern will be evaluated.
23.3.1 What is the Concern?
In human health risk assessment and risk management, the assessors are dealing with a single
organism (human beings) and the precedent and rationale for specific risk management goals
(such as the 1x10"6 to 1x10"4 cancer risk range) are generally well established. The parallel
process for ecosystems, however, is not as easy to study or as straightforward to manage. To
begin with, it can be difficult to choose which of many organisms in a study area to evaluate.
Moreover, there is little agreement on which (if any) organisms or ecosystems are important
enough to single out for protection. These factors make planning, evaluation, and management
of ecological risks more complicated and time-consuming (and often, more controversial).
EPA's Risk Assessment Forum developed draft guidance(6) to help decision-makers work with
risk assessors, stakeholders, and other analysts to plan for ecological risk assessments that will
effectively inform the decisions they need to make. Planning for ecological risk assessment
includes three primary steps:
1. Defining the risk management decision to be made, the context in which it will be made,
and its purpose. This includes articulating the decision or problem that the risk manager
faces, understanding the social and legal context for the decision, placing preliminary
boundaries on the scope of the risk assessment, and identifying who needs to be involved.
Appropriately framing the context will help ensure that management objectives are relevant
to the risk manager's decision and increase the likelihood that the information generated by
the risk assessment will be useful.
2. Developing objectives. This starts with a clear statement of the problem, issue, or
opportunity identified in the first step and ends with a set of specific objectives which will
guide all of the remaining steps. An important determination is the "what to protect" (i.e., the
assessment endpoint) question for ecological issues and to describe what is at stake. Key
questions include:
- What should be protected? Define the entities, ecological processes, and geographic
areas to be considered.
- How is "protection" defined? Define the ecological objectives.
- What are the most important objectives and how can they be achieved? Review and
structure objectives.
In some cases, there is a strong consensus on "what to protect" (e.g., if a commercially
important resource such as a fishery is potentially exposed). In many other cases, it is not
always obvious to a risk manager or the public what features of an ecosystem are of potential
concern or what the broader consequences would be from adverse effects to those features.
April 2004 Page 23-10
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Developing a consensus on the specific risk management objectives maybe a difficult and
time-consuming part of the planning and scoping process.
3. Identifying what information is needed to inform the decision. When identifying
information needs, planners are encouraged to think ahead about everything that will be
needed to decide what to do about identified risks. Ecological risk is part of the picture, but
issues such as feasibility, practicability, cost, and acceptability also need to be factored into
the decision. They should also consider who and what resources are available to perform the
ecological risk assessment. The aim of this step is to narrow down which questions the risk
assessment should address and identify those that will be addressed elsewhere.
The questions identified at this step will be examined during the remainder of the problem
formulation process. Management objectives are by definition closely related to the assessment
endpoints evaluated in ecological risk assessment, and it should be possible to characterize them
using the measures described below.
S N
Assessment Endpoints
According to EPA's Guidelines for Ecological Risk Assessment,^ an assessment endpoint is an
explicit expression of the environmental value that is to be protected, and is operationally defined by
an ecological entity and its attributes. For example, a particular area has air toxics releases that may
be affecting area salmon populations that are important for location recreation and commercial
fishermen as well as an important resource for a local Native American tribe. In the study area, the
salmon population is the valued ecological entity; reproduction and age class structure of a salmon
population are some of their most important attributes. An appropriate assessment endpoint for this
study area might be stated as salmon reproduction and age class structure. The ecological risk
assessment for this study area would be structured to evaluate whether this specific salmon population
is at risk from air toxics with regard to healthy reproductive ability and age class structure.
Given the diversity of species and other ecological attributes in almost any study area, the assessors
generally establish at least one assessment endpoint that will, together, provide an assessment of air
toxics impacts on the ecosystem as a whole. More than one assessment endpoint may be necessary at
the ecosystem level.
23.3.2 Identifying The Participants
The participants for the ecological risk assessment may include some of the same people as those
for the human health multipathway risk assessment (e.g., multimedia modelers that understand
how to model for both human and ecological receptors). However,
• Additional risk managers may be involved, including natural resource management agencies
such as the U.S. Fish and Wildlife Service; state, local, or tribal (S/L/T) fish and game
departments; and/or private-sector risk managers.
• The risk assessment technical team will need significantly different experts (e.g., aquatic
ecologists, experienced ecological risk assessors).
April 2004 Page 23-11
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• The specific set of interested or affected parties may change or be expanded (e.g., different
environmental groups may be more concerned/involved; local fishermen may become
interested).
EPA's Public Involvement Policy may be helpful in performing this task (see
http://www.epa.gov/stakeholders/policy2003/index.htm). Part V of this document provides
additional information on community involvement.
23.3.3 Determining the Scope of the Risk Assessment
The scope of the human health multipathway risk assessment may expand to include additional
exposure pathways and exposure routes, and to address ecological receptors of concern.
• The specific chemicals that will be the focus of the ecological risk assessment will generally
be those that persist, bioaccumulate, and biomagnify (the PB-HAP compounds); however, a
different set of PB-HAP compounds maybe of more concern for the ecological risk
assessment than for human health risk assessment. As with human health risk assessment,
additional compounds may need to be added to the analysis, depending on study-area specific
considerations.
• The specific sources included in the analysis may be focused on the subset that releases most
or all of the identified COPECs.
• The physical boundaries of the study area may need to expand to include geographic areas
where COPECs may be transported after deposition (e.g., the COPECs may have the
potential to be deposited in a watershed and be carried out of the geographic area defined for
the human health multipathway modeling).
23.3.4 Study-Specific Conceptual Model
A study-specific conceptual model for the ecological risk assessment is developed using the
fundamental elements of the conceptual model developed for the human health multipathway
assessment as a starting point. Steps to develop the study-specific ecological risk conceptual
model include the following:
• Determine whether the set of potential sources and chemicals that were identified in the
human health multimedia risk assessment are appropriate for the ecological risk assessment.
• Consider expanding the set of potential sources, chemicals, and exposure pathways to include
those identified below (potential exposure pathways are listed in Exhibit 23-3).
• Identify ecological receptors of concern (see Section 23.3.4.1).
• Formulate a risk hypothesis that describes possible relationships between emissions of a
chemical, exposure, and assessment endpoint response, including the information that sets
the problem in perspective, as well as an identification of the proposed relationships that need
evaluation.
April 2004 Page 23-12
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Identify assessment endpoints and measures of effects (See Section 23.3.4.2).
Exhibit 23-3. Common Exposure Pathways Considered for
Ecological Air Toxics Risk Assessments
Direct exposure pathways:
air -•• soil -•• soil-dwelling biota
air -•• soil -•• water -•• aquatic biota
air -•• water -•• aquatic biota
air -•• water -•• sediment -•• aquatic biota
air -•• soil -•• water -•• sediment -•• aquatic biota
air -•• vegetation
Indirect exposure pathways:
air -•• vegetation -•• bird/mammal
air -•• soil -•• vegetation -•• bird/mammal
air -•• soil -•• water -•• aquatic biota -•• fish
air -•• soil -•• water -•• aquatic biota -•• fish -•• bird/mammal
air -•• water -•• aquatic biota -•• fish
air -•• water -•• aquatic biota -•• fish -•• bird/mammal
air -•• soil -•• water -•• sediment
air -•• soil -•• water -•• sediment
aquatic biota -•• fish
aquatic biota ^ fish ^ bird/mammal
Conceptual model diagrams, such as the example illustrated in Exhibit 23-4, are used (along with
the risk hypothesis) to select the pathways to be evaluated in the analysis phase of the ecological
risk assessment, as well as to assist in communication with risk managers.
As with human health risk assessments, the conceptual model for an ecological risk assessment
must provide both a graphical representation of the important exposure pathways that are
presumed to be occurring along with a written description that outlines each element of the
conceptual model. Taken together, these two parts of the conceptual model clearly identify the
sources of concern, the COPECs that will be evaluated, the exposure pathways, and the
assessment endpoints. Similar to conceptual models for human health analysis, the conceptual
model may be modified (perhaps a number of times) as more is learned about the study area.
23.3.4.1 Identifying Receptors of Concern
Ecological receptors of concern are an important part of the conceptual model. These may be
plants, animals, habitats, communities, or larger ecosystem elements. Specific receptors maybe
of concern for a variety of reasons, including:
• The receptor (or one of it's life stages) is particularly vulnerable or sensitive to one or more
COPECs;
• The receptor (usually a species or a community such as a wetland) is listed as endangered or
threatened or is otherwise given special legal protection by the state or federal government;
April 2004
Page 23-13
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The receptor plays an important part in the overall structure or function of the ecological
community or ecosystem;
The receptor is of particular economic or cultural value to stakeholders.
Exhibit 23-4. Conceptual Model Diagram for Exposure of Piscivorous Birds to Air Toxics
Risk Hypothesis 2
Primary
Soiree
(Stack
Emissions)
ik
f
Secondary
Source
(Surface
Water)
f
Primary
Receptor
(Aquatic
Invertebrate)
h,
f
Secondary
(Fish)
f
Tertiary
Receptor
(Piscivorous
Bird)
Risk Hypothesis 1
(Endpoint
] Reproductive
Success)
Risk Hypothesis 3
Conceptual model diagrams are used, along with the risk hypothesis, to select the pathways to be
evaluated in the analysis phase of the ecological risk assessment, as well as to assist in communication
with risk managers. The three risk hypotheses in this hypothetical example are:
• Risk Hypothesis 1: Concentrations of chemical X in the surface water column are less than a
level known to cause adverse effects on survival and reproduction mDaphnia
- Mechanism: Chemical X causes mortality and inhibits larval development
• Risk Hypothesis 2: Dietary intake levels of chemical X in lake trout are less than a level known
to cause adverse effects on reproductive ability
- Mechanism: Due to a lack of enzyme A in lake trout, chemical X rapidly accumulates in lipid
tissues and damages reproductive organs
• Risk Hypothesis 3: Dietary intake levels of chemical X in kingfisher chicks (passed to them by
their parents) is less than a level known to adversely affect their survival
- Mechanism: Chemical X accumulating in egg lipids is a metabolic toxin to the developing
embryo
April 2004
Page 23-14
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For taxonomic, physiological, and exposure reasons, it is important to consider a broad range of
potential ecological receptors during problem formulation. For example, the types of adverse
effects that may occur to terrestrial plant communities (e.g., impacts to photosynthesis, nitrogen
fixation, nutrient uptake; foliar damage) are very different than the types of adverse effects that
may occur to terrestrial mammals. Many ecological receptors (e.g., molds, lichens, many
invertebrates) have unique physiological and biochemical features that may make them
particularly sensitive to air toxics. Sensitive life stages often are a particular concern. In surface
waters and sediments, early life stages (e.g., eggs, larvae) maybe particularly sensitive to
contaminants due to their small size (e.g., contaminants may readily penetrate cell membranes)
and developmental processes (e.g., major metamorphosis from one life stage to another). Many
terrestrial organisms (e.g., amphibians, dragonflies) have aquatic-dwelling early life stages. In
addition, many invertebrates that can bioaccumulate PB-HAPs (e.g., aquatic dwelling dragonfly
larvae) maybe sources of food for sensitive life stages of other species (e.g., nestling birds).
Often it is important to understand the aquatic and terrestrial food webs in the habitats of concern
because these can be important parts of ecological exposure pathways. Top predators are often
of special concern for exposure to PB-HAP compounds.
Ecological receptors for each habitat potentially impacted should be identified to ensure (1) plant
and animal communities representative of the habitat are represented by the habitat-specific food
web, and (2) potentially complete exposure pathways are identified. Screening-level ecological
assessments often focus on the most sensitive organisms within an ecosystem or on the most
sensitive life stages within a species, if these are known. Ecological receptor identification may
need to include species both known and expected to be present in a specific habitat being
evaluated, and include resident and migratory populations. Consultation with ecological experts
is recommended. Potential sources of information include:
• Government Organizations. The U.S. Fish and Wildlife Service has biologists and other
ecological experts and also maintains National Wetland Inventory maps.(7) State Natural
Heritage Programs provide maps or lists of species based on geographic location, and are
very helpful in identifying threatened or endangered species or areas of special concern.
• Private or Local Organizations. Private or professional organizations that are examples of
sources of information include: National Audubon Society, the Nature Conservancy, local
wildlife clubs, and universities.
• General Literature. Monographs, field guides, and other literature describing the flora and
fauna of America and/or a particular region or state may be useful sources of information.
23.3.4.2 Identifying Assessment Endpoints and Measures of Effects
As previously noted, an assessment endpoint is an explicit expression of the environmental
value that is to be protected or is of concern. It includes the identification of the ecological entity
for the analysis (e.g., a species, ecological resource, habitat type, or community) as well as the
attribute of that entity that is potentially at risk and important to protect (e.g., reproductive
success, production per unit area, surface area coverage, biodiversity). The measures of effects
are the measures used to assess these endpoints.(8)
April 2004 Page 23-15
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Generally, a manageable subset of the most important assessment endpoints is selected for the
risk assessment, and specific measures of effects that address each assessment endpoint are
identified. EPA guidance documents discuss additional issues that are important in the
identification of assessment endpoints.(9)
Appropriate selection of relevant assessment endpoints is critical so that the risk assessment
provides valuable information for the associated risk management decisions. Assessment
endpoints that can be measured directly are most effective, although assessment endpoints that
cannot be measured directly, but can be represented by measures that are easily monitored or
modeled, may also be used. Additional uncertainty is introduced depending on the relationship
between the measurement and the assessment endpoints. Exhibit 23-5 provides examples of
assessment endpoints, measures of effect, and other elements of the problem formulation phase.
EPA has recently released guidance that describes a set of endpoints, known as Generic
Ecological Assessment Endpoints (GEAE), that can be considered and adapted for specific
ecological risk assessments/9' The entities and properties comprising the initial set of GEAEs is
presented in Exhibit 23-6. The EPA Guidance defines GEAE further and provides the basis for
the terms assessment community and assessment population, which are used in the definitions.
In addition, EPA's Science Advisory Board recently published a Framework for Assessing and
Reporting on Ecological Condition,,(10) which includes a checklist of ecological attributes that
should be considered when conducting ecological risk assessments and developing ecological
management objectives (Exhibit 23-7). Note that many of these GEAEs and attributes focus at
levels of ecological organization higher than organisms (e.g., species richness) or on ecological
processes (e.g., nutrient cycling) rather than attributes of organisms (e.g., growth, reproduction).
It often is useful to summarize the results of the problem formulation process in a problem
formulation summary that lists management objectives, assessment endpoints, and the structure
of the risk assessment from exposure scenarios through risk characterization. Exhibit 23-8
provides an example problem formulation summary.
23.3.5 Analysis Plan and Quality Assurance Program Plan (QAPP)
As noted in Parts II and III of this reference manual, the Analysis Plan and QAPP are formulated
by considering both the the conceptual model and the data quality required for the risk
management decision. The Analysis Plan and QAPP, including data quality objectives, are just
as important for the ecological risk assessment as they are for the human health risk assessment,
and in some cases may be more complex. The analysis plan for the ecological risk assessment
will need to match each of the elements of the conceptual model with the analytical approach that
will be used to develop data about the element, including: sources; exposed populations and
exposure pathways; exposure concentrations of COPEC; exposure conditions; toxicity of
COPECs; risk characterization; QA/QC; documentation; roles and responsibilities; resources;
and schedule.
Because the focus is on ecological receptors, additional types of monitoring (sampling and
analysis) may need to be conducted. For example, it may be important to measure concentrations
of COPECs in the sediments of surface water bodies as part of the analysis of direct exposures
for sediment-dwelling invertebrates as well as bioaccumulation from these invertebrates to
predatory fish through the aquatic food web.
April 2004 Page 23-16
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Exhibit 23-5. Example of Ecological Risk Assessment Problem Formulation:
EPA's Water Quality Criteria
A specific example of elements of the problem formulation step in a national-level ecological risk
assessment can be found in the development of Ambient Water Quality Criteria by EPA's Office of
Water pursuant to the Clean Water Act (CWA).(11) Water quality criteria have been developed for the
protection of aquatic life from chemical stressors. The following elements of problem formulation
support subsequent analyses in the risk assessments used to establish specific criteria.
Regulatory Goal
• CWA Section 101: Protect the chemical, physical, and biological integrity of the Nation's water.
Program Management Decisions
• Protect 99 percent of individuals in 95 percent of the species in aquatic communities from acute
and chronic effects resulting from exposure to a chemical stressor.
Assessment Endpoints
• Survival offish, aquatic invertebrates, and algal species under acute exposure
• Survival, growth, and reproduction offish, aquatic invertebrates, and algal species under chronic
exposure
Measures of Effect
• Laboratory LC50s for at least eight species meeting certain requirements
• Chronic no-observed-adverse-effect-levels (NOAELs) for at least three species meeting certain
requirements
Measures of Ecosystem and Receptor Characteristics
• Water hardness (for some metals)
• pH
The water quality criterion is a TRV derived from a distributional analysis of single-species toxicity
data. It is assumed that the species tested (which represent a range of taxonomic groups) adequately
represent the composition and sensitivities of species in a natural community.
April 2004 Page 23-17
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Exhibit 23-6. Generic Ecological Assessment Endpoints(a)
Entity
Attribute
Organism-level endpoints
Organisms (in an assessment
population or community)
Kills (mass mortality,
conspicuous mortality)
Gross anomalies
Survival, fecundity, growth
Population-level endpoints
Assessment population
Extirpation
Abundance
Production
Identified EPA Precedents
Vertebrates
Vertebrates, shellfish, plants
Endangered species, migratory
birds, marine mammals, bald
and golden eagles, vertebrates,
invertebrates, plants
Vertebrates
Vertebrates, shellfish
Vertebrates (game/resource
species), harvested plants
Community and ecosystem-level endpoints
Assessment communities,
assemblages, and ecosystems
Taxa richness
Abundance
Production
Area
Function
Physical structure
Aquatic communities, coral reefs
Aquatic communities
Plant assemblages
Wetlands, coral reefs,
endangered/rare ecosystems
Wetlands
Aquatic ecosystems
Officially designated endpoints
Critical habitat for endangered
or threatened species
Special places
Area
Quality
Ecological properties that
relate to the special or legally
protected properties
e.g., National Parks, National
Wildlife Refuges, Great Lakes
(a)Generic ecological assessment endpoints for which EPA has identified existing policies and precedents (in
particular, the specific entities listed in the third column). Bold indicates protection by federal statute.
Source: EPA's Generic Ecological Assessment Endpoints (GEAE) for Ecological Risk Assessment^
April 2004
Page 23-18
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Exhibit 23-7. Essential Ecological Attributes and Reporting Categories
Landscape Condition
• Extent of ecological system/habitat types
• Landscape composition
• Landscape pattern and structure
Biotic Condition
• Ecosystems and communities
- Community extent
- Community composition
- Trophic structure
- Community dynamics
- Physical structure
• Species and populations
- Population size
- Genetic diversity
- Population structure
- Population dynamics
- Habitat suitability
• Organism condition
- Physiological status
- Symptoms of disease or trauma
- Signs of disease
Chemical and Physical Characteristics
(Water, Air, Soil, and Sediment)
• Nutrient concentrations
- Nitrogen
- Phosphorus
- Other nutrients
• Trace inorganic and organic chemicals
- Metals
- Other trace elements
- Organic compounds
• Other chemical parameters
- pH
- Dissolved oxygen
- Salinity
- Organic matter
- Other
• Physical parameters
Ecological Processes
• Energy flow
- Primary production
- Net ecosystem production
- Growth efficiency
• Material flow
- Organic carbon cycling
- Nitrogen and phosphorus cycling
- Other nutrient cycling
Hydrology and Geomporphology
• Surface and groundwater flows
- Pattern of surface flows
- Hydrodynamics
- Pattern of groundwater flow
- Salinity patterns
- Water storage
• Dynamic structural characteristics
- Channel/shoreline morphology, complexity
- Distribution/extent of connected floodplain
- Aquatic physical habitat complexity
• Sediment and material transport
- Sediment supply/movement
- Particle size distribution patterns
- Other material flux
Natural Disturbance Regimes
• Frequency
• Intensity
• Extent
• Duration
Source: U.S. EPA. 2002. A Framework for Assessing and Reporting on Ecological Condition(W)
April 2004
Page 23-19
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Exhibit 23-8. Example Problem Formulation Summary
1. Management Objective
• Bald eagle (entity), local population size (attribute), should be stable (desired state)
2. Assessment Endpoints
• Bald eagle (entity), reproduction (measurable attribute)
• Bald eagle (entity), chick survival (measurable attribute)
3. Exposure Scenario
• Sediment -> pore water -> benthic invertebtrates -> forage fish -> bald eagle
4. Risk Hypothesis
• Dose of chemical X to adult bald eagles from consumption of fish is less than a level known to
cause adverse effects on reproductive ability
- Mechanism: Chemical X damages reproductive organs (or interferes with egg shell
development)
• Dose of chemical X to bald eagle chicks (passed to them by their parents) is less than a level
known to adversely affect their survival
- Mechanism: Chemical X accumulating in egg lipids is a metabolic toxin to the developing
embryo
5. Metrics of Exposure
• Concentration of chemical X in fish
• Dose of chemical X received through consumption of fish
6. Measure of Effect
• TRV for chemical X (NOAEL or LOAEL) where adult reproduction was an endpoint
• TRV for chemical X (NOAEL or LOAEL) where chick survival (mortality) was and endpoint
7. Measure of Characteristics
• Proximity of bald eagle nest site to potentially contaminated foraging areas
• Proximity of alternative (non-contaminated) foraging areas to the nest site
8. Risk Characterization
• HQ = Oral Intake of chemical X/TRV (separate calculations for adults and chicks)
April 2004 Page 23-20
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23.4 Tiered Ecological Risk Assessments
One of the key elements in the ecological risk assessment process is deciding if and when further
analysis is warranted. As with human health risk assessment, EPA recommends a tiered
approach to ecological risk assessment/1' Each of these tiers follows the basic three steps
(problem formulation, analysis, and risk characterization) but with varying levels of complexity
in the assessment and with varying requirements for resources. Examples of the three tiers of
ecological risk assessment approaches are described briefly below.
• Screening-Level ecological risk assessments provide a general indication of the potential for
ecological risk (or lack thereof) and may be conducted for several purposes including: (1) to
prioritize COPECs based on their relative environmental behavior (e.g., relative potential for
bioaccumulation or to exhibit chronic toxicity) or determine their relative contribution to the
overall risk estimate; (2) to estimate the likelihood that a particular ecological risk exists; (3)
to identify the need for additional data collection efforts; or (4) to focus more detailed
ecological risk assessments where warranted. Screening assessments often use simplified
conservative assumptions in place of detailed modeling. For example, concentrations in
aquatic invertebrates or fish might be estimated from the modeled or measured water
concentrations (obtained as part of a multipathway human health risk assessment) and
available bioconcentration factors (BCFs) or bioaccumulation factors (BAFs). Another
example is the comparison of maximum sediment and water concentrations to screening level
TRVs. A screening level assessment, while abbreviated, is nonetheless a complete risk
assessment. Therefore, each assessment should include documentation supporting the risk
characterization and uncertainty analysis. Some examples of screening level TRVs used in
screening level ecological risk assessments are available from EPA's draft Ecological Soil
Screening Level Guidance (http://www.epa.gov/superfund/programs/risk/ecorisk/
guidance.pdf) and EPA Region 4 (http://www.epa.gov/region4/waste/ots/ecolbul.htm).
• More Refined assessments are generally used to: (1) identify and characterize the current and
potential threats to the environment from an air toxics release; (2) evaluate the ecological
impacts of alternative emissions control or abatement policies; and (3) establish emissions
levels that will protect those natural resources at risk. A more refined assessment may
contain a more intensive evaluation than a screening level assessment, and usually employs
multipathway analysis to estimate if, and to what extent, ecological receptors (e.g., an oyster
fishery, a wild duck population, or a unique wetland community) may be exposed. The
exposure and potential impact are characterized and evaluated against predetermined
assessment endpoints (i.e., edibility of oysters, sustainability of the duck population,
maintenance of the integrity of the wetland community). This tier may be iterative. For
example, a multipathway analysis using conservative assumptions may first be performed to
identify whether any of the COPECs emitted from the sources in an area pose a potentially
significant concern to one or more ecological receptors. If so, a more detailed multipathway
risk assessment, using more site-specific data, may be performed. From this last stage a
detailed characterization of the environmental risks is developed.
• Probabilistic assessments are used to increase the strength of the predictive evaluation of
ecological risks, as well as help better evaluate distributions of observational data for an
ecological risk assessment. Screening-level and more refined assessments usually utilize
simplified point estimates in the development of a risk characterization, while the
April 2004 Page 23-21
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probabilistic tier of assessment uses probability distributions as inputs. Therefore, this tier
generally can yield risk estimates that allow for a more complete characterization of
variability and uncertainty. Although probabilistic assessments generally are resource-
intensive, they may be especially valuable in situations when the risks are close to a policy
threshold or if the management decisions, if implemented, would require significant
expenditures.
^ "N
Additional Reference Materials
EPA has developed extensive technical and policy guidance on how ecological risk assessments
should be planned and performed. These are available at EPA's "Tools for Ecological Risk
Assessment" website http://www.epa.gov/superfund/programs/risk/tooleco.htm.
• EPA's Guidelines for Ecological Risk Assessment, April 1998. This document expands upon and
replaces the earlier 1992 Framework for Ecological Risk Assessment.
• EPA's Ecological Risk Assessment Guidance for Superfund (ERA GS): Process for Designing and
Conducting Ecological Risk Assessments, Interim Final, June 1997. This document includes
processes and steps for use in ecological risk assessments at Superfund sites. This document
supersedes the 1989 RAGS, Volume II, Environmental Evaluation Manual, Interim Final.
Supplements to ERAGS include the Eco Updates (Intermittent Bulletin Series, 1991 to present),
which provide brief recommendations on common issues for Superfund ecological risk
assessments. The approaches and methods outlined in the Guidelines and in ERAGS are generally
consistent with each other.
• Risk Assessment Guidance for Superfund (RAGS): Volume 1-Human Health Evaluation Manual
(Part D, Standardized Planning, Reporting, and Review of Superfund Risk Assessments), June
2001. This guidance specifies formats that are required to present data and results in baseline risk
assessments at Superfund sites; many of these formats are useful for air toxics ecological risk
assessments.
• Policy Memorandum: Guidance on Risk Characterization for Risk Managers and Risk Assessors,
F. Henry Habicht, Deputy Administrator, Feb. 26, 1992. This policy requires baseline risk
assessments to present ranges of risks based on "central tendency" and "high-end" exposures with
corresponding risk estimates.
• Policy Memorandum: Role of the Ecological Risk Assessment in the Baseline Risk Assessment,
Elliott Laws, Assistant Administrator, August 12, 1994. This policy requires the same high level of
effort and quality for ecological risk assessments as commonly performed for human health risk
assessments at Superfund sites.
• Policy Memorandum: EPA Risk Characterization Program, Carol Browner, Administrator, March
21, 1995. This policy clarifies the presentation of hazards and uncertainty in human health and
ecological risk assessments, calling for clarity, transparency, reasonableness, and consistency.
• Issuance of Final Guidance: Ecological Risk Assessment and Risk Management Principles for
Superfund Sites. Stephen D. Luftig for Larry D. Reed, October 7, 1999. This document presents
six key principles in ecological risk management and decision-making at Superfund sites; these
principles are also useful for air toxics ecological risk assessments.
April 2004 Page 23-22
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References
1. U.S. Environmental Protection Agency. 1998. Guidelines for Ecological Risk Assessment.
Risk Assessment Forum, Washington, D.C., April 1998. EPA/630/R095/002F. Available at:
http ://cfpub. epa. gov/ncea/cfm/recordisplay.cfm?deid= 12460.
2. U.S. Environmental Protection Agency. 1999. Residual Risk Report to Congress. EPA-
453/R-99-001. Available at: http://www.epa.gov/ttn/oarpg/t3/reports/risk_rep.pdf.
3. U.S. Environmental Protection Agency. 1995. Ecological Risk and Decision Making
Workshop. December 1995. EPA 230/B96/004B.
4. Moore, D.W.J., et al. 1999. A probabilistic risk assessment of the effects of methylmercury
and PCBs on mink and kingfishers along East Fork Poplar Creek, Oak Ridge, Tennessee,
USA. Environmental Toxicology and Chemistry 8:2941-2953.
5. Suter II, G.W., et al. 2000. Ecological Risk Assessment of Contaminated Sites. Lewis
Publishers, Boca Raton, FL. (see pages 228-231).
6. U.S. Environmental Protection Agency. 2001. Planning for Ecological Risk Assessment:
Developing Management Objectives (External Review Draft). Risk Assessment Forum,
Washington, D.C., June 2001. EPA/630/R01/001A. Available at:
http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=20683
7. U.S. Fish and Wildlife Service. 2003. National Wetlands Inventory Maps. Available at:
http://nwi.fws.gov.
8. U.S. Environmental Protection Agency. 1992. Framework for Ecological Risk Assessment.
Risk Assessment Forum, Washington, D.C., February 1992. EPA/630/R92/001.
9. U.S. Environmental Protection Agency. 2003. Generic Ecological Assessment Endpoints
(GEAE) for Ecological Risk Assessment. Risk Assessment Forum, Washington, B.C.,
October 2003. Available at: http://cfpub.epa.gov/ncea/raf/recordisplay.cfm?deid=55131.
10. U.S. Environmental Protection Agency. 2002. A Framework for Assessing and Reporting on
Ecological Condition. Science Advisory Board, Washington, B.C., September 2002. EPA-
SAB-EPEC-02-009A Available at: http://www.epa.gov/sab/pdf/epec02009a.pdf.
11. U.S. Environmental Protection Agency. 1985. Guidelines for Deriving Natural Numerical
Water Quality Criteria for the Protection of Aquatic Organisms and Their Uses. Office of
Water Regulations and Standards, Washington, B.C. EPA/822/R85/100. Available at:
http://vosemite.epa.gOv/water/owrccatalog.nsf/0/3fab714d53e9ae5385256b0600723bd37Ope
nBocument
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Chapter 24 Analysis: Characterization of Ecological
Exposure
Table of Contents
24. 1 Introduction
24.2 Characterization of Exposure [[[ 1
24.2. 1 Quantifying Releases [[[ 3.
24.2.2 Estimating Chemical Fate and Transport .................................... 3_
24.2.2.1 Physical and Chemical Parameters ............................ 3_
24.2.2.2 Multimedia Modeling ...................................... 3_
24.2.2.3 Multimedia Monitoring ..................................... 4
24.2.3 Quantifying Exposure [[[ 5
24.2.3.1 Metrics of Exposure ........................................ _5
24.2.3.2 Dimensions of Exposure .................................... 7
24.2.3.3 Exposure Profile .......................................... 9
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24.1 Introduction
As noted in the previous chapter, the analysis step of ecological risk assessment includes both
characterization of exposures and characterization of ecological effects. This chapter describes
the approaches and methods used for exposure characterization. Chapter 25 discusses the
approaches and measures used for characterization of ecological effects. The discussion in this
chapter is based largely on EPA's Guidelines for Ecological Risk Assessment^ Readers are
referred to that document for a more complete discussion of available approaches and methods.
24.2 Characterization of Exposure
Ecological exposure refers to the contact of an ecological receptor with an air toxic through
direct or indirect exposure pathways. As with human health risk assessment, characterization of
ecological exposure should initially evaluate (in the problem formulation phase) all exposure
pathways that are potentially complete. Unlike human health exposure, ecological risk
assessments will generally identify a limited number of specific metrics of exposure to actually
quantify since it is not usually possible to evaluate all exposure pathways for all the species or
other ecosystem attributes present in any given study area. Initially the assessors will generally
consider all exposure pathways broadly, but then identify the assessment endpoints which will
lead to a specific and narrowly defined set of exposure pathways to actually study in depth.
Ecological exposure pathways that are generally important for air toxics include all pathways
where contaminants are taken up directly from environmental media (e.g., air, soil, sediment, and
surface or rain water) for lower trophic level organisms (including plants) and ingestion of
contaminated plant or animal food items for higher trophic level receptors. Pathways that may be
important in specific cases include foliar and root uptake by plants, deposition and dermal
exposure pathways, and ingestion via grooming, preening, and food consumption.
Once the specific set of exposure pathways to be studied are determined (and the matching
assessment endpoints that are to be assessed are determined), characterization of ecological
exposure is based initially on information derived from modeling and/or existing monitoring
data. Later, additional modeling and/or site-specific empirical information may be obtained. The
objective of the exposure characterization is to produce a summary exposure profile that
identifies the exposed ecological entity, describes the course a stressor takes from the source to
that entity (i.e., the exposure pathway), and describes the intensity and spatial and temporal
extent of co-occurrence or contact (see Section 24.2.4.3). The exposure profile also describes the
influence of variability and uncertainty on exposure estimates and reaches a conclusion about the
likelihood that exposure will occur. Exhibit 24-1 provides a list of questions that can help define
the specific information needed to characterize exposure.
Exposure characterization includes the following steps, each of which is discussed in a separate
subsection below:(1)
• Quantifying releases of contaminants of potential ecological concern (COPEC);
• Estimating chemical fate and transport via modeling and/or monitoring;
• Quantifying exposure (e.g., exposure concentrations and dietary intakes);
• Evaluating uncertainty; and
• Preparing documentation.
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Exhibit 24-1. Questions to Ask Concerning Source, Stressor,
Exposure, and Ecosystem Characteristics
Source and Stressor Characteristics
• What is the nature of the source(s) (e.g., point vs. nonpoint vs. mobile sources)?
• What is the intensity of the Stressor (e.g., the dose or concentration of a chemical)?
• What is the chemical form of the Stressor and its lability as a function of local physical-chemical
conditions?
• What is the mode of action? How does the Stressor impact organisms or ecosystem functions?
• How does the Stressor come into contact with a receptor (transport)?
Exposure Characteristics
• With what frequency does a stressor release occur (e.g., is it episodic or continuous; is it subject to
daily, seasonal, or annual periodicity)?
• What is the duration of release and exposure? How long does the stressor persist in the
environment (e.g., what is its half-life)?
• What is the timing of exposure? When does it occur in relation to critical organism life cycles or
ecosystem events (e.g., reproduction, lake overturn)?
• What is the spatial scale of exposure? Is the extent or influence of the stressor local, regional,
global, habitat-specific, or ecosystem-wide?
• What is the distribution? How does the stressor move through the environment (e.g., fate and
transport)?
Ecosystems Potentially at Risk
• What are the geographic boundaries of the study area? How do they relate to functional
characteristics of the ecosystem?
• What are the key abiotic factors influencing the ecosystem (e.g., climatic factors, geology,
hydrology, soil type, water quality)?
• Where and how are functional characteristics driving the ecosystem (e.g., energy source and
processing, nutrient cycling)?
• What are the structural characteristics of the ecosystem (e.g., species number and abundance,
trophic relationships)?
• What habitat types are present?
• How do these characteristics influence the susceptibility (sensitivity and likelihood of exposure) of
the ecosystem to the stressor(s)? For example, what portion of the receptor's home range is in the
area of impact?
• Are there unique features that are particularly valued (e.g., the last representative of an ecosystem
type)?
• What is the landscape context within which the ecosystem occurs?
Source: EPA Guidelines for Ecological Risk Assessment
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24.2.1 Quantifying Releases
The process used to quantify releases of air toxics for purposes of ecological risk assessment is
identical to that for the human health analyses (see Chapter 7).
24.2.2 Estimating Chemical Fate and Transport
The process and methods used to estimate chemical fate and transport generally are similar to
those used for multipathway human health risk assessments. Key differences and special
considerations are highlighted in the subsections that follow.
24.2.2A Physical and Chemical Parameters
The same physical and chemical parameters identified in Chapter 17 affect the persistence of air
toxics in the environment and their potential to accumulate in ecological food webs. Additional
considerations are specific to ecological risk assessment.
• The bio concentration factors (BCFs) and bioaccumulation factors (BAFs) used to
characterize ecological exposure may be different than corresponding factors used for the
human health exposure assessment. For example, wildlife may eat different species of
fish/shellfish than humans; these may have different BCFs or BAFs. Also, whole-fish BCFs
or BAFs are used for ecological exposure rather than those specific to the parts of the fish
people normally eat (e.g., fillets).
• Chemical speciation (e.g., for metals such as mercury) may be an important determinant of
exposure and bioavailablity.(a)
• Fate and transport analysis may need to examine a wider range of lower-trophic level
organisms to assess impacts to the communities and ecosystems of interest as well as to
develop exposure estimates for ecological food webs.
24.2.2.2 Multimedia Modeling
As with human health exposure assessment, some combination of multimedia modeling and
monitoring is generally used for ecological exposure assessment. The appropriate mix of
modeling and monitoring will depend on the level of assessment and the risk management goals.
Modeling is relatively easy and inexpensive to implement and can be used to evaluate not only
risks from current levels of contamination, but also how risks might change over time (e.g.,
concentrations of persistent bioaccumulative hazardous air pollutant [PB-HAP] compounds in
fish may slowly increase over time in the presence of a continuous release) or as a result of
aEPA's Science Policy Council is embarking on the development of an assessment framework for metals.
The first step in the process is formulation of an Action Plan that will identify key scientific issues specific to metals
and metal compounds that need to be addressed by the framework, potential approaches to consider for inclusion in
the framework (including models and methods), an outline of the framework, and the necessary steps to complete the
framework.
April 2004 Page 24-3
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potential changes in land use (a change in land use might alter a number of habitat factors that
influence the number and identity of ecological receptors). The modeling approach, however,
has inherent uncertainties, which may lead to either over- or underestimates of exposure.
Model choices range from simple, screening-level procedures that require a minimum of data to
more sophisticated methods that describe processes in more detail, but require a considerable
amount of data. The same multimedia models used for the multipathway human health exposure
assessment generally can be used for at least part of the ecological exposure assessment (e.g., the
same models can be used to estimate concentrations in abiotic media at specific locations,
whether for human health or ecological exposure assessment). However, choice of specific
exposure points or areas may differ due to the focus on ecological receptors, as will the specific
food webs being evaluated. Specific models may also be configured in ways that facilitate
ecological exposure assessments. For example, TRIM (Total Risk Integrated Methodology)
includes a fate, transport, and ecological exposure model (TRIM.FaTE) which simulates
multimedia pollutant transfers and ecological receptor exposures in an ecosystem of interest (see
Part in).(2) However, other approaches (e.g., Multiple Pathways of Exposure) are not specifically
designed for ecological exposure assessment).
24.2.2.3 Multimedia Monitoring
The term monitoring in ecological risk assessment can also be more broadly used to mean
collection of any type of empirical field data for the assessment (e.g., plant counts and spatial
distribution in an assessment area). The use of monitoring in ecological risk assessment can
serve a number of purposes. For example, if there is a need to reduce uncertainties in the
predictive modeling approach, monitoring can be performed in various media and biota in the
study area. As with human health exposure assessment, monitoring can be used to confirm or
calibrate predictive modeling estimates of contaminant concentrations in media or biota.
For higher-tier risk assessments, monitoring for ecological exposures also may include site-
specific toxicity or bioaccumulation studies, in which test organisms are exposed to the actual
mixtures of contaminants from within the study area to develop site-specific and
chemical-specific toxicological and/or bioaccumulation relationships (See Chapter 25).
However, poorly designed sampling or toxicological evaluations of environmental media from
the site may not allow a definitive identification of the cause of adverse response. For example,
receptor abundance and diversity as demographic data reflect many factors (e.g., habitat
suitability, availability of food, and predator-prey relationships). If these factors are not properly
controlled in the experimental design of the study (e.g., through use of a comparison site or a
gradient design that examines effects along a two-dimensional gradient downwind of sources),
conclusions regarding chemical stressors can be confounded. In addition, monitoring may not
provide sufficient information to develop estimates of potential risks should land use or exposure
change in the future.
Monitoring techniques for ecological exposure characterization may differ from those used for
multipathway human health exposure assessment. In particular, different species or components
of the food web maybe of concern. For example, large invertebrates such as dragonfly larvae
often are a focus for ecological exposure assessments because they are important components of
surface water ecosystems as well as key prey items for both aquatic (e.g., fish) and terrestrial
(e.g., birds) predators.
April 2004 Page 24-4
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Example Consideration in Monitoring: Soil Sampling for Ecological Risk Assessments
The depth over which surface soils are sampled should reflect the type of exposure expected in the
study area, the type of receptors expected in the study area, the depth of biological activity, and the
depth of potential contamination. For example, if exposures to epigeic (surface dwelling) earthworms
are a concern, concentrations in the first few inches of soil are most relevant. On the other hand, if a
burrowing mammal is of concern, concentrations at a depth of two or more feet may need to be
estimated. Careful consideration of the size, shape, and orientation of sampling volume is important
since they have an effect on the reported measured contaminant concentration values/3' Selection of
sampling design and methods can be accomplished by use of the Data Quality Objectives (DQO)
process discussed in Chapter 7. Additional soil sampling guidance that maybe consulted includes
EPA's Preparation of Soil Sampling Protocols: Sampling Techniques and Strategies (4) and Guidance
for Data Usability in Risk Assessment.^
24.2.3 Quantifying Exposure
Three elements are important components of quantifying exposure: the specific metrics of
exposures that are to be used, the dimensions of exposure, and the exposure profile. Each is
described in a separate subsection below. These estimates can be produced by some models such
as TRIM.FaTE.(6)
24.2.3.1 Metrics of Exposure
Depending on the specific receptors and pathways of concern, ecological exposure is quantified
generally in one of three ways.(1)
• Exposures to abiotic media may be evaluated using contaminant media concentrations as the
exposure concentrations - that is, concentrations of air toxics in soil, sediment, and/or
surface water at the exposure points. This is because the ecological toxicity reference levels
(TRVs) used to characterize risk are based on laboratory studies that directly relate
environmental concentrations in these media to adverse ecological impacts (e.g., a laboratory
study that dissolves known concentrations of a chemical in water and measures adverse
responses in the invertebrates or fish living in that water - the resulting concentration in water
that shows no effect is then compared to modeled or monitored concentrations of the
chemical in study area surface water).
• Exposures via the ingestion route of exposure may be evaluated using the average daily dose
(ADD), generally expressed as mg of chemical per kg of body weight per day (mg/kg-d). The
general formula(b) for calculating ADD for ecological receptors is similar to that used for
human health ingestion exposure:(1)
m
ADDpof = ^ (Cfr X FRk X MRk) (Equation 24-1)
The TRIM.FATE model'6' can output estimates of ingestion intake at user-designated time points in a
dynamic simulation, and as an average over a user-designated period, as well as estimates for steady-state simulation.
April 2004 Page 24-5
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where
ADD pot = Potential average daily dose, expressed in units of mg/kg-day.
Chemical-related variable:
Ck = Average contaminant concentration in the kth type of food, expressed in units
of mg/kg (wet weight)
Variables that describe the exposed ecological receptor population (also termed "wildlife
exposure factors "):
FRk = Fraction of intake of the kth food type that is from the contaminated area (unitless).
NIRt = Normalized ingestion rate of the kth food type of a wet-weight basis, expressed in
kg food/kg body-weight-day.
m = Number of contaminated food types
Exposure factors can be found in the EPA Wildlife Exposure Factors Handbook.(1)
Contaminant concentration (Ck) is commonly estimated with the use of multimedia models.
In some situations (e.g., a higher tier of analysis), Ck in food has been measured directly at the
point of contact where exposure occurs. An example is the use of food collected from the
mouths of nestling birds to evaluate exposure to pesticides through contaminated food.
Although such measurements can be difficult to obtain, they reduce the need for assumptions
about the frequency and magnitude of contact.
• Exposures to some stressors are evaluated using uptake. Some stressors must be internally
absorbed to exhibit adverse effects. For example, a contaminant that causes liver tumors in
fish must be absorbed and reach the target organ to cause the effect. Uptake is evaluated by
considering the amount of stressor internally absorbed by an organism and is a function of the
following:
- Chemical form of the contaminant (speciation);
- Medium (sorptive properties or presence of solvents);
- Biological membrane (e.g., integrity, permeability); and
- Organism (e.g., sickness, active uptake).
Because of interactions among these factors, uptake will vary on a study-specific basis. Uptake
is usually assessed by modifying an estimate of the exposure concentration indicating the
bioavailable fraction (i.e., the proportion of the stressor that is available for uptake) actually
absorbed (e.g., monomeric aluminum is generally bioavailable to certain aquatic receptors while
polymeric aluminum generally is not). Absorption factors and bioavailability measured for the
chemical, ecosystem, and organism of interest are preferred. Internal dose can also be evaluated
using a physiologically-based pharmacokinetic (PBPK) model or by measuring biomarkers or
residues in receptors.
When using a tiered approach, conservative assumptions generally are used at the screening
level. Exhibit 24-2 presents examples of conservative assumptions; these are described in more
detail in EPA's Guidelines for Ecological Risk Assessment.^
April 2004 Page 24-6
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Exhibit 24-2. Examples of Conservative Assumptions for Ecological Exposure Estimation
Exposure Factor
Area-use factor (factor related to home range
and population density)
Bioavailability
Life stage
Body weight
Food ingestion rate
Dietary composition
Assumed Value
1 00 percent (organism lives completely within area of
highest exposure concentrations)
1 00 percent
most sensitive life stage
minimum possible
maximum possible
1 00 percent of diet consists of the most contaminated
dietary component
The use of conservative assumptions should be informed by study -specific information. For example,
assuming 100 percent for area-use factor and diet would not be appropriate if study-specific
information indicates otherwise (e.g., the receptor is only present in the assessment area part of the
year). Similarly, use of the most sensitive life stage would only be appropriate if that life stage were
reasonably expected to be exposed to the chemical.
24.2.3.2 Dimensions of Exposure
Three dimensions are considered when quantifying exposure: intensity, time, and space.
• Intensity. Intensity is generally expressed as the amount of chemical contacted per day.
Intensity may be affected by a number of factors, including the concentration of the chemical
in various media and biota and chemical form (e.g., speciation), which may affect toxicity,
bioavailabilty, and/or bioconcentration.
• Time. The temporal dimension has aspects of duration, frequency, and timing. For air toxics
assessments, intensity and time may sometimes be combined by averaging intensity over
time. Due to the emphasis on persistence and bioaccumulation, the focus of the ecological
exposure characterization for air toxics is generally on chronic (long-term) exposures. In
using predictive modeling to estimate exposure concentrations, an average annual
concentration generally is sufficient, at least for screening-level analyses. An exception
would include situations where the release and the presence of ecological receptors are both
periodic (e.g., releases are much higher in the spring and summer, when ecological receptors
are more abundant and active). If using predictive modeling to develop estimates of the
average daily dose (ADD), the duration of time modeled generally should be sufficient for
concentrations of air toxics in the media and biota of concern to reach equilibrium. If the
models indicate that equilibrium is not reached, the duration of time modeled generally
should be at least as long as the period of time over which releases are likely to occur (e.g.,
the design life of a specific facility). Timing is particularly important if the exposure
coincides with a sensitive life stage of the receptor organism.
April 2004
Page 24-7
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• Space. Space is important because ecological risk assessments generally focus at the
population level or higher (e.g., community, ecosystem). Therefore, space is a measure of the
total fraction of the population, community, or ecosystem that is potentially exposed - a
factor that will impact the overall risk characterization. Space is generally expressed in terms
of areas (e.g., hectares, acres, square meters) that exceed a particular chemical threshold
level. However, another important spatial consideration is the fraction of the overall habitat
type that is potentially affected. At larger spatial scales, the shape or arrangement of
exposure may be an important issue, and area alone may not be the appropriate descriptor.
Geographic Information Systems (GIS) have greatly expanded the options for analyzing and
presenting the spatial dimension of exposure (see Part VII of this reference manual for more
information about GIS). Several recent papers discuss ways to incorporate spatial
considerations in ecological risk assessments/8'
Sometimes, temporal and spacial considerations must both be considered together. For example,
in the case of acidic deposition, the andromous fish species in Maryland and other middle-
Atlantic states have a special risk scenario. Specifically, their spawning run occurs at the same
time when the weather pattern changes in the late winter and early spring from a coastal to a
continental pattern. This increases acidic deposition to the headwaters where the spawning
occurs and the eggs and hatchlings are at the most vulnerable part of their life cycle.
Using Spatial Information in Ecological Exposure Assessment
Many terrestrial organisms that might be evaluated
in an ecological risk assessment are mobile. Where
these populations spend their time depends on the
locations of habitats necessary to provide food,
breeding sites, and protection from predators.
Behaviors such as migration also affect locations of
receptor populations. Screening-level assessments
usually assume that the ecological receptors of
interest reside at the locations of the highest
exposures modeled In subsequent tiers of analysis,
the assessor may spatially refine the exposure
estimate by considering the habitat use and foraging
areas of the receptor(s) of interest. GIS land cover
and land use information can be used to estimate
where an ecological receptor is likely to reside or
breed. For example, EPA's Western Ecology Division of the National Health and Environmental
Effects Laboratory developed a model called Program to Assist in Tracking Critical Habitat
(PATCH), which can be used to generate "patch-by-patch" descriptions of landscapes, assessments of
the number, quality, and spatial orientation of breeding sites, and map-based estimates of the
occupancy rate. In the example output shown here, the medium grey areas denote
significant/acceptable habitat and the lighter gray (or light green) areas denote areas suitable for
breeding. This information can be used to identify where the ecological receptors are likely to reside
or breed, and the modeled exposure concentrations at those locations can be used in the risk
characterization calculations. The PATCH software and user's guides are available at:
http://www.epa.gov/wed/pages/models/patch/patchmain.htm.
Example PATCH Output.
April 2004
Page 24-i
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24.2.3.3 Exposure Profile
The final product of the ecological lr^ I- 4 ,, ,, ,, „ I, ~ \
. Questions Addressed by the Exposure Proiile
exposure assessment is an exposure
How may exposure occur?
What may be exposed?
How much exposure may occur?
When and where may exposure occur?
•9
How may exposure vary?
How uncertain are the exposure estimates?
What is the likelihood that exposure will occur?
profile. Exposure is generally described
in terms of intensity, space, and time, and
in units that can be combined with the
ecological effects assessment (see Chapter
25). The exposure profile identifies the
receptor and describes each exposure
pathway as well as the intensity, spatial
extent, and temporal extent of exposure.
The exposure profile also describes the
impact of variability and uncertainty on exposure estimates and reaches a conclusion about the
likelihood that exposure will occur. Depending on the risk assessment, the exposure profile may
be a written stand alone document or a module of a larger document. In either case, the objective
is to ensure that the information needed for risk characterization has been collected, evaluated,
and presented in a clear, concise, and transparent way. The exposure profile also provides an
opportunity to verify that all of the important exposure pathways identified in the conceptual
model (i.e., those that support an evaluation of the assessment endpoints) were evaluated.
24.2.3.4 Evaluating Variability and Uncertainty
The exposure profile described in the previous section should aid understanding of how exposure
can vary depending on receptor attributes (exposure factors) or stressor levels. Variability can be
described qualitatively, by using a distribution or by describing where a point estimate is likely to
fall on a distribution. EPA policy recommends the use of both central tendency and high-end
exposure estimates .(9)
The exposure profile also should summarize important uncertainties (e.g., lack of knowledge),
including:
• Identification of key assumptions and how they were addressed;
• Discussion (and quantification, if possible) of the magnitude of modeling, sampling, and/or
measurement error;
• Identification of the most sensitive variables influencing the exposure estimate; and
• Identification of which uncertainties can be reduced through additional data collection,
modeling, or analysis (e.g., in a subsequent tier of analysis).
Professional judgment often is needed to determine the uncertainty associated with information
taken from the literature and any extrapolations used in developing a parameter to estimate
exposures. All assumptions used to estimate exposures should be stated, including some
description of the degree of bias possible in each. Where literature values are used, an indication
of the range of values that could be considered appropriate also should be indicated. The
uncertainty and variability associated with ecological effects criteria must also be taken into
April 2004 Page 24-9
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consideration. A more thorough description of how to deal with variability and uncertainty in the
risk assessment process is provided in Chapter 31.
References
1. U.S. Environmental Protection Agency. 1998. Guidelines for Ecological Risk Assessment.
Risk Assessment Forum, Washington, D.C., April 1998. EPA/630/R095/002F. Available at:
http://cfpub.epa. gov/ncea/cfm/recordisplay. cfm?deid= 12460.
2. U. S. Environmental Protection Agency. Total Risk Integrated Methodology (TRIM).
Documentation is available at: http://www.epa.gov/ttn/FERA/urban/trim/trimpg.html.
3. U.S. Environmental Protection Agency. 2000. Draft Ecological Soil Screening Level
Guidance. Office of Emergency and Remedial Response, Washington, B.C., July 10, 2000.
4. U.S. Environmental Protection Agency. 1992. Guidance for Data Useability in Risk
Assessment (Part A). Office of Emergency and Remedial Response Publication 9285.7-09A,
PB92-963356, Washington, D.C., April 1992.
5. U.S. Environmental Protection Agency. 1992. Preparation of Soil Sampling Protocols:
Sampling Techniques and Strategies. Office of Research and Development, Washington,
D.C. EPA/600/R92/128.
6. U. S. Environmental Protection Agency. 2002. Total Risk Integrated Methodology.
TRIM.FaTE Technical Support Document. Volume 1: Description of Module. EPA-453/R-
02-01 la; Volume 2: Description of Chemical Transport and Transformation Algorithms.
EPA/453/R-02/011b. Evaluation of TRIM.FaTE. Volume 1: Approach and Initial Findings.
EPA/453/R-02/012; TRIM.FaTE User's Guide. Office of Air Quality Planning and
Standards, Research Triangle Park, NC. These documents and information are available at:
http://www.epa. gov/ttn/fera/trim_fate .html#current_user.
7. U.S. Environmental Protection Agency. 1993. Wildlife Exposure Factors Handbook. Office
of Research and Development, Washington, D.C. EPA/600/R93/187. Available at:
http ://cfpub. epa. gov/ncea/cfm/wefh. cfrn? ActType=de fault.
8. Freshman, J.S., and Menzie, C.A. 1996. Two wildlife exposure models to assess impacts at
the individual and population levels and the efficacy of remedial actions. Human and
Ecological Risk Assessment 2:481-498.
Hope, B.K. 2001. A case study comparing static and spatially-explicit ecological exposure
analysis methods. Risk Analysis 21:1001-1010.
Linkov, I., Burmistrov, D., Cura, J., and Bridges, T.S. 2002. Risk-based management of
contaminated sediments: Consideration of spatial and temporal patterns in exposure
modeling. Environmental Science and Technology 36:238-246.
9. U.S. Environmental Protection Agency. 1992. Guidance on Risk Characterization for Risk
Managers and Risk Assessors. National Center for Environmental Assessment. Risk
Assessment Council, Washington, D.C. February 1992.
April 2004 Page 24-10
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Chapter 25 Analysis: Characterization of Ecological
Effects
Table of Contents
25. 1 Introduction
25.2 Ecological Response Analysis [[[ 1
25.2.1 Stressor- Response Analysis ............................................... 1
25.2.1.1 Ecological Effect Levels .................................... I
25.2.1.2 Selection of TRVs for a Particular Assessment .................. 7
25.2.1.3 Stressor- Response Curves .................................. H
25. 2.1. 4 Species Sensitivity Distribution .............................. 1J_
25.2.2 Linking Measures of Effects to Assessment Endpoints ........................ 12
25.3 Stressor-Response Profile [[[ 16.
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25.1 Introduction
As noted in the previous chapter, the analysis step of ecological risk assessment includes
characterization of exposures and characterization of ecological effects. Chapter 24 described
the approaches and methods used for exposure characterization. This chapter describes the
approaches and measures used for characterization of ecological effects. The discussion in this
chapter is based largely on EPA's Ecological Risk Assessment Guidelines^ Readers are referred
to that document for a more complete discussion of available approaches and methods.
The methodology used to characterize ecological effects is generally similar to that used for
human health toxicity assessment. One of the distinctive features of ecological effects
characterization relates to the more general management goal of protecting a receptor population
or community rather than a single individual. This has led to the development of water,
sediment, and soil quality criteria that are designed to protect the communities of organisms that
inhabit surface waters and soils. It also provides the option of using a distribution or range of
values to characterize chemical toxicity (an option not generally available in human health risk
assessment).
Characterization of ecological effects involves describing the potential effects resulting from
exposure to a stressor, linking these effect to the assessment endpoints identified during problem
formulation, and evaluating the stressor-response relationship (i.e., how the effects will change
with varying stressor levels). The characterization begins by evaluating effects information to
specify the resulting effects, verifying that these effects are consistent with the assessment
endpoints, and confirming that the conditions under which the effects occur are consistent with
the conceptual model. Once this has been done, the effects characterization involves two
additional steps: (1) performing an ecological response analysis, and (2) developing a stressor-
response profile which also contains an analysis of uncertainty and variability. Each of these
additional steps is discussed in a separate section below.
25.2 Ecological Response Analysis
Ecological response analysis examines three primary elements: identifying stressor-response
relationships, establishing causality, and determining the linkages between measurable ecological
effects and assessment endpoints. Each is described in a separate subsection below.
25.2.1 Stressor-Response Analysis
Stressor-response analysis for ecological effects is functionally similar to dose-response analysis
for human health effects (e.g., see Chapter 12). The specific stressor-response relationship(s)
used in a given risk assessment depend on the scope and nature of the assessment as defined in
the problem formulation and reflected in the analysis plan. Three types of stressor-response
relationships are commonly used: point estimates, stressor-response curves, and cumulative
distribution functions. Each of these is discussed in a separate subsection below.
25.2.1.1 Ecological Effect Levels
Ecological effect levels are point estimates of an exposure associated with a given effect (e.g., a
concentration that results in 50 percent mortality in the exposed population, or LC50) used to
April 2004 Page 25-1
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compare with an environmental exposure concentration. Data on the toxicity of a chemical is
usually obtained from laboratory studies in which groups of organisms (e.g., invertebrates,
benthic organisms, plants, earthworms, laboratory mammals, fish) are exposed to varying levels
of the chemical, and one or more responses (endpoints such as survival, growth, reproduction)
are measured. Various statistical methods are used to establish thresholds for adverse ecological
effects associated with acute or chronic exposures. Risk assessors often choose no-effect or low-
effect levels as screening values. Stressor-response relationships may be relatively simple (as
illustrated in Exhibit 25-1) or may be very complex.
Exhibit 25-1. Hypothetical Simple Stressor-Response Relationship
90 -
05
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o;
so -
10 _
LC10 LC50 LC90
Intensity of Stressor (Exposure Concentration)
Hypothetical relationship between intensity of stressor (in this example, concentration of a
chemical in water) and ecological response (in this example, percent mortality of an exposed
population of minnows). Different points on the curve represent, respectively, the
concentration resulting in 10 percent mortality (LC10), 50 percent mortality (LC50), and 90
percent mortality (LC90).
Several specific point estimates are commonly used to characterize ecological effects (Exhibit
25-2):
• Median effect concentrations or doses are those levels that result in effects that occur in 50
percent of the test organisms exposed to a stressor. The median effect level is always
associated with a time parameter (e.g., 24 hours, 48 hours). Because the tests used to derive
median effects levels seldom exceed 96 hours, these values are used primarily to assess acute
(short-term) exposures.
April 2004
Page 25-2
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Exhibit 25-2. Commonly Used Point Estimates
Median effect concentrations or doses (acute exposures)
LC50 Concentration (food or water) resulting in mortality in 50 percent of the exposed organisms
LD50 Dose (usually in dietary studies) resulting in mortality in 50 percent of the exposed organisms
EC50 Concentration resulting in a non-lethal effect (e.g., growth, reproduction) in 50 percent of the
exposed organisms
ED50 Dose resulting in a non-lethal effect (e.g., growth, reproduction) in 50 percent of the exposed
organisms
Low- or no-effect concentrations or doses (chronic exposures)
NOAEL no-observed-adverse-effect-level, the highest dose for which adverse effects are not
statistically different from controls
LOAEL lowest-observed-adverse-effect level, the lowest dose at which adverse effects are
statistically different from controls
no-observed-effect-concentration, the highest ambient concentration for which adverse
effects are not statistically different from controls
lowest-observed-effect concentration, the lowest ambient concentration at which adverse
effects are statistically different from controls
maximum acceptable toxicant concentration, the range of concentrations between the
LOEC and NOEC
GMATC geometric mean of the MATC, the geometric mean of the LOEC and NOEC
NOEC
LOEC
MATC
13
o
Q.
ce
30 -
20 -
f
NOAEC MATC LOAEC
Intensity of Stnessor (Exposure Concentration)
Low- or no-effect concentrations or doses are derived from experimental data using
statistical estimates. The no-effect level is determined by experimental conditions as well as
the variability inherent in the experimental data. Thus, depending on experimental conditions
(e.g., the range of concentrations tested), two separate tests using the same chemical and the
same organism could result in different no-effect levels. Low- or no-effect levels are used
primarily to assess chronic (longer-term) exposures.
April 2004
Page 25-3
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A variety of different types of studies can be / „ . , „ ,. , T^,, , „ . ,
J yr Point Estimates, 1 RVs, and Benchmarks
used to develop ecological stressor-response
relationships, including field studies,
laboratory studies, and microcosm studies
(Exhibit 25-3).
For air toxics, stress-response analysis can
include both primary and secondary effects.
• Primary effects (e.g., lethality, reduced
The terms Toxicity Reference Values (TRVs)
and Ecological Benchmarks are used to describe
those Point Estimates identified or derived for
use in ecological risk assessments. These
particular point estimates may be derived from a
single study (e.g., an NOEC or EC50) or from the
integration of multiple studies (e.g., water quality
criteria). When TRVs or benchmarks are drawn
,, , -i/ut, • i j r- •* from a single study, they are usually set in
growth, neurologica^ehavioral deficits, ., & c \ • , j- , f ,
... , . , , ,, consideration of multiple studies (e.g., from the
impaired reproduction) result from
study most relevant to the purposes and specifics
of the assessment has been selected, or the most
sensitive result among the relevant studies)
exposure of aquatic and terrestrial
organisms to air toxics. An example of a
chronic effect would be reduced
reproduction in a fish species exposed to
air toxics in a surface water body or in a terrestrial bird eating contaminated fish from a small
pond. An extreme example of an acute primary effect might be deaths of birds caused by
inhalation of a particular toxin. Toxic effects on survival, growth, development, and
reproduction might have population-level consequences for a species (e.g., result in local
population extinction over time) and are widely accepted as endpoints for characterizing
ecological risks. In recent years, more subtle effects have been investigated, including those
pertaining to clinical signs of poisoning, immunotoxicity, and even behavioral changes that
might influence survival, growth, development, or reproduction.
• Secondary effects (e.g., loss of prey species in the community) result from the action of air
toxics on supporting components of the ecosystem. These secondary effects occur through
biological interaction of one or more species' populations with individuals or populations
that have been primarily affected. For example, exposure to an air toxic may adversely affect
one or more species of microscopic algae, bacteria, or fungus, which can adversely affect an
ecosystem's nutrient cycling and primary production. This can lead to an alteration in the
abundance, distribution, and age structure of a species or population dependent on these
microscopic organisms, which can then lead to changes in competition and food web
interactions in other species. These ecosystem effects can be propagated to still other
populations, affecting their presence or representation within the ecosystem. A relatively
simple example of secondary effects involves the aerial application of pesticides that
dramatically reduced the population of an aquatic insect. This impact to the insect population
indirectly affects wild ducklings in the ecosystem, which depend on the insects as a food
supply.(2) Although it often is possible to identify the potential for secondary effects,
developing stressor-response functions for secondary effects (e.g., in a manner analogous to
that illustrated in Exhibit 25-2) is not an easy task. A recent paper provides one example of
the evaluation of secondary effects in ecological risk assessment.(3)
The use of the point estimate approach has some potential limitations. The most important is
that the point estimate established by a given study depends on both the range of doses tested and
the statistical power of the study (e.g., the ability to detect an effect if it occurs). For example,
studies with low power (e.g., those with only a few test animals per dose group) tend to yield
NOAEL or NOEC values that are higher than studies with good power (those with many animals
April 2004 Page 25-4
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per dose group). In addition, the choice of some point estimates (e.g., NOEC and LOEC) is
restricted to concentrations that were tested, which may or may not be close to the
environmentally relevant concentrations, and this uncertainty increases as the interval between
doses increases. Finally, it is not always easy to interpret the significance of an exposure that
exceeds some particular point estimate, since the severity and incidence of response depends on
the shape and slope of the exposure response curve (information that is not captured in a point
estimate).
Exhibit 25-3. Types of Ecological Stressor-Response Studies
Laboratory Studies. Most information on ecological stressor-response comes from laboratory
ecotoxicology studies using a generic set of species to represent different components of terrestrial
or aquatic ecosystems. For example, the freshwater crustacean Daphnia, is often used as a
surrogate for all small invertebrates that inhabit surface waters, and various species of minnows are
used as surrogates for fish. Laboratory studies are relatively easy and inexpensive to conduct, and
effects can be directly linked to exposure to a single air toxic. There is uncertainty, however, in
extrapolating the results from standard laboratory species to the wide array of species in the
environment or from the controlled laboratory conditions to the complex conditions that occur in
nature. Additionally, in most cases, laboratory studies are not designed to assess effects on
populations, communities, and ecosystems.
Field Studies. Studies of wildlife, populations, communities, and ecosystems exposed to air toxics
in natural settings can provide valuable information on stressor-response effects. Field data can be
valuable in demonstrating the presence or absence of a cause-effect relationship that can provide a
basis for prioritization or for recognizing the efficacy of a risk reduction action. These studies also
can be used to assess stressor-response relationships for the site-specific mixtures of concern.
However, the study organisms may be exposed to numerous types of stressors (chemical and non-
chemical), and the effects of individual air toxics (and sometimes site-specific mixtures) may be
difficult to isolate. In addition, field studies are conducted infrequently due to the significant time
and resources required. Comparison of the study area to a control area is necessary to evaluate the
potential impact of the chemical release.
Microcosm Studies. Microcosm studies use assemblages of several different taxa and
environmental media in an enclosed experimental system as a surrogate for natural ecosystems.
Such studies can control for some of the uncertainty associated with multiple stressor exposure in
field studies. These studies also may provide information about food web dynamics and the
interactions of populations or organisms. As with field studies, microcosm studies are time and
resource intensive and, therefore, maybe relatively uncommon for air toxic studies.
A variety of point estimates are used in ecological risk assessments. Some are developed from
acute (short-term) exposures; others are developed from chronic (long-term) exposures. Three
general types of point estimates are available for use in ecological risk assessments:
• Community-level criteria. EPA has developed ambient water quality criteria (AWQC) and
sediment quality criteria for the protection of aquatic communities. These values are based
on consideration of a cumulative distribution function (see Section 25.2.1.4). For example,
AWQC are designed to protect 95 percent of all aquatic species in freshwater or marine
environments. Criteria have been developed for both acute and chronic exposures, although
for a limited number of chemicals.
April 2004 Page 25-5
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• Effect levels from laboratory toxicity tests. A variety of aquatic species are routinely used
in ecological toxicity tests, including fathead minnows (a small fish species) andDaphnia (a
tiny freshwater crustacean). Effects of concern can include acute effects such as mortality
(e.g., LD50) as well as chronic effects such as reproduction. Toxicity tests also are available
for terrestrial organisms (e.g., earthworms) and occasionally involve vertebrate species of
wildlife (e.g., the effects of polychlorinated biphenyls (PCBs) have been studied extensively
in mink).
• Effect levels from field bioassays. In some cases, ecological effects are evaluated directly
by exposing test organisms to ambient conditions. This most often is done where complex
mixtures of chemicals are present (e.g., in soils or sediments).
The point estimates employed in ecological risk assessments may be generally termed toxicity
reference values (TRVs).(a) They maybe values taken from individual toxicity studies (e.g.,
NOECs or EC50s)or the result of integration of multiple studies (e.g., water quality criteria).
TRVs may be developed for site-specific ecological receptors, depending on the importance of
those receptors to the local ecosystem, or for an endpoint not previously evaluated. For example,
while some TRVs may be based on survival, growth, and reproductive success of a population,
TRVs protective of a threatened or endangered species, a valuable game species (e.g., trout), or
an ecologically key species (e.g., wolf) might be based on an endpoint that is relevant to
individual organism health (e.g., a neurological deficit) rather than to population maintenance.
On the other hand, TRVs based on higher effect levels (e.g., 20 to 50 percent or higher of the
population is affected) might be appropriate for species for which great functional redundancy
exists in the ecosystem (e.g., different herbaceous plants).(4)
Derivation of TRVs for pathways involving wildlife ingestion would require information on food
ingestion rates for sensitive and highly exposed animal species and information on the degree of
bioaccumulation in appropriate trophic components. Examples of these derivations for aquatic
systems can be found in the Great Lakes Water Quality Initiative (GLWQI) for mercury,
dichlorodiphenyltrichloroethane (DDT), PCBs, and dioxin (2,3,7,8-TCDD)(5) and for terrestrial
systems in the EPA methods of assessing exposures to combustor emissions/6' EPA's Wildlife
Exposure Factors Handbook(7) also provides data, references, and guidance for conducting
exposure assessments for wildlife species exposed to toxic chemicals in their environment.
EPA and other organizations have developed a number of types of TRVs based on data for a
chemical's toxicity to freshwater or saltwater organisms (see Exhibit 25-4). Toxicity data for
longer term or chronic exposures generally will be more useful for an air toxics risk assessment;
however, short term or acute toxicity data may be used for chemicals that lack or have
incomplete chronic data. EPA has in the past used acute values in conjunction with conversion
factors (i.e., acute-to-chronic ratios) to estimate chronic toxicity values, specifically for the
derivation of chronic Ambient Water Quality Criteria and Great Lakes Water Quality Initiative
criteria for aquatic life.
Note that some ecological risk assessment guidance refers to the point estimates of ecological effects
selected for a given assessment as Toxicity Reference Values (TRVs), while others use the term ecological
benchmarks.
April 2004 Page 25-6
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25.2.1.2 Selection of TRVs for a Particular Assessment
In reviewing toxicity studies for potential use in identifying or developing specific TRVs to use
in a given assessment, the following questions should be considered:
• What taxa are used in the study?
• Did the study present any significant methodological difficulties?
• Did the study identify a LOAEL?
• Were the adverse effects seen possibly related to growth and survival, or reproduction and
development?
• Did the study identify a NO AEL?
• Was the study duration appropriate to assess potential effects of chronic exposure?
If the test species are not within the taxonomic group of the ecological receptors of concern, the
study may need to be rejected because the test species are too distantly related to assume similar
physiological responses to a toxic agent.
Many studies maybe of limited use in selection of TRVs. Potential deficiencies include:
• No control group was analyzed, or there was a high incidence of effects in the control group
(applies to laboratory studies);
• No reference area was analyzed, or there was a high incidence of effects in the reference area
(applies to field studies);
• No statistical analysis of results was conducted;
• In the case of fish/shellfish, body burdens were estimated, not measured;
• In the case offish/shellfish, only fillet, carcass (guts, gills, and scales removed), or other body
part concentrations were measured, not the whole body;
• In the case of wildlife, insufficient data were provided to calculate the dose to the animal; and
• Multiple contaminants were present in the experimental studies.
Most environmental contamination concerns for air toxics that persist and bioaccumulate will
tend to be long-term and relatively low-level. As such, the most appropriate toxicity studies are
those evaluating chronic (long-term) toxicity or, if chronic studies are not available, subchronic
(medium-term) exposure durations. Although no one definition of "chronic" is accepted by
human or ecological toxicologists, the general concept is that the duration encompasses a
significant portion of the species life span (e.g., ten weeks for birds and one year for mammals).
"Subchronic" is commonly defined as a 90-day or longer study for mammals and 10 weeks or
fewer for birds. For aquatic bioassays, chronic tests may span multiple generations and assess
sensitive growth or reproductive endpoints. In mammalian and avian tests, the term average
daily dietary dose (e.g., expressed as mg/kg-day) generally implies chronic or subchronic
exposure.(8)
In order to develop TRVs (sometimes termed benchmarks) for avian and mammalian receptors,
Oak Ridge National Laboratory's Toxicological Benchmarks for Wildlife/1!) and some
information from EPA's Integrated Risk Information System(9) can be used (in a more limited
fashion). Information provided in these sources has to be modified using allometric information
available in EPA's Wildlife Exposure Factors Handbook to better represent potential wildlife
species sensitivity.
April 2004 Page 25-7
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Exhibit 25-4. Sources of Ecological TRVs or Benchmarks
Data Source
Available Toxicity
Reference Value(s)
Overview of Data Source and Values
EPA Office of Water
Ambient Water Quality
Criteria (AWQC)
• AWQC Chronic Criteria
• AWQC Acute Criteria
Note: many state water quality
standards are based on AWQC
EPA has developed national recommended water quality criteria for the
protection of aquatic life for approximately 150 pollutants. These
criteria are published pursuant to Section 304(a) of the Clean Water Act
(CWA) and provide guidance for States and Tribes to use in adopting
water quality standards under Section 303(c) of the CWA.
Source: http://www.epa.gov/waterscience/criteria/aqlife.html
Great Lakes Water Quality
Initiative (GLWQI) Criteria
Documents
GLWQI Tier I Criteria
Final Chronic Values (FCVs)
GLWQI Tier I criteria and final chronic values (FCVs) are calculated
under the same guidelines as the Sediment Quality Criteria (SQC).
Draft GLWQI criteria documents were released for public review and
were revised as necessary before they were published as "final."
• Tier I Criteria are designed to be protective of aquatic communities
• FCVs are designed to measure chronic toxicity to aquatic organisms
Source: Final Water Quality Guidance for the Great Lakes System.
Federal Register, Mar. 23, 1995, vol. 60, no. 56, p. 15365-15424
EPA Soil Screening Levels
Soil screening levels
EPA has developed a methodology and initial soil screening levels
protective of ecological receptors.
Source: U.S. Environmental Protection Agency. 2000. Ecological Soil
Screening Guidance (Draft). Office of Emergency and Remedial
Response, Washington, D.C., July 2000.
http://www.epa.gov/superfund/programs/risk/ecorisk/ecossl.htm.
EPA Region 4 Soil Screening
Levels
Soil screening levels
Source: U.S. Environmental Protection Agency. 1995. Supplemental
Guidance to RAGS: Region 4 Bulletins No. 2. Ecological Risk
Assessment. Region IV, Waste Management Division.
http://www.epa.gov/region04/waste/ots/ecolbul.htm
April 2004
Page 25-1
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Exhibit 25-4. Sources of Ecological TRVs or Benchmarks
Data Source
Available Toxicity
Reference Value(s)
Overview of Data Source and Values
Ecotox Thresholds ECO
Update and EPA's
Hazardous Waste
Identification Rule (HWIR)
documents
GLWQI Tier H Criteria
Secondary Chronic Values
(SCVs)
The GLWQI Tier n criteria and SCVs have received some peer review
prior to publication, and 12 of them are included in the HWIR, which
underwent public comment before promulgation. The GLWQI Tier II
methodology calculates SCVs in a similar way to FCVs, but uses
statistically derived "adjustment factors" and has less rigorous data
requirements.
• Tier II Criteria are designed to be protective of aquatic communities
• SCVs are designed to measure chronic toxicity to aquatic organisms
Source: Ecotox Thresholds ECO Update (volume 3, No. 2, January
1996,EPA/540/F-95/038).
ECOTOXicology database
(ECOTOX)
Point Estimates from Chronic
Tests (e.g., EC50, EC10 LC50 or
GMATC)
Point Estimates from Acute
Tests (e.g., LC50)
ECOTOX is a source for locating single chemical toxicity data for
aquatic life, terrestrial plants, and wildlife. ECOTOX was created and
is maintained by EPA's Office of Research and Development and the
National Health and Environmental Effects Research Laboratory's
Mid-Continent Ecology Division. ECOTOX is a source for locating
single chemical toxicity data from three EPA ecological effects
databases: AQUIRE, TERRETOX, and PHYTOTOX. AQUIRE and
TERRETOX contain information on lethal, sublethal, and residue
effects. AQUIRE includes toxic effects data on all aquatic species
including plants and animals and freshwater and saltwater species.
TERRETOX is the terrestrial animal database. It primarily focuses on
wildlife species but the database does include information on domestic
species. PHYTOTOX is a terrestrial plant database that includes lethal
and sublethal toxic effects data. Source: http://www.epa.gov/ecotox.
Sediment Quality Criteria
Varies
EPA and other agencies have developed sediment quality criteria for
the protection of benthic communities. These criteria are highly
specific to regions and bodies of water in the U.S. Regional experts are
the recommended source for appropriate site-specific criteria.
April 2004
Page 25-9
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Exhibit 25-4. Sources of Ecological TRVs or Benchmarks
Data Source
Available Toxicity
Reference Value(s)
Overview of Data Source and Values
Ecological Structure Activity
Relationships (ECOSAR)
Estimated Chronic GMATC
Estimated Acute Data (LC50 or
EC50)
ECOSAR is a computer program that uses structure-activity
relationships (based on available data) to predict the acute and chronic
toxicity of organic chemicals to aquatic organisms. ECOSAR provides
quantitative estimates of chronic values (e.g., GMATC), acute LC50
values, and acute EC50 values for industrial chemicals for several
aquatic species (e.g., fish, daphnia, green algae, mysids). When the
estimated aquatic toxicity value exceeds the water solubility of the
compound, the estimated value is flagged; this situation generally is
interpreted to mean that the chemical has no toxic effects in a saturated
solution. Source: http://www.epa.gov/oppt/newchems/21 ecosar.htm
Exposure-Related Effects
Database (ERED)
Tissue-based effects values for fish
and benthic invertebrates
The U.S. Army Corps of Engineers Exposure-Related Effects Database
(ERED) lists toxicity information for a large number and wide
taxonomic range of fish and shellfish. ERED is constantly being
updated. Source: http://www.wes.army.mil/el/ered/
Jarvinen and AnHey
database
Fish and shellfish exposure and
effects information
The authors assembled a database offish and shellfish exposure and
effect information. Source: Jarvinen and Ankley (1999)(9)
Oak Ridge National
Laboratory (ORNL) Soil
Invertebrate toxicity database
Acute and chronic TRVs for soil
invertebrates and microbial
processes
This report focuses on chemicals found at U.S. Department of Energy
(DOE) sites; however there are overlaps with air toxics (metals and
organics). Source: Efroymson et al. (1997);(8)
http://www.esd.ornl.gov/programs/ecorisk/documents/tml26r21.pdf
ORNL Plant toxicity
database
Acute and chronic TRVs for
terrestrial plants
This report presents a standard method for deriving TRVs, a set of data
concerning effects of chemicals in soil or soil solution on plants, and a
set of phytotoxicity TRVs for 38 chemicals potentially associated with
DOE sites. Source: Efroymson et al. (1997)(8)
ORNL Wildlife toxicity
database
Wildlife NOAEL and LOAELs
This report presents both NOAEL- and LOAEL-based TRVs for
assessment of effects of 85 chemicals on 9 representative mammalian
wildlife species and 11 avian wildlife species.
Source: Sample et al. (1996)(10)
April 2004
Page 25-10
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25.2.1.3 Stressor-Response Curves
One way to resolve some of the limitations in the TRV approach is to fit a mathematical equation
to the available exposure-response data and describe the entire stressor-response curve. Data
from individual experiments may be used to develop curves and point estimates both with and
without associated uncertainty estimates. The advantages of curve-fitting approaches include
using all of the available experimental data, the ability to interpolate to values other than the data
points measured, and an improved ability to extrapolate to values outside the range of
experimental data (e.g., for a low- or no-effect level). Curve-fitting often is used to extrapolate
from observed effects levels to develop estimates of NOAELs, NOECs, and/or GMATCs.
Stressor-response curves can be developed using any convenient data fitting software, but EPA
has developed a software package specifically designed for this type of effort. This software is
referred to as the Benchmark Dose Software (BMDS). More information on this software can be
found on the National Center for Environmental Assessment's webpage.(11) A disadvantage of
curve fitting is that the number of data points required may not always be available (e.g.,
especially for toxicity tests with wildlife species)
25.2.1.4 Species Sensitivity Distribution
In some cases, risk management decisions may also consider community-level effects as well as
population-level or sub-population effects (one example is the Ambient Water Quality Criteria
for the protection of aquatic life discussed in Section 25.2.1.1). That is, a stressor might be
considered to be below a level of concern for the sustainability of a community if only a small
fraction of the total number of exposed species are affected. In this case, toxicological responses
may be best characterized by the distribution of toxicity values across species. This is called a
Species Sensitivity Distribution (SSD). The SSD approach is generally used for communities
of aquatic receptors, since all of the different species that make up the community (e.g., all fish,
benthic invertebrates, aquatic plants, and amphibians that reside in a stream) will be exposed to
approximately the same concentration of contaminant in the water.
The process for generating an SSD consists of the following steps:
(1) Select an appropriate type of endpoint (e.g., lethality, growth, reproduction), and select an
appropriate type of point estimate from the exposure-response curve for each species. For
example, the TRV might be the LC50 for lethality or the EC20 for growth. The key
requirement is that the SSD be composed of TRVs that are all of the same type, not a
mixture.
(2) Collect all reliable values for that type of TRV from the literature for as many relevant
species as possible. When more than one value is available for a particular species, either
select the value that is judged to be of highest quality and/or highest relevance, or combine
the values across studies to derive a single composite value for each species. It is important
to have only one value per species to maintain equal weighting across species.
(3) Characterize the distribution of values across species with an appropriate SSD. Note that
there is no a priori reason to expect that an SSD will be well characterized by a parametric
distribution, so both parametric and empirical distributions should be considered.
April 2004 Page 25-11
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Once an SSD has been developed, the fraction of species in the exposed community that maybe
affected at some specified concentration may be determined either from the empirical distribution
or from the fitted distribution. These distributions can help identify stressor levels that affect a
minority or majority of species.
A limiting factor in the use of SSDs is the amount of data needed as inputs. SSDs also can be
derived from models that use Monte Carlo or other methods to generate distributions based on
measured or estimated variation in input parameters for the models.
25.2.2 Linking Measures of Effects to Assessment Endpoints
As noted in Chapter 23, assessment endpoints f I ~,_ , ~. ^
. r Examples oi Extrapolations
express the environmental values of concern
Between taxa (e.g., minnow to rainbow trout)
Between responses (e.g., mortality to growth
or reproduction)
From laboratory to field
Between geographic areas
Between spatial scales
From data collected over a short time frame to
longer-term effects
for the risk assessment; however they cannot
always be measured directly. For example,
the assessment endpoint may be maintaining a
healthy population of trout in a lake, but
measures of effect (e.g., toxicity tests) were
conducted on different species (e.g., fathead
minnows). Where there is a lack of time,
monetary resources, or practical means to
acquire more data, extrapolations may be the
only way to bridge the gap in available data. Two general approaches are used for such
extrapolations:
• Empirical extrapolations or process models. Empirical extrapolations use experimental or
observational data; process-based approaches rely on some level of understanding of the
underlying operations of the system of interest.
• Professional judgment. This is not as desirable as empirical or process-based approaches,
but it is the only option when data are lacking. However, professional judgment can be
credible, provided it has a sound scientific basis.
One of the most common types of extrapolations is that of effects observed in the laboratory
(e.g., toxicity tests) to those observed in the field. Exhibit 25-5 highlights the general questions
to consider when performing such an extrapolation.
When conducting field sampling or other monitoring studies, it sometimes is difficult to identify
exposure-response relationships. However, there are a number of reasons why a relationship
between a chemical and a toxic response in a natural system may not be apparent (Exhibit 25-6).
Therefore, the lack of an observed exposure-response relationship does not disprove that one or
more air toxics caused an apparent toxic effect. These sources of variation should be considered
during planning and scoping, but may not become apparent until field studies have begun.
April 2004 Page 25-12
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Exhibit 25-5. Questions to Consider When Extrapolating from Effects
Observed in the Laboratory to Potential Effects in Natural Systems
Exposure Factors
• How will environmental fate and transformation of the air toxic affect exposure in the field?
• How comparable are exposure conditions and the timing of exposure?
• How comparable are the routes of exposure?
• How do abiotic factors influence bioavailability and exposure?
• How likely are preference and avoidance behaviors in the receptors of concern?
• How does life-stage affect exposure?
Effects factors
• What is known about the biotic and abiotic factors controlling populations of the receptors of
concern?
• To what degree are critical life-stage data available?
• How may exposure to the same or other stressors in the field have altered organism sensitivity?
Empirical approaches are derived from experimental data or observations. They commonly are
used when adequate effects data are available, but the understanding of the underlying
mechanisms, action, or ecological principles is limited. Two types of empirical approaches are
generally used:
• Uncertainty factors are derived numbers that are divided into measure of effects values to
derive an estimated level of stressor that should not cause adverse effects to the assessment
endpoint. An example might be an uncertainty factor of 10 to convert an acute LC50 value
into a presumed NOAEL. Uncertainty factors should be used with caution, especially when
used in an overly conservative fashion, as when chains of factors are multiplied together
without sufficient justification.
• Allometric scaling is used to extrapolate the effects of a chemical stressor on one species to
another species. Allometry is the study of change in the proportions of various parts of an
organism as a consequence of growth and development. Processes that influence
toxicokinetics (e.g., renal clearance, basal metabolic rate, food consumption) tend to vary
across species according to allometric scaling factors that can be expressed as a nonlinear
function of body weight. Allometric scaling factors are commonly used for human health
toxicity assessments (see for example Chapter 12), but have not been applied as extensively
to ecological effects.
When sufficient information on stressors and receptors is available, process-based approaches
such as population or ecosystem process models may be used. Process models allow information
on individual effects (e.g., mortality, growth, reproduction) to be extrapolated to potential
alterations in specific populations, communities, or ecosystems. Such models are particularly
useful in evaluating hypotheses about the duration and severity of impacts from a stressor on an
assessment endpoint (e.g., species diversity) that cannot be tested readily in a laboratory. Two
types of process-based models are commonly used:
April 2004 Page 25-13
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Exhibit 25-6. Reasons Why Contaminant Concentrations in Ambient Media
May Not Be Correlated with Toxicity of Those Media
Variation in bioavailability
• Due to variance in medium characteristics
• Due to variance in contaminant age among locations (contaminants deposited to soil and sediments
may become less bioavailable over time due to sequestration)
• Due to variance in transformation or sequestration rates among locations
Variation in the form of the chemical (e.g., ionization state)
Variation in the concentration over time or space (i.e., samples for analysis may not be the same as
those tested)
• Spatial heterogeneity
• Temporal variability (e.g., aqueous toxicity tests last for several days but typically water from only
one day is analyzed)
Variation in the composition of releases (concentrations of components of releases other than the
individual air toxic that is believed to be the principal toxicant may vary over space and time, thereby
obscuring the relationship)
Variation in co-occurring contaminants (concentrations of contaminants from upgradient
[background] sources may vary over time)
Inadequate detection limits (if detection limits are too high, gradients of toxic effect may be
observed even when the chemicals are at the "not detected" levels)
Variation in toxicity tests
• Inherent variation
• Variation due to variance in medium characteristics (e.g., hardness, organic matter content, pH)
Source: Guidelines for Ecological Risk Assessment
• Single-species population models describe the dynamics of a finite group of individuals
through time. They have been used extensively in ecology and fisheries management to
assess the impacts of power plants and toxic chemicals on specific fish populations.
• Community and ecosystem models are particularly useful when the assessment endpoint
involves structural (e.g., community composition) or functional (e.g., primary productivity)
elements or when secondary effects are of concern.
Exhibit 25-7 provides further discussion of process-based models, highlighting a few models that
have been applied in ecological risk assessment.
April 2004 Page 25-14
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Exhibit 25-7. Process-based Model Applications in Ecological Risk Assessment
Process-based models can help the assessor understand the potential significance of toxicant effects to
the population structure, and ecosystem models can help determine whether the effect may result in
secondary effects on other species in the system that are linked in the food web or on overall
ecosystem functions. Pastorok et al.(12) review a number of population, and community and ecosystem
models, as well as software that implement these models.
Population models typically deal with the dynamics of the abundance or distribution of a single
species, sometimes with explicit descriptions of endpoints in time and space. These models can be
categorized as scalar abundance, life history, individual-based, and metapopulation models. The first
two types of models are highlighted here:
• Scalar abundance models, which represent populations as a single scalar dimension without a
breakdown of population age structure, are frequently used in screening assessments. These
models include Malthusian population growth models and logistic population growth models.
• Life history models estimate population characteristics such as survival rates and fecundity as a
function of age or size/morphological state. These models are important because toxicants can
have a differential impact on different demographic sections of the same species. These models
include deterministic and stochastic age- or stage-based models, which are implemented in
software by programs such as RAMAS-Age®, -Stage®, -Metapop®, or -Ecotoxicology®; and ULM*'.
Community and Ecosystem models are intended to describe ecological systems composed of
interacting species. These models incorporate species dynamics and specific biological interactions
(predator-prey, competition, dependence) to predict ecosystem endpoints such as species richness or
the productivity of a multi-species assemblage. Pastorok et al. categorize these models as food web,
aquatic, and terrestrial models.
• Food web models capture feeding relationships between all or some species in an ecological
community, thus determining population dynamics as well as identifying key exposure pathways
for bioaccumulative chemicals. These models include predator-prey models and population-
dynamic food chain models, which are implemented in software such as RAMAS Ecosystem*,
Populus®, and Ecotox.
• Aquatic ecosystem models are spatially aggregated models that represent biotic and abiotic
structures in combination with physical, chemical, biological, and ecological processes in rivers,
lakes, reservoirs, estuaries, or coastal ecosystems. A number of models exist for each type of
aquatic ecosystem. The standard water column model orSWACOM® requires the use of laboratory
data to predict changes in the parameters of an entire ecosystem. The extrapolation is
accomplished with knowledge of toxicological modes of action, and by simulation of the effects of
a toxic substance across different trophic levels according to the relationship between nutrients,
phytoplankton, zooplankton, and fish. AQUATOX (http://www.epa.gov/ost/models/aquatox/)
predicts the fate of various pollutants, such as nutrients and organic chemicals, and their effects on
the aquatic ecosystem, including fish, invertebrates, and aquatic plants. The Comprehensive
Aquatic Simulation Model (CASM) is a bioenergetics-based food web model that includes
phytoplankton, periphyton, macrophytes, zooplankton, benthic invertebrates, fish, bacteria, and
cyanobacteria.
• Terrestrial ecosystem models represent biotic and abiotic components in deserts, forests,
grasslands, or other terrestrial environments, and often include physical, chemical, biological, and
ecological processes. The primary endpoints of these models include the abundance of individuals
within species or guilds, biomass, productivity, and food-web endpoints such as species richness
or trophic structure.
April 2004 Page 25-15
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25.3 Stressor-Response Profile
The final product of an ecological response analysis is a summary profile in the form of a written
document or a component of a larger process model. The stressor-response profile should
address the following questions:
• What ecological entities are affected? These may include single species, populations, general
trophic levels, communities, ecosystems, or landscapes.
• What are the nature of the effects? The nature of effects should be germane to the assessment
endpoints. For example, if a single species is affected, the effects should represent
parameters (e.g., growth, reproduction) appropriate for that level of organization.
• Where appropriate, what is the time scale for recovery? Short- and long-term effects should
be reported as appropriate.
• How do changes in measures of effects relate to changes in assessment endpoints (see
Section 25.2.2 above)?
• What is the uncertainty associated with the analysis (see Section 25.4)?
25.4 Evaluating Variability and Uncertainty
The stressor-response profile described in the previous section should include an explicit
description of any uncertainties associated with the ecological response analysis. If it was
necessary to extrapolate from measures of effect to the assessment endpoint, both the
extrapolation and its basis should be described. Similarly, if a TRV was calculated, the
extrapolations, assumptions, and uncertainties associated with its development should be
described. The discussion also should include any information about known or potential
variability in a stressor-response profile (e.g., among different species or taxa).
Professional judgment often is needed to determine the uncertainty associated with information
taken from the literature and any extrapolations used in developing a parameter to estimate
stressor-response. All assumptions used to develop stressor-response relationships and TRVs
should be stated, including some description of the degree of bias possible in each. Where
literature values are used, an indication of the range of values that could be considered
appropriate also should be indicated. A more thorough description of how to deal with
variability and uncertainty in the risk assessment process is provided in Chapter 31.
References
1. U.S. Environmental Protection Agency. 1998. Guidelines for Ecological Risk Assessment.
Risk Assessment Forum, Washington, D.C., April 1998. EPA/630/R095/002F. Available at:
http://cfpub.epa. gov/ncea/cfm/recordisplay. cfm?deid= 12460.
2. Sheehan, P.J., Baril, A., Mineau, P., Smith, O.K., Harfenist, A., and Marshall,W.K. 1987.
The Impact of Pesticides on the Ecology of Prairie-nesting Ducks. Technical Report Series,
No. 19. Canadian Wildlife Service, Ottawa.
April 2004 Page 25-16
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3. Lohman, K. et. al. 2000. A probabilistic analysis of regional mercury impacts on wildlife.
Human and Ecological Risk Assessment 6:103-130.
4. Lawton, J.H. and Brown, V.K. 1994. Redundancy in Ecosystems: Biodiversity and
Ecosystem Function. Springer-Verlag, Berlin Heidelberg, Germany, pp. 255-270.
5. U.S. Environmental Protection Agency. 1995. Great Lakes Water Quality Initiative Criteria
Documents for the Protection of Wildlife: DDT, Mercury, 2,3,6,8-TCDD, PCBs. Office of
Water, Washington, D.C. EPA/820/B95/008.
U.S. Environmental Protection Agency. 1995. Final Water Quality Guidance for the Great
Lakes System. Final Rule. Federal Register 60:15366, March 23, 1995.
6. U.S. Environmental Protection Agency. 1993. Addendum to the Methodology for Assessing
Health Risks Associated with Indirect Exposure to Combustor Emissions. Office of Research
and Development, Washington, DC. EPA/600/AP93/003.
7. U.S. Environmental Protection Agency. 1993. Wildlife Exposure Factors Handbook. Office
of Research and Development, Washington, D.C. EPA/600/R93/187. Available at:
http ://cfpub. epa. gov/ncea/cfm/wefh. cfrn? ActType=de fault.
8. Efroymson, R.A., Will, M.E., and Suter II, G.W. 1997. Toxicological Benchmarks for
Contaminants of Potential Concern for Effects on Soil and Litter Invertebrates and
Heterotrophic Processes: 1997 Revision. Oak Ridge National Laboratory, Oak Ridge TN.
ES/ER/TM-126/R2.
9. U.S. Environmental Protection Agency. 2003. Integrated Risk Information System. Office of
Research and Development, National Center for Environmental Assessment. Available at:
http ://www. epa. gov/iris/.
10. Sample, B.E., Opresko, D.M., and Suter II, G.W. 1996. Toxicological Benchmarks for
Wildlife: 1996 Revision. June 1996. ES/ER/TM-86/R3. Available at:
http://www.hsrd.ornl.gov/ecorisk/tm86r3.pdf.
12. U.S. Environmental Protection Agency. 2003. Benchmark Dose Software. National Center
for Environmental Assessment. Available at: www.epa.gov/ncea/bmds.htm.
13. Pastorok, R.A., Bartell, S.M., Person, S., Ginzburg, L.R.(eds). 2002. Ecological Modeling
in Risk Assessment: Chemical Effects on Populations, Ecosystems and Landscapes. Lewis
Publishers, Boca Raton, FL.
April 2004 Page 25-17
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Chapter 26 Ecological Risk Characterization
Table of Contents
26. 1 Introduction
26.2 Risk Estimation [[[ 2
26.2.1 Single-Point Exposure and Effects Comparisons .............................. 2
26.2.2 Comparisons Involving the Entire Stressor-Response Relationship ................ 3.
26.2.3 Comparisons Involving Variability ......................................... 4
26.2.4 Process Models [[[ 4
26.3 Risk Description [[[ 5
26.3.1 Lines of Evidence [[[ 5
26.3.2 Significance of the Effects ................................................ 6
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26.1 Introduction
Similar to human health risk characterization, ecological risk characterization combines
information concerning exposure to chemicals with information regarding effects of chemicals to
estimate risks. The major difference in ecological risk characterization is the necessity for
estimating risks based on individual lines of evidence and then combining them through a
process of weighing the evidence." Another difference is that in human health assessment, we
primarily consider health effects in the bodies of individual people. In ecological assessment, we
consider various "health" issues that can range from actual health effects in the bodies of
individual ecological receptors to something more attuned to the "health" of the ecosystem as
measured by species richness and diversity. This chapter provides an overview of the approaches
and methods used for ecological risk characterization. As before, additional information is
provided in EPA's Guidelines for Ecological Risk Assessment^ and readers are referred to that
document for a more complete discussion of available approaches and methods.
Risk characterization is the final phase of ecological risk assessment and is the culmination of the
planning and scoping, problem formulation, and analysis of predicted or observed adverse
ecological effects related to the assessment endpoints. It is also based on metrics of exposure and
ecosystem and receptor characteristics that are used to analyze air toxics sources, their
distribution in the environment, and the extent and pattern of contact. Risk characterization is
used to clarify the relationships between stressors, effects, and ecological entities, and to reach
conclusions regarding the occurrence of exposure and the likelihood of anticipated effects. The
results of the analysis phase are used to develop an estimate of the risk posed to the ecologically
valued entities that are the focus of the assessment endpoints.(2) After estimating the risk, the risk
estimate is described in the context of the significance of any adverse effects and lines of
evidence supporting their likelihood. Finally, the uncertainties, assumptions, and qualifiers in the
risk assessment are identified and summarized, and the conclusions are reported to risk
managers.
Conclusions presented in the risk characterization should provide clear information to risk
managers in order to be useful for environmental decision making. If the risks are not
sufficiently defined to support a management decision, risk managers may elect to proceed with
another iteration of one or more phases of the risk assessment process. Re-evaluating the
conceptual model (and associated risk hypotheses) or conducting additional studies may improve
the risk estimate.
Characterization of ecological risk includes risk estimation, (usually a quantitative risk estimate;
see Section 26.2), risk description (Section 26.3), and documentation of results (Section 26.4).
"Consistent with EPA's Guidelines for Ecological Risk Assessment,^ the term "lines of evidence" includes
a "weight of evidence" in order to emphasize that both qualitative evaluation and quantitative weighting may be
used.
April 2004 Page 2 6-1
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26.2 Risk Estimation
Several general techniques are available for characterizing ecological risks associated with air
toxics that persist and bioaccumulate. These are divided broadly into single-point comparisons,
comparisons incorporating the entire stressor-response relationship, comparisons involving
variability in exposure and/or effects, and process models. Each is described in a separate
subsection below. EPA's Guidelines for Ecological Risk Assessment1-1 provides additional
discussion and examples of these techniques.
26.2.1 Single-Point Exposure and Effects Comparisons
The simplest approach for comparing exposure and effects estimates for air toxics ecological risk
assessments is the Hazard Quotient (HQ) approach (also referred to as the "quotient method"),
which is similar to that used for human noncancer health risk assessments (see Chapter 13). In
this approach, modeled or measured concentrations of the chemical in each environmental
medium are divided by the appropriate point estimate for ecological effects to yield a HQ for an
individual chemical.
Oral Intake EEC BB
TRY or HQ = or HQ = Option 26-1)
where:
HQ = hazard quotient
Oral Intake = estimated or measured contaminant intake relevant to the oral intake-based
TRV (usually expressed as mg/kg-day)
TRV = Toxicity reference value. This may be in terms of oral intake, media
concentration, or body burden. As described elsewhere, it may be a result of a
single study (e.g., NOAEL) or the result of integration of multiple studies
(e.g., water quality criterion).
EEC = estimated or measured environmental media concentration at the exposure
point (usually expressed as mg/L for water and mg/kg for soil and sediment)
BB = estimated or measured body burden (usually expressed as mg/kg wet weight)
As with human health assessments, the measure of oral intake, EEC, or BB must be in the same
units as the TRV to which the measure is being compared.
As chronic risk will usually "drive" an ecological assessment, the HQ approach will usually be
employed for chronic exposure scenarios using chronic duration TRVs. For initial screening,
conservative exposure factors maybe used (see Exhibit 24-2). As in human health risk
assessment, an HQ greater than one indicates the potential for adverse ecological effects to occur,
but does not predict their occurrence (see Chapter 13).
April 2004 Page 26-2
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When ecological toxicity data for complex mixtures are unavailable, the hazard index (HI)
approach13 may sometimes be used in screening assessments, as scientifically appropriate, to
assess potential ecological risks associated with simultaneous exposure to multiple air toxics.(1)
If the HI approach is used, the assumptions and associated limitations should be clearly
documented. It may often be the case that a single chemical is responsible for the HI exceeding
one, and the assessment can then focus on the HQ for that chemical. In more refined
assessments, an alternative approach may be necessary.
State Water Quality Standards
Pursuant to Section 303 of the Clean Water Act,
States have developed numerical water quality
standards for the protection of aquatic ecosystems.
These standards generally are considered regulatory
requirements that must be met, and often are based
on EPA's Ambient Water Quality Criteria (see
Chapter 25). If persistent, bioaccumulative
hazardous air pollutants (PB-HAPs) enter surface
waters, one way to assess risk is to compare the EEC
to a water quality standard using the HQ approach.
State water quality standards can be accessed via
EPA's national water quality standards database at
http ://www. epa. gov/ost/wqs/.
As with human health assessments, a
number of limitations restrict application
of the HQ approach. While a quotient can
be useful in answering whether adverse
effects are likely to occur or not, it may
not be helpful to a risk manager who
needs to make a decision requiring an
incremental quantification of ecological
hazard. For example, it is seldom useful
to say that a mitigation approach will
reduce the value of a quotient from 25 to
12, since this reduction cannot, by itself,
be clearly interpreted in terms of effects
on an assessment endpoint. Quotients
also may not be the most appropriate
methods for predicting secondary effects
(e.g., bioaccumulation, loss of prey species). Finally, in most cases the quotient does not
explicitly consider uncertainty, such as extrapolation from the test species to the species or
community of concern. Some uncertainties, however, can be incorporated into single-point
estimates to provide a statement of likelihood that the effects point estimate exceeds the exposure
point estimate (see Exhibit 26-l).(1)
26.2.2 Comparisons Involving the Entire Stressor-Response Relationship
If a curve relating the intensity or level of the stressor to the magnitude of response is available
(for example, see Exhibit 25-1), the risk characterization can examine risks associated with many
different levels of exposure. These estimates are particularly useful when the risk management
decision is not based on exceeding a pre-determined reference value or regulatory standard (e.g.,
a state water quality standard). This approach provides a predictive ability lacking in the hazard
quotient approach, and it may be used in screening level assessments or subsequent more refined
risk analyses. Because the slope of the effects curve relates the magnitude of change in effects to
incremental changes in exposure, the ability to predict changes in the magnitude and likelihood
of effects for different exposure scenarios can be used to compare different risk management
options. Also, uncertainty can be incorporated by calculating uncertainty bounds on the stressor-
response or exposure estimates. Limitations to this approach may include: lack of consideration
The HI approach is termed the "quotient addition approach" in EPA's Guidelines for Ecological Risk
Assessment^
April 2004
Page 26-3
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for secondary effects, assuming the exposure pattern used to derive the stressor-response curve is
comparable to the environmental exposure pattern; and failing to consider uncertainties such as
extrapolations from tests species to the species or communities of concern.
Exhibit 26-1. Example Comparison of Point Estimates with Associated Uncertainties
(fl
c
Q
3-
o
CL
Uncertainty around EC
Uncertainty around LCS
Concentration of Air Toxic
Probability that LCsn> EC
26.2.3 Comparisons Involving Variability
If the exposure or stressor-response profiles describe the variability in exposure or effects, then
many different risk estimates can be developed. Variability in exposure can be used to estimate
risks to moderately or highly exposed members of a population being investigated, while
variability in effects can be used to estimate risks to average or sensitive members of
populations. As an example, exposure can vary by life-stage (e.g., exposure maybe greater
during spawning or migration). Likewise, effect may also vary by life-cycle (e.g., hatchlings may
be more sensitive to a chemical than are adults). A major advantage of this approach is its ability
to predict changes in the magnitude and likelihood of effects for different exposure scenarios and
thus provide a means for comparing different risk management options. Limitations include the
increased data requirements compared with previously described techniques and the implicit
assumption that the full range of variability in the exposure and effects data is adequately
represented. In addition, secondary effects are not readily evaluated with this approach. This
risk estimation technique would likely be used in more refined risk assessments. (A discussion
of probabilistic techniques, including Monte Carlo Simulation, is provided in Chapter 31.)
26.2.4 Process Models
Process models are mathematical expressions that represent understanding of the mechanistic
operation of a system under evaluation. They can be useful tools in both analysis and risk
characterization (process models are discussed briefly in Chapter 25). A major advantage of
using process models is the ability to consider "what if scenarios and to forecast beyond the
limits of observed data that constrain approaches based solely on empirical data. Process models
April 2004
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also can consider secondary effects, and in some cases, the combined effects of multiple
stressors. Process model outputs may be point estimates, distributions, or correlations.
However, since process models are only as good as the assumptions on which they are based, the
outputs from these models should be interpreted with care. The lack of knowledge on basic life
histories for many species, and incomplete knowledge about the structure and function of natural
ecosystems are some of the many uncertainties that need to be considered. These models are
complex and, are usually reserved for more refined risk assessments.
Risk Assessment Frontiers: Integrating Human Health and Ecological Risk Assessment
Many tribal cultures view ecological and human health in an integrated way such that they cannot be
easily separated. Similarly, there is some effort (especially in Canada) toward an integration of human
health and ecological assessment, as well as decision-making, in a field known as strategic
environmental assessment/3' This approach has not been applied widely in the United States, and it
remains to be seen how it will develop in the next few years.
The World Health Organization has published approaches to integrating human health and ecological
risk assessments to improve data quality and understanding of cumulative risks for decision making/4'
This approach includes an integrated framework (modified from EPA's guidance)0' and case studies.
EPA, in its Framework for Cumulative Risk Assessment,^ offers a flexible structure for conducting
and evaluating cumulative risk assessment. By "cumulative risk," EPA means "the combined risks
from aggregate exposures to multiple agents or stressors." Agents or stressors may be chemicals, but
they may also be biological agents or physical agents, or an activity that, directly or indirectly, alters
or causes the loss of a necessity such as habitat.
26.3 Risk Description
The results of the risk characterization should be documented in the risk description, which
includes an evaluation of the lines of evidence supporting or refuting the risk estimate(s) and an
interpretation of the significance of the observed and/or predicted effects.
26.3.1 Lines of Evidence
The development of lines of evidence provides both a process and a framework for reaching a
conclusion regarding confidence in the risk estimate. Confidence in the conclusions of a risk
assessment may be increased by using several lines of evidence to interpret and compare risk
estimates. These lines of evidence may be derived from different sources or by different
techniques relevant to adverse effects on the assessment endpoints (e.g., hazard quotients,
modeling results, or field observational studies). There are three principal categories of factors to
consider when evaluating lines of evidence:
1. Data adequacy and quality. Data quality directly influences confidence in the results of a
risk assessment and the conclusions that can be drawn from the study. Specific concerns
include: whether the experimental design was appropriate for the questions being evaluated
in the risk assessment; whether data quality objectives were clear and adhered to; and
whether the analyses were sufficiently sensitive and robust to identify stressor-caused effects
in light of natural variability of the attributes of the ecological receptors of concern.
April 2004 Page 26-5
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2. Relative uncertainty. One major source of uncertainty comes from extrapolations (e.g.,
from one species to another; from one temporal scale to another; from laboratory to field
effects). In general, the greater the number of extrapolations, the greater the uncertainty.
3. Relationship to the risk hypothesis. Finally, the relative importance of each line of
evidence may be determined by how directly they relate to the risk hypothesis developed
during planning and scoping. For example, lines of evidence based on a definitive
mechanism rather than associations alone are likely to be relatively important.
The evaluation of lines of evidence involves more than just listing the evidence that supports or
refutes the risk estimate. Each factor should be examined carefully, and its contribution in the
context of the risk assessment should be evaluated. For example, data or study results are often
not reported or carried through the risk assessment because they are of insufficient quality. If
such data or results are eliminated from the evaluation process, however, valuable information
may be lost with respect to needed improvements in methodologies or recommendations for
further studies.
When lines of evidence do not point toward the same conclusion, it is important to investigate
possible reasons for the disagreements. A starting point is to distinguish between true
inconsistencies and those related to methodology (e.g., statistical powers of detection). For
example, if a model predicts adverse effects that were not observed in the field, it is important to
determine whether the model predictions were unrealistic, or the experimental design of the field
study was inadequate to detect the predicted effects, or both.
26.3.2 Significance of the Effects
In this step, the significance of the observed or estimated changes in the assessment endpoints is
interpreted in light of the lines of evidence evaluated above. In this context, significance refers to
a conclusion as to whether the observed or estimated changes are considered "adverse." Adverse
ecological effects represent changes that are undesirable because they alter valued structural or
functional attributes of the ecological receptors of concern (e.g., the loss of akeystone species).
This determination is difficult and is frequently based on professional judgment. The assessment
of degree of adversity, along with other factors such as the economic, legal, or social
consequences of the ecological change, maybe considered in the risk management decision.
Unless an endangered or threatened species is at issue, society is generally not concerned with the
death of individual plants or animals, and therefore significance is generally assessed at the
population, community, or ecosystem level(s). The following factors maybe used to evaluate the
degree of adversity (see also Exhibit 26-2):
• Nature and intensity of effects. This focuses on distinguishing adverse changes from those
that are within the normal pattern of ecosystem variability or that result in little or no
significant alteration of biota. For example, if survival of offspring will be affected, by what
percentage will it diminish, and is that likely to have a major impact on population dynamics?
It is important to consider both ecological and statistical information in evaluating the nature
and intensity of effects. For example, a small change in a growth rate may not be statistically
distinguishable from natural variation; however, its impact may be more significant for a
population of slowly reproducing fish than for rapidly reproducing algae. When performing a
more refined assessment, it is necessary to compare the potentially impacted ecosystem to a
April 2004 Page 26-6
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non-impacted ecosystem (i.e., a "control" site) so there is a basis for statistical comparisons
between the two systems.
Exhibit 26-2. Examples of Considerations for Determining Ecological Significance
How large is the area where ecological criteria have been exceeded?
What proportion of the habitat is affected at local, county, State, and national levels?
Are the exposure concentrations and ecological criteria above background levels for the area of
interest?
What types of ecological impacts have been associated with this pollutant or similar pollutants in
the past?
Is the criterion or stressor-responsive curve based on high quality data (i.e., is there a high degree
of confidence in the criterion)?
• Spatial and temporal scale. The spatial dimension encompasses both the extent and pattern
of effect as well as the context of the effect within the broader ecosystem or landscape.
Factors to consider include the absolute area affected, the percentage of area affected
compared with a larger area of interest, and the relative importance of the affected area(s) to
the ecological receptors of concern (e.g., are they critical breeding or overwintering areas?).
For air toxics that persist and bioaccumulate, the temporal dimension of concern generally
will be in the years to decades range, although effects in other time frames may be important
in specific cases. Temporal responses for ecosystems may involve intrinsic time lags, so
responses to a stressor (or risk mitigation effort) may be delayed.
• Potential for recovery. Recovery refers to the rate and extent of return of a population or
community to some aspect of its condition prior to exposure to the stressor(s) of concern.
Because ecosystems are dynamic, even under natural conditions, it is unrealistic to expect
that a system will remain static at some level or return to exactly the same state that it was
before it was disturbed. Thus, the "attributes" of a recovered population, community, or
ecosystem should be carefully defined. In general, changes that preclude recovery or result in
long recovery times are more significant than changes that allow rapid recovery. Note that
different components of a community or ecosystem may recover at different rates. For
example, stream chemistry may recover relatively rapidly after removal of a stressor, but re-
establishment of predatory fish populations may take several years or more.
26.4 Risk Characterization Report
The information on estimates of ecological risk, the overall degree of confidence in the risk
estimates, lines of evidence, and the interpretation of the significance of ecological effects
generally is included in a risk assessment or risk characterization report. Exhibit 26-3 lists
the elements that generally are considered in the risk characterization report. A risk
characterization report maybe briefer extensive, depending on the nature of and resources
available for the assessment. The report need not be overly complex or lengthy; it is most
important that the information required to support the risk management decision be presented
clearly and concisely. To facilitate mutual understanding, EPA policy^ requires that risk
characterizations 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." It
describes a philosophy of transparency, clarity, consistency, and reasonableness (TCCR), and
April 2004 Page 26-7
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provides detailed approaches to achieving TCRR. Exhibit 26-4 provides an overview of the
TCRR principles (these are the same principles listed in Chapter 13).
Exhibit 26-3. Possible Risk Characterization Report Elements
Describe risk assessor/risk manager planning results.
Describe the scope of the assessment.
Review the conceptual model and the assessment endpoints.
Describe the measures of effect.
Discuss the major data sources and analytical procedures used.
Review the stressor-response and exposure profiles.
Assign risks to the assessment endpoints, including risk estimates and adversity evaluations.
Review and summarize major areas of uncertainty (as well as their direction) and the approaches
used to address them:
- Discuss the degree of scientific consensus in key areas of uncertainty;
- Identify major data gaps and, where appropriate, indicate whether gathering additional data
would add significantly to the overall confidence in the assessment results;
- Discuss science policy judgments or default assumptions used to bridge information gaps and
the basis for these assumptions; and
- Discuss how the elements of quantitative uncertainty analysis are embedded in the estimate of
risk.
Exhibit 26-4. Transparency, Clarity, Consistency, and Reasonableness Principles
Principle
Definition
Criteria for a Good Risk Characterization
Transparency
Explicitness in the risk
assessment process
Describe assessment approach, 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 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
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26.5 Evaluating Variability and Uncertainty
An important part of the Risk Characterization Report is a discussion and assessment of
variability and uncertainty in all aspects of the ecological risk assessment. Note that ecological
risk assessments are subject to additional sources of uncertainty and variability as compared to
multipathway human health risk assessments. In addition to the uncertainties associated with
multimedia modeling and sampling, the ecological risk assessment involves many decisions
regarding choice of ecological receptors of concern and associated assessment and measures of
effect. Some of these maybe at levels of organization above individual species (e.g.,
communities, ecosystems), where stressor-response relationships are poorly understood. Because
many different species and higher taxonomic groups may be included in the assessment, selection
of many parameter values such as bioconcentration factors, dose-response values, and dietary
intake is more complex and uncertain for the ecological risk assessment as compared to the
human health multipathway risk assessment.
References
1. U.S. Environmental Protection Agency. 1998. Guidelines for Ecological Risk Assessment.
Risk Assessment Forum, Washington, D.C., April 1998. EPA/630/R095/002F. Available at:
http://cfpub.epa. gov/ncea/cfm/recordisplay. cfm?deid= 12460.
2. U.S. Environmental Protection Agency. 1992. Framework for Ecological Risk Assessment.
Risk Assessment Forum, Washington, D.C., February 1992. EPA/630/R92/001.
3. Bonnell, S., and Storey, K. 2000. Addressing Cumulative Effects Through Strategic
Environmental Assessment: a Case Study of Small Hydro Development in Newfoundland,
Canada. Journal of Environmental Assessment Policy and Management 2: 477-499.
4. World Health Organization (WHO). 2001. Approaches to Integrated Risk Assessment.
International Programme on Chemical Safety, Geneva. WHO/ffCS/IRA/01/12. Available at:
http://www.who.int/pcs/emerg_main.html
5. U.S. Environmental Protection Agency. 2002. Framework for Cumulative Risk Assessment.
Office of Research and Development, Washington, D.C., October 2002.
EPA/630/P-02/001A.
6. U.S. Environmental Protection Agency. 2000. Supplementary Guidance for Conducting
Health Risk Assessment of Chemical Mixtures. Risk Assessment Forum, Washington, DC.
EPA/630/R-00/002. Available at:
http ://cfpub. epa. gov/ncea/raf/recordisplay.cfm?deid=2053 3.
April 2004 Page 26-9
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PARTY
RISK-BASED DECISION MAKING
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Introduction to Part V
Part V of this Reference Manual provides an overview of three components of risk-based
decision making.
• Risk Management (Chapter 27) refers to the regulatory and other actions taken to limit or
control exposures to air toxics, including the role of risk management in regulating hazards.
• Community Involvement (Chapter 28) is an integral part of many risk management strategies
because good community involvement helps ensure that the strategy selected will have the
highest likelihood of success. Various levels of community involvement are also required by
many laws.
• Risk Communication (Chapter 29) describes the process of planning the risk assessment
(during scoping) and conveying the results of the risk assessment in a way that meets the
information requirements for the risk management decisions. This chapter discusses the
importance of risk communication, and planning and implementing a risk communication
strategy.
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Chapter 27 Risk Management
Table of Contents
27.1 Introduction 1
27.2 Role of Risk Management in Regulating Hazards 1
27.3 Types of Risk Management Decisions Related to Air Toxics 4
27.4 Use of Risk Estimates in Decision-Making 5
27.5 Process for Making Risk Management Decisions 9
27.5.1 Define the Problem and Put it in Context 9
27.5.2 Analyze the Risks Associated with the Problem in Context 9
27.5.3 Examine Options for Addressing the Risks H
27.5.4 Make Decisions about Which Options to Implement 1_2
27.5.5 Take Actions to Implement the Decisions 13
27.5.6 Conduct an Evaluation of the Action's Results 14
27.6 Information Dissemination 14
References 15
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27.1 Introduction
This chapter introduces risk management, focusing on its role in addressing the risks that air
toxics pose. It provides an overview of the types of risk management decisions related to air
toxics, a discussion of how risks to individuals and populations are presented to the public, and
options for implementing decisions (e.g., regulation, voluntary risk reduction activities).
Specifically, risk management refers to the regulatory and other actions taken to limit or control
exposures to a chemical. Risk assessment, on the other hand, is a tool used to support risk
management decisions by providing quantitative and qualitative expressions of risk, along with
attendant uncertainties. Specifically, the risk assessment conveys a quantitative and qualitative
description of the types of impacts that may occur from exposure to an air toxic, the likelihood
that these impacts will occur given existing conditions, and the uncertainties surrounding the
analysis. Risk management considers these principle factors along with a variety of additional
information (which may include the cost of reducing emissions or exposures, the statutory
authority to take regulatory actions, and the acceptability of control options) to reach a final
decision.
27.2 Role of Risk Management in Regulating Hazards
Risk management may include implicit or explicit policy and value judgments. Therefore, one
would expect there to be differences of opinion concerning what represents an appropriate risk
management action. Even the most basic risk management decision can be highly controversial.
A classic example is the decision(s) needed to answer the question how clean is clean? This
question refers to a risk management decision that must establish a target level to which existing
levels of contamination/pollution should be reduced. Establishing this level is not a trivial
matter. Working through these issues can be complicated by the different values of the
stakeholders and debates over individual perceptions about risk. As discussed below, many
authors and organizations stress the importance of understanding risk management mandates,
options, and concerns throughout the risk assessment process, from the initial problem
formulation steps to the final risk characterization and risk communication. Many of the critical
decisions in structuring the technical risk assessment depend on risk management concerns (e.g.,
what risk management options are feasible, what level of certainty in the risk estimate is
acceptable).
Although the National Academy of Sciences and others stress the distinction between risk
assessment and risk management, they also stress the integration of the two efforts (see Exhibit
27-1). Risk assessments are often designed and conducted with awareness of the risk
management options available to decision-makers and the social, economic, and political context
in which those decisions are to be made. Likewise, periodically reviewing the risk management
options during the risk assessment effort ensures that the results of the risk assessment will
provide meaningful input into the decision-making process. The National Research Council
(NRC) of the National Academy of Sciences (NAS), in their 1983 study entitled Risk Assessment
in the Federal Government: Managing the Process (the "Red Book"),(1) advocated a clear
conceptual distinction between risk assessment and risk management, noting, for example, that
maintaining the distinction between the two would help to prevent the tailoring of risk
assessments to the political feasibility of regulating a chemical substance. However, the NRC
also recognized that the choice of risk assessment techniques could not be isolated from society's
April 2004 Page 27-1
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risk management goals. Ultimately, the risk assessors should be aware of risk management
goals; however, the fundamental science performed in the risk assessment should be impartial
and based on the factual base of information, to the extent possible.
Use of the Term "Safe"
Safe: Condition of exposure under which there is a practical certainty that no harm will result
to exposed individuals (as defined in EPA's Terms of Environment).
Safe: Free from harm or risk (as defined in the Merriam-Webster Collegiate Dictionary).
During government and community interactions and risk communication, it is important to be
sensitive to perceived meanings of the term "safe." Regulators and scientists are often reluctant to use
the term "safe," because many people understand "safe" to mean "zero risk." Ideally, one would like
to eliminate all risks, but this is usually not a realistic expectation. Regulators commonly work to
address the most important risks and decrease them to the level at which they believe the risks are
smaller than the benefits of the activity causing the problem (in this case, risk from exposure to air
toxics). They commonly refer to this level as "acceptably low risk."
However, community members may become frustrated with regulators who are reluctant to use the
term "safe," potentially perceiving the regulators' choice of words as a dodge of the issue. Therefore,
it is important for government representatives to address perceptions of the meaning of safe during
risk communication and, as appropriate, use risk comparisons to help in communicating the concepts
of safe versus acceptably low risk. Information on risk communication is provided in Chapter 29, and
Section 29.4 provides specific information about risk comparisons.
Exhibit 27-1. Illustration of the Integration Between Risk Assessment and Risk Management
« ,
Risk Management
Decision
Planning,
Scoping and
Problem
Formulation
April 2004
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The NRC, in their 1994 report, Science and Judgment in Risk Assessment (the "Blue Book"),(2)
noted that, while the Red Book emphasized the distinction between risk assessment and risk
management, the purpose of separation was not to prevent any exercise of policy judgment when
evaluating science or to prevent risk managers from influencing the type of information that
assessors would collect, analyze, or present. The Blue Book concluded further that the science-
policy judgments that EPA makes in the course of a risk assessment would be improved if there
were more clearly informed by the Agency's priorities and goals in risk management. Protecting
the integrity of the risk assessment, while building more productive linkages to make risk
assessment more accurate and relevant to risk management, is essential.
The integration between risk assessment and risk management also has been emphasized by
Presidential/Congressional Commission on Risk Assessment and Risk Management. In their
Reports Framework for Environmental Health Risk Management and Risk Assessment and Risk
Management In Regulatory Decision-Making (the two-volume "White Book"),(3) the
Commission developed a six-stage integrated framework for environmental health risk
management that can be applied to most situations (Exhibit 27-2):
1. Define the problem and put it in context;
2. Analyze the risks associated with the problem in context;
3. Examine options for addressing the risks;
4. Make decisions about which options to implement;
5. Take actions to implement the decisions; and
6. Conduct an evaluation of the action's results.
Exhibit 27-2. The CRARM Framework for Risk Management
Engage
Stakeholde
Actions ^^^^ Options
April 2004
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The Commission noted that the process of examining risk management options does not have to
wait until the risk analysis is completed, although a risk analysis often will provide important
information for identifying and evaluating risk management options. In some cases, examining
risk management options may help refine a risk analysis. The Commission also recommended
that all of these steps involve stakeholders (see Chapter 28).
When discussing risk management, it is important to consider where and how changes or
interventions may occur in the causal sequence of environmental impacts since interventions may
reduce pollutants a number of ways along the critical path of environmental impacts. For
example, interventions such as changing manufacturing processes, implementing emissions
controls, or influencing worker behaviors that actively reduce exposure may have a positive
mitigating effect on environmental impacts. In the discussion of risk management that follows, it
is critical to keep in mind the range of ways in which environmental risks can be mitigated; it is
up to the risk managers to determine the most feasible and critical "points of entry" along the
path when developing a risk management strategy.
27.3 Types of Risk Management Decisions Related to Air Toxics
Two general categories of risk management
decisions are relevant to air toxics: emissions
control and siting.
• Emissions control. Emissions control
decisions may involve "command-and-
control" decisions (e.g., emissions limits)
or incentives (e.g., tax credits for reduced
emissions). EPA's preference is to
encourage pollution prevention whenever
feasible (see Exhibit 27-3). Emissions
control decisions are most likely to
involve formal risk assessments.
• Siting/locating. These decisions involve
where to locate industrial facilities,
businesses, waste disposal facilities, and transportation routes. Siting decisions are typically
made by S/L/T governments through mechanisms such as zoning, deed restrictions and other
property controls, and in some cases regulation. Many of these decision-making processes
include public involvement in which citizens may seek to influence the final decision. Siting
decisions may involve assessment of environmental impacts pursuant to the National
Environmental Policy Act, other federal statutes, or similar state statutes. Siting decisions
may increasingly involve air toxics risk assessments.
Not All Risk Management
Decisions are Regulatory
Some risk management decisions are made by
EPA or state, local and tribal (S/L/T) regulators
pursuant to specific statutory criteria. However,
government agencies may have limited authority
to impact many other decisions. For example,
some decisions are made by the individuals who
own or operate the facilities that release air
toxics, while others are made by citizens who are
being impacted by emissions. Risk management
decisions may need to consider looking beyond
technological solutions.
April 2004
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Exhibit 27-3. Pollution Prevention Hierarchy
In the Pollution Prevention Act of 1990, Congress established a hierarchy for the handling of pollution
(see graphic). The Act established as United States policy that pollution should be prevented or
reduced at the source whenever feasible, that pollution that cannot be prevented should be recycled in
an environmentally safe manner whenever feasible, and that pollution that cannot be prevented or
recycled should be treated in an environmentally safe manner whenever feasible. Disposal or other
release into the environment should be
employed only as a last resort and pollution Prevention
should be conducted in an
environmentally safe manner.
Pollution prevention is the reduction or
elimination of pollutants at the source. R djn
As defined in the Pollution Prevention
Act, "source reduction" means any
practice which (1) reduces the amount of
any hazardous substance, pollutant, or
contaminant entering any waste stream
, . , Disposal
or otherwise released into the
environment (including fugitive
emissions) prior to recycling, treatment,
or disposal, and (2) reduces the hazards to public health and the environment associated with the
release of such substances, pollutants, or contaminants. It includes equipment or technology
modifications, process or procedure modifications, reformulation or redesign of products, substitution
of raw materials, and improvements in housekeeping, maintenance, training, or inventory control.
Examples of the value of pollution prevention for reducing environmental risks at the community level
are demonstrated by EPA's Environmental Justice through Pollution Prevention (EJP2) grant program.
EPA encouraged community groups, tribes, and local governments to identify environmental problems
and generate potential pollution prevention solutions for their communities.
Source: U.S. Environmental Protection Agency. 2002. EnvironmentalJustice Through Pollution
Prevention Program. Updated July 9, 2002. Available at: http://www.epa.gov/opptintr/eip2/. (Last
accessed April, 2004.)
27.4 Use of Risk Estimates in Decision-Making
Decision-makers have a number of options when deciding what types of risk estimates to
consider as inputs to risk management decisions. Estimates of human health risk generally fall
into two categories, estimated cancer risk and the estimated noncancer hazard magnitude of
exposure concentration or dietary intake greater than a pre-established reference exposure level),
as described in more detail in Chapters 13 and 22. Non-cancer hazard may be considered for
both acute (short-term) and chronic (longer-term) exposures. In some cases, ecological risk may
be a factor in decision-making.
In some situations, risk managers may choose to consider EPA's approach for assessing an
"ample margin of safety." For cancer risks, EPA generally considers incremental risk (or
probability) of cancer for an individual potentially exposed to one or more air toxics. In
protecting public health with an ample margin of safety, EPA strives to provide maximum
feasible protection against risks to health from HAPs by (1) protecting the greatest number of
April 2004 Page 27-5
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persons possible to an individual lifetime risk level no higher than IxlO"6 (one in one million)
and (2) limiting to no higher than approximately 1 x 10"4 (one in ten thousand) the estimated risk
that a person living near a source would have if exposed to the maximum pollutant
concentrations for 70 years. These goals are described in the preamble to the benzene National
Emissions Standards for Hazardous Air Pollutants (NESHAP) rulemaking (54 Federal Register
38044, September 14, 1989) and are the goals incorporated by Congress for EPA's residual risk
program under Clean Air Act (CAA) section 112(f). Exhibit 27-4 describes some of the key
steps in the development of the IxlO"4 to IxlO"6 carcinogenic risk range.
For non-carcinogenic substances, on the other hand, risk managers may consider a reference level
that is developed based on data from laboratory animal or human epidemiology studies (see
Chapter 12), and to which uncertainty factors are applied. The reference level is usually an
exposure level below which there are not likely to be any adverse effects from exposure to the
chemical. Exposures above the reference level may have some potential for causing adverse
effects. This concept may also be applied generally to ecological risks.
Risk estimate options generally revolve around estimates of individual risk, the number of people
at different risk levels (population risk), and occasionally include the expected incidence of
disease in the entire population. Risk estimates can be derived for the current population as
currently distributed in an area or for a population size and geographic distribution that might
occur in the future; similarly, they may focus on risk estimates for persons currently exposed or
possible risks calculated for a hypothetical individual located where exposures are expected to be
relatively high. It is important to note that risk estimates should strive to take into account both
indoor and outdoor exposure to toxics, when possible.
• Risk to a specified individual. Most risk assessments focus on estimating individual risk
rather than the incidence of adverse effects (e.g., numbers of predicted cancer cases per year)
in a population. There are two general estimates of individual risk:
- High-end risk estimates seek to determine a "plausible worst case" situation among all of
the individual risks in the population. This estimate is meant to describe an individual
who, as a result of where they live and what they do, experiences the highest level of
exposure within some reasonable bounds. Reasonable maximum risk estimates are often
defined conceptually as "above the 90th percentile of the population'^4' but not at a higher
exposure level than the person exposed at the highest level in the population. When
calculated using deterministic methods, the high-end individual is calculated by
combining upper-bound and mid-range exposure factors (e.g., an average body weight,
but high-end ingestion rate) so that the result represents an exposure scenario that is both
protective and reasonable, but not higher than the worst possible case.
- Central-tendency risk estimates seek to determine a reasonable "average" or
"mid-range" situation among all of the individual risks in the population. Many risk
management decisions related to exposure to radioactive substances (e.g., in nuclear
power plants) are based on central-tendency risk estimates.
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Exhibit 27-4. Development of the IxlO4 to 1x106 Carcinogenic Risk Range
The 1970 CAA established Section 112 to deal with hazardous air pollutants. Once the EPA
Administrator had identified such a pollutant and "listed" it, he/she was directed to set emission
standards for sources emitting it at levels that would "provide an ample margin of safety to protect the
public health." The regulation of benzene pursuant to Section 112 illustrates the evolution of risk-
based decision-making for carcinogens and the consideration of the "ample margin of safety."
• EPA listed benzene as a HAP in June 1977 and indicated that the "relative risk to the public"
would be considered in judging "the degree of control which can and should be required."
• In 1980, the first round of benzene standards followed the proposed procedures in EPA's 1979
draft airborne carcinogen policy, which reflected a technology-based approach to emission
standard development with a limited role for quantitative risk assessment in establishing priorities
and ensuring that the residual risks following the application of "best available technology" (BAT)
were not unreasonable.
• In 1984, after "weighing all factors," EPA made several changes to the proposed benzene rules,
arguing that the risks were "too small to warrant Federal regulatory action." These decisions were
promptly challenged by the Natural Resources Defense Council, who argued about the
uncertainties in the risk estimates and the inappropriate consideration of cost in regulatory
decisions made under Section 112. The issues raised were similar to litigation already pending on
amendments to the original vinyl chloride standards.
• On July 28, 1987, Judge Robert Bork, writing for the D.C. Circuit Court of Appeals, remanded the
vinyl chloride amendments to EPA, finding that the Agency had placed too great an emphasis on
technical feasibility and cost rather than the provision of an "ample margin of safety" as required
by the statute. The opinion also laid out a process for making decisions, consistent with the
requirements of the law. The Bork opinion held that EPA must first determine a "safe" or
"acceptable" level considering only the potential health impacts of the pollutant. Once an
acceptable level was identified, the level could be reduced further, as appropriate and in
consideration of other factors, including cost and technical feasibility to provide the required
ample margin of safety. The Court also held, however, that "safe" did not require a finding of
"risk-free" and that EPA should recognize that activities such as "driving a car or breathing city
air" may not be considered "unsafe."
• In September of 1989, after proposing several options and receiving considerable public comment,
EPA promulgated emission standards for several categories of benzene sources. EPA argued for
the consideration of all relevant health information and established "presumptive benchmarks" for
risks that would be deemed "acceptable." The goal, which came to be known as the "fuzzy bright
line," is to protect the greatest number of persons possible to an individual lifetime risk no higher
than one in 1,000,000 and to limit to no higher than approximately one in 10,000 the estimated
maximum individual risk. The selection of even "fuzzy" risk targets placed greater emphasis on
the development and communication of risk characterization results.
Source: National Academy of Sciences' Science and Judgment in Risk Assessment (The Blue Book).(2)
April 2004 Page 27-7
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Note that, when calculating deterministic risk estimates, both a high end and central tendency
estimate of risk give the risk manager some sense of the range of risks in the population. When
risks to a population are developed using probabilistic methods, this becomes a moot point, since
the result is a distribution of risks across the population, which necessarily includes information
about the full variability of risk across the population - including both high and central tendency
risks. See Chapter 31 for more information on probabilistic approaches to risk assessment.
• Risk to the total population. Whether or not risk to the total population is considered by
EPA may depend on the regulatory authority provided by the CAA. For example, Section
112(k) of the CAA requires EPA to develop an Urban Air Toxics Strategy to reduce HAPs
from area sources to achieve a 75 percent reduction in cancer incidences attributable to such
sources. Two general types of descriptors are used for population risk. One, sometimes
termed population at risk is derived by determining the number of people in a population
with a particular individual risk level (e.g., "1,340,000 people are exposed at the IxlO"6 level,
and 320 people are exposed at the IxlO"4 level"). This is a useful estimate of the variability
of risk in a population.
• Incidence, another descriptor used for population risk, is an estimate of the total number
(incidence) of adverse effects in a population over a specified time period (e.g., a period of 70
years). A screening approach to deriving this estimate for a 70-year period involves
multiplying the estimate of individual risk (central tendency and/or reasonable maximum) by
the number of persons for which that risk estimate was predicted. For example, in a
population of 200 million persons, an individual cancer risk of 1 x 10"4 (i.e., one in ten
thousand) for everyone in the population would translate to an incidence of hundreds or
thousands of excess cancer cases over a 70-year period (depending on the exposure
assumptions). However, in a small population (e.g., a town of 200 persons), the same
individual cancer risk to everyone would translate to an excess incidence of cancer of less
than one over a 70-year period.
• Present versus future scenarios. Risks may be characterized using present or future
scenarios. Use of present scenarios involves predicting risks associated with the current
exposures to individuals (or populations) that currently reside in areas where exposures are
predicted to occur. For example, a current population risk estimate would use the existing
population within some specified area. The resultant risk estimates are associated with the
presumption that the current exposure conditions exist for the current population over the
period of time associated with the assessment (e.g., into the future). Use of future population
scenarios involves estimating risks associated with exposure conditions to individuals that
might reside, at some future point, in areas where potential exposures may occur (e.g., if a
housing development were built on currently vacant land).
• Potential risk. Risks may be sometimes be characterized for hypothetical exposures. For
example, in a screening air toxics modeling application, a potential risk estimate may be
derived using the location where the maximum modeled exposure concentration occurs,
regardless of whether there is a person there or not. This estimate may be considered along
with the predicted individual risk associated with a currently populated area, such as the MIR,
which reflects risk associated with the maximum exposure concentration at an actual
residence or in a census block with a non-zero population (see Chapter 11).
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27.5 Process for Making Risk Management Decisions
A number of different authors and organizations have identified key steps or factors to consider
in making risk management decisions. The discussion in this section is taken largely from the
risk management framework developed by the Presidential/Congressional Commission on Risk
Assessment and Risk Management.(3) The Commissions's framework has six stages, each of
which is briefly described below. The Commission also noted that the framework is conducted:
• In collaboration with stakeholders; and
• Using iterations if new information is developed that changes the need for or nature of risk
management.
27.5.1 Define the Problem and Put it in Context
The problem/context stage is the most important step in the Risk Management Framework. It
involves:
• Identifying and characterizing an environmental health problem, or a potential problem,
caused by chemicals or other hazardous agents or situations;
• Putting the problem into its public health and ecological context;
• Determining risk management goals;
• Identifying risk managers with the authority or responsibility to take the necessary actions;
and
• Implementing a process for engaging stakeholders.
These steps are all important, but may be conducted in different orders, depending on the
particular situation. For example, when a federal or S/L/T regulatory agency is mandated by law
to take the lead on an air toxics issue, the steps they take often will proceed in the order listed
above, with the identity of the risk managers already clear, since the agency will have assumed
that role from the start. On the other hand, in a community based effort to characterize the
cumulative risk posed by multiple sources of air toxics in a neighborhood, stakeholders might
have to engage in a collaborative stakeholder process first to identify resources as well as risk
managers with the needed authority to act before the other steps can take place.
27.5.2 Analyze the Risks Associated with the Problem in Context
The nature, extent, and focus of a risk assessment should be guided by the risk management
goals. The results of a risk assessment - along with information about public values, statutory
requirements, court decisions, equity considerations, benefits, and costs - all can influence
whether and how to manage the risks.
Risk assessment can be controversial, reflecting the important role that both science and
judgment play in drawing conclusions about the likelihood of effects on human health and the
April 2004 Page 2 7-9
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environment. Often, the controversy arises from what we do not know and from what risk
assessments cannot tell us, because our knowledge of human vulnerability and of environmental
impacts is incomplete, especially at the relatively low levels of chemical exposure commonly
encountered in the general community.
S N
Some Factors to Consider in Defining the Problem for an Air Toxics Risk Assessment
Risk. The specific estimates of risk to be used as inputs to the decision should be defined as
explicitly as possible. Are acute risks (e.g., short-term exposures) the primary concern, or are
exposures over the longer-term more important? Are ecological risks a concern? How certain are
we that our risk estimates are an accurate reflection of true exposure and risk?
Air toxics of concern. What are the primary air toxics of concern? Are they more prevalent in
indoor or outdoor environments? How many individual chemicals contribute to the risks that need
to be managed? Do these chemicals exert their effects independently, or are some acting in a
synergistic (or antagonistic) manner? Are all equally important, or will reducing exposures to a
subset of these air toxics result in adequate risk reduction? How important is it to manage every
chemical of concern versus only those that pose the greatest risk?
Sources. What are the primary sources of the air toxics that need to be managed? Where are these
sources located? How many are there? Are they all equally important, or will controlling a subset
result in adequate risk reduction?
Exposure pathway considerations. What exposure pathways/routes are most important? Are all
equally important, or does a subset represent the greatest risk? Does control of each pathway
require controls over all components of the pathway (e.g., emissions, exposure), or can the
pathway be controlled by controlling a subset of these components?
Amount of emissions reduction desired/achievable. What is the overall target for
emissions/exposure reduction? How does this relate to risk reduction by the estimates identified
above? Will partial reductions result in significant risk reduction, or is it more of an all-or-none
situation? What technologies are available to achieve the desired level of risk reduction? How
much do the various options cost?
Spatial and temporal factors. Are releases of concern limited to a relatively brief period of time,
or do data support the emissions being relatively continuous over a longer period of time? Are the
released toxics specific to a single location or are there several wide-spread emission points?
What is the fate and transport of the released chemicals? How does background risk relate to the
risk reduction strategy?
Data gaps and uncertainties. What are the main sources of uncertainty in the data used in the risk
assessment? How do these uncertainties affect the risk management decision? Will more
information reduce these uncertainties and can the uncertainty be addressed with available time
and resources? Approaches for identifying and managing uncertainties associated with risk
assessment are discussed in Chapters 13 and Part VII.
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27.5.3 Examine Options for Addressing the Risks
This stage of the risk management process involves identifying potential risk management
options and evaluating their effectiveness, feasibility, costs, benefits, unintended consequences,
and cultural or social impacts. This process can begin whenever appropriate after defining the
problem and considering the context. It does not have to wait until the risk analysis is completed,
although a risk analysis often will provide important information for identifying and evaluating
risk management options. In some cases, examining risk management options may help refine a
risk analysis. Risk management goals may be redefined after risk managers and stakeholders
gain some appreciation for what is feasible, what the costs and benefits are, and what
contribution reducing exposures and risks can make toward improving human and ecological
health.
The Commission noted that stakeholders can play an important role in all facets of identifying
and analyzing options. They can help risk managers:
• Develop methods for identifying risk-reduction options;
• Develop and analyze options; and
• Evaluate the ability of each option to reduce or eliminate risk, along with its feasibility, costs,
benefits, and legal, social, and cultural impacts.
Chapter 28 provides an overview of community involvement and its role in risk assessment and
risk management.
mental Excellence and Leadership
Alternative Solutions to Unique Problems
Project XL, which stands for "excellence and Leadership," is a national
pilot program that allows state and local governments, businesses, and
Federal facilities to develop with EPA innovative strategies to test
better or more cost-effective ways of achieving environmental and
public health protection. In January 2001, EPA signed the 50th XL
Final Project Agreement. Although EPA is no longer accepting
proposals for new XL projects, EPA will continue to fulfill each of its
commitments under Project XL and will track and monitor the progress
of each XL pilot for the duration of the project.
See www. epa. gov/proi ectxl for more information.
Supplemental Environmental Projects (SEPs) are part of enforcement
settlements connected with violations of an environmental statutory or
regulatory requirement. As part of the enforcement settlement, a violator
voluntarily agrees to undertake an environmentally beneficial project in
exchange for a reduction in the penalty. See
www.epa.gov/compliance/civil/programs/seps for more information.
Beyond Compliance:
Supplemental Environmental Projects
April 2004
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27.5.4 Make Decisions about Which Options to Implement
In most risk management situations, decision-makers will have a number of options from which
to choose. Which option is optimal depends on the particular situation (and in some cases may
be driven by statutory requirements). The following seven are fundamental characteristics of
sound risk management decision making:
• Base the decision on the best available scientific, economic, and other technical information;
• Be sure the decision accounts for the problem's multisource, multimedia, multichemical, and
multirisk contexts;
• Choose risk management options that are feasible, with benefits reasonably related to their
costs;
• Give priority to preventing risks, not just controlling them;
• Use alternatives to command-and-control regulation, where applicable;
• Be sensitive to political, social, legal, and cultural considerations; and
• Include incentives for innovation, evaluation, and research.
Options to be considered for air toxics fall into the following general categories:
• Regulatory approaches. Pursuant to various sections of the CAA, Congress has authorized
EPA to regulate air toxics. Many S/L/T governments have also authorized agencies to
regulate air toxics. Regulatory approaches include enforceable requirements that identified
sources must meet (or else be subject to legal action, such as fines) as well as
emissions-trading type requirements that focus on controls over sources in total while
allowing flexible emissions among individual sources.
• Voluntary approaches. EPA and other regulatory agencies are looking beyond regulatory
approaches to reduce risks from air toxics. Non-regulatory (voluntary) approaches are
frequently the preferred option in a number of cases. Decision-makers at S/L/T agencies may
not currently have specific regulatory authority to address specific air toxics problems
identified in a risk analysis (particularly in a novel analysis such as a multi-source,
community-based risk assessment). The types of problems identified may not lend
themselves to regulatory solutions (e.g., they may require changes in the behavior of the
exposed population). Voluntary programs may also allow sources to significantly reduce
overall risk at much lower cost than various regulatory options. Various incentives such as
tax reductions or consumer rebates can be used to encourage voluntary responses.
• Permits and related authorities. Permits offer opportunities for both regulatory and
voluntary risk-management strategies. Many sources release air toxics to the atmosphere
pursuant to permits and related authorities. Permits generally need to be renewed
periodically and/or modified if conditions at the source change beyond some specified
April 2004 Page 27-12
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amount. This may provide an opportunity to re-write permit conditions so as to reduce high-
risk emissions. This might be coupled with voluntary measures or other flexible solutions to
result in overall risk reduction (see box). Agencies may also work with emission sources to
incorporate voluntary measures or other flexible solutions into the permit.
' >
Example Factors to Consider When Evaluating Risk Management Options
• Risk reduction benefits to be realized. Risk management decisions often focus on the
incremental risk associated with the chemical or other hazard being regulated in the absence of
background risks. However, background risk may be important in certain situations. For example,
if a monitoring program measures concentrations of air toxics being transported into a given study
area that result in risks above an "acceptable" level, no level of emissions control within the study
area will be able to reduce risk to an "acceptable" level, and the community may wish to address
the incoming air toxics via discussions beyond the local community.
• Level of uncertainty in the analysis. In the face of highly uncertain risks, decision-makers have
to carefully weigh the consequences of two or more options: making a decision to control
emissions or exposures only to find out later that there was little actual risk (e.g., incurring
unnecessary "cost" to the community), or making a decision not to control emissions or exposures
only to find out later that the risks were real and large (e.g., incurring potentially preventable harm
to the community).
• Implementation costs, both for voluntary approaches (e.g., marketing, process changes, tax
incentives) as well as to regulatory agencies, the regulated community, and the general community
(consumers).
• Technical feasibility. Short of shutting down the emission source altogether, is there an available
technology to reduce or eliminate emissions?
• Legal feasibility. Does the decision-making body have legal authority to both establish and
enforce requirements?
• Effectiveness/timing. Will the option provide effective management of the problem within a
reasonable time-frame?
• Political feasibility. Does the option have the necessary political support?
• Community Acceptance. Do the stakeholders buy-in to the proposed risk reduction alternatives?
Each of these factors may be more or less important depending on the context for the risk
management decision. For example, the risk manager may be required by statute to weigh economic
. factors less than technical factors. j
27.5.5 Take Actions to Implement the Decisions
Traditionally, implementation has been driven by regulatory agencies' requirements. Businesses
and governments (e.g., local municipalities) are generally the implementers. However, the
chances of success may be significantly improved when other stakeholders also play key roles.
Depending on the situation, action-takers may include public health agencies, other public
April 2004 Page 27-13
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agencies, community groups, citizens, businesses, industries, unions/workers, and technical
experts. These groups can help:
• Develop and implement a plan for taking action;
• Explain to affected communities what decision was made and why and what actions will be
taken; and
• Monitor progress.
27.5.6 Conduct an Evaluation of the Action's Results
At this stage of risk management, decision-makers and other stakeholders review what risk
management actions have been implemented and how effective they have been. Evaluating
effectiveness involves monitoring and measuring, as well as comparing the actual benefits and
costs to estimates made in the decision-making stage. The effectiveness of the process leading to
implementation should also be evaluated at this stage. Evaluation provides important
information about:
• Whether the actions were successful, whether they accomplished what was intended, and
whether the predicted benefits and costs were accurate;
• Whether any modifications are needed to the risk management plan to improve success;
• Whether any critical information gaps hindered success;
• Whether any new information has emerged that indicates a decision or a stage of the process
should be revisited;
• Whether the process was effective and how stakeholder involvement contributed to the
outcome; and
• What lessons can be learned to guide future risk management decisions or to improve the
decision-making process.
27.6 Information Dissemination
The Presidential/Congressional Commission on Risk Assessment and Risk Management noted
that effective risk communication is critical to successful implementation of the risk management
framework.(3) Risk communication engages both the communicator and the audience in listening
and in explaining information and opinions about the nature of risk and other topics that express
concerns, opinions, or reactions to risk messages.(5) The Commission made the following
recommendations with respect to risk communication:
• The complex and often confusing process of communicating information about risks to
diverse affected parties must be improved;
April 2004 Page 27-14
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• Decisions about how to allocate resources to reduce risks can be made and explained partly
on the basis of risk comparisons;
• The use of "bright lines" which distinguish between contaminant emissions and exposures
associated with negligible risk levels and those associated with unacceptable risk levels,
needs to be clarified;
• Moving from command-and-control regulation to non-regulatory approaches to risk reduction
can increase both efficiency and effectiveness; and
• Criteria for judicial review, a common element in major regulatory actions, should be
reaffirmed.
Chapter 29 provides an overview of risk communication and it's role in risk assessment and risk
management.
References
1. National Research Council (NRC). 1983. Risk Assessment in the Federal Government:
Managing the Process (The "Red Book"). National Academy Press, Washington, B.C.
2. National Research Council (NRC). 1994. Science and Judgment in Risk Assessment (The
"Blue Book"). National Academy Press, Washington, B.C.
3. Presidential/Congressional Commission on Risk Assessment and Risk Management. 1997.
Framework for Environmental Health Risk Management (Final Report, Volume 1).
Available at www.riskworld.com/Nreports/1996/risk_rpt.
Presidential/Congressional Commission on Risk Assessment and Risk Management. 1997.
Risk Assessment and Risk Management In Regulatory Decision-Making (Final Report,
Volume 2). Available at www.riskworld.com/Nreports/1996/risk_rpt.
4. U.S. Environmental Protection Agency. 1995. Guidance for Risk Characterization. Science
Policy Council, Washington, B.C., February 1995. Available at:
epa. gov/osp/spc/rcguide.htm.
5. National Research Council. 1989. Improving Risk Communication. National Academy Press,
Washington, B.C.
April 2004 Page 27-15
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Chapter 28 Community Involvement
Table of Contents
28.1 Introduction 1
28.2 Why is Community Involvement Important? 1
28.3 When to Involve the Community 2
28.4 How to Involve the Community 2
28.4.1 Understand Goals, Objectives, and Responsibilities for Effective Community
Involvement 4
28.4.2 Identify Community Concerns and Interest 5
28.4.3 Plan Community Involvement Strategy and Activities 5
28.4.4 Identify Possible Tools and Implement Community Involvement Activities 6
28.4.5 Provide Opportunity for Continued Public Interaction 7
28.4.6 Release of Risk Assessment and Risk Management Documents £
References 10
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28.1 Introduction
Community involvement can be an important aspect of the risk assessment and risk management
process. Participation of local stakeholders, at various levels and in various forms, can help
ensure a better understanding of the risk assessment results and will promote buy-in to the
selected risk reduction strategies. Encouraging and facilitating community involvement also is
sometimes required by law.
This chapter provides a broad overview of community involvement in air toxics risk assessment
and risk management and identifies helpful references on this topic. Also included throughout
this chapter are descriptions of successful air toxics projects and programs where community
involvement was a central component of that success.
This chapter describes the key tools, resources, and other considerations for an effective study
area-specific approach. It is not, however, intended to provide all the information about
conducting community involvement activities. If additional information is needed, contact the
community involvement specialist for your agency.
28.2 Why is Community Involvement Important?
When performing an air toxics risk assessment in a particular geographic area, the community is
often thought of as the people who live within the area of impact of air toxic sources. However,
other parties in the area, such as local industry, also may consider themselves part of the
community.
In addition to the people who actually live and work in an area, a number of other stakeholders
also may have a stake in the community's concerns (e.g., local officials, health professionals,
local media). It is often helpful, when dealing with a community, to keep in mind that many
different people (not just the people who live there) may have an interest in the risk assessment
and management work being undertaken.
As noted above, many laws recognize and accommodate the idea that government decisions
should be open to citizen input before a decision is finalized. This is realized through the
required public meetings and public comment periods associated with many government actions.
For example, the Clean Air Act (CAA) has a number of requirements to provide an opportunity
for the public to review and comment on Agency proposals. In some cases, the public is brought
in at an even earlier stage.
When risk assessors and risk managers have the opportunity to do so, they should consider
including the public as early as possible in the process. Doing so can lead to some very positive
benefits. For example, if the community participates early on and throughout the process, they
will be in a better position to understand what assessors and risk managers are doing, and there is
a better chance that they will believe that the work being done is in their best interest. The
process works best when the community appreciates that assessors and managers are working
with them and respecting their input (keeping them informed and involved). Ultimately, a
community that is involved early on in the process is a community that may be more willing to
support the risk assessment process and results. This may, in turn, foster the development of risk
reduction strategies the community as a whole can live with and have a stake in.
April 2004 Page 28-1
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In contrast, excluding the public from the process may result in community resentment and
rejection of even a sound risk assessment and risk management approach. A "guardian-like"
attitude toward the community that treats people as unknowledgeable and incapable of
meaningful participation does not foster trust and can eventually undermine the process.
In addition to fostering the trust and acceptance of the community, there are many other positive
reasons for early and ongoing involvement. For example, important unrecognized sources of
emissions and exposure pathways may be identified through the community involvement
process. Ultimately, it is important to recognize that community members know their
community and understand the types of solutions that will be most accepted - after all, they live
there!
28.3 When to Involve the Community
When appropriate, community involvement should begin at the earliest possible stage and span
the entire risk and assessment and management process. The level of participation that
community members have in some of the more technical phases of the assessment maybe
tailored to their background, expertise, and interest; however, this does not mean the community
cannot serve an important role in the technical phase, as well. The approach taken, as well as the
assumptions and limitations of the analysis, should be clearly explained to the community and
their input should be valued in return.
For certain CAA requirements, the question of when to involve the public is established by law.
For example, in the Title V permitting process the permitting agency must provide a public
notice and an opportunity to comment on a draft new or revised permit when:
• A facility applies for its first Title V permit;
• A Title V permit is renewed (5 years after issuance);
• The permit is reopened because there is a material mistake in the permit or an update to the
permit is needed because of new requirements (review is limited to the part of the permit that
is being revised); and
• The facility makes a significant change in its operations and applies for a revision to its
permit (review is limited to the part of the permit that is being revised).
For a community-level effort that may include non-regulatory aspects, on the other hand, a
community involvement plan will need to be tailored to specific local needs, particularly if the
ultimate risk reduction efforts will likely involve voluntary action on the part of industry and/or
citizens. As noted above, involving the community at the beginning of and throughout the
process will greatly enhance the likelihood that the air toxics risk reduction plan will receive
community support (even if the community does not agree with all aspects of the analysis).
28.4 How to Involve the Community
Many different approaches have been developed for involving the community in a risk analysis
and management strategy. Exhibit 28-1 illustrates the general framework used both by some
programs in EPA and by the Agency for Toxic Substances and Disease Registry (ATSDR). This
framework emphasizes the need for involving the community throughout the process.
April 2004 Page 28-2
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Exhibit 28-1. ATSDR's Components of Effective Community Involvement
Understand goals, objectives,
and responsibilities for effective
community involvement
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Identify community
concerns and interests
Plan community
Involvement strategy
and activities
Identify possible tools and
implement community
involvement activities
Respond to community health
concerns in risk anctfor public
health assessment and
management documents
Provide opportunity
for public comment
Source: Community Involvement in ATSDR 's Public Health Assessment Process (see box of additional
references at the end of this chapter)
In identifying community concerns and interests, it often is useful to develop a "conceptual map"
of the key organizations and decision-making processes in a community. The map would include
information such as who speaks for various parts of the community, who serves in formulating
perspectives, and what is the process for obtaining consensus within the community.
April 2004
Page 28-3
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TIP: Identify local associations or groups by asking community members, respected "elders," or
other associations. This also can go a long way in demonstrating a commitment to involving and
mobilizing all stakeholder groups, which helps to build trust and creates a more successful
community-involvement process. But, in seeking out community members, do not rely solely on
existing community organizations. Very often community members are not well organized or
represented by existing groups. Just because there is not an organization or group in the study area
does not mean that you can bypass that part of the community.
28.4.1 Understand Goals, Objectives, and Responsibilities for Effective Community
Involvement
At a minimum, goals and objectives for community involvement should include the following
items. All study areas are different, however, and this list is just a suggested starting point (and
may need to be expanded).
• Earning trust and credibility through open and respectful communications;
• Including the community in the design and implementation of risk assessment and risk
management;
• Helping community members understand what the process involves;
• Assisting communities in understanding the possible health impact of exposure to air toxics;
• Informing and updating communities about risk management activities; and
• Promoting collaboration between decision-makers, communities, and other agencies and
stakeholders when carrying out risk management activities.
To reach these goals and objectives, the
following key principles are important:
• Be aware of confidentiality and privacy
issues. Any personal information that
analysts or decision-makers receive from
community members should be respected,
/
TIP: Local public health providers, such as
county health departments and hospitals can be a
key partner in the risk analysis and management
processes. These organizations often have
resources (staff and funding) that can be used in
community health activities. Because they are
locally based, involving them as key partners in
as annronriate e Process can create strong local leaders to
promote sustainable activities once a study is
complete. ,
Be aware of special needs and cultural ^ •-/
differences. When conveying information
about air toxics and the risk management process, agencies should be aware of non-English
speaking community members and other citizens who may need help in understanding
complicated messages. Also, be sure to consider cultural symbolism. There are notable
examples of the use of a symbol that is acceptable in one culture but that has an unacceptable
meaning in another.
Maintain effective communication. As part of the trust-building process, analysts and risk
managers should keep community members informed of progress, opportunities for
community involvement, how community input will be used, how community members can
help to reduce exposures, and upcoming issues and events.
April 2004 Page 28-4
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• Respect community knowledge and values. It is important to recognize that community
knowledge can provide valuable information for the deliberative processes of risk assessment
and risk management and potentially help to address data gaps. It is particularly important to
try to understand people's interests (what they care about) during the process (more
discussion of this subject is provided in the next section).
28.4.2 Identify Community Concerns and Interest
One important activity that risk assessors and risk managers can do at the outset of any study is
simply to listen to the community. Since their concerns may or may not match those of the
assessors and managers, the initial phase of community involvement often involves a fair amount
of listening and discussion to help both groups develop a common understanding of what will
and will not be studied during the course of the assessment. In those instances where a
community concern is outside the scope of what can be studied (e.g., occasional combined
stormwater/sewer overflows that cause odors), a willingness on the part of the assessment team
to at least help identify resources or connect them to agencies that can address these concerns
will go a long way to building trust and credibility. Not listening and not responding to
community concerns at the outset may make the process of air toxics assessment and risk
reduction more difficult in the long run and may set expectations that are ultimately not met.
28.4.3 Plan Community Involvement Strategy and Activities
Planning a community involvement strategy and activities is one of the most critical components
for effective community involvement. The type and nature of communication and involvement
activities will depend on (1) the needs and interests expressed by the community during the
previous stages, (2) the potential public health issues, and (3) the resources available for
communication and involvement activities. Exhibit 28-2 provides a broad list of issues to be
considered when developing a community involvement strategy. Not all of these issues must
have solutions initially; however, they may need to be addressed eventually.
AEPA
Baltimore Community
Environmental Partnership
Air Committee
Technical Report
Community Risk-Based
Air Screening:
A Case Study in Baltimore. MD
Community Involvement Example. Southern Baltimore &
Northern Anne Arundel County Community Environmental
Partnership (CEP). In 1996, the residents, businesses, and
organizations of five Baltimore, MD neighborhoods joined with
local, State, and Federal governments in a CEP to begin a new
effort to find ways to improve the local environment and
economy. This CEP conducted a comprehensive screening of the
cumulative concentration of air toxics from all the industrial and
city facilities in and around the neighborhoods and developed a
first-for-Maryland survey of cancer incidence at the
neighborhood level. Based on this work the CEP began work
with local facilities on pollution prevention. The work of the
Baltimore CEP was a learning experience for all of the people
who participated. The Partnership tried a lot of new things - some
of them worked and some didn't. Lessons learned from this work
were carefully documented. The risk screening methodology and
lessons learned are being translated into a how-to manual for community use. For more information
( on this manual and other CEPs, see http ://www. epa. gov/oppt/cahp.
A Product of the
Community Environmental Partnership
April 2004
Page 28-5
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28.4.4 Identify Possible Tools and Implement Community Involvement Activities
An enormous number of tools and activities exist that risk assessors and managers can use to
encourage community involvement - more than can be described here (the additional resources
listed at the end of this chapter, however, should provide most of any team's needs in this
regard). They range from the simple phone call, to block parties (at which food may be
provided), to the complex mapping of emissions sources and populations. How many and which
tools and activities should be used or initiated for a given situation depends on the phase of the
risk or public health assessment and management process, the level of community interest, and
the degree of hazard a study area poses. The formation of a partnership with stakeholders or
community-based coalitions can be an effective way to involve the community, access technical
expertise, achieve consensus, leverage resources, and obtain results.
Exhibit 28-2. Issues to Consider When Developing Community Involvement Strategies
Community health concerns:
• How many community members are concerned about the study area?
• What is the level of the community's concern?
• Is the level of community concern higher (or lower) than the actual risk would suggest?
• Are community concerns unknown?
• Would a physician enhance outreach at community meetings?
• Is information/outreach/health education available now or can this wait until reports are
generated?
Demographics:
• How many community members are potentially affected?
• Are there any potentially sensitive populations that may be exposed?
• Do socio-demographic data suggest need for additional resources, such as translation?
• How do the community members receive information (e.g., newspaper, radio, word-of-mouth)?
Community interest in the risk assessment and management process:
• How involved in the process would the community like to be?
• How would the community like to be kept updated and informed (e.g., newsletters, e-mails)?
• How many community groups or activist groups are involved? How active are they?
• Should the risk assessment/management team facilitate the creation of a community group if one
has not been formed?
• Can information be disseminated at cultural centers? Informal gatherings?
Media support:
• What has the community already heard from the media? Are there misconceptions that need to be
dispelled?
• Will media support require more community involvement resources than usual?
Support of the community:
• Are there Native American communities affected by the pollution? Should a relevant agency be
involved?
• Does the pollution involve an environmental justice issue, air toxics "hot spot," or other type of
special sites?
• What past experiences has the community had with "the government"? Other agencies?
• Is there a higher than average need for resources, such as for more frequent community updates?
• How active will any regional agency representatives or other agencies be in community
involvement efforts?
April 2004 Page 28-6
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Exhibit 28-2. Issues to Consider When Developing Community Involvement Strategies
(Continued)
Public health:
• Is the study area a designated public health hazard? Is hazard acute or chronic?
• Are environmental health risks largely unknown?
• Is the study area considered a high priority? By whom?
• Is there already some risk or health outcome results? Are biological data available?
• Is a health connection plausible between contaminant exposures and community health concerns?
• Are data available for review now ? When will they be available?
• Are there toxics reduction steps already in process?
Community culture and setting:
• What are the current community priorities and projects?
• What are the community organizations?
• Who are the community leaders (unelected)?
• What activities constitute community life?
Other:
• How many people on the study area team? Does everyone know their role?
• What is the time-frame for report development and communication?
• Will any special clearances will be required? At what levels?
• Will document or graphics development resources be needed?
• Are there schools or locations where community meetings can be held?
28.4.5 Provide Opportunity for Continued Public Interaction
While a risk assessment is underway, primary communication and involvement goals include
updating the community on the status of the assessment, obtaining ongoing feedback on the
process, obtaining additional information as needed or available from the community for the
assessment, and recommending public health actions, if needed, about how community members
can reduce exposures. Throughout this process,
the risk assessment/management team should
continue to listen to community concerns and
clearly explain how they will respond to these
concerns. The team also should leverage
community outreach resources whenever possible.
For instance, federal agencies, state health and
environmental agencies, local health departments,
citizens' advisory groups, and medical advisory
groups may have funds for involving community
members in the risk assessment/management
process. Collaborating with partner organizations
can strengthen community outreach depth and
coverage.
Generally, community involvement strategies are
situation-specific - risk assessment/management
teams should determine which community
Non-English Speakers and
Other Special Needs?
To ensure the participation of everyone in the
community, agencies often use one or more
of the following strategies:
• Offer translators and signers at community
meetings, and check for wheelchair
accessibility.
• Provide additional sessions of meetings
that are offered exclusively in the
community's secondary language(s).
• Seek out advocates for the severely
disabled or others with special needs.
• Provide education and outreach materials
in both English and secondary languages.
• Develop understandable and culturally
appropriate messages and materials.
April 2004
Page 28-7
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involvement strategies are appropriate given the potential seriousness of the risk, the abilities and
involvement of the community, and the resources available for communication, training, and
outreach. If resources for community outreach are limited, the team may wish to consider how
they can best prioritize resources for community involvement.
When resources are limited, the team should look for community outreach opportunities during
other community activities, if it would be culturally acceptable. For a determination of cultural
acceptability, ask community leaders or "trusted elders."
Finally, some community analyses foster highly interactive relationships with community
members and other stakeholders. For example, the risk assessment and risk management teams
may establish ad hoc working groups to work on specific issues. These groups may include
advisory members from the community or their representatives (e.g., community consultants) and
may be more or less formal, as the circumstances require.
28.4.6 Release of Risk Assessment and Risk Management Documents
At the end of the analysis phase, the next stage of community involvement generally begins (i.e.,
after a draft risk assessment is written). Since the process of data gathering, analysis, and risk
assessment preparation can take many months to years, community interest may have decreased
significantly. However, once the risk assessment is ready for release, public interest often peaks
again. To help ensure a fair and balanced release of information, the risk
assessment/management team and their partners may consider using a more formal process to
release the risk assessment. For example, the team may release the draft for a period of time for
people to read and comment. During the review period, meetings may be held to help describe
the results and how the analysis was done. Once the risk assessment document is finalized, there
typically is a need to communicate the key results, limitations, and recommendations through a
variety of materials including fact sheets, press releases, public meetings, and websites. The risk
management strategy may be presented in a similar fashion, with a draft and final document
presented to - if not also partly written by - the community.
If an agency or other parties will be conducting any follow-up activities in the area (such as
additional environmental sampling or emissions monitoring, cost analyses, health education,
health studies), then additional appropriate community involvement may be planned.
April 2004 Page 28-1
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Additional References
Public Health Assessment Guidance Manual (2002 Draft Update) describes the process that ATSDR
uses to sort through the many hazardous waste sites in the U.S. and to determine where, and for whom,
public health actions should be undertaken. Chapter 4 addresses community involvement and
communication. See www.atsdr.cdc.gov/HAC/PHAManual/co ver.html.
The Annual EPA Community Involvement Conference brings together public participation and
community involvement professionals from across all EPA programs, as well as their local, State,
Federal, and tribal partners. Conference presentations are designed to emphasize the process of public
participation and community involvement by focusing on techniques and approaches used in EPA's
national and regional community involvement programs. See epancic.org for upcoming conferences
as well as the proceedings of past conferences.
Public Involvement in Environmental Permits: A Reference Guide (2000) at
www.epa.gov/permits/publicguide.htm was developed by EPA to help make it easier for state and
local agencies to facilitate public participation in environmental permitting decisions for businesses
and facilities under your authority. This guide provides basic information about public participation
requirements and gives examples under several major permits issued by EPA's air, water, and waste
programs. This guide also details what public participation activities are required under these
programs, as a minimum, as well as those suggested activities that serve to augment the regulatory
requirements.
Air Toxics Community Assessment and Risk Reduction Projects Database at
vosemite.epa.gov/oar/CommunityAssessment.nsf/Welcome has been compiled to provide a resource
of planned, completed, and ongoing community level air toxics assessments across the country. By
sharing information about efforts at the local level to measure, understand, and address air toxics
emissions, this database will help ensure that communities designing and implementing their own
assessments will be able to build upon past efforts and lessons learned.
Community Involvement in ATSDR's Public Health Assessment Process (2002) provides an overview
of how ATSDR works to involve communities in the public health assessment (PHA) process. It
describes how ATSDR develops community involvement strategies and plans community involvement
activities.
April 2004 Page 28-9
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Additional References (continued)
Superfund Community Involvement Web Site provides communities with a range of tools, including
guidance documents and other information to increase their understanding of Superfund and the
services available to them (e.g., the Technical Outreach Services for Communities Program, Technical
Assistance Grants). See www.epa.gov/superfund/action/community/index.htm.
Superfund Community Involvement Handbook (2002) presents legal and policy requirements for
Superfund community involvement and additional suggestions for involving the community in the
Superfund process. This handbook also provides guidance for community involvement outside of
Superfund. See www.epa.gov/superfund/tools/cag/ci handbook.pdf for more information.
Community Culture and the Environment: A Guide to Understanding a Sense of Place (2002)
addresses the social and cultural aspects of community-based environmental protection. The
document offers a process and set of tools for defining and understanding the human dimension of an
environmental issue. The report, published by EPA's Office of Water, is available on the web from
EPA's publication Web site. The report number is EPA/842/B-01/003.
Community Air Screening How To Manual: A Step-by-Step Guide to Using a Risk-based Approach to
Identify Priorities for Improving Outdoor Air Quality (to be published in 2003) is being developed by
the EPA's Community Assistance Technical Air Team to make air quality assessment tools more
accessible to communities. It will present and explain a step-wise process that a community can
follow to form a partnership, identify and inventory all local sources of air pollutants, review these
sources to identify the hazards and potential risks, and set priorities and develop a plan for making
improvements.
References
1. Agency for Toxic Substances and Disease Registry (ATSDR). 2002. Public Health
Assessment Guidance Manual (Update): Draft for Public Comment.. Available at:
http ://www. atsdr. cdc. gov/H AC/PHAManual/cover .html.
April 2004 Page 28-10
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Chapter 29 Risk Communication
Table of Contents
29.1 Introduction 1
29.2 Risk Perception 2
29.3 Your Risk Communication Strategy 2
29.4 Risk Comparisons 3_
29.5 Implementing Risk Communication Strategies 5
29.5.1 Presentation of Risk Results 5
29.5.2 Working with the Media 8
References 14
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29.1 Introduction
The purpose of an air toxics risk assessment is to evaluate the magnitude and extent of exposure
to air toxics and the potential effects on humans and the environment. Risk assessments aid the
process of developing risk management alternatives that minimize risk and maximize
environmental benefits.
s~"N
What is Risk Communication?
Risk communication is the way in which decision-makers communicate with various interested parties
about the nature and level of risk, and about the risk reduction strategies to reduce the risk.
The purpose of risk communication is to help in the planning of the risk assessment and to
convey the results of the risk assessment in a way that effectively supports risk management
decisions; this is so that the risk management decisions both meet the goals of the project and
provide some comfort level for stakeholders. Good risk communication strategies are a
fundamental aspect of developing trust among various stakeholders and the community and are
often considered an important first step that can begin even before conducting the risk
assessment. Involving the community, establishing and maintaining relationships, and
networking with other partners (e.g., agencies, organizations, officials, the media) are key
elements in a risk communication strategy. Tailoring communications to the cultural diversity of
the community is important because it may help establish the trust necessary to complete a risk
assessment that meets all stakeholder and community needs. Risk management rooted in
voluntary measures requires effective risk communication to get buy-in.
The subject of risk communication overlaps considerably with related topics discussed in
Chapter 13, including EPA's philosophy of transparency, clarity, consistency, and reasonableness
(TCCR) as described in its Policy For Risk Characterization.m
This chapter provides an overview of information developed by the Agency for Toxic Substances
and Disease Registry (ATSDR) and other authors to assist the risk assessment team in
communicating the context and results of the risk assessment to the public. Readers are
encouraged to consult the references at the end of this chapter for a more complete discussion of
this important topic. ATSDR also has an excellent website on risk communication resources
(See http ://www. atsdr. cdc. gov/HEC/primer.html).
/" ~\
Effective Risk Communication: '
Can determine and respond to community concerns;
Can reduce tension between concerned communities and agency staff; and
Can explain health risk information more effectively to communities.
ATSDR has published a handbook on risk communication for its staff.(2) Although focused on
agency staff, this handbook clearly and effectively outlines the detailed steps necessary in order
to develop an effective risk communication plan, and is applicable to all risk assessors and risk
management teams. The tools and information in the ATSDR handbook (and discussed in this
Chapter) will help the risk assessment team:
April 2004 Page 29-1
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Develop a communication strategy;
Conduct community outreach and evaluation;
Develop communication messages; and
Interact effectively with the news media.
Why is Risk Communication Important?
1. Provides an opportunity to communicate health risks in a caring, concerned, and
well-planned manner
2. Involves the community in the risk management process
3. Helps alleviate fear or anger and establish trust
29.2 Risk Perception
If people perceive themselves to be at risk, their perception is unlikely to change even if they are
not being exposed or harmed. Elements that affect risk perception include experience, culture,
level of education, outrage factors, who is affected/how they are affected (equal treatment), and
the level of control exercised on an event or events. People's perceptions of the magnitude of
risk also are influenced by factors other than numerical data. According to Covello(3) and other
authors :(4)
• Risks perceived to be voluntary are more accepted than risks perceived to be imposed.
• Risks perceived to be under an individual's control are more accepted than risks perceived to
be controlled by others.
• Risks perceived to have clear benefits are more accepted than risks perceived to have little or
no benefit.
• Risks perceived to be fairly distributed are more accepted than risks perceived to be unfairly
distributed.
• Risks perceived to be natural are more accepted than risks perceived to be manmade.
• Risks perceived to be generated by a trusted source are more accepted than risks perceived to
be generated by an untrusted source.
• Risks perceived to be familiar are more accepted than risks perceived to be exotic.
• Risks perceived to affect adults are more accepted than risks perceived to affect children.
/-""N
Two-way risk communication works best. Non-experts want access to information and to gain
knowledge. Technical experts and officials also want to learn more about non-experts' interests,
values and concerns. The audience includes government, industry, citizens, and both technical and
non-technical people. They can all be included in the process as partners.
29.3 Your Risk Communication Strategy - The Overall Plan
In general, planning a risk communication strategy includes the following steps:
• Determine the goals of the communication effort;
• Identify communication restraints;
• Identify the audience(s);
• Identify audience concerns;
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• Identify what the audience(s) knows about the issues, both correct information and
misinformation;
• Design the message(s) to be sent out to the community;
• Design the "channels'Vchoose the best methods to reach people;
• Prepare to deliver/present the message;
• Anticipate communication problems;
• Evaluate the program; and
• Modify program as needed.
When working through this process, it is important to know and understand the communication
limits and purpose, know your audience, and whenever possible, pretest your message(s). You
also should communicate early, often, and fully and remember that for many of the people in
your audience, perception is reality.
A good communication strategy also will use tested principles of good presentation, such as the
use of simplified language to present important content and the ability to be objective (not
subjective) and balanced. Presentations also should not be limited to just one form or just one
medium.
Try to use spokespersons who can communicate knowledgeably, honestly, clearly, and
compassionately and will listen and deal with specific concerns. Finally, it is important to make
sure that the information provided in the risk communication strategy is conveyed to all segments
of the audience at a level that they can understand and that the communication materials are
honest and up-front about uncertainties. It is often better to say "I don't know" than to hedge.
The ability to establish constructive communication will be determined, in large part, by whether
or not the audiences perceive the speaker to be trustworthy and believable. Public assessment of
how much we can be trusted and believed is based upon four factors:(1)
• Empathy and caring;
• Competence and expertise;
• Honesty and openness; and
• Dedication and commitment.
29.4 Risk Comparisons
Many successful risk communication efforts have had one major thing in common - a portrayal
that puts the calculated exposure risks from an assessment in perspective, with risk ranges the
public can easily relate to and understand.
Risk comparisons can help to put risks into perspective. However, irrelevant or misleading
comparisons can harm trust and credibility. Thus, while risk comparisons are commonly used,
they should be used with caution, because some kinds of risk comparisons are more likely to be
perceived as pre-conceived judgments about the acceptability of risks.(1) Guidelines for risk
comparisons have been published/5' and provide rankings of risk comparisons in terms of their
acceptability to the community. The highest-ranking comparisons are those that presume a level
of trust between the risk communicator and the public, and that consider the factors that people
use in their perception of risk. Exhibit 29-1 describes several example risk comparison rankings.
April 2004 Page 29-3
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The general rule-of-thumb is to select from the highest-ranking risk comparisons whenever
possible. When there is no choice but to use a low-ranking risk comparison, do so cautiously,
being aware that it could backfire. The fifth rank, which risk assessors rarely use, consists of
comparisons of unrelated risks (e.g., involuntary vs. voluntary risks). These comparisons have
been found to be very problematic. For example, the risk of driving without a seat belt is a
voluntary risk, while exposure to air toxics is generally considered involuntary by community
members. Covello et al.(5) provide specific examples of each of the comparison ranks, as
associated with a manufacturing facility (http ://www.psandman. com/articles/cma-4 .htm). Risk
comparison charts are also provided in Appendix B of that document
(http://www.psandman.com/articles/cma-appb.htm). although the authors do not recommend
their use in public presentations.
Exhibit 29-1. Relative Acceptability of Risk Comparisons
First-rank risk comparisons (most acceptable)
- Of the same risk at two different times
- With a standard
- With different estimates of the same risk
Second-rank comparisons (less desirable)
- Of the risk of doing something versus not doing it
- Of alternative solutions to the same problem
- With the same risk experienced in other places
Third-rank comparisons (even less desirable)
- Of average risk with peak risk at a particular time or location
- Of the risk from one source of an adverse effect with the risk from all sources of the same
effect
Fourth-rank comparisons (marginally acceptable)
- With cost; or one cost/risk ratio with another
- Of risk with benefit
- Of occupational risk with environmental risk
- With other risks from the same source
- With other specific causes of the same disease, illness, or injury
Fifth-rank comparisons (rarely acceptable - use with caution)
- Of risks that may seem unrelated to community members (e.g., smoking, driving a car,
lightning)
EPA has included risk comparisons in some air toxics analyses. For example, the results section
of EPA's National-Scale Air Toxics Assessment (http://www.epa.gov/ttn/atw/nata/) discusses
general U.S. background risks from air toxics, originating from both mobile sources and other
background sources:
• Mobile Sources. For on-road and non-road mobile sources, EPA estimates that more than
100 million people live in areas of the U.S. where the combined upper-bound lifetime cancer
risk from all air toxics compounds exceeds 10 in a million. This risk estimate is dominated
by the emissions of benzene, formaldehyde, acetaldehyde, and 1,3 butadiene. Regarding
effects other than cancer, acrolein emissions are estimated to lead to exposures above the
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reference concentration (i.e., a hazard quotient above 1.0) for approximately 200 million
people in the U.S. EPA expects that in 2007, existing standards affecting emissions of air
toxics compounds from new vehicles will reduce exposure from on-road sources by about 50
percent from 1996 levels, and that substantial reductions also will occur for non-road
emissions.
• Background Sources. EPA estimates that combined upper-bound cancer risks associated
with air toxics compounds from background sources are less than 100 in 1 million throughout
the U.S. However, the entire U.S. population is estimated to exceed an upper-bound cancer
risk level of 10 in a million due to background sources alone (note that in this study
background concentrations include both uncontrollable emissions [e.g., persistent historic
emissions, international or global pollutant transport, contributions from natural sources and
emissions that can be controlled such as long-range pollutant transport within the U.S.]).
29.5 Implementing Risk Communication Strategies
In order to implement risk communication strategies, agencies may need to plan approaches to
public presentations and working with the media. The purpose of communication with the public
is to inform, educate, and enhance cooperative problem solving and conflict resolution.
29.5.1 Presentation of Risk Results
Risk communication strategies also consider the meaning of the information (e.g., will the
listener understand how to use the information in forming opinions, making decisions, and taking
actions). When risks are calculated for air toxics and the risk results are presented to the public,
the community may not be familiar with quantitative risk data and what it means for them. In
order to prevent panic and to encourage participation in and buy-in of risk management
decisions, risk communication strategies are developed that not only reassure the community, but
also explain the potential risks and uncertainties in an understandable, clear, and honest way.
Effective communications also provide information in a community-compatible language or
form. For example, if the community speaks Spanish, then the communications could be in
Spanish as well as English. Similarly, if the community includes Native Americans, the
communications could be in the appropriate language and employ appropriate symbolism. The
effective communication of risks will allow stakeholders to better participate in management
decisions that weigh the benefits of different alternatives against the costs of achieving
"acceptable" levels of risks and the costs of disruptions associated with implementation.
When developing messages, it is important to consider the following questions:
• What does the community already know?
• Is this information factual?
• What does the community want to know?
• What does the community need to know?
• Can the information be misunderstood?
When developing a public education campaign, it is generally most effective if the campaign
highlights no more than three primary messages. More than three primary messages may
convolute the focus of the education campaign. Those developing public education campaigns
April 2004 Page 29-5
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may wish to test their risk communication messages with trusted audience members before
releasing them to the public. This can ensure that the messages are on-target and help avoid
community objections that decision-makers may not have anticipated. It also is important to
ensure that the message is culturally attuned and fits the language needs of the audience.
"Outrage reducers" are outlined by risk communication specialist Peter Sandman
(www.petersandman.com).
When developing risk-communication messages, decision-makers should (1) review the concerns
and worries of their audience; (2) cover WHO, WHAT, HOW, WHEN, WHERE and WHY; and
(3) develop messages that are consistent with their actions.
Different messages and channels maybe needed for different audiences. To communicate
effectively, the risk communicator should try to understand the audience's values, concerns, and
perceptions. Credibility is enhanced by the degree to which the risk communicator correctly
identifies, anticipates, and empathizes with the specific concerns of his or her audience(s), which
may include:
Health concerns;
Safety concerns;
Environmental concerns;
Economic concerns;
Aesthetic concerns;
Lifestyle/cultural concerns;
Data and information concerns;
Fairness/Equity concerns;
Trust and credibility concerns;
Process/value concerns (e.g., who makes
decisions and how); and
Risk management concerns.
Audiences may include:
Environmental groups;
Civic organizations;
Professional and trade organizations;
Educational and academic groups;
Religious groups;
Other government agencies;
Neighborhood/school organizations;
Industries; and
Other organizations.
It may be worthwhile to develop audience profiles for key audiences. Profiles describe the
members of the audience, whom they trust and go to for information (decision-makers can seek
these people out for advice on communicating with the community), what their prevailing
attitudes and perceptions are, and what concerns and worries motivate their actions.
It is important to clearly communicate scientific information and uncertainty:
• Provide all information possible, as soon as possible;
• Communicate when there is progress being made;
• Maintain your relationship with the community;
• Be honest about what you do not know;
• Explain how you will work together to find the answers;
• Help the audience understand the process behind your findings;
• Avoid acronyms and jargon;
• Carefully consider what information is necessary; and
• Use familiar frames of reference to which the audience can relate.
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Public interactions may also include availability sessions, informal discussions, or poster
sessions. Presentations can occur in a variety of venues some of which are better suited than
others to different situations. Determining the best channels for your message depends on
understanding when to use which tool and knowing how the community prefers to receive
information. Message delivery channels include:
1. Presentations: Speeches to public groups. Benefit: offers the audience a chance to ask
questions; reaches many people at one time. Limitations: if poorly presented, can distort
community perception; cannot sufficiently address individual concerns; can become
argumentative or confrontational.
2. Open Houses/Availability Sessions: Informal meeting where public can talk to staff on a
one-to-one basis. Benefit: allows for one-to-one conversation; helps build trust and rapport.
3. Small Group Meetings: Sharing information with interested community members and
government officials. Benefit: allows two-way interaction with the community. Limitations:
may require more time to reach only a few people; may be perceived by community groups as
an effort to limit attendance; be sure your information is identical or you may be accused of
telling different stories to different groups.
4. Briefings: Can be held with key officials, media representatives, and community leaders;
generally not open to the public. Benefit: allows key individuals to question risk assessment
staff before release of public information. Limitations: should not be the only form of
community communication; bad feelings may arise if someone feels that they were left off
the invite list.
5. Community mailings: Sends information by mail to key contacts and concerned/involved
members of the community. Benefit: delivery of information quickly; may require less
planning than a meeting. Limitation: no opportunity for feedback.
6. Exhibits: Visual displays to illustrate health issues and proposed actions. Benefits: creates
visual impact. Limitations: one-way communication tool, no opportunity for community
feedback.
7. Fact Sheets: To introduce new information. Benefit: brief summary of facts and issues;
provides background for information discussed during a meeting. Limitations: one-way
communication tool; needs to be well-written and understandable.
8. Newsletters: To inform community of ongoing activities and findings. Benefit: explains
findings; provides background information. Limitations: can backfire if community
members do not understand or misinterpret contents.
9. News Release: Statement for the news media to disseminate information to large numbers of
community members. Benefit: reaches large audience quickly and inexpensively.
Limitations: may exclude details of possible interest to the public; can focus unneeded
attention on a subject.
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10. Public Meetings: Large meeting open to the public where experts present information and
answer questions and community members ask questions and offer comments. Benefit:
allows community to express concerns and agency to present information. Limitations: can
intensify conflicts, rather than resolve controversies.
Presentations require a careful balancing act between effectively conveying key messages and
avoiding a range of pitfalls. Important "Dos" and "Don'ts" to avoid presentation pitfalls, are
outlined in Exhibit 29-2.
29.5.2 Working with the Media
The media can be a primary source of information on risks to the public. Effective news media
relations have many benefits, complementing other communication efforts. What people read,
see, or hear in news coverage can lend credibility to agencies associated with air toxics risk
assessment, and can help to make it a familiar topic for public discussion. News coverage can
inform people about air toxics issues and help them ask appropriate questions. Skill in media
relations can help risk communications avoid or dispel rumors, respond to criticism, defuse
controversy, and even turn adversity to advantage.
News coverage is crucial to engaging the attention of decision-makers and earning the support of
opinion leaders. Also, because the news media pay distribution costs, helping journalists cover
the issues is a cost-effective way to communicate.
The best approach to the media, as with the public, is to be open and honest, provide information
tailored to the needs of each type of media, such as graphics and other visual aids, and provide
background material. Journalists also should welcome such materials as fact sheets, press kits,
and lists of experts. Establishing an information center also can be an effective way to make
materials available to the news media (and to the general public). It also is very important that
the material and discussions you have with the media clearly articulate the messages that you
want to find their way into print or onto the TV or radio.
Like other communication efforts, working with the news media is done best when it is based on
a strategy and follows a systematic process. A good strategy seeks opportunities to match the
goals and objectives of the organization with the interests of journalists. As in other
communication strategies, assessing the needs of the audience -journalists - is important to
reaching them effectively.
After you determine that the rules of your organization concerning contacts with the media have
been met, here are a few suggestions on how to deal with news reporters:
• When a reporter calls, be sure to get a name and media affiliation; if what the reporter wants
is not clear to you, ask for a clear explanation; if you are uneasy with a reporter's query,
decline in a friendly way to continue the conversation.
• Reporters are often under deadline pressure, but you can take enough time to respond
effectively; don't get pressured into hasty comments that might backfire.
April 2004 Page
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• Do not hesitate to ask for more information about a story before responding to a request for
an interview.
In working with journalists, it is vital to develop good interpersonal relationships. How can you
do that? One rule of thumb followed by experienced practitioners is to adhere to the "Five Fs" -
Fast, Factual, Frank, Fair, and Friendly (Exhibit 29-3).(6)
Interviews. Frequently, the best way to get a message out is through an in-person interview.
You should generally assume that all statements you make are "on the record." Exhibit 29-4
outlines some techniques to prevent poor transmittal of your message.
Press Releases. Press releases may not be an effective way to transmit a message. However,
in some cases, releases that are targeted to particular media outlets and purposes can be
useful. For example, the publication of a report on air toxics risk might be newsworthy and
of concern to the community, and thus would be sent to local community newspapers.
Remember that your press release should emphasize, upfront, the messages that you want to
get out to the public.
Other Platforms. You may have the opportunity to communicate your message through
other platforms such as:
- Letters to the Editor. Keep them short, to the point, and prompt.
- Commentaries. Radio broadcasts and newspapers print a number of opinion pieces each
day. Bear in mind that submissions are numerous, acceptances rare.
- Talk Radio (and TV). Talk shows may request experts to address various environmental
issues.
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Exhibit 29-2. Presentation Dos and Don'ts
Pitfall: Jargon
Do: Define all technical terms and acronyms.
Don't: Use language that may not be understood by even a portion of your audience.
Pitfall: Humor
Do: Direct it at yourself, if used.
Don't: Use it in relation to safety, health, or environmental issues.
Pitfall: Negative Allegations
Do: Refute the allegation without repeating it.
Don't: Repeat or refer to them.
Pitfall: Negative Words and Phrases
Do: Use positive or neutral terms.
Don't: Refer to national problems (problems unrelated to the issue at hand), i.e., "This is not Love Canal."
Pitfall: Reliance on Words
Do: Use visuals to emphasize key points, but be culturally correct for the audience.
Don't: Rely entirely on words.
Pitfall: Temper
Do: Remain calm. Use a question or allegation as a springboard to say something positive.
Don't: Let your feelings interfere with your ability to communicate positively.
Pitfall: Clarity
Do: Ask whether you have made yourself clear.
Don't: Assume you have been understood.
Pitfall: Abstractions
Do: Use examples, stories, and analogies to establish a common understanding, but test them out first to make
sure they are clear, make your point, and are culturally acceptable.
Pitfall: Nonverbal Messages
Do: Be sensitive to nonverbal messages you are communicating. Make them consistent with what you are
saying.
Don't: Allow your body language, your position in the room, or your dress to be inconsistent with your
message.
Pitfall: Attacks
Do: Attack the issue.
Don't: Attack the person or organization.
Pitfall: Promises
Do: Promise only what you can deliver. Set and follow strict orders.
Don't: Make promises you can't keep or fail to follow up.
Pitfall: Numbers
Do: Emphasize performance, trends, and achievements.
Don't: Focus on or emphasize large negative numbers.
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Exhibit 29-2. Presentation Dos and Don'ts (continued)
Pitfall: Guarantees
Do: Emphasize achievements made and ongoing efforts.
Don't: Say there are no guarantees.
Pitfall: Speculation
Do: Provide information on what is being done.
Don't: Speculate about worst cases.
Pitfall: Money
Do: Refer to the importance you attach to health, safety, and environmental issues; your first obligation is to
public health.
Don't: Refer to the amount of money spent as a representation of your concern.
Pitfall: Organizational Identity
Do: Use personal pronouns ("I," "we").
Don't: Take on the identity of a large organization.
Pitfall: Blame
Do: Take responsibility for your share of the problem.
Don't: Try to shift blame or responsibility to others.
Pitfall: "Off the Record"
Do: Assume everything you say and do is part of the public record.
Don't: Make side comments or "confidential" remarks.
Pitfall: Risk/Benefit/Cost Comparisons
Do: Discuss risks and benefits carefully (consider putting them in separate communications).
Pitfall: Risk Comparison
Do: Use them to help put risks in perspective.
Don't: Compare unrelated risks.
Pitfall: Health Risk Numbers
Do: Stress that true risk is between zero and the worst-case estimate. Base actions on federal and state
standards, when possible, rather than risk numbers.
Don't: State absolutes or expect the lay public to understand risk numbers.
Pitfall: Technical Details and Debates
Do: Focus your remarks on empathy, competence, honesty, and dedication.
Don't: Provide too much detail or take part in protracted technical debates.
Pitfall: Length of Presentations
Do: Limit presentations to 15 minutes.
Don't: Ramble or fail to plan the time well.
(2)
Source: ATSDR Risk Communication Primer
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Exhibit 29-3. The "Five Fs" of Media Relations
Fast. Respect journalists' deadlines. If a journalist telephones for information, return the call
immediately, even if it is past normal office hours. A phone message returned the next day is often too
late. By then, the story already may have been aired or printed.
Factual. Be factual, and make the facts interesting. Stories are to be based on facts. Journalists also
appreciate a dramatic statement, creative slogan, or personal anecdote to help illustrate your point.
Give the source of any facts and statistics provided.
Frank. Be candid. Never mislead journalists. Be as open as possible and respond frankly to their
questions. As long as there is an explanation of the reason, most journalists will understand and
respect a source even if he or she is not able to answer a question completely or at all.
Fair. Organizations should be fair to journalists if they expect journalists to be fair to them. Favoring
one news outlet consistently, for example, will lose the confidence of the others.
Friendly. Like everyone else, journalists appreciate courtesy. Remember their names; read what they
write; listen to what they say; know their interests; thank them when they cover the issues in a factual,
unbiased way.
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Exhibit 29-4. Interviewing Techniques
Always think carefully before you answer a question. People often ramble - and say something
they wish they hadn't if they answer too quickly. Take a moment to consider what you want to say.
If you need more time, ask for the question to be repeated.
Don't talk just to keep a conversation going with a reporter. Experienced reporters will be silent
because often people they interview will talk to fill awkward voids and then say something they
don't mean to say.
Ask the reporter to make your affiliation clear in the story.
Listen carefully to questions and respond clearly. Avoid jargon. If you have a key idea that you
want to get across, repeat it several times, perhaps using different words. This is especially useful
for broadcast: no matter how the tape is edited, you will make your point.
Don't hurry: speak slowly, and in short, concise sentences. State your position in simple,
easy-to-understand language. Use everyday examples and analogies, when possible.
Never talk down to a reporter. You are partners in getting your message across. Arrogance will
come across negatively to an audience. An "attitude" can turn an interview into a confrontation.
Don't lose your temper! No matter how antagonized you feel, recognize that this can be a tactic to
get you to say something you do not wish to say.
If you don't know the answer to a reporter's question, or cannot answer, just refrain from
answering. A lie or bad guess will return to haunt you. You will lose credibility.
Some reporters may ask to tape an interview over the telephone. This is a common practice for
radio reporters to obtain "sound bites" and to get accurate quotes. The reporter should inform you
of the taping before it begins. Do not repeat an allegation - it could be taken out of context.
Additional Suggested References
Calow, P. 1997. Handbook of Environmental Risk Assessment and Management. Blackwell
Publishers.
Crawford-Brown, D. 1999. Risk-based Environmental Decisions: Culture and Methods. Kluver
Academic Publishers.
Johnson, B.B., Sandman, P.M., and Miller, P. 1992. Testing the Role of Technical Information in
Public Risk Perception by RISK. Issues in Health and Safety, Fall 1992:341-364.
Lundgren, R.E. 1994. Risk Communication: A Handbook for Communicating Environmental, Safety,
and Health Risks. Battelle Press, Columbus, OH.
Langford, Ian. 2002. An existential approach to risk perception. Risk Analysis 22(1): 101 -120.
U.S. Environmental Protection Agency. 1992. Air Pollution and the Public: A Risk Communication
Guide for State and Local Agencies. EPA 450/3-90/025.
For an additional list of risk communication references, see
i http://www.psandman.com/articles/cma-bibl.htm.
April 2004 Page 29-13
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References
1. U.S. Environmental Protection Agency. 1995. Policy for Risk Characterization ("Browner
Memorandum"). Science Policy Council, Washington, DC., March 1995. Available at:
http://64.2.134.196/committees/aqph/rcpolicy.pdf
2. Agency for Toxic Substances and Diseases Registry (ATSDR). 1994. Tools and Techniques
for Effective Health Risk Communication. This is an update of the ATSDR Primer on Health
Risk Communication Principles and Practices, October 1994. Available at:
http://www.atsdr.cdc.gov/HEC/primer.htmlffEARNING
3. Covello, V.T., Sandman, P. 2001. Risk communication: Evolution and Revolution, in
Wolbarst A. (ed.). Solutions to an Environment in Peril. John Hopkins University Press,
Baltimore, MD: pp. 164-178. Available at:
http://www.phli.org/riskcommunication/article.htm
4. Fischhoff B, Lichtenstein S, Slovic P, Keeney D. 1981. Acceptable Risk. Cambridge
University Press, Cambridge, Massachusetts.
5. Covello, V.T., Sandman, P.M., Slovic, P. 1988. Risk Communication, Risk Statistics and
Risk Comparisons: A Manual for Plant Managers. Chemical Manufacturers Association,
Washington, D.C., 1988. Available at: http://www.psandman.com/articles/cma-0.htm
6. Cutlip, S.M., Center, A.H., and Broom, G.M. 1985. Effective Public Relations.
Prentice-Hall, Englewood Cliffs, New Jersey.
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PART VI
SPECIAL TOPICS
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Introduction to Part VI
Part VI of this Reference Manual provides an overview of three special topics related to air
toxics risk assessment.
• Public Health Assessment (Chapter 30) provides an overview of the process by which public
health agencies may evaluate the public health implications posed by the emissions from air
toxic sources in a community. The public health assessment, if performed, is a
complementary process to risk assessment.
• Probabilistic Risk Assessment (Chapter 31) discusses the process by which probability
distributions are used to characterize variability or uncertainty in risk estimates, a process
aimed at describing risks as a distribution (or range) of potential outcomes.
• Use of Geographical Information Systems (GIS) in Risk Assessment (Chapter 32) provides
an overview of the software and geographic data that allow efficient storage, analysis, and
presentaiton of spatially explicit and geographically referenced information that can help in
the process of conducting risk assessments and reporting results
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Chapter 30 Public Health Assessment
Table of Contents
30.1 Introduction 1
30.2 History of Public Health Assessment 2
30.3 Relationship of Public Health Assessment to Risk Assessment 3_
30.4 What Is Public Health Assessment? 4
30.5 How Is a Public Health Assessment Conducted? 6
30.5.1 Conduct Scoping 6
30.5.2 Obtain Study Area Information 7
30.5.3 Community Involvement/Outreach/Response to Community Concerns 7
30.5.4 Exposure Evaluation £
30.5.5 Health Effects Evaluation 9
30.5.6 Draw Public Health Conclusions 12
30.5.7 Recommend Public Health Actions 13
30.5.8 Prepare PHA Documents 13.
References 14
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30.1 Introduction
An adjunct to conducting air toxic risk assessments is public health assessments, which uses
public health tools (e.g., health questionnaires, epidemiology) to investigate the incidence and
prevalence of disease and to find out the current or past health of individuals. While public
health methods are not always used for air toxics risk assessments, they can provide useful
information to answer the question of whether there is evidence that there is a public health
concern, particularly if disease rates are elevated in the assessment area.
Air toxics risk assessment, the main topic of this manual, focuses on assessing the potential risk
that people have for experiencing adverse health effects from exposure to air toxics. The
outcome of a risk assessment is a statement about the likelihood that exposure may result in
disease (e.g., the probability of people developing cancer). The risk assessment process links the
potential exposures to emissions from (often) specific sources to the likelihood of disease
occurring.
However, in any community, concerns about more than just estimates of the likelihood of risk
often come up. For example, communities where risk assessments are being performed often
express concern about current health effects that may have resulted from past exposures.
Questions like "was my cancer caused by air pollution" are often on the minds of people who
live where an air toxics risk assessment is being performed.
The risk assessment process, while a powerful predictive tool for evaluating public health
impacts from air pollution, is not amenable to answering these types of questions. Nevertheless,
questions about disease and past exposures will inevitably come up as the air toxics risk
assessment study moves forward. The risk assessment and risk management team will almost
always have to explain that their assessment tool (risk assessment) is not being used to answer
questions about existing cases of disease.
To help risk assessors and other stakeholders respond to these types of questions, this chapter
provides information on a complementary process to risk assessment called Public Health
Assessment or PHA. It is taken largely from the ATSDR Public Health Assessment Guidance
Manual.m A PHA for air toxics is an analysis and statement of the public health implications
posed by a source or group of sources of air toxics on a given geographic area. It usually is
conducted by a public health agency such as the Agency for Toxics Substances and Disease
Registry or ATSDR (a federal Agency within the Centers for Disease Control and Prevention) or
one of their partner state or local public health agencies. PHAs are not generally performed by
EPA or state, local, or tribal air agencies since PHAs often rely on specialized medical and
epidemiological expertise and due to the difficulty facing these agencies in obtaining and
reviewing medical information for individuals. PHAs are normally performed:
• In response to a request by concerned community members or physicians;
• In response to a real or perceived increase in a health problem noted during routine disease
surveillance systems; and/or
• As part of a broader program such as a proactive analysis of region-specific air quality.
April 2004 Page 30-1
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PHAs are performed by ATSDR at each
Superfund site on the National Priorities List.
ATSDR also performs PHAs when petitioned.
The term public health assessment (PHA) as
used here, refers to a broad range of
assessment types - from screening-level health
consultations to comprehensive
epidemiological assessments - that are
commonly performed by ATSDR in its work.
The PHA process, while commonly thought of
as a Superfund-related activity, is amendable
to a wide range of exposure scenarios,
including the evaluation of air toxics impacts
at the community level.
The types of air toxics assessments most likely
to include a PHA are those where the pollutants
have a clearly identifiable effect, where the
exposure is relatively widespread, or where there
is a high level of public concern. A PHA will
not necessarily be needed every place an air
toxics risk assessment is performed. However,
the use of the PHA process, in conjunction with
the risk assessment process, is becoming a more
common practice for the purpose of providing
holistic evaluations of air toxics impacts on
communities.
A PHA may involve an assessment of relevant
environmental data, health outcome data
(e.g., cancer statistics), and community concerns generally associated with a study area where
air toxics are or have been released. A PHA identifies populations living or working on or near
areas for which more extensive public health actions or studies are indicated and is generally
more qualitative, more focused on actual, measurable harm, and past and current exposures.
This chapter describes the history of PHAs, what they are, how they compare to and work in
concert with risk assessments, and how they are conducted. Several case studies are included to
help illustrate the diversity of PHAs and how they compare with and are used with risk
assessments.
30.2 History of Public Health Assessment
PHA as a tool for characterizing and protecting the health of a society can be traced back
thousands of years. The ancient Babylonians, Egyptians, Greeks, and Romans were among the
first known civilizations to describe associations between diseases and sources such as place,
water conditions, climate, eating habits, and housing. One of the
first documented public health "assessments" (though later proven
incorrect) connected the presence of "bad air" around swamps and
marshes with the prevalence of malaria, one of the world's most
devastating diseases. (It was determined later that the prevalence
of malaria was associated not with air, but with mosquitos, the
transmission vector for the disease, which breed in standing water
associated with those places.) Infectious diseases continued to
dominate public health concerns until the industrial revolution,
although the problems of poor urban air quality from the use of
coal were well documented as early as the end of the 16th century.
The modern use of PHA for air toxics in the U.S. probably began in the mid-1900s in response to
events such as the incapacitating smog episodes in Los Angeles in the 1940s, the polluted air
inversion that killed 20 people in Donora, Pennsylvania in 1948, and the atmospheric nuclear
weapons tests in Nevada in the 1950s. Myriad state and local public health agencies shouldered
much of the burden of air pollutant health assessment at first. Then, at the federal level, the
Federal Air Pollution Control Act of 1955 authorized the Public Health Service (PHS) to conduct
The earliest "bad air"?
April 2004
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research and technical assistance and work towards a better understanding of the causes and
effects of air pollution.
In 1980, ATSDR was created specifically to conduct PHAs at hazardous waste (Superfund) sites.
That role has expanded over time to address additional pollution sources, including air toxics.
ATSDR is not a regulatory agency like EPA, but rather is a public health agency that conducts
assessments and makes recommendations to EPA and others when specific actions at study areas
in question are needed to protect the public's health. ATSDR conducts PHAs when petitioned by
concerned community members, physicians, state or federal agencies, or tribal governments.
State and local public health agencies also play an important role with regard to PHAs for air
toxics and other hazards.
30.3 Relationship of Public Health Assessment to Risk Assessment
Both the PHA and the quantitative risk assessment address the potential human health effects of
environmental exposures, but they use different approaches and have different purposes. As
illustrated in Exhibit 30-1, the PHA tends to be less quantitative than the risk assessment and to
focus more on actual past and current exposures. The PHA evaluates observed health outcome
and related data (e.g., cancer clusters, breathing problems, toxics residues in biologic samples) to
determine whether rates of disease or death are or could be elevated in a community and, if so,
whether these outcomes are due to a specific source. The risk assessment, on the other hand,
starts with a specific source and evaluates estimated potential health outcomes, or risks. The
PHA's subsequent conclusions generally complement the risk assessment process and help
inform the decisions that the state, tribal, or local agency is reaching about a given study area.
Similarly, the risk assessment provides considerable data to the PHA.
In addition to its focus on health outcome data, such as cancer or asthma incidence, the PHA also
helps put community-provided data and information and community concerns into perspective,
which in turns helps both (1) the community better understand whether they have been exposed
to hazardous substances and, if so, what that means in terms of possible health outcomes, and (2)
the decision-maker better determine what needs to be done to prevent or further study these
exposures (e.g., emissions reductions, health education, biologic monitoring).
The PHA may use similar techniques to those of the quantitative risk assessment, but primarily
as tools either to clearly rule out the existence of public health hazards, to determine that a
clinical disease is really likely in the community, or to identify areas for additional study. At a
minimum, the PHA helps to identify a baseline in the level of disease in a community so that
later studies will have a basis for comparison.
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Exhibit 30-1. PHAs and Risk Assessments: Differences and Similarities
In a PHA.
In a risk assessment.
OVERALL
More qualitative
More community involvement
Conduct less frequently
More quantitative
Less community involvement
Conducted more frequently
EXPOSURE ASSESSMENT
Similar for air sampling and modeling Air sampling
Biomonitoring possible Fate/transport modeling
Past, current/future Future/hypothetical
TOXICITY ASSESSMENT
Similar (for health effects screening) Similar (for toxicity)
CHARACTERIZATION
Margin for exposure comparisons
Public health implications
Needed public health actions
Informs the risk assessment
Modeled risk
Informs the PHA
30.4 What Is Public Health Assessment?
A PHA is an evaluation of relevant
environmental data, health outcome data, and
community concerns associated with a study
area where hazardous substances have been
released. A PHA identifies populations living or
working on or near areas for which more
extensive public health actions or studies are
indicated.
PHAs can range from simple to complex, with the
former activity often termed a health
consultation rather than PHA. This more simple
form generally is conducted in response to a
ATSDR Definition of PHA
The evaluation of data and information on
the release of hazardous substances into the
environment in order to assess any [past],
current, or future impact on public health,
develop health advisories or other
recommendations, and identify studies or
actions needed to evaluate and mitigate or
prevent human health effects (42 Code of
Federal Regulations, Part 90, published in
55 Federal Register 5136, February 13,
1990).
April 2004
Page 30-4
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specific question or request for information pertaining to a hazardous substance or facility. It
often contains a time-critical element that necessitates a rapid response. More complex forms of
a PHA can involve a wide geographical area, many pollution sources, and take months or years
to complete.
Understanding and responding to study area-specific community health concerns is an important
part of the PHA process. These investigations can be conducted to confirm case reports,
determine an unusual disease occurrence, and explore potential risk factors. One frequently cited
concern is the disease cluster - the occurrence of a specific disease or condition above the
expected number for a given geographic location and time period (e.g., the high incidence of
leukemia in a given area). The health agency needs to learn what people in the area know about
a source and source-related exposures and what concerns they may have about its impact on their
health. Therefore, starting early in the assessment process, the health agency generally gathers
information and comments from the people who live or work near the source(s), including area
residents, civic leaders, health professionals, and community groups. Throughout the PHA
process, the health agency should communicate with the public about the purpose, approach, and
results of its public health activities.
The PHA process is iterative and dynamic and may lead to a variety of products or public health
actions. The findings maybe communicated in public health assessment or public health
consultation documents, which serve as an aid for developing additional public health actions.
The audience for such products often includes environmental and public health agencies,
communities, and the public health agency itself.
During the course of the PHA process, the public health agency may identify the need to prevent
or better define exposures or illnesses in a particular community. The agency's response to such
a need might include:
• Issuing a public health advisory (if there is an urgent health threat);
• Initiating an exposure investigation (to better define study area exposures);
• Recommending a health study (to identify elevated illness or disease rates in a community);
and/or
• Conducting health education (for the study area community or health professionals within
the community).
The PHA process also can serve as a triage mechanism, enabling the public health agency to
prioritize and identify additional steps needed to answer public health questions. The science of
environmental health is still developing, and sometimes information on the health effects of
certain substances is not available. When this occurs, rendering certain questions unanswerable
by the available literature, the public health agency will suggest what further research studies
and/or health education services are needed.
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30.5 How Is a Public Health Assessment Conducted?
PHAs generally are conducted by public health agency assessors, often supported by a
multi-disciplinary team of scientists, health communication specialists, health educators, and/or
medical professionals. The health agency solicits and evaluates information from other local,
state, tribal, and/or federal agencies; parties responsible for operating sources at a particular study
area; and the community. All of these stakeholders play an integral role in the PHA process.
The public health agency promotes a team approach to ensures that information used in the
assessment is accurate and up-to-date, ensure that community concerns are identified and
addressed, and fosters cooperative efforts in implementing recommendations and public health
activities.
Many technical resources exist that provide details about conducting a PHA (see Exhibit 30-2),
and, thus, only a broad overview is provided here. One of the most comprehensive resources is
the ATSDR PwMc Health Assessment Guidance Manual.m The ATSDR manual focuses on
site-specific PHAs such as Superfund sites; nevertheless, it also can be used to assess air
emissions within a limited geographical area. As described in detail in the ATSDR manual, the
steps of a PHA — whether conducted by ATSDR or a state or local public health agency, and
whether comprehensive or limited to a screening assessment - can be multifaceted and
interactive. Exhibit 30-3 illustrates this by providing an overview of a typical PHA process. The
following subsections describe this process in more detail.
30.5.1 Conduct Scoping
The first step is to establish an overall understanding of the study area and begin to identify the
most pertinent issues. The objective is to quickly gain some baseline information about the study
area and start developing a strategy for conducting the PHA. To help ensure a consistent
approach across study areas, the following steps are followed during this initial phase:
• Initiate study area scoping by performing an initial review of permits and other sources of
study area information, identifying any past health agency or partner activities, identifying
and communicating with study area contacts, and determining the need for a study area visit
to observe actual conditions and speak with study area representatives.
• Define roles and responsibilities of team members (internal and external).
• Establish communication mechanisms (internal and external) by developing a schedule for
team meetings, thinking about how to present the findings of the assessment, and developing
health communication strategies.
• Develop a study area strategy for completing the various steps in the PHA process and
develop a strategy, identifying the tools and resources that might be needed to evaluate the
study area, communicate the findings, and implement public health actions.
• Based on information obtained during study area scoping, develop an approach that focuses
on the most pertinent public health issues.
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Exhibit 30-2. Selected Public Health Assessment Resources
Agency for Toxic Substances and Disease Registry (ATSDR; www.atsdr.cdc.gov). which publishes
the Public Health Assessment Guidance Manual (current draft is available online; Guidance for
ATSDR Health Studies (1996; available online), Environmental Data Needed for Public Health
Assessments (1994, available online), and other guidance.
National Institute of Environmental Health Sciences (NIEHS; www.niehs.nih. gov). which
publishes Environmental Health Perspectives and sponsors multidisciplinary biomedical research,
prevention and intervention efforts, and communication strategies that encompass training,
technology transfer, and community outreach.
American Public Health Association (APHA; www.apha.org). which publishes the American
Journal of Public Health and provides many other resources related to environmental public health.
National Association of County and City Health Officials (NACCHO; www.naccho.org). which
publishes the Protocol for Assessing Community Excellence in Environmental Health (2000) and
Assessment to Action: Improving the Health of Community Affected by Hazardous Waste (2002).
National Association of Local Boards of Health (NALBOH) (www.nalboh.org). which maintains
an up-to-date database of contact information for all local boards of health, provides technical
assistance to existing boards of health, and will soon publish the Environmental Health Primer.
30.5.2 Obtain Study Area Information
Throughout the PHA process, various team members will collect information about the study
area, although the initial collection of information is typically the most intensive. Information
sources typically include interviews (in-person or via telephone); study area-specific
investigation reports prepared by federal, state, and local environmental and health departments;
and study area visits. Gathering pertinent study area information requires a series of iterative
steps, including gaining a basic understanding of the study area, identifying data needs and
sources, conducting a study area visit, communicating with community members and other
stakeholders, critically reviewing study area documentation, identifying data gaps, and compiling
and organizing relevant data to support the assessment.
30.5.3 Community Involvement/Outreach/Response to Community Concerns
The community associated with a study area is both an important resource for and a key audience
in the PHA process. Community involvement activities should be developed and implemented
with the following objectives in mind:
• Earning trust and credibility through open, compassionate, and respectful communications.
• Helping community members understand what the PHA process involves and what it can and
cannot do.
• Providing opportunities for communities to become involved in the PHA activities.
• Promoting collaboration between the public health agency, communities, and other agencies.
• Informing and updating communities about the health agency's work.
• Assisting communities in understanding the possible health impact of exposures to hazardous
substances.
April 2004 Page 30-7
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Exhibit 30-3. Overview of a Typical Public Health Assessment Process
00
O
Health Effects Evaluation
Conduct Screening Analysis:
Identify pathways and substances
requiring further evaluation
1
1 Conduct In-Depth Analysis
^
r
Draw Public Health Conclusions
1
r
Recommend Public Health Actions
^
r
Prepare Public Health Assessment Documents
•4 —H
> O
o
O "
O
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t/1
Chapter 28 of this reference manual provides a more detailed discussion of community
involvement and outreach.
30.5.4 Exposure Evaluation
For the exposure evaluation, public health assessors review environmental data to determine the
sources of pollutants and exposure pathways/routes. The conceptual model described in Chapter
6 should be a reasonable starting point for the PHA exposure evaluation. Generally, the public
health agency involved does not collect its own environmental sampling data, at least at first, but
rather reviews information provided by federal, state, and local government agencies and/or their
contractors, businesses, and the public. Assessors can indicate what further environmental
sampling may be needed and may collect environmental and biologic samples when appropriate.
This step involves two key substeps:
April 2004
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Evaluate Environmental Contamination Exposure Investigations
Data. This step involves determining what
pollutants people may be exposed to and in
what concentrations. This evaluation
involves assessing the quality and
representativeness of available monitoring
data and measurements or modeled estimates
of exposure point concentrations. This is an
important way to ensure that any public health
conclusions and recommendations for the
, , , , sampling, exposure-dose reconstruction.
study area are based on appropnate and ,., • ,. j- i + +• j/
J fff biologic or biomedical testing, and/or
When a PHA exposure evaluation concludes
that additional exposure information is
needed, an exposure investigation generally is
conducted. An exposure investigation is the
collection and analysis of study area-specific
information to determine if human
populations have been exposed to air toxics.
This information may include environmental
evaluation of medical information.
reliable data. Both sampling data and
modeling techniques described in Chapters 9,
10, 18, and 19 are sometimes used to generate
data for PHAs. Evaluation of environmental contamination data typically proceeds
simultaneously with the exposure pathway evaluation.
• Characterize Exposure Pathways. During the exposure pathway characterization, the
assessor evaluates who may be or has been exposed to study area contaminants, for how long,
and under what conditions. This involves identifying and studying the following five
components of a "complete" exposure pathway: a source of air toxics; a mechanism for
release into the air and, in some cases, transfer between media (i.e., the fate and transport of
environmental contamination); an exposure point or area; an exposure route (e.g., ingestion,
dermal contact, inhalation); and a potentially exposed population. The overall purpose of this
evaluation is to understand how people might become exposed to study area contaminants
and to identify and characterize the size and susceptibility of the potentially exposed
populations. If no complete or potentially complete exposure pathways are identified, no
public health hazards exist and there is no need to perform further scientific evaluation.
When complete environmental or biologic data are lacking for a study area, an exposure
investigation may be recommended to better assess possible impacts to public health.
30.5.5 Health Effects Evaluation
If the exposure evaluation shows that people have been or could be exposed to pollutants such as
air toxics, the public health assessor will evaluate whether this contact could have resulted in
harmful effects. Assessors use existing scientific information to determine the health effects that
may result from exposures. Public health agencies recognize that children, because of their play
activities and their growing bodies, maybe particularly vulnerable to exposures to air toxics.
Developing fetuses also may be more vulnerable to such exposures. Thus, the impact to children
and developing fetuses is considered first when evaluating the health threat to a community. The
health effects evaluation is composed of two basic substeps: a screening analysis and a more in-
depth analysis.
• Screening Analysis. Screening is a first step in understanding whether the detected
concentrations to which people maybe exposed are harmful. The screening analysis is a
fairly standard process developed to help health assessors sort through the large volumes of
environmental data for a study area. It enables the assessor to safely rule out substances that
are not at levels of health concern and to identify substances and pathways that need to be
April 2004 Page 30-9
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examined more closely. For complete or potential exposure pathways identified in the
exposure pathway evaluation, the screening analysis may involve comparing media
concentrations at points of exposure to "screening" values (based on protective default
exposure assumptions) and estimating exposure doses based on study area-specific exposure
conditions. The assessor then compares estimated doses with health-based guidelines to
identify substances requiring further evaluation. Exhibit 30-4 describes several of the
ATSDR-derived comparison values available. See Chapter 12 for how these values are used
in an air toxics risk assessment.
Exhibit 30-4. Definitions of ATSDR-Derived Comparison Values
Environmental Media Evaluation Guides (EMEGs). EMEGs are estimated contaminant
concentrations that are not expected to result in adverse noncarcinogenic health effects based on
ATSDR evaluation. EMEGs are based on ATSDR MRLs and conservative assumptions about
exposure, such as intake rate, exposure frequency and duration, and body weight.
Minimal Risk Levels (MRLs). An MRL is an estimate of daily human exposure to a substance (in
mg/kg/day for oral exposures and parts per million [ppm] for inhalation exposures) that is likely to be
without noncarcinogenic health effects during a specified duration of exposure based on ATSDR
evaluations.
Cancer Risk Evaluation Guides (CREGs). CREGs are estimated contaminant concentrations that
would be expected to cause no more than one excess cancer in a million (10"6) persons exposed during
their lifetime (70 years). ATSDR's CREGs are calculated from EPA's cancer slope factors (CSFs) for
oral exposures or unit risk values for inhalation exposures. These values are based on EPA
evaluations and assumptions about hypothetical cancer risks at low levels of exposure.
Reference Media Evaluation Guides (RMEGs). ATSDR derives RMEGs from EPA's oral reference
doses, which are developed based on EPA evaluations. RMEGs represent the concentration in water
or soil at which daily human exposure is unlikely to result in adverse noncarcinogenic effects.
• In-depth Analysis. For those pathways and substances that were identified in the screening
analysis as requiring more careful consideration, the assessor will examine a host of factors to
help determine whether study area-specific exposures are expected to result in illness. In this
in-depth analysis, exposures are studied in conjunction with substance-specific toxicologic,
medical, and epidemiologic data. Through this analysis, the assessor will be answering the
following question: Based on available exposure, toxicologic, epidemiologic, medical, and
study area-specific health outcome data, are adverse health effects expected in the
community?
Answering this last question can be very challenging. For example, evaluating epidemiological
data involves addressing a number of criteria to assist in judging the causal significance of
associations revealed in studies (epidemiology is described in more detail in Exhibit 30-5).
Individual criteria, if met, support a causal relationship but do not prove it. The more criteria that
are met, the more likely it is that an observed health effect is causally related to the exposure
under study. The criteria for evaluating causation are:
• Time sequence. Exposure must precede the onset of the disease. A logical sequence of
events must be demonstrated.
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Exhibit 30-5. What Are Epidemiologic Data and How Might They Be Used
in an In-Depth Analysis?
Epidemiologic data are one of the key distinguishing features of PHAs compared to most quantitative
risk assessments. Understanding the strengths and weaknesses of the various types of epidemiologic
studies will help determine the suitability of a particular study in supporting and drawing study area
and substance-specific public health conclusions. Because of the inherent limitations and
uncertainties associated with environmental epidemiologic evaluations (generally due to the lack of
adequate exposure data or sample size), however, epidemiologic data should be used with caution.
The health assessor should call upon an epidemiologist to assist in evaluating the applicability and
usability of literature-based or study area-specific epidemiologic data. The types of epidemiologic
data that may be available and how they may be used are briefly summarized below, in order of
greatest potential utility:
• Analytical studies, such as case-control or cohort studies, evaluate the role of various risk factors
in causing illness or disease by relying on comparisons between groups. Depending on the quality
of the study, it may provide insight to the study area-specific exposure situation under evaluation.
Study area-specific analytical studies that meet certain design criteria examine study area-specific
exposures and health outcomes in community members. When available, these studies are the most
relevant to the PHA. These data are rarely initially available, but the PHA process may lead to a
recommendation to collect such data. Depending on the individual study design and health
outcome studied, results may provide some insight on the presence or absence of a particular
illness of concern in the community. Unfortunately, establishing a definitive link with a study
area-related exposure is generally difficult if not impossible.
• Descriptive (or ecological) studies examine differences in disease rates among populations over
time or in different geographical locations and may be helpful in identifying plausible associations
between a particular substance and disease. However, descriptive studies provide limited
information on causal relationships (i.e., the degree of exposure or causal agent).
• Case reports that describe an effect in an individual or small group can be considered in the in-
depth analysis, but may have limited usefulness due to the generally small size of the affected
population and sometimes anecdotal nature of the reports.
Strength of association. The stronger the association, the more likely it is causal. The
relative magnitude of the incidence of disease in those exposed compared to the incidence in
those who are not exposed can be a valuable measure of the strength of the association.
Dose-response relationship. The probability and/or severity of the effect should increase
with increasing intensity and duration of exposure.
Specificity of association. If the effect is unusual or is specific to the studied exposure, a
causal relationship is more easily demonstrated.
Consistency. A relationship should be reproducible (i.e., observed in other studies or
analyses).
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• Biologic plausibility (or coherent explanation). The link between the "cause" and the
effect should make sense biologically, by what is known about the disease and the exposure
under study. The findings should be validated by what is known about animal models.
Similarly, biologic sampling results (biomarkers) need to be interpreted with caution.
Specifically, issues to consider include: (1) as with environmental sampling data, biologic data
need to be collected by trained professionals and analyzed in a standard way; (2) detected levels
may not be the result of study area-related exposures (e.g., blood lead levels resulting from non-
air toxics sources such as flaking paint); (3) results will likely only represent a snapshot of
conditions in time; (4) the association between detected levels and clinical effects may not be
understood based on scientific knowledge; (5) "normal" ranges, particularly for trace elements,
may not be known; and (6) the people tested may not be fully representative of the exposed
population, resulting from a small sample size and variations in exposures across the exposed
population due to different activity patterns.
30.5.6 Draw Public Health Conclusions
Upon completing the exposure and health effects evaluations, the assessor will draw conclusions
regarding the degree of hazard posed by a study area - that is, they will conclude either that the
study area does not pose a public health hazard, that the study area does pose a public health
hazard, or that insufficient data are available to determine whether any public health hazards
exist. The process also involves assigning a hazard conclusion category for the study area or
for an individual exposure pathway (Exhibit 30-6).
Exhibit 30-6. Summary of ATSDR Conclusion Categories
Category
1 . Urgent Public
Health Hazard
2. Public Health
Hazard
3. Indeterminate
Public Health
Hazard
4. No Apparent
Public Health
Hazard
5. No Public Health
Hazard
Definition
Applies to study areas that have certain physical hazards or evidence of
short-term (less than 1 year), study area-related exposure to hazardous
substances that could result in adverse health effects and require quick
intervention to stop people from being exposed.
Applies to study areas that have certain physical hazards or evidence of
chronic, study area-related exposure to hazardous substances that could
result in adverse health effects.
Applies to study areas where critical information is lacking (missing or has
not yet been gathered) to support a judgment regarding the level of public
health hazard.
Applies to study areas where exposure to study area-related chemicals might
have occurred in the past or is still occurring, but the exposures are not at
levels expected to cause adverse health effects.
Applies to study areas where no exposure to study area-related hazardous
substances exists.
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30.5.7 Recommend Public Health Actions
After drawing conclusions, the public health assessor - usually in cooperation with other team
members and stakeholders - will develop recommendations for actions, if any, to prevent
harmful exposures, obtain more information, or conduct other public health actions. These
actions generally will be detailed in a public health action plan, which will ultimately be part of
the PHA document (or possibly the public health consultation document) developed for the study
area. Note that some public health actions may be recommended earlier in the process. See
Exhibit 30-7 for an overview of the conclusions and recommendations process.
30.5.8 Prepare PHA Documents
The public health assessor may develop various materials during the PHA process to
communicate information about the assessment, including outreach materials, health advisories
that alert the public and appropriate officials to the existence of an imminent public health threat,
and, at the end of the assessment process, a report that summarizes the approach, results,
conclusions, and recommendations. This report generally is either a public health assessment
(PHA) document or a public health consultation (PHC).
Exhibit 30-7. Overview of Typical PHA Conclusion and Recommendation Process
Cat. 1: Urgent Public
Health Hazard
Cat. 4: Mo Apparent
Public Health Hazard
Cat. 5: No Public
Health Hazard
I
Determining
Recommendations
aad Public
Health Actions'
• Health advisory
Mwsures to
stop or reduce
exposures
Health education
surveillance
Cat. 3: indeterminate
Public I • i!f
Hazard
Further
charactizatian
of sile-reialed
exposures.
where possible
• Sent* oociusxxis art nwmwwwpu&tehsal^
April 2004
Page 30-13
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References
1. Agency for Toxic Substances and Disease Registry (ATSDR). 2002. Public Health
Assessment Guidance Manual (Update): Draft for Public Comment.. Available at:
http://www.atsdr.cdc.gov/HAC/PHAManual/cover.html.
April 2004 Page 30-14
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Chapter 31 Probabilistic Risk Assessment
Table of Contents
31.1 Introduction 1
31.2 Tiered Approach for Risk Assessment 2
31.3 Methods for Probabilistic Risk Assessment 4
31.4 Presenting Results for Probabilistic Risk Assessment 6
References 10
-------
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31.1 Introduction
Probabilistic risk assessment (PRA) uses probability distributions to characterize variability or
uncertainty in risk estimates. In a PRA, one or more variables in the risk equation is defined as a
probability distribution rather than a single number. Similarly, the output of a PRA is a range or
probability distribution of risks experienced by the receptors. Note that the ability to perform a
PRA often is limited by the availability of distributional data that adequately describe one or
more of the input parameters. For example, data often are insufficient to assess toxicity in a
probabilistic manner (and therefore, dose-response values such as inhalation unit risks (lURs)
and reference concentrations (RfCs) are included in a PRA analysis as point values). This
general lack of data impacts both human health and ecological receptors.
The primary advantage of PRA is that it can provide a quantitative description of the degree of
variability or uncertainty (or both) in risk estimates for both cancer and noncancer health effects
and ecological hazards. The quantitative analysis of uncertainty and variability can provide a
more comprehensive characterization of risk than is possible in the point estimate approach.
Another significant advantage of PRA is the additional information and potential flexibility it
affords the risk manager. Risk management decisions are often based on an evaluation of high-
end risk to an individual - for deterministic analyses, this is generally developed by the
combination of a mix of central tendency and high-end point values for various exposure
parameters (see Part n, Chapters 9 and 13). When using PRA, the risk manager can select a
specific upper-bound level from the high-end range of percentiles of risk, generally between the
90th and 99.9th percentiles.
PRA may not be appropriate for every analysis. The primary disadvantages of PRA are that it
generally requires more time, resources, and expertise on the part of the assessor, reviewer, and
risk manager than a point estimate approach. The chief obstacle to using PRA in air toxics risk
assessments is usually the lack of well-documented frequency distributions for many input
variables.
A detailed discussion of PRA is beyond the scope of this document. Two documents provide
more detailed introductory information and guidance and should be reviewed if a PRA is
contemplated:
U.S. EPA. 2001. Risk Assessment Guidance for Superfund (RAGS), Volume III - Part A,
Process for Conducting Probabilistic Risk Assessment. Office of Solid Waste and Emergency
Response. December. EPA 540-R-02-002, OSWER 9285.7-45, PB2002 963302, available
at: http://www.epa.gov/superfund/programs/risk/rags3a/index.htm.
National Council on Radiation Protection and Measurements (NCRP). 1996. A Guide for
Uncertainty Analysis in Dose and Risk Assessments Related to Environmental Contamination.
NCRP Commentary No. 14, May 1996.
V
April 2004 Page 31-1
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This chapter provides a general overview of PRA as it applies to air toxics risk assessment. It
revisits the tiered approach to risk assessment, introduces calculation algorithms, and identifies
advanced statistical methods currently available to support risk policy decisions.
31.2 Tiered Approach for Risk Assessment
The tiered approach is a process for a systematic, informed progression to increasingly more
complex risk assessment methods including PRA. Exhibit 31-1 presents a schematic
representation of the tiered approach. Higher tiers reflect increasing complexity and, in many
cases, will require more time and resources. Higher tiers also reflect increasing characterization
of variability and/or uncertainty in the risk estimate, which may be important for making risk
management decisions. Central to the concept of a systematic, informed progression is an
iterative process of evaluation, deliberation, data collection, work planning, and communication.
All of these steps should focus on deciding: (1) whether or not the risk assessment, in its current
state, is sufficient to support risk management decisions (a clear path to exiting the tiered process
is available at each tier), and (2) if the assessment is determined to be insufficient, whether or not
progression to a higher tier of complexity (or refinement of the current tier) would provide a
sufficient benefit to warrant the additional effort.
• The problem formulation step precedes Tier 1 and includes scoping and refinement of the
conceptual site model, including exposure pathways/routes, and identifying chemicals of
potential concern (COPCs).
• In Tier 1, deterministic (point estimate) risk assessment is then performed using the basic
methodology described in Part II (inhalation) and/or Part IE (multipathway) of this Reference
Manual. In deciding whether the results of a deterministic risk assessment are sufficient for
decision-making or whether more refined analyses should be implemented, two factors
generally are considered: (1) the magnitude of the estimates of risk (i.e., the value of hazard
indices [His] or cancer risks for COPCs), and (2) the level of confidence in these estimates.
In a Tier I deterministic risk assessment, quantitative risk estimates can be easily calculated,
but the level of confidence associated with these calculations can be difficult to assess. For
example, variability in exposure levels among individual members of the population can
generally only be assessed semi-quantitatively by considering central tendency and high-end
exposure estimates. Uncertainty can often be evaluated only as confidence limits on certain
point estimates (e.g., the concentration term).
In some cases, the results of a Tier 1 risk analysis may be sufficient for decision-making. For
example, a deterministic analysis may indicate very low levels of risk for some air toxics. If
the assessment is considered to be overly conservative (even in light of uncertainties), this
may be sufficient for a "no action" decision for those chemicals. The same analysis may
indicate a very high potential for risk for other air toxics. EPA generally recommends that
the risk manager proceed to higher tiers only when site decision-making would benefit from
additional analysis beyond the point-estimate risk assessment (i.e., when the risk manager
needs more complete or certain information to complete the risk management process).
April 2004 Page 31-2
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Thus, only the combinations of COPC-exposure pathway-receptors of highest potential
concern are generally analyzed using higher level techniques such as PRA.
Exhibit 31-1. Example of a Tiered Approach for Risk Assessment
Tier 3: High Complexity
Probabilistic exposure assumptions
Detailed, site-specific modeling
High cost
IZ
to
o
g-c
E o
o ^
0
'tn "G
(C (O
D e cis i on-m ak ing cycle: Evaluating the
adequacy of the risk assessment and the
value of additional com p lexityd eve I of effort
Ti er 2: Moderate Co m pi ex it/
Realistic exposure assumptions
More detailed modeling
Moderate cost
DecEion-making cycle: Evaluating the
adequacy of the risk assessment and the
value of additional com p lexityd eve I of effort
Tier!: Screening Level
Conservative expo sure assumptions
Simple modeling
bow cost
Adapted from Volume III of EPA's Risk Assessment Guidance for Superfund(1)
• Tier 2 is represented as an intermediate-level analysis using more realistic exposure
assumptions (e.g., use of actual receptor locations) and more detailed modeling (e.g., a model
that requires additional site-specific inputs). Although not depicted, Tier 2 could incorporate
a sensitivity analysis to identify the most important parameters that are driving the risk
estimate for specific receptors or population groups. Tier 2 also could incorporate limited
(one-dimensional) Monte Carlo techniques.
• Tier 3 is represented as an advanced analysis using probabilistic techniques such as two-
dimensional Monte Carlo analysis. Results of sensitivity analyses (Tier 2 or Tier 3) could be
used to assess risk distributions for the high-end individuals within the population. The one-
dimensional Monte-Carlo simulation does not separate variability and uncertainty associated
with the risk estimates. If necessary, separate analyses of uncertainty and variability can be
performed in Tier 3. Techniques such as two-dimensional Monte Carlo simulation can be
used to estimate the relative impact of natural variability and lack of data on the overall
uncertainty in the risk estimate, and can be used to direct additional data gathering or to
support mitigation decisions.
The deliberation cycle provides an opportunity to evaluate the direction and goals of the
assessment as new information becomes available. It may include evaluations of both scientific
and policy information. (Also note that, while a three-tiered approach was provided in Exhibit
April 2004
Page 31-3
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31-1, the tiered approach is really more of a continuum from a point where the analysis is done
with little data and conservative assumptions to a point where there is an extensive data set and
fewer assumptions. In between, there can be a wide variety of tiers of increasing complexity, or,
as discussed in Chapter 3, there may only be a few reasonable choices between screening
methods and highly refined analyses. The three tiered approach is only provided here as an
illustration of the concept, not a prescriptive, fixed methodology.)
31.3 Methods for Probabilistic Risk Assessment
As discussed in previous chapters, there are a number of approaches available for analyzing
uncertainty in risk assessments. For simple screening level analyses, or analyses where there are
only a few major sources of uncertainty, sensitivity analyses maybe used to estimate the impacts
of likely variations in the key parameter values. Where scenario uncertainty is important (that is,
there are multiple sequences of events that could contribute to risk), decision tree or Bayesian
statistical analysis are commonly used. The most common numerical technique for PRA
(analyses in which a large number of variables need to be evaluated simultaneously) in large-
scale air risk assessments is Monte Carlo simulation. Monte Carlo simulation integrates varying
assumptions, usually about exposure, to come up with possible distributions (or ranges) of risk
instead of point estimates. A continuous probability distribution can be displayed in a graph in
the form of either probability density functions (PDFs) or corresponding cumulative
distribution functions (CDFs); however, for clarity, it is recommended that both representations
be presented in adjacent (rather than overlaid) plots.
Exhibit 31-2 illustrates a PDF and CDF for a normal probability distribution for adult body
weight. Both displays represent the same distribution, but are useful for conveying different
information. PDFs are most useful for displaying (1) the relative probability of values; (2) the
most likely values (e.g., modes); and (3) the shape of the distribution (e.g., skewness, kurtosis,
multimodality). CDFs can be used to display (1) percentiles, including the median; (2) high-end
risk range (e.g., 90th to 99th percentiles); (3) confidence intervals for selected percentiles; and (4)
stochastic dominance (i.e., for any percentile, the value for one variable exceeds that of any other
variable). Note that it is helpful to include a text box with summary statistics relevant to the
distribution (e.g., mean, standard deviation).
These results expressed as probability distributions help risk managers decide whether and what
actions are necessary to reduce risk. Monte Carlo simulation has been widely used to explore
problems in many disciplines of science as well as engineering, finance, and insurance.0' The
process for a Monte Carlo simulation is illustrated in Exhibit 31-3. In its general form, the risk
equation can be expressed as a function of a toxicity term (as a point value) and multiple
exposure variables (Vn) represented as distributions (not point values):
Risk = [(V^ V2, V3 ...Vn) x Toxicity Equation 3 1-4
The first decision(s) the risk assessor has to make is which of the "Vs" are going to be evaluated
probabilistically. Ideally, every model input that is variable or uncertain should be evaluated to
provide a comprehensive characterization of uncertainty in exposure estimates. In practice, the
April 2004 Page 3 1-4
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number of variables that can be addressed systematically is severely limited by lack of data
related to variability, uncertainty, or both. Sensitivity analyses can often be used to focus the
analysis on the variables that contribute most to the overall uncertainty in risks.
Exhibit 31-2. Examples of Probability Density and Cumulative Distribution Functions
PDF
100 2CO
Body Weight (kg)
3CO
LCD
B 0.75 H
?'
f.
;i C.5D -
J
o 0.25
C.CD
CDF
100 200
Body Weight (kg)
303
Example of a normal distribution that characterizes variability in adult body weight (males and
females combined). The arithmetic mean = 71.7 kg, and standard deviation = 15.9 kg. Body weight
may be considered a continuous random variable. The left panel shows a bell-shaped curve and
represents the PDF, while the right panel shows an S-shaped curve and represents the CDF. Both
displays represent the same distribution (including summary statistics), but are useful for conveying
different information.
Source: Finley and Paustenbach(2)
Solutions for equations with PDFs are typically too complex for even an expert mathematician to
calculate the risk distribution analytically. However, numerical techniques applied with the aid
of computers can provide very close approximations of the solution. This is illustrated here for
the simplified case in which the assessment variables are statistically independent, that is, the
value of one variable has no relationship to the value of any other variable. In this case, the
computer selects a value for each variable (Vn) at random from a specified PDF and calculates
the corresponding risk. This process is repeated many times (e.g., 10,000), each time saving the
set of input values and corresponding estimate of risk. For example, the first risk estimate might
represent a hypothetical individual who drinks 2 L/day of water and weighs 65 kg, the second
estimate might represent someone who drinks 1 L/day and weighs 72 kg, and so forth. Each
calculation is referred to as an iteration, and a set of iterations is called a simulation.
Each iteration of a Monte Carlo simulation should represent a plausible combination of input
values (i.e., exposure or ecotoxicity variables), which may require using bounded or truncated
probability distributions. However, risk estimates are not intended to correspond to any one
person. The "individuals" represented by Monte Carlo iterations are "virtual," and the risk
distributions derived from a PRA allow for inferences to be made about the likelihood or
probability of risks occurring within a specified range for an exposed human or ecological
April 2004
Page 31-5
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population. A simulation yields a set of risk estimates that can be summarized with selected
statistics (e.g., arithmetic mean, percentiles) and displayed graphically using PDF and CDF for
the estimated risk distribution.
Exhibit 31-3. Conceptual Model of Monte Carlo Analysis
Probability Distribution for Random Variables
n
Risk - f(V{. V,. +»» Vn) \ To>LiLy
I
U.lH-HH L.UG-X 2.UC-06
Risk
Random variables (Vl7 V2, ...Vn) refer to exposure variables (e.g., body weight, exposure frequency,
ingestion rate) that are characterized by probability distributions. A unique risk estimate is calculated
by sampling each set of the random values and calculating a result. Repeated sampling results in a
frequency distribution of risk can be described by a probability density function. In human health risk
assessments, the toxicity term is usually expressed as a point estimate. In ecological risk assessments,
the toxicity term may be expressed as a point estimate or as a probability distribution.
31.4 Presenting Results for Probabilistic Risk Assessment
The complexity of risk evaluation, and particularly of probabilistic methods, may pose a
significant barrier to understanding among the affected and interested parties (and thus to the
utility of the analysis). In the past, regulatory decisions have been evaluated primarily in terms of
point estimates of risk and simple dichotomous decision rules (e.g., "If the point estimate of risk
April 2004
Page 31-6
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is above a certain level, take a certain action. If not, take another action."). In contrast, it may
not be intuitively obvious, even to relatively sophisticated audiences, how to relate the outputs of
quantitative uncertainty evaluation to a particular decision. For example, important aspects of a
regulatory decision may rest on relatively subtle statistical distinctions (e.g., the difference
between a 95th percentile risk estimate and a 95th percent upper confidence limit on a risk
estimate), and the challenges in presenting such information can be formidable. In its recent
guidance, EPA has begun to define concrete approaches to presenting risks and uncertainty
information to decision-makers and stakeholders .(5)
The key factors for successful communication of PRA include early and continuous involvement
of affected and interested parties, a well-developed communication plan, good graphics, a
working knowledge of the factors that may influence perceptions of risk and uncertainty, and a
foundation of trust and credibility. A certain amount of training for interested stakeholders will
likely be necessary to help them understand the complexities of not only risk assessment in
general, but the intricacies of higher levels of analysis. Part IE of this Reference Manual
provides guidance on community involvement and risk communication.
When summarizing results of PRA, graphs and tables should generally also include the results of
the point estimates of risk (e.g., central tendency and high-end).
Consistent with EPA's guidance on risk characterization/3' the central tendency and high-end
cancer risks and noncancer hazards, along with decision points, should be highlighted on
graphics. The discussions accompanying the graph should emphasize that these values represent
risks to the average and high-end individuals, respectively, and serve as a point of reference to
EPA's decision point. The distribution of risks should be characterized as representing
variability among the population based on differences in exposure. Similarly, graphics that show
uncertainty in risk estimates can be described using terms such as "confidence interval,"
"credible interval," or "plausible range," as appropriate. The graphics need not highlight all
percentiles. Instead, selected percentiles that may inform risk management decisions (such as the
5th, 50th, 90th, 95th, and 99th percentiles) should be the focus. Exhibit 31-4 presents an example of
a PDF for variability in risk with an associated text box for identifying key risk descriptors.
By understanding the assumptions regarding the inputs and modeling approaches used to derive
point estimates and probabilistic estimates of risk, a risk communicator will be better prepared to
explain the significant differences in risk estimates that have been developed. Special emphasis
should be given to the model and parameter assumptions that have the most influence on the risk
estimates, as determined from the sensitivity analysis.
April 2004 Page 31-7
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Exhibit 31-4. Example of Presenting the Results of a Probabilistic Risk Assessment
0.06
le=1.8E-Oa
95lh %ile= 1.2E-06.
90lh %ile = 9.2E-07
50lh
D.OE*OD 5.DE-Q7 I.D&Dfl 1.5E-OG 2.QE-D6 2.5E-06 10E-06
Risk
1.0D
[CDF
99(h %ile = 1 .SE-06
95th tale = 1 .2E-06
90th tale = S.2E-07
50th %ile = 4.1E-07
1.0E-06 1.SE-06
Risk
::-; :e
2.5E K
-3.0E06
Hypothetical PRA results showing a PDF (top panel) for cancer risk with selected summary statistics
for central tendency and high-end percentiles. This view of a distribution is useful for illustrating the
shape of the distribution (e.g., slightly right-skewed) and explaining the concept of probability as the
area under a curve (e.g., most of the area is below IxlO"6, but there is a small chance of 2xlO"6).
Although percentiles can also be overlayed on this graphic, a CDF (bottom panel) may be preferable
for explaining the concept of a percentile.
April 2
Page 31-I
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Additional References on Uncertainty Analysis
Burmaster, D.E. and Anderson, P.D. 1994. Principles of good practice for the use of Monte Carlo
techniques in human health and ecological risk assessments. Risk Analysis 14: 477-481.
Cullen, A.C. and Frey, H.C. 1999. Probabilistic Techniques in Exposure Assessment. New York:
Plenum Press.
Fayerweather, W.E., Collins, J.J., Schnatter, A.R., Hearne, F.T., Menning, R.A., and Reyner, D.P.
1999. Quantifying uncertainty in a risk assessment using human data. Risk Analysis 19: 1077-1090
Finkel, A.M. and Evans, J.S. 1987. Evaluating the benefits of uncertainty reduction in environmental
health risk management. Journal of the Air Pollution Control Association. 37: 1164-1171.
Frey, H.C. 1992. Quantitative analysis of uncertainty and variability in environmental policy making.
Pittsburgh: Carnegie Mellon University.
Hattis, D. and Burmaster, D.E. 1994. Assessment of variability and uncertainty distributions for
practical risk assessments. Risk Analysis 14: 713-730.
Hope, B. K. 1999. Assessment of risk to terrestrial receptors using uncertainty analysis - A case
study. Human and Ecological Risk Assessment 5(1): 145-170.
Moore, D.R.J., Sample, B.E., Suter, G.W., Parkhurst, B.R., and Teed, R.S. 1999. A probabilistic risk
assessment of the effects of methylmercury and PCBs on mink and kingfishers along East Fork Poplar
Creek, Oak Ridge, Tennessee, USA. Environmental Toxicology and Chemistry 18: 2941-2953.
National Research Council (NRC). 1991. Human Exposure Assessment for Airborne Pollutants.
Washington DC: National Academy Press.
Roberts, S.M. 1999. Practical issues in the use of probabilistic risk assessment and its applications to
hazardous waste sites. Human and Ecological Risk Assessment. 5(4): 729-868. Special Issue.
Smith, R.L.. 1994. Use of Monte Carlo simulation for human exposure assessment at a Superfund
site. Risk Analysis 14(4): 433-439.
U.S. Environmental Protection Agency. 1985. Methodology for Characterization of Uncertainty in
•, Exposure Assessments. Washington DC, EPA-600/8-85-009). ,
April 2004 Page 31-9
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References
1. Rugen, P. and B. Callahan. 1996. An overview of Monte Carlo: A fifty year perspective.
Human Health and Ecological Risk Assessment 2(4): 671-680.
2. Finley, B. and D. Paustenbach. 1994. The benefits of probabilistic exposure assessment:
Three case studies involving contaminated air, water, and soil. Risk Analysis 14(1): 53-73.
3. U.S. Environmental Protection Agency. 1992. Guidance on Risk Characterization for Risk
Managers and Risk Assessors. Risk Assessment Council, Washington, DC, February 26,
1992.
April 2004 Page 31-10
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Chapter 32 Use of Geographic Information Systems
(GIS) in Risk Assessment
Table of Contents
32.1 Introduction !
32.2 Selecting a GIS 2
32.3 Acquiring and Using Demographic Data 4
32.3.1 U.S. Census Data 5
32.3.2 Current and Small-Area Demographic Estimates 5
32.3.3 Public Health Applications 7
32.3.4 Data Access and Distribution 7
32.4 Cartographic Concepts 7
32.4.1 Generalization, Simplification, and Abstraction K)
32.4.2 Map Projections K)
32.5 Using the Internet as a GIS Tool 10
32.6 Current GIS Applications at EPA jj.
32.6.1 ORD/ESD 12
32.6.2 ATtlLA 12
32.6.3 ReVA 12
32.7 GPS Technology 13
References 15
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32.1 Introduction
A geographic information system (GIS) can be defined as an organized collection of software
and geographic data that allow efficient storage, analysis, and presentation of spatially explicit
and geographically referenced information. Traditional methods of processing such data have
been extremely labor intensive, such as manually digitizing a map from an aerial photograph and
then adding information about chemical contaminants. A GIS provides a powerful analytical tool
that can be used to create and link spatial and descriptive data for problem solving, spatial
modeling and presentation of results in tables or maps. For air toxics risk assessment, GIS can
be a powerful tool for displaying and analyzing data during the planning, scoping, and problem
formulation phases, during the exposure assessment, and displaying and evaluating the results of
the risk characterization. It is also a very helpful means for communicating information to risk
managers and other stakeholders.
GIS data generally consist of two components: (1) graphical data about geographic features (e.g.,
rivers, land use, political boundaries), and (2) tabular data about features in the geography (e.g.,
population, elevation, modeled ambient concentrations of air toxics). GIS combines these
different types of data using a "layering" technique that references each type of data to a uniform
geographic coordinate system (usually a grid such as latitude and longitude coordinates).
Layered data can then be analyzed using special software to create new layers of data (see Exhibit
32-1).
Over the last several years, GIS applications have evolved from very specialized and expensive
analyses that required specialized computers (e.g., supercomputers and workstations) to user-
friendly desktop applications utilized by everyday users to do such mundane tasks as print maps
or driving directions. Libraries of geographical information developed for general use (e.g.,
topographical maps, infrastructures, natural resources), and for use by EPA and other regulatory
agencies, can be easily downloaded from different servers and used in air toxics risk assessments.
One example of a GIS Web-based application is EPA's Envirofacts system(1) which provides
website access to several EPA databases that provide information about environmental activities
that may affect air, water, and land anywhere in the United States (with much of the data
available in GIS format).
This chapter provides an overview of GIS and its application to air toxics risk assessment. More
detailed information is provided in the Agency for Toxic Substances and Disease Registry
(ATSDR)/Southern Appalachian Assessment GIS (SAAGIS) publication Introduction to
ArcView and Spatial Analysis Techniques for Public Health Professionals.^
April 2004 Page 32-1
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Exhibit 32-1. Example Conceptual Model Using CIS
Monitoring Wells
Well ID
C-6A
C-8A
C-13A
C-17A
Date Sampled
S&/94
5to94
•V.'vi'i
5ft/94
Concentration
300
30
130
sea
Industries
FaoWy
ACIT»
Fox
TPC
Addiess
3029 Cortvington Dr.
742 West Lake St,
90 Aspen Dr.
Population
Family Name
BJehe
Hernandez
Joy
Smith
O':i:u|j jnlr;
B
2
4
5
Addre&ss
79 Circirt St
1 48 Plain St.
18 Webster Si.
4321 Tecumseh Dr
Example of layering within a GIS. The location of monitoring wells, industries, and potential
receptors (homes) are all referenced to the same geographic coordinates. This allows spatial
analysis of the overlap of sources, contaminant plumes, and receptors, as well as a visual
means to communicate complex data sets.
32.2 Selecting a GIS
After risk assessors decide to use a GIS, they must choose a software system. A variety of GIS
software is available from commercial vendors. A key feature in selecting a GIS is identifying a
minimal set of capabilities needed. Important functional capabilities to consider include: data
capture, data storage, data management, data retrieval, data analysis, and data display.(3)
• Data Capture. All data used in a GIS must have a spatial component. This means that all
information brought into the system must be geo-referenced (i.e., correspond to some
physical location). Data capture is the process of incorporating map and attribute data into
the GIS. Geocoding, which is the conversion of analog data to geo-referenced digital format,
is a common way for GIS users to bring map and attribute data into their GIS analyses. Two
common methods of geocoding are scanning and digitizing. Both involve taking non-digital
information (e.g., a hard-copy map), and converting it into a digital format. In addition to
paper files, GIS users often import files from common formats such as AutoCAD DXF. The
April 2004
Page 32-2
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newly imported digital information (e.g., the boundary of a state), is geo-referenced by
coordinates so that it corresponds to a physical location.
In addition to graphical data, GIS incorporates tabular data for objects included in a data
layer. For example, the graphical data associated with a home could consist of its size and
location. The tabular data associated with that home consists of attributes such as who lives
there, when it was built, where its water supply comes from, and what type of heating system
it uses. These attributes would be listed in a table that is linked to the physical location of the
house by the GIS. While obtaining geographical base layers that show boundaries is
essential, data capture also involves attribute data, which necessitates that the GIS software
package have some level of database manager associated with the program. A useful
program will generally have features that allow it to import common database files such as
those from dBASE®, Access®, Excel®, and Paradox®. The different software packages will
vary in their ability to check the characteristics of the databases.
Data Storage. A GIS can incorporate a tremendous amount of data into a map. Space is a
key issue related to data storage in a GIS. With the decrease in cost of disk storage, the
development of high-density storage media (e.g., CD-ROM), and the incorporation of
compression methods, space is not as critical an issue as it has been in the past. However,
GIS is still relatively memory-intensive. GIS microcomputer software can take up tens of
megabytes of space without data, and a more complete workstation version may use hundreds
of megabytes of space. Add to this the datasets with very high resolution (that can move into
the gigabyte range in size), and there is a the potential for a significant storage problem.
Some storage problems can be resolved by establishing data sets on a common server,
accessible to multiple users.
Data Management. A powerful GIS is one which has the ability to manage both map and
attribute data. Every GIS is built around the software capabilities of a database management
system (DBMS). A DBMS is software that is capable of storing, selecting, retrieving, and
reorganizing attribute information. It allows data entry, data editing, and supports several
different types of output. Functions include the ability to select records based on their value.
Several database functions can work independently of the GIS functions.
Data Retrieval. A GIS will support the retrieval of features by their attributes or by their
spatial characteristics. A basic retrieval based on spatial characteristics is used to show the
position of a single feature. In addition, a GIS is capable of allowing the operator to use the
map as a query vehicle. A simple way of doing this is to point to a feature and retrieve the
list of attributes for that feature. The database management function also is important for the
data retrieval capacity because it allows for the selection and retrieval based on an attribute.
Buffering is one retrieval operation that defines a GIS. Buffering allows the user to retrieve
features within a specified distance of a point, line, or area. Overlay is another spatial
retrieval operation in which non-overlapping regions are joined to create a new area. More
sophisticated retrieval operations also are available.(2)
April 2004 Page 32-3
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• Data Analysis. GIS systems vary a great deal in their data analysis capabilities. Basic tasks
that should be included in a GIS are: spreadsheet and database analysis, computing new
attributes, generating summary statistics, creating reports, statistics such as mean and
variance, significance testing, and plotting residuals. In addition, selected geometric tests
should be included (e.g., point-in-polygon analysis, surface partitioning).
• Data Display. GIS software displays information visually as data layers of a map. GIS users
must select the correct map projection to make sure that their maps are not distorted. For
example, large areas, such as continents, must be projected with the earth's curvature taken
into consideration. Small areas can be projected essentially as fiat. GIS software gives users
as wide variety of map projection options to ensure that maps are as accurate as possible.
Section 32.4.2 discusses map projections in further detail.
Different data sources and agencies provide digital data that has been processed using
different coordinate systems and map projections. Risk assessors may want to use data layers
from many different sources to create a single map. For example, a topography layer from
the U.S. Geologic Survey might be combined with a layer showing census blocks from the
U.S. Census and a layer showing lead smelters from EPA. Software that can handle a variety
of coordinate systems and map projections is essential to GIS capability to overlay layers
created from many different sources.
32.3 Acquiring and Using Demographic Data
Demography is the study of the size, composition, distribution, and change in population.
Geographers focused on population studies are also interested in the spatial distribution of
demographic characteristics.^ Data from the U.S. Bureau of the Census decennial census is the
most common source of residential population information for states, the District of Columbia,
and many U.S. territories (e.g., Puerto Rico, U.S. Virgin Islands, American Samoa, and Guam).
These data also provide the base for current year population estimates and projections. Risk
assessors are often interested in using demographic data because it allows them to identify
sensitive sub-populations, such as children or the elderly. A GIS lets risk assessors combine
demographic data with data on the location of sources (or estimated ambient air concentrations)
to visualize where human health is potentially at risk (see Exhibit 32-2).
Within a GIS, political and statistical geographic area boundary files are linked to the attribute
data (e.g., age, race, housing value) describing residents and housing units in that area using
Federal Information Processing Standard (FIPS) codes. These codes provide unique identifiers
for various geographic areas. When analyzing census data that is nested within the data hierarchy
(e.g., census blocks within census tracts), it is best to include the FIPS codes for the larger
geographic areas in that hierarchy to ensure that you are using a unique identifier. For example,
connecting the FIPS codes for block 201, census tract 12, Fulton county, state of Georgia, results
in the unique identifier "13089001200201" for that block. Because the codes are nominal
numerals, it is best to treat them as character data (or strings) rather than numbers in the GIS
database (although this may not be consistent across data sources).
April 2004 Page 32-4
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Exhibit 32-2. Illustration of the Use of CIS to Identify
Sensitive Receptors Close to Emissions Sources
"Vf^f^^j w/1
In this map, the squares represent hazardous waste sites, and the flagged
symbols represent schools. Schools and other locations where sensitive
subpopulations may occur that are close to air toxics emissions sources may
be of particular interest in a risk assessment.
32.3.1 U.S. Census Data
U.S. census data describing the residential population and housing in the U.S. provide the most
complete picture of our nation and its subareas, which makes them very valuable demographic
data. Exhibit 32-3 shows the type of information collected in the 2000 census. Many of the
Census 2000 data files are available for use in GIS.
32.3.2 Current and Small-Area Demographic Estimates
An issue with census data is that the information represents a "snapshot" in time (generally based
on April 1 of the census year). As one moves forward in time, such data may be less reflective of
the actual demographic conditions in the study area. This problem is more pronounced for small-
area data (e.g., census tracts and block groups). While the census data typically are appropriate
for screening-level assessments (e.g., some air quality models include the 2000 census data),
more refined assessments may require more current information, which is available from several
commercial sources.
April 2004
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Exhibit 32-3. Information Collected in the 2000 Census
During census years, households received and were asked to respond to one of two census forms - the
"short form," which gives the "100-percent component," or the "long form," which gives the "sample
component." Questions on the short form were also found on the long form and thus, were
(theoretically) asked of every household in the nation. Basic population and housing data were
gathered in this way. More detailed population information was obtained from the long form sent to a
sample of households. On average, approximately one in six households received the long form. The
rate varied from one in two households in some smaller areas, to one in eight households for more
densely populated areas.
100 Percent Component from the Short Form
Population
• Name
• Household relationship
• Sex
• Age
• Hispanic or Latino origin
• Race
Housing
• Tenure - owned or rented
Sample Component from the Long Form
Population
Social characteristics
• Marital status
• Place of birth, citizenship, year of entry to the
U.S.
• School enrollment and attainment
• Ancestry
• Residency five years ago (migration)
• Language spoken at home and ability to speak
English
• Veteran status
• Disability
• Grandparents as care givers
Economic characteristics
• Labor force status
• Place of work and journey to work
• Occupation, industry, and class of worker
• Work status in 1999
• Income in 1 999
Housing
• Units in structure
• Year structure built
• Number of rooms and number o f bedrooms
• Year moved into residence
• Plumbing and kitchen facilities
• Telephone service
• Vehicles available
• Heating fuel
• Farm residence
Financial Characteristics
• Value of home or monthly rent paid
• Utilities, mortgage, taxes, insurance, and
fuel costs
Source: U.S. Census. Census 2000 Basics. Available at:
http://www.census.20v/mso/www/c2000basics/OOBasics.pdf
April 2004
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A number of commercial entities provide annual small-area population and housing estimates
and projections. Estimates are calculated using the most recent decennial census as the
population base and incorporating other, often proprietary, data sources to refine the estimates.
In addition to providing updated demographics, some vendors have developed segmentation
systems that classify the U.S. population into distinct lifestyle segments or clusters depending on
residential location ("geodemographics"). The idea of clustering is based on the notion that,
more often than not, people will choose to live near others like themselves. This is important to
public health because assessors can be more efficient in identifying and understanding where
potential hazards are concentrated, as well as developing messages that reach people living in
those areas.
32.3.3 Public Health Applications
The use of census data is central for public health communication planning, program planning,
implementation and information dissemination. For example, the Georgia Division of Public
Health used demographic information to target mammography programs in factory towns
classified as "Mines & Mills" because women in those communities were found to have higher
rates of breast cancer.(5) As another example, the Centers for Disease Control (CDC) Office of
Communication has collaborated with a number of centers on projects that integrate
epidemiological and other data for communication planning including HIV status awareness and
hantavirus prevention/6' Because exposure to air toxics is often influenced significantly by
proximity to sources, spatial information is essential to identifying areas where human health
might be adversely impacted.
32.3.4 Data Access and Distribution
There are numerous sources for acquiring U.S. census data. In addition to the Census Bureau's
data access tools, including Factfinder, its Web-based data dissemination system, many public
and private organizations are including census data with GIS or mapping software (e.g., ESRI,
EPA LandView, HUD Community 2020, Geolytics, Claritas, CACI). State governments,
universities, and non-governmental organizations (e.g., CIESIN) are also sources for data. Costs
associated with obtaining the data vary.
32.4 Cartographic Concepts
While spatial information and GIS can be extremely useful, people must have assistance in
observing and studying the great amount and variety of information that is represented on maps.
Geographic data are extensive and voluminous, so cartography, a technique that is fundamentally
concerned with reducing the spatial characteristics of a large area, makes maps readable and
meaningful. A map is more than a reduction of information to an understandable level. If it is
well made, it is a carefully designed instrument for recording, calculating, analyzing, and in
general, understanding the interrelation of things in their spatial relationship. This section
provides an overview of cartography. A more complete discussion can be found in The
Geographer's Craft Project.,(7)
April 2004 Page 32-7
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One of the most useful approaches to the study of cartography is to view maps as a form of visual
communication - a special purpose language for describing spatial relationships. Cartography is
related to, but different from other forms of visual communication. Cartographers must pay
special attention to coordinate systems, map projections, and issues of scale and direction that are
in most cases of relatively little concern to other graphic designers or artists. But, because
cartography is a type of graphical communication, some insights to the demands of cartography
can be gleaned from the literature of graphical communication and statistical graphics. By
stressing cartography as a form of communication, it is easier to make the point that maps are
really symbolic abstractions - or representations - of real world phenomena. In most cases, this
means that the world represented on a map has been greatly simplified, or generalized, with
symbols being used like words to stand for real things. Some of the most important decisions
cartographers make in the process of cartographic design revolve around: (1) how much to
simplify the situation being depicted; and (2) how to symbolize the relationships being
represented. In order to make good choices, cartographers often ask themselves the following
questions:
• What is the motive, intent, or goal of the map?
• Who will read the map?
• Where will the map be used?
• What data is available for the composition of the map?
• What resources are available in terms of both time and equipment?
By identifying the most important points to be conveyed by the map along with the map's main
audience, cartographers can prioritize where to direct the audience's attention with larger
symbols or brighter colors.
April 2004 Page 32-i
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Basic Map Elements
A legend and symbols that inform the viewer of distance, scale, and direction, are basic elements to
any map. The USGS (http://edc.usgs.gov/earthshots/slow/Help-GardenCity/legendstext) provides
examples of common map legends.
Example U.S. Geological Survey (USGS) Topographic Map Legend
ROADS AM) REUTED FEATURES
BUILDINGS AND RE1ATID FEATURES
F-ir- i-y highway
Buttng
SAtandiry highway
School; church
Unimpcmid rrud
Trail
Airport
Landing itrip
Dual Ngfrvfty wrttl iMdiin «f*
Roid under tnnitrucMn
UrJcrpsss: cvnrpjjs — j —
Bridg*
Or»«bSE3
!»• f-
"**
...
• G j>; -^g staho-i •
( • landmark object i!a-i:ui e at iitHl«4l D
t- Camp9f«gr>d; picnic if» 1 ~
TMMSMISS1DN LINES AND PIPELINES
Comotery: j.-nul! :'.;L'
Rumor IrimmiHiM b»: pole; lovrtr
on* lin*
Attf.fjround oil cr gas pipchrtt
a- gw pp*ir«
Example Legend for Universal Transverse Mercator (UTM) Projection Zones
BLUE HUMBefieo LIKES INDICATE 100.000 METERS. TICKS 10.000 METERS
UKIVEftSAL TRANSVERSE MERCATOR GRIP. ZOMES 18H. 19H. 20H. I8J, 19J. JOi
SAM PU UEA: TO R[fEREKCE ID N [AStST 1.000 M EIEK
«*OH.
SAMPLE POINT RAOAL
1. bid kites Miniltnm 100.000 rnHlr
squire in «rtiir,h lite Mint it!
? l«iir llrsl VtPTIUL (rid liw a lick la
LEFT ol poinl ind «et«irnlnt LMfif l||
uie vjKit
{MinulF lentm Irgn iiid lint to pcim
! Louie nisi H WON ML (iin Hnr or
lick BElOW poim ind d«ermrrc UKi
filuit .Hut
iv, ir«n trirj tat te point:
SAMPLE KFEfltNCE.
II reputing >.:,JK y N.S. w If E.W..
pielii Grd .' .inn Dnijnation, K
YB2581
18HYB2581
COMPUTE CHID VALUES ARE SHOWN 10 DETERMINE FUU COOROIKATES. REMAINING
VALUES IM BORDER ARM REFIECTOWSSWH OF LAST FOUR WCffS. ~--^
April 2004
Page 32-9
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32.4.1 Generalization, Simplification, and Abstraction
As noted above, cartography is a process of f ,, A„ .. ™
' ° F -^ F Map Making Tips
abstraction in which features of the real world
Experiment with different layouts
Think carefully about every element on your
map and whether it has an essential function
Less is more
are generalized or simplified to meet the
demands of the theme and audience. Not all
elements or details have a bearing on the
pattern or process being studied and so some
are eliminated to draw the reader's attention x' "^
to those facts that are relevant. Too much
detail can even hide or disguise the message of a map. The amount of detail that can be included
is very much dependent on the scale at which the map will be produced (see Exhibit 32-4).
32.4.2 Map Projections
As section 32.2 notes, the projection used to create a map influences the representation of area,
distance, direction, and shape. This is readily apparent when looking at a flat map of the world
versus looking at a spherical map of the world (i.e., a globe). Maps that ignore the natural shape
of the earth distort the places they are trying to represent. It should be noted when these
characteristics (e.g., area, distance, direction, and shape), are of prime importance to the
interpretation of any map. Some widely used locational reference systems such as the U.S. State
Plane Coordinate system and Universal Transverse Mercator system are based on predefined
projective geometries that are implicit in the use of the coordinate systems themselves. GIS
software packages make it easy for users to choose an appropriate map projection.
32.5 Using the Internet as a GIS Tool
The internet can be a valuable resource for GIS users looking for data. Many federal agencies
provide digital data free for download that can be used with GIS. The Census Bureau, EPA, and
the United States Geological Survey are all good sources of GIS data. For example, in addition
to demographic data, the Census bureau distributes what are called Topologically Integrated
Geographic Encoding and Referencing (TIGER) files. The TIGER/Line files are a digital
database of geographic features, such as roads, lakes, political boundaries, and census statistical
boundaries, available for the entire United States. The database contains tabular information
about these features such as their location in latitude and longitude, the name, the type of feature,
and other important attributes. GIS clearinghouses, universities, and data supply companies are
also good places to look for data. A Web search engine can help users locate sites that contain
the type of data needed for a given project.
Once users locate relevant data, they must then get the data onto their computer. GIS coverages
can take up a lot of computer memory, so choosing the right file transfer method is very
important. Many websites allow direct downloads. This type of transfer involves clicking a link
and specifying a target directory. Other data providers require users to go through a file transfer
protocol (FTP) site. FTP sites allow people to exchange large data files more readily than with
other protocols.
April 2004 Page 32-10
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Exhibit 32-4. Effect of Scale on Detail and Abstraction
1:250,000
Increasing need for
generalization.
Notice how details
become blurred as
the scale decreases.
Finally, the internet can serve as a resource for users looking for technical support or advice.
Most users will find that GIS software manufacturers offer online support. Some companies
even have online courses.
32.6 Current GIS Applications at EPA
EPA is an excellent source of GIS data and information for risk assessors. Several offices and
branches can serve as resources for those interested in learning more about GIS and its uses,
especially in the areas of landscape, land cover, and land use. GIS helps EPA integrate geo-
spatial data on a region (e.g., landscape, elevation, climate, slope) with information about
potential exposures to give risk assessors a comprehensive picture of that region's hazards.
Because projected land use maybe an important input to air models, risk assessors may want
more information on landscape change models. For an overview on this subject, see EPA's
Projecting Land-Use Change: A Summary of Models for Assessing the Effects of Community
Growth and Change on Land-Use Patterns.^
April 2004
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32.6.1 ORD/ESD
EPA's Office of Research and Development/Environmental Sciences Division (ORD/ESD)
conducts research, development, and technology transfer programs on environmental exposures
to ecological and human receptors. GIS is an important tool for the type of chemical and
physical stressors characterization conducted, especially with ESD's emphasis on ecological
exposure. The Division develops landscape and regional assessment capabilities through the use
of advanced spatial monitoring and analysis techniques, such as remote sensing and GIS. For
more information, go to http://www.epa. gov/nerlesd 1 /.
32.6.2 ATtlLA
Another EPA resource is the Landscape Ecology Branch's ATtlLA program, which stands for
Analytical Tools Interface for Landscape Assessments. The Branch uses ATtlLA, which is a
GIS, to conducts multiple-stressor regional assessments based largely on geo-spatial landscape
data. As part of these assessments, ATtlLA generates complicated landscape metrics, which are
quantitative measurements of the environmental condition or vulnerability of an area (e.g.,
ecological region). ATtlLA provides an interface that allows users to easily calculate many
common landscape metrics regardless of their level of GIS knowledge, despite the complexity of
developing the metrics. Four metric groups are currently included in the package (e.g.,
Landscape Characteristics, Riparian Characteristics, Physical Characteristics, and Human
Stresses). ATtlLA runs within Arc View®, and is designed to be flexible enough to accommodate
spatial data from a variety of sources. More information is available at:
http ://www. epa. gov/nerlesd 1 /land-sci/northern_california/attila/b ackground.html.
32.6.3 ReVA
Also from EPA's ORD is the Regional Vulnerability Assessment (ReVA) program. This
program is an approach to regional scale, priority-setting assessment meant to expand
cooperation among the laboratories and centers of ORD, by integrating research on human and
environmental health, ecorestoration, landscape analysis, regional exposure and process
modeling, problem formulation, and ecological risk guidelines. Currently, ReVA is working in
the Mid-Atlantic region to predict future environmental risk. This will help EPA prioritize
efforts to protect and restore environmental quality efficiently and effectively. ReVA is being
developed to identify those ecosystems most vulnerable to being lost or permanently harmed in
the next 5 to 25 years and to determine which stressors are likely to cause the greatest risk. The
goal of ReVA is not exact predictions, but identification of the undesirable environmental
changes expected over the coming years.
Many functions work together to provide ReVA's regional assessment capability. GIS puts into
a spatial context data on stressors and effects from many sources. Research guides how to apply
this data at the landscape and regional scale and helps EPA understand how socioeconomic
drivers affect environmental condition. The transfer of data and analytical tools to regional
managers is also critical for this tool to be useful. ReVA is considered a GIS because it is
designed to analyze the spatial distribution of sensitive ecosystems by analyzing known
April 2004 Page 32-12
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distributions of plant and animal populations or communities within ecosystems. Modern
methods in landscape ecology and characterization help further identify the locations of
ecosystems that are vulnerable to future stress through features such as topography (i.e. increased
erosion potential) and habitat patch configurations. Multimedia assessments across water, air,
terrestrial, and demographic variables are possible at various scales with this tool. For more
information on ReVA, see http://www.epa.gov/reva/approach.htm.
32.7 GPS Technology
Global Positioning System (GPS) technology can be integrated with GIS. GPS technology
allows users with the appropriate technology to obtain almost the exact location of any GPS
receiver. This means that cars can get driving directions while moving, hikers can always know
their exact position for navigating in and out of the wilderness, and the military can track
movements of troops or vehicles. For risk assessments, the location of specific sources (i.e.,
vents) or receptor locations can be accurately determined with GPS. GPS is funded and
controlled by the U.S. Department of Defense (DOD). While there are many thousands of civil
users of GPS world-wide, the system was designed for, and is operated by the U.S. military.
The system works through specially coded satellite signals that can be processed in a GPS
receiver, enabling the receiver to compute position, velocity, and time (see Exhibit 32-5). Four
GPS satellite signals are used to compute positions in three dimensions and the time offset in the
receiver clock (see Exhibit 32-6).
The GPS provides two levels of service - a Standard Positioning Service (SPS), and a Precise
Positioning Service (PPS). Access to the PPS is restricted to U.S. Armed Forces, U.S. Federal
agencies, and selected allied armed forces and governments. The SPS is available to all users on
a continuous, worldwide basis, free of any direct user charge. A nationwide differential GPS
service (NDGPS) is being established pursuant to the authority of Section 346 of the Department
of Transportation and Related Agencies Appropriation Act. When complete, this service will
provide uniform differential GPS coverage of the continental U.S. and selected portions of
Hawaii and Alaska regardless of terrain, man-made, and other surface obstructions. NDGPS
accuracy is specified to be 10 meters or better. Typical system performance is better than 1 meter
in the vicinity of the broadcast site. Achievable accuracy degrades at an approximate rate of 1
meter for each 150 km distance from the broadcast site.(9)
Receiver costs vary depending on capabilities. Small civil SPS receivers can be purchased for
under $200. Receivers that can store files for post-processing cost more ($2,000 to 5,000).
Receivers that can act as DGPS reference receivers (computing and providing correction data)
and carrier phase tracking receivers (and two are often required) can cost many thousands of
dollars ($5,000 to $40,000).
Receivers are important because they are the intermediary part of the system that connect real
world data to GIS. Satellites send signals to the receiver and users and store the information.
Sometimes, the user will have to manually record position and time readings and then type those
April 2004 Page 32-13
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into a computer later. Other times the user can plug the receiver into a special port on her
computer and download the digital data directly.
Exhibit 32-5. Global Positioning System (GPS) Satellites
Peter H Dana 9/22V9I
GPS Nominal Constellation
24 Satellites in 6 Orbital Planes
4 Satellites in each Plane
20,200 km Altitudes, 55 Degree Inclination
GPS satellites orbit the Earth every 12 hours, sending signals to receivers
around the world
Exhibit 32-6. Positioning and Time from Four GPS Satellites
XYZT
The Global Positioning System
Measurements of code-phase arrival times from at least four satellites are used to estimate four
quantities: position in three dimensions (X, V, Z) and GPS time (T).
Measurements of code-phase arrival times from at least four satellites are used to estimate four
quantities: position in three dimensions (X, Y, and Z) and GPS time (T).
April 2004
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References
1. U.S. Environmental Protection Agency. 2004. Envirofacts Data Warehouse. Available at:
http://www.epa.gov/enviro/index.html (Last accessed March 2004).
2. Agency for Toxic Substances and Disease Registry. 2004. Introduction to ArcView and
Spatial Analysis Techniques for Public Health Professionals. An ATSDR/SAAGIS
publication (in press).
3. Clarke, K.C. 1997. Getting Started with Geographic Information Systems. Prentice Hall,
Upper Saddle River, NJ.
4. Plane, D.A., and Rogerson, P. A. 1994. The Geographical Analysis of Population. John Wiley
& Sons, Inc, New York, NY.
5. Weiss, M.J. 2000. The Clustered World. Little, Brown and Company, Boston, MA.
6. Pollard, W., and Kirby, S. 1999. Geographical Information Systems (GIS), Public Health
Data, and Syndicated Market Research Data Bases in Health Communication. Presented at
the National Conference on Health Statistics, Washington, B.C.
7. Kenneth E.F. and Crum, S. The Geographer's Craft Project. Department of Geography,
University of Texas at Austin.
8. U.S. Environmental Protection Agency. 2000. Projecting Land-Use Change: A Summary of
Models for Assessing the Effects of Community Growth and Change on Land-Use Patterns.
Office of Research and Development, Cincinnati, OH. EPA/600/ROO/098.
9. U.S. Department of Defense and U.S. Department of Transportation. 2001. 2001 Federal
Radionavigation Plan, DOT/VNTSC/RSPA-01/3; DOD-4650.5. Available at:
http://www.navcen.uscg.gov/pubs/frp2001/FRP2001.pdf. (Last accessed March 2004.)
April 2004 Page 32-15
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Glossary
This list of glossary terms was compiled from existing EPA definitions and supplemented, where
necessary, by additional terms and definitions. The wording of selected items may have been
modified from the original in order to assist readers who are new to risk assessment more readily
comprehend the underlying concept of the glossary entry. As such, these glossary definitions
constitute neither official EPA policy nor preempt or in any way replace any existing legal
definition required by statute or regulation.
-------
-------
Absorbed Dose - the amount of a substance that has penetrated the absorption barriers (e.g.,
skin, lung tissue, gastrointestinal tract) of an organism through either physical or biological
processes.
Absorption - The process of taking in, as when a sponge takes up water. Chemicals can be
absorbed through the skin into the bloodstream and then transported to other organs. Chemicals
can also be absorbed into the bloodstream after breathing in or swallowing.
Absorption Barrier - Exchange barriers of the body that allow differential diffusion of various
substances across a boundary. Examples of absorption barriers are the skin, lung tissue, and
gastrointestinal tract wall.
Abiotic Degradation - Degradation via purely physical or chemical mechanisms. Examples
include hydrolysis and photolysis.
Acceptable Risk - The likelihood of suffering disease or injury that will be tolerated by an
individual, group, or society. The level of risk that is determined to be acceptable may depend
on a variety of issues, including scientific data, social, economic, legal, and political factors, and
on the perceived benefits arising from a chemical or process.
Accuracy - The measure of the correctness of data, as given by the difference between the
measured value and the true or standard value.
Active Monitor - A type of personal exposure monitoring device that uses a small air pump to
draw air through a filter, packed tube, or similar device.
Activity Patterns - A series of discrete events of varying time intervals describing information
about an individual's lifestyle and routine. This information typically includes the locations
visited, the amount of time spent in the locations, and a description of what the individual was
doing in each location.
Acute Effect - Any toxic effect produced with a short period of time following an exposure, for
example, minutes to a few days
Acute Exposure Limits - A variety of short-term exposure limits to hazardous substances,
designed to be protective of human health. Published by different organizations, each limit has a
different purpose and definition.
Acute Exposure - One dose (or exposure) or multiple doses (or exposures) occurring within a
short time relative to the life of a person or other organism (e.g., approximately 24 hours or less
for humans).
Actual Risk - The damage to life, health, property, and/or the environment that may occur as a
result of exposure to a given hazard. Risk assessment attempts to estimate the likelihood of
actual risk.
April 2004 Page 1
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Additive Effect - The overall result of exposure to two or more chemicals, in which the resulting
effect is equal to the sum of the independent effects of the chemicals. "Effects" or "Response
Addition" is a method employed in EPA risk assessments of mixtures in which the components
act or are presumed to act independently (without interaction).
Additive Dose - The overall result of exposure to two or more chemicals, when each chemical
behaves as a concentration or dilution of the other chemicals in the mixture. The response of the
combination is the response expected from the equivalent dose of an index chemical. The
equivalent dose is the sum of component doses scaled by their toxic potency relative to the index
chemical.
Adjusted Exposure Concentration - Also called a refined exposure concentration, an estimate
of exposure concentration that has been refined, usually by application of an exposure model, to
better understand how people in a particular location interact with contaminated media.
Administered Dose - The amount of a substance received by a test subject (human or animal) in
determining dose-response relationships, especially through ingestion or inhalation.
Advection - In meteorology, the transfer of a property, such as heat or humidity, by motion
within the atmosphere, usually in a predominantly horizontal direction. Thermal advection, for
example, is the transport of heat by the wind. Advection is most often used to signify horizontal
transport but can also apply to vertical movement. Large-scale horizontal advection of air is a
characteristic of middle-latitude zones and leads to marked changes in temperature and humidity
across boundaries separating air masses of differing origins.
Adverse Environmental Effect - Defined in the CAA section 112(a)(7) as "any significant and
widespread adverse effect, which may reasonably be anticipated, to wildlife, aquatic life, or
other natural resource, including adverse impacts on populations of endangered or threatened
species or significant degradation of environmental quality overbroad areas."
Adverse Health Effect - A health effect from exposure to air contaminants that may range from
relatively mild and temporary (e.g., eye or throat irritation, shortness of breath, or headaches) to
permanent and serious conditions (e.g., birth defects, cancer or damage to lungs, nerves, liver,
heart, or other organs), and which negatively affects an individual's health or well-being, or
reduces an individual's ability to respond to an additional environmental challenge.
Affected (or Interested) Parties - Individuals and organizations potentially acted upon or
affected by chemicals, radiation, or microbes in the environment or influenced favorably or
adversely by proposed risk management actions and decisions.
Agent - A chemical, physical, or biological entity that may cause deleterious, beneficial, or no
effects to an organism after the organism is exposed to it.
Aggregate exposure - The combined exposure of an individual (or defined population) to a
specific agent or stressor via relevant routes, pathways, and sources.
Aggregate risk - The risk resulting from aggregate exposure to a single agent or stressor.
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AirData - An EPA website (http://www.epa.gov/air/data/info.htmn that provides access to
yearly summaries of United States air pollution data, taken from EPA's air pollution databases.
The data include all fifty states plus District of Columbia, Puerto Rico, and the U. S. Virgin
Islands. AirData has information about where air pollution comes from (emissions) and how
much pollution is in the air outside our homes and work places (monitoring).
Air Emissions - The release or discharge of a pollutant into the air.
Air Pressure (Atmospheric Pressure, Barometric Pressure) - The pressure experienced
above the Earth's surface at a specific point as a result of the weight of the air column, extending
to the outer limit or top of the atmosphere. Consequently, pressure declines exponentially with
height, the rate of decrease being a function of the temperature of the atmosphere. Atmospheric
pressure is generally measured, in meteorology, either in the SI unit hectopascals (hPa) or in the
c.g.s. unit of the same size, the millibar (mb) using a mercury or aneroid barometer, or a
barograph. In the U.S., surface atmosphere pressure is measured in inches of mercury (Hg).
Air Mass - A large volume of air with certain meteorological or polluted characteristics (e.g., a
heat inversion or smogginess) while in one location. The characteristics can change as the air
mass moves away.
Air Toxic - Any air pollutant that causes or may cause cancer, respiratory, cardiovascular, or
developmental effects, reproductive dysfunctions, neurological disorders, heritable gene
mutations, or other serious or irreversible chronic or acute health effects in humans. See
hazardous air pollutant.
Ambient Medium (e.g., Ambient Air) - Material surrounding or contacting an organism (e.g.,
outdoor air, indoor air, water, or soil), through which chemicals can reach an organism.
Ambient Water Quality Criteria (AWQC) - A ecological benchmark level for aquatic
contaminants, published by EPA Office of Water, which is designed to protect 95 percent of all
aquatic species in freshwater or marine environments. Criteria have been developed for both
acute and chronic exposures, although for a limited number of chemicals.
Ample Margin of Safety - This term has regulatory significance in EPA's air toxics program. It
was interpreted by the Agency in the 1989 notice of final benzene NESHAP (FR54:38044-
38072), and reiterated in the 1990 amendments to the Clean Air Act (sections 112(f) and 112(c)).
AMTIC - Ambient Monitoring Technology Information Center. An EPA website that contains
information and files on ambient air quality monitoring programs, details on monitoring
methods, monitoring-related documents and articles, information on air quality trends and
nonattainment areas, and federal regulations related to ambient air quality monitoring.
[http://www.epa.gov/ttn/amticA 2003]
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Analysis - The systematic application of specific theories and methods, including those from
natural science, social science, engineering, decision science, logic, mathematics, and law, for
the purpose of collecting and interpreting data and drawing conclusions about phenomena. It
may be qualitative or quantitative. Its competence is typically judged by criteria developed
within the fields of expertise from which the theories and methods come.
Analysis Plan - A plan that provides all the details of exactly how each part of the risk
assessment will be performed. It usually describes in detail what analyses will be performed,
how they will be performed, who will perform the work, schedules, resources, quality
assurance/quality control requirements, and documentation requirements.
Animal Studies - Toxicity investigations using animals. Such studies may employ animals as
surrogates for humans with the expectation that the results are pertinent to humans or for
investigation of effects pertinent to animals (e.g., for ecological risk assessment).
Antagonistic Effect - The situation where exposure to two chemicals together has less effect
than the sum of their independent effects.
AP-42 - A compilation of air pollutant emission factors. Volume I of the fifth edition addresses
stationary point and area source emission factors. AP-42 is accessible on the Air CHIEF website
(http://www.epa.gov/ttn/chief/ap42A and is also included on the Air CHIEF CD-ROM.
Applied Dose - The amount of a substance in contact with an absorption boundary of an
organism (e.g., skin, lung, gastrointestinal tract) and is available for absorption.
Area of Impact - The geographic area affected by a facility's emissions (also known as the zone
of impact).
Area Source (legal sense) - A stationary source that emits less than 10 tons per year of a single
hazardous air pollutant (HAP) or 25 tons per year of all HAPs combined.
Area Source (modeling sense) - An emission source in which releases are modeled as coming
from a 2-dimensional surface. Emissions from the surface of a wastewater pond are, for
example, often modeled as an area source.
Area Use Factor - For an animal, the ratio of its home range, breeding range, or
feeding/foraging range to the area of contamination or the site area under investigation.
Assessment Endpoint - An explicit expression of the environmental value to be protected. An
assessment endpoint includes both an ecological entity and specific attributes of that entity. For
example, salmon are a valued ecological entity; reproduction and population maintenance (i.e.,
the attribute) form an assessment endpoint.
Assessment Questions - The questions asked during the planning/scoping phase of the risk
assessment process to determine what the risk assessment will evaluate.
Atmospheric Stability (Stability) - the degree of resistance of a layer of air to vertical motion.
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ATSDR (Agency for Toxic Substances and Disease Registry) - An Agency of the US
Department of Health and Human Services, whose goal is to serve the public by using the best
science, taking responsive public health actions, and providing health information to prevent
harmful exposures and diseases to toxic substances. Its website (www.atsdr.cdc.gov) includes
information on hazardous substances [e.g., toxicological profiles, minimal risk levels (MRLs)],
emergency response, measuring health effects, hazardous waste sites, education and training,
publications, and special issues (e.g., Children Health).
Averaging Time - The time period over which something is averaged (e.g., exposure, measured
concentration).
B
Background Levels - The concentration of a chemical already present in an environmental
medium due to sources other than those under study. Two types of background levels may exist
for chemical substances: (a) Naturally occurring levels of substances present in the environment,
and (b) Anthropogenic concentrations of substances present in the environment due to human
associated activities (e.g., automobiles, industries).
Background Source - Any source from which pollutants are released and contribute to the
background level of a pollutant, such as volcano eruptions, windblown dust, or manmade source
upwind of the study area.
Benchmark Dose - An exposure due to a dose of a substance associated with a specified low
incidence of risk, generally in the range of 1% to 10%, of a health effect; or the dose associated
with a specified measure or change of a biological effect.
Benthic Burial Rate (k,) - Rate of the deposition of the sediment suspended in a surface water
body column to the benthic sediment surface that becomes no longer available for resuspension
in the water column, effectively becoming part of the sediment "sink."
Best Available Control Technology (BACT) - An emission limitation based on the maximum
degree of emission reduction (considering energy, environmental, and economic impacts)
achievable through application of production processes and available methods, systems, and
techniques. BACT does not permit emissions in excess of those allowed under any applicable
Clean Air Act provisions. Use of the BACT concept is allowable on a case by case basis for
major new or modified emissions sources in attainment areas and applies to each regulated
pollutant.
Best Professional Judgement - Utilizing knowledge based on education and experience to
determine the best course of action during the course of performing a risk assessment project.
Bias - systematic error introduced into sampling or analysis by selecting or encouraging one
outcome or answer over others.
Binational Toxics Strategy - A Canada-United States jointly-sponsored program that provides a
framework for actions to reduce or eliminate persistent toxic substances, especially those which
bioaccumulate, from the Great Lakes Basin.
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Bioaccumulation - The net accumulation of a substance by an organism as a result of uptake
from and or all routes of exposure (e.g., ingestion of food, intake of drinking water, direct
contact, or inhalation).
Unavailability - The ability to be absorbed and available to interact with the metabolic
processes of an organism.
Bioaccumulation Factor (BAF) - The concentration of a substance in tissue of an organism
divided by its concentration in an environmental medium in situations where the organism and
its food are exposed (i.e., accounting for food chain exposure as well as direct chemical uptake).
[EPA, 1999: Residual Risk Report to Congress. EPA453R9900L]
Bioassay - A test conducted in living organisms (in vivo) or with living cells (in vitro) to
determine the hazard or potency of a chemical by its effect on animals, isolated tissues, or
microorganisms. [Based on Air Risk Information Support Center, OAQPS, March 1989:
Glossary of Terms Related to Health, Exposure, and Risk Assessment. EPA/450/3-88/016.]
Bioavailability - A measure of the degree to which a dose of a substance becomes
physiologically available to the body tissues depending upon adsorption, distribution,
metabolism and excretion rates. [Air Risk Information Support Center, OAQPS, March 1989:
Glossary of Terms Related to Health, Exposure, and Risk Assessment. EPA/450/3-88/016.]
Bioconcentration - The net accumulation of a substance by an organism as a result of uptake
directly from an environmental medium (e.g., net accumulation by an aquatic organism as a
result of uptake directly from ambient water, through gill membranes or other external body
surfaces).
Bioconcentration Factor (BCF) - The concentration of a substance in tissue of an organism
divided by the concentration in an environmental medium (e.g., the concentration of a substance
in an aquatic organism divided by the concentration in the ambient water, in situations where the
organism is exposed through the water only).
Biological Medium - Any one of the major categories of material within an organism (blood,
adipose tissue, breath), through which chemicals can move, be stored, or be biologically,
physically, or chemically transformed.
Biological Monitoring - The measurement of chemicals in biological media (e.g., blood, urine,
exhaled breath) to determine whether chemical exposure in humans, animals, or plants has
occurred.
Biologically Effective Dose - The amount of chemical that reaches the cells or target site where
an adverse effect may occur.
Biomagnification or Biological Magnification - The process whereby certain substances, such
as pesticides or heavy metals, transfer up the food chain and increase in concentration. For
example, a biomagnifying chemical deposited in rivers or lakes absorbs to algae, which are
ingested by aquatic organisms, such as small fish, which are in turn eaten by larger fish, fish-
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eating birds, terrestrial wildlife, or humans. The chemical tends to accumulates to higher
concentration levels with each successive food chain level.
Biotic Degradation (Biodegredation) - Decomposition or metabolism of a substance into more
elementary compounds by the action of organisms (e.g., bacteria, fungi).
Bounding Estimate - An estimate of exposure or risk that is higher or lower than that incurred
by any person in the population. Bounding estimates are useful in developing statements that
exposures or risks are within an estimated range.
Blue Book - The 1994 National Research Council (NRC) report entitled Science and Judgement
in Risk Assessment.
Body Weight (Mass) - The weight or mass of an individual's body. It can apply to a human or
an ecological receptor.
Breathing Zone - Air in the vicinity of an organism from which respired air is drawn. Personal
monitors are often used to measure pollutants in the breathing zone.
Bright Line - Specific levels of risk or of exposure that are meant to provide a practical
distinction between what is considered "safe" and what is not.
Building Downwash (Plume Downwash) - The interaction of a plume with a structure, such as
a building, which causes the plume to fall to ground.
CalEPA (California Environmental Protection Agency) - An Agency within the California
State government whose goal is to protect human health and the environment and to assure the
coordinated deployment of State resources against the most serious environmental risks. There
are six boards that address environmental issues, including air quality, pesticides, toxic
substances, waste management, water control, and the Office of Environmental Health Hazard
Assessment (OEHHA). Note that OEHHA is responsible for developing and providing state and
local government agencies with toxicological and medical information relevant to decisions
involving public health and is a good resource for such information.
Cancer - A group of related diseases characterized by group of diseases characterized by the
uncontrolled growth of abnormal cells.
Cancer Incidence - The number of new cases of a disease diagnosed each year.
Cancer Risk Estimates - The probability of developing cancer from exposure to a chemical
agent or a mixture of chemicals over a specified period of time. In quantitative terms, risk is
expressed in values ranging from zero (representing an estimate that harm certainly will not
occur) to one (representing an estimate that harm certainly will occur). The following are
examples of how risk is commonly expressed: l.E-04 or IxlO"4 = a risk of 1 additional cancer in
an exposed population of 10,000 people (i.e., 1/10,000); l.E-5 or IxlO'5 = 1/100,000; l.E-6 or
lxlQ-6= 1/1,000,000.
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Cancer Risk Evaluation Guides (CREGs) - Developed by ATSDR, the concentration of a
chemical in air, soil or water that is expected to cause no more than one excess cancer in a
million persons exposed over a lifetime. The CREG is a comparison value used to select
contaminants of potential health concern and is based on the cancer slope factor (CSF).
Cancer Slope Factor (CSF) - An upper bound (approximating a 95% confidence limit) on the
increased cancer risk from a lifetime exposure to an agent. This estimate, usually expressed in
units of proportion (of a population) affected per mg/kg/day, is generally reserved for use in the
low-dose region of the dose-response relationship; that is, for exposures corresponding to risks
less than 1 in 100. This term is usually used to refer to oral slope factors (i.e., slope factors used
for assessing ingestion exposure).
Carcinogen(ic) - An agent capable of inducing cancer.
Carcinogenesis - The origin or production of a benign or malignant tumor. The carcinogenic
event modifies the genome and/or other molecular control mechanisms of the target cells, giving
rise to a population of altered cells.
Census Bureau (Bureau of the Census) - A Bureau within the Department of Commerce, this
is the country's preeminent statistical collection and dissemination agency of national
demographic information. It publishes a wide variety of statistical data about people, housing,
and the economy of the nation. The Census Bureau conducts approximately 200 annual surveys
and conducts the decennial census of the United States population and housing and the
quinquennial economic census and census of governments.
Census Block - An area bounded by visible and/or invisible features shown on Census Bureau
maps. A block is the smallest geographic entity for which the Census Bureau collects and
tabulates 100-percent decennial census data.
Census Tract - A small, relatively permanent statistical subdivision of a county or statistically
equivalent entity, delineated for data presentation purposes by a local group of census data users
or the geographic staff of a regional census center in accordance with Census Bureau guidelines.
Designed to be relatively homogeneous units with respect to population characteristics,
economic status, and living conditions at the time they are established, census tracts generally
contain between 1,000 and 8,000 people, with an optimum size of 4,000 people. Census tract
boundaries are delineated with the intention of being stable over many decades, so they generally
follow relatively permanent visible features. However, they may follow governmental unit
boundaries and other invisible features in some instances; the boundary of a state or county (or
statistically equivalent entity) is always a census tract boundary.
Census Tract (or Census Block) Internal Point - A set of geographic coordinates (latitude and
longitude) that is located within a specified geographic entity such as a Census Tract or Census
Block. For many Census Tracts or Blocks, this point represents the approximate center of the
Census Tract or Block; for some, the shape of the entity or the presence of a body of water
causes the central location to fall outside the Census Tract or Block or in water, in which case
the point is relocated to land area within the Census Tract or Block. The geographic coordinates
are shown in degrees to six decimal places in census products.
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Chemical Abstracts Service Registry Number (CASRN) - A unique, chemical-specific
number used in identifying a substance. The registry numbers are assigned by the Chemical
Abstract Service, a division of the American Chemical Society. (Note that some mixtures of
substances, such as mixtures of various forms of xylene, are also given CAS numbers.)
Chemicals of Potential Concern - Chemicals that may pose a threat to the populations within
the study area. These are the chemicals which are carried through the risk assessment process.
Chemical Speciation - Detailed identification of the specific identities and forms of chemicals
in a mixture.
Chemical Transformation - The change of one chemical into another.
Chronic Exposure - Continuous exposure, or multiple exposures, occurring over an extended
period of time or a significant fraction of the animal's or the individual's lifetime.
Chronic Health Effects - An effect which occurs as a result of repeated or long term (chronic)
exposures.
Coefficient of Variation (CV) - A dimensionless measure of dispersion, equal to the standard
deviation divided by the mean, often expressed as a percentage.
Cohort - A group of people within a population that can be aggregated because the variation in a
characteristic of interest (e.g., exposure, age, education level) within the group is much less than
the group-to-group variation across the population.
Community - The persons associated with an area who may be directly affected by area
pollution because they currently live in or near the area, or have lived in or near the area in the
past (i.e., current or past residents), members of local action groups, local officials, tribal
governments, health professionals, and local media. Other entities, such as local industry, may
also consider themselves part of the community.
Comparative Risk Assessment - The process of comparing and ranking various types of risks
to identify priorities and influence resource allocations.
Conceptual Model - A written description and/or a visual representation of actual or predicted
relationships between humans or ecological entities and the chemicals or other stressors to which
they may be exposed.
Conductivity (Conductance) - The ability of a material to carry and electrical current.
Confidence Interval - A range of values that has a specified probability (e.g., 95 percent) of
containing the statistical parameter (i.e., a quantity such as a mean or variance that describes a
statistical population) in question. The confidence limit refers to the upper or lower value of the
range.
Coning - In pollution studies, emissions from a chimney stack under atmospheric conditions of
near neutral stability such that concentrations of a pollutant at a given distance downwind from
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the stack may be described by a normal or Gaussian distribution, being the same for both vertical
and horizontal cross-sections perpendicular to the flow.
Consumption Rate - The average quantity of an item consumed or expended during a given
time interval, expressed in quantities by the most appropriate unit of measurement per applicable
stated basis.
Continuous Monitoring - The measurement of the air or water concentration of a specific
contaminant on an uninterrupted, real-time basis by instrumental methods.
Control Technology/Measures - Equipment, processes or actions used to reduce air pollution at
the source.
Convection - The transfer and mixing of heat by mass movement through a fluid (e.g., air or
water). It is one of the major mechanisms for the transfer of heat within the atmosphere, together
with conduction and radiation. The convection process is of major importance in the
troposphere, transferring sensible heat and latent heat from the Earth's surface into the boundary
layer, and by promoting the vertical exchange of air-mass properties (e.g., heat, water vapor, and
momentum) throughout the depth of the troposphere. Convection is generally accepted to be
vertical circulation, whereas advection is usually horizontal.
Cost-Benefit Analysis - An evaluation of the costs which would be incurred versus the overall
benefits of a proposed action, such as the establishment of an acceptable exposure level of a
pollutant.
Criteria Air Pollutant - One of six common air pollutants determined to be hazardous to human
health and regulated under EPA's National Ambient Air Quality Standards (NAAQS). The six
criteria air pollutants are carbon monoxide, lead, nitrogen dioxide, ozone, sulfur dioxide, and
particulate matter. The term "criteria pollutants" derives from the requirement that EPA must
describe the characteristics and potential health and welfare effects of these pollutants. It is on
the basis of these criteria that standards are set or revised.
Critical Effect - The first adverse effect, or its known precursor, that occurs to the most
sensitive species as the dose rate of an agent increases.
Cumulative Risk - The combined risk from aggregate exposures to multiple agents or stressors.
Cumulative Risk Assessment - An analysis, characterization, and possible quantification of the
combined risks to health or the environment from multiple agents or stressors.
Cumulative Distribution Function (CDF) - The CDF is alternatively referred to in the
literature as the distribution function, cumulative frequency function, or the cumulative
probability function. The cumulative distribution function, F(x), expresses the probability the
random variable X assumes a value less than or equal to some value x, F(x) = Prob (X < x). For
continuous random variables, the cumulative distribution function is obtained from the
probability density function by integration, or by summation in the case of discrete random
variables.
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Cumulative Risk Assessment - An analysis, characterization, and possible quantification of the
combined risks to health or the environment from multiple agents or stressors.
D
Data Integrity - Refers to security (i.e., the protection of information from unauthorized access
or revision) to ensure that the information is not compromised through corruption or
falsification. Data integrity is one of the constituents of data quality.
Data Objectivity - A characteristic indicating whether information is being presented in an
accurate, clear, complete, and unbiased manner, and as a matter of substance, is accurate,
reliable, and unbiased. Data objectivity is one of the constituents of data quality.
Data Quality - The encompassing term regarding the quality of information used for analysis
and/or dissemination. Utility, objectivity, and integrity are constituents of data quality.
Data Quality Objectives (DQOs) - Qualitative and quantitative statements derived from the
DQO process that clarify study objectives, define the appropriate type of data, and specify
tolerable levels of potential decision errors that will be used as the basis for establishing the
quality and quantity of data needed to support the decisions.
Data Quality Objectives Process - A systematic planning tool to facilitate the planning of
environmental data collection activities. Data quality objectives are the qualitative and
quantitative outputs from the DQO Process.
Data Utility - Refers to the usefulness of the information to the intended users. Data utility is
one of the constituents of data quality.
Delivered Dose - The amount of the chemical available for interaction by any particular organ or
cell.
Deposition (Wet and Dry) - The removal of airborne substances to available surfaces that
occurs as a result of gravitational settling and diffusion, as well as electrophoresis and
thermophoresis in the absence of active precipitation (Dry) or in the presence of active
precipitation (Wet).
Deposition (Flux) - The removal of airborne substances from the air to available surfaces that
occurs as a result of gravitational settling and diffusion, as well as electrophoresis and
thermophoresis.
Dermal - Referring to the skin. Dermal absorption means absorption through the skin.
Dermal Exposure - Contact between a chemical and the skin. [EPA, 1997: Terms of
Environment, http://www.epa.gov/OCEPAterms/.]
Detection Limit - The lowest concentration of a chemical that can reliably with analytical
methods be distinguished from a zero concentration.
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Deterministic - A methodology relying on point (i.e., exact) values as inputs to estimate risk;
this obviates quantitative estimates of uncertainty and variability. Results are also presented as
point values. Uncertainty and variability may be discussed qualitatively, or semi-quantitatively
by multiple deterministic risk estimates.
Developmental Toxicity - The potential of an agent to cause abnormal development.
Developmental toxicity generally occurs in a dose-related manner, may result from short-term
exposure (including single exposure situations) or from longer term low-level exposure, may be
produced by various routes of exposure, and the types of effects may vary depending on the
timing of exposure because of a number of critical periods of development for various organs
and functional systems. The four major manifestations of developmental toxicity are death,
structural abnormality, altered growth, and functional deficit.
Dietary Composition - The fractions of different foods that constitute a given diet.
Differential Heating - The property of different surfaces which causes them to heat and cool at
different rates.
Direct Exposure - Contact between a receptor and a chemical where the chemical is still in the
medium to which it was originally released. For example, direct exposure occurs when a
pollutant is released to the air and a person breathes that air.
Direct-read Monitor - Using a pump to draw the air sample through the detector, this type of air
toxics monitoring device provides a direct reading of the pollutant measurement. The monitor
may be designed as a table-top unit, for example, or it may be rack-mounted such as for use in an
ambient air monitoring station.
Dispersion - Pollutant or concentration mixing due to turbulent physical processes.
Disease Cluster - An unusual number, real or perceived, of health events (i.e., reports of cancer)
grouped together in time and location.
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Dose - The amount of substance available for interaction with metabolic processes or
biologically significant receptors after crossing the outer boundary of an organism. The potential
dose is the amount ingested, inhaled, or applied to the skin. The applied dose is the amount of a
substance presented to an absorption barrier and available for absorption (although not
necessarily having yet crossed the outer boundary of the organism). The absorbed does is the
amount crossing a specific absorption barrier (e.g., the exchange boundaries of skin, lung, and
digestive tract) through uptake processes. Internal dose is a more general term denoting the
amount absorbed without respect to specific absorption barriers or exchange boundaries. The
amount of the chemical available for interaction by any particular organ or cell is termed the
delivered dose for that organ or cell.
Dose-Response Assessment - A determination of the relationship between the magnitude of an
administered, applied, or internal dose and a specific biological response. Response can be
expressed as measured or observed incidence, percent response in groups of subjects (or
populations), or as the probability of occurrence within a population.
Dose-Response Curve - A graphical representation of the quantitative relationship between
administered, applied, or internal dose of a chemical or agent, and a specific biological response
to that chemical or agent.
Dust Resuspension - Involves the deposition of dust from the air and its subsequent
resuspension or re-entrainment into the atmosphere.
E
Ecological Risk Assessment - The process that evaluates the likelihood that adverse ecological
effects may occur or are occurring as a result of exposure to one or more stressors.
Eddy - In the atmosphere, a distinct mass within a turbulent fluid that retains its identity and
behaves differently for a short period within the general larger volume flow. An eddy thus
ranges in size from microscale turbulence (1 cm for example) to many hundreds of kilometers in
the form of frontal cyclones and anticyclones. The smallest scale eddies are critical in the
process of, for example, heat and water vapor transfer from the Earth's surface into the air, while
frontal cyclones transport heat toward the poles.
Emission Factor - The relationship between the amount of pollution produced and the amount
of raw material processed or product produced. For example, an emission factor for a blast
furnace making iron could be the number of pounds of particulates released per ton of raw
materials used.
Emission Inventory - A listing, by source, of the amount of air pollutants discharged into the
atmosphere in a particular place. Two of the more important publicly available emissions
inventories for air toxics studies are the National Emissions Inventory (NEI) and the Toxics
Release Inventory (TRI).
Emission Rate - The amount of a given substance discharged to the air per unit time, expressed
as a fixed ratio (e.g., tons/yr).
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Emissions Inventory Improvement Program (EIIP) - A jointly sponsored effort of the State
and Territorial Air Pollution Program Administrators/Association of Local Air Pollution Control
Officials (STAPPA/ALAPCO) and EPA, and is an outgrowth of the Standing Air Emissions
Work Group (SAEWG). The goal of EIIP is to provide cost-effective, reliable inventories by:
(1) Improving the quality of emissions information, and (2) Developing system(s) for collecting,
calculating, and reporting emissions data. The goal is achieved by developing a set of "preferred
and alternative methods" for all inventory associated tasks. This standardization improves the
consistency of collected data and results in increased usefulness of emissions information.
Emissions Monitoring - The periodic or continuous physical surveillance or testing to
determine the pollutant levels discharged into the atmosphere from sources such as smokestacks
at industrial facilities and exhaust from motor vehicles, locomotives, or aircraft.
Emissions Tracking System (ETS) - This EPA system contains all emissions data submitted
under various clean air market programs. Data from Continuous Emissions Monitoring Systems
at utilities sends the emission data to the utility's computer system, which then compiles the data
for submission to EPA on a quarterly basis. At the end of each calendar year, EPA compares
tons of emissions emitted with the allowance holdings of the utility unit to ensure that it is in
compliance with the relevant program.
Endocrine Disrupter - Substances which interfere with endocrine system function.
Environmental Data - Any measurements or information that describe environmental
processes, location, or conditions; ecological or health effects and consequences; or the
performance of environmental technology. Environmental data include information collected
directly from measurements, produced from models, and compiled from other sources such as
data bases or the literature.
Environmental Media Evaluation Guides - Environmental Media Evaluation Guides
(EMEGs) are concentrations of a contaminant in water, soil, or air that are unlikely to be
associated with any appreciable risk of deleterious noncancer effects over a specified duration of
exposure. EMEGs are derived from ATSDR minimal risk levels by factoring in default body
weights and ingestion rates. Separate EMEGS are computed for acute (14 days), intermediate
(15-364 days), and chronic (365 days) exposures.
Environmental Medium - Any one of the major categories of material found in the physical
environment (e.g., surface water, ground water, soil, or air), and through which chemicals or
pollutants can move.
Epidemiology - The study of disease patterns in human populations.
Epidemiologic Study, Case Study - A medical or epidemiologic evaluation of one person or a
small group of people to gather information about specific health conditions and past exposures.
Epidemiologic Study, Descriptive - An evaluation of the amount and distribution of a disease
in a specified population by person, place, and time.
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Epidemiologic Study, Analytical - An evaluation of the association between exposure to
hazardous substances and disease by testing scientific hypotheses.
Exposure - Contact made between a chemical, physical, or biological agent and the outer
boundary of an organism.
Exposure Assessment - An identification and evaluation of a population exposed to a toxic
agent, describing its composition and size, as well as the type, magnitude, frequency, route and
duration of exposure.
Exposure Concentration - The concentration of a chemical in its transport or carrier medium
(i.e., an environmental medium or contaminated food) at the point of contact.
Exposure Duration - The total time an individual is exposed to the chemical being evaluated or
the length of time over which contact with the contaminant lasts.
Exposure Factors - Any of a variety of factors that relate to how an organism interacts with or
is otherwise exposed to environmental pollutants (e.g., ingestion rate of contaminated fish).
Such factors are used in the calculation of exposure to toxic chemicals.
Exposure Frequency - The number of occurrences in a given time frame (e.g., a lifetime) of
contact or co-occurrence of a stressor with a receptor.
Exposure Investigation (in Public Health Assessment) - The collection and analysis of
site-specific information and biologic tests (when appropriate) to determine whether people have
been exposed to hazardous substances.
Exposure Modeling - The mathematical equations simulating how people interact with
chemicals in their environment.
Exposure Pathway - The course a chemical or physical agent takes from a source to an exposed
organism. An exposure pathway includes a source and release from a source, an exposure point,
and an exposure route. If the exposure point differs from the source, a transport/exposure
medium (e.g., air) or media (in cases of intermedia transfer) also is included.
Exposure Profile - The exposure profile (ecological) identifies the receptors and describes the
exposure pathways and intensity and spatial and temporal extent of exposure. It also describes
the impact of variability and uncertainty on exposure estimates and reaches a conclusion about
the likelihood that exposure will occur. The profile may be a written document or a module of a
larger process model.
Exposure Route - The way a chemical enters an organism after contact (e.g., by ingestion,
inhalation, dermal absorption).
Exposure Scenario - A set of conditions or assumptions about sources, exposure pathways,
concentrations of toxic chemicals, and populations (numbers, characteristics and habits) which
aid the investigator in evaluating and quantifying exposure in a given situation.
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Exposure Unit (in Geographical Information System applications) - The geographical area in
which a receptor moves and contacts the contaminated medium during the period of exposure.
Factor Information Retrieval System (FIRE) - A database management system containing
EPA's recommended emission estimation factors for criteria and hazardous air pollutants. FIRE
includes information about industries and their emitting processes, the chemicals emitted, and
the emission factors themselves. FIRE allows easy access to criteria and hazardous air pollutant
emission factors obtained from the Compilation of Air Pollutant Emission Factors (AP-42),
Locating and Estimating (L&E) documents, and the retired AFSEF and XATEF documents.
Fate and Transport - A description of how a chemical is carried through and changes in the
environment.
Fate and Transport Analysis - The general process used to assess and predict the movement
and behavior of chemicals in the environment.
Fate and Transport Modeling - The mathematical equations simulating a physical system
which are used to assess and predict the movement and behavior of chemicals in the
environment.
Fence Line - Delineated property boundary of a facility.
Field Study - Scientific study made in the ambient air to collect information that can not be
obtained in a laboratory.
Food Chain - A sequence of organisms, each of which uses the next lower member of the
sequence as a food source.
Forage - (1) Edible parts of plants, other than separated grain, that can provide feed for grazing
animals or can be harvested for feeding, including browse, and herbage. (2) To search for or to
consume forage (of animals).
Fugitive Release - Emission of a chemical to the air that does not occur from a stack, vent, duct,
pipe or other confined air stream (e.g., leaks from joints).
Fumigation - (1) The use of a chemical compound in a gaseous state, often to kill pests such as
insects, nematodes, arachnids, rodents, weeds, and fungi in confined or inaccessible locations or
in the field. (2) a pattern of plume dispersion produced when a convective boundary layer grows
upward into a plume trapped in a stable layer. The elevated plume is suddenly brought
downward to the ground, producing high surface concentrations.
Future Scenario - A scenario used in risk assessment to anticipate potential future exposures of
individuals (e.g., a housing development could be built on currently vacant land).
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G
Geographic Information Systems (GIS) - A computer program that allows layering of different
types of spatial information (i.e., on a map) to provide a better understanding of the
characteristics of a certain place.
Generally Available Control Technology (GACT) Standard - These standards are less
stringent standards than the Maximum Available Control Technology (MACT) standards, and
are allowed at the Administrator's discretion for area sources according to the 1990 Clean Air
Act Amendments for area sources.
Grab Sample -A single sample collected at a particular time and place that represents the
composition of the water, air, or soil only at that time and place.
Great Waters Pollutants of Concern - The toxic pollutants of concern to the Great Waters
program are mercury; cadmium and lead (and their compounds); dioxins; furans; polycyclic
organic matter; polychlorinated biphenyls (PCBs); and the pesticides chlordane, DDT/DDE,
dieldrin, hexachlorobenzene, alpha-hexachlorocyclohexane, lindane and toxaphene. Nitrogen
compounds such as nitrogen oxides and ammonia are also pollutants of concern.
Greenhouse Effect - Trapping and build-up of heat in the atmosphere (troposphere) near the
earth's surface. Some of the heat flowing back toward space from the earth's surface is absorbed
by water vapor, carbon dioxide, ozone, and several other gases in the atmosphere and then re-
radiated back toward the earth's surface. If the atmospheric concentrations of these greenhouse
gases rise, the average temperature of the lower atmosphere will gradually increase.
Greenhouse Gas (GHG) - Any gas that absorbs infrared radiation in the atmosphere.
Greenhouse gases include, but are not limited to, water vapor, carbon dioxide (CO2), methane
(CH4), nitrous oxide (N2O), hydrochlorofluorocarbons (HCFCs), ozone (O3), hydrofluorocarbons
(HFCs), perfluorocarbons (PFCs), and sulfur hexafluoride (SF6).
Guidelines (human health and ecological risk assessment) - Official documentation stating
current U.S. EPA methodology in assessing risk of harm from environmental pollutants to
human populations and ecological receptors.
H
Half-Life - The time required for a reaction or process to proceed such that half of the original
amount of the substance of interest has reacted or undergone the process. Examples include: (1)
the time required for a pollutant to degrade to one-half of its original concentration; (2) the time
required for half of the atoms of a radioactive element to undergo self-transmutation or decay
(half-life of radium is 1620 years); (3) the time required for elimination from the body to half a
total dose.
Hazard - In a general sense, "hazard" is anything that has a potential to cause harm. In risk
assessment, the likelihood of experiencing a noncancer health effect is called hazard (not risk).
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Hazard Identification - The process of determining whether exposure to an agent can cause a
particular adverse health effect (e.g., cancer, birth defect) and whether the adverse health effect
is likely to occur in humans at environmentally relevant doses.
Hazard Index (HI) -The sum of more than one hazard quotient for multiple substances and/or
multiple exposure pathways. The HI is calculated separately for chronic, subchronic, and
shorter-term duration exposures.
Hazardous Air Pollutants (HAP) - Defined under the Clean Air Act as pollutants that cause or
may cause cancer or other serious health effects, such as reproductive effects or birth defects, or
adverse environmental and ecological effects. Currently, the Clean Air Act regulates 188
chemicals and chemical categories as HAPs.
Hazard Quotient (HQ) - The ratio of a single substance exposure level over a specified time
period (e.g., chronic) to a reference value (e.g., an RfC) for that substance derived from a similar
exposure period.
Health Effects Assessment Tables (HEAST) - An older listing of (usually) interim toxicity
values for chemicals of interest to Superfund, the Resource Conservation and Recovery Act
(RCRA), and the EPA in general. HEAST values are generally placed low on the hierarchy of
Agency recommended toxicity data sources and the compilation will eventually be phased out
altogether.
Health Endpoint - An observable or measurable biological event used as an index to determine
when a deviation in the normal function of the human body occurs.
Health Outcome Data (in Public Health Assessment) - Community-specific health
information such as morbidity and mortality data, birth statistics, medical records, tumor and
disease registries, surveillance data, and previously conducted health studies that may be
collected at the local, state, and national levels by governments, private health care
organizations, and professional institutions and associations.
Health Outcomes Study (in Public Health Assessment) - An investigation of exposed persons
designed to assist in identifying exposure or effects on public health. Health studies also define
the health problems that require further inquiry by means of, for example, a health surveillance
or epidemiologic study.
Health Education (in Public Health Assessment) - Programs designed with a community to
help it know about health risks and how to reduce these risks.
Health Consultation (in Public Health Assessment) - A review of available information or
collection of new data to respond to a specific health question or request for information about a
potential environmental hazard. Health consultations are focused on a specific exposure issue.
Health consultations are therefore more limited than a public health assessment, which reviews
the exposure potential of each pathway and chemical.
Henry's Law Constant - The ratio at equilibrium of the gas phase concentration to the liquid
phase concentration of the gas.
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High-End Exposure Estimate - A plausible estimate of individual exposure or dose for those
persons at the upper end of an exposure or dose distribution, conceptually above the 90th
percentile, but not higher than the individual in the population who has the highest exposure or
dose.
Human Exposure Model (HEM) - An EPA model combining the Industrial Source Complex
Short Term air dispersion model (ISCST) with a national set of meteorology files, U.S. census
data, and a risk calculation component that can be used to estimate individual and population
risks.
Hydrolysis - The decomposition of organic compounds by interaction with water.
Impervious Surface - A surface that cannot be penetrated by water (e.g., pavement).
Indirect Exposure Pathway - An indirect exposure pathway is one in which a receptor contacts
a chemical in a medium that is different from the one to which the chemical was originally
released (an example occurs with dioxin, which is emitted into the air, deposited on soil and
accumulated in plants and animals which are then consumed by humans).
Individual Risk or Hazard - The risk or hazard to an individual in a population rather than to
the population as a whole.
Indoor Source - Objects or places within buildings or other enclosed spaces that emit air
pollutants.
Industrial Source Complex (ISC) Model - A steady-state Gaussian plume model which can be
used to assess pollutant concentrations from a wide variety of sources associated with an
industrial complex. This model can account for the following: settling and dry deposition of
particles; downwash; point, area, line, and volume sources; plume rise as a function of
downwind distance; separation of point sources; and limited terrain adjustment. ISC3 operates
in both long-term (ISCLT) and short-term (ISCST) modes.
Influential Information - Scientific, financial, or statistical information that will have or does
have a clear and substantial impact on important public policies or important private sector
decisions.
Ingestion - Swallowing (such as eating or drinking).
Ingestion Exposure - Exposure to a chemical by swallowing it (such as eating or drinking).
Inhalation - Breathing.
Inhalation Exposure - Exposure to a chemical by breathing it in.
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Inhalation Unit Risk (IUR) - The upper-bound excess lifetime cancer risk estimated to result
from continuous exposure to an agent at a concentration of 1 |ig/m3 in air. The interpretation of
unit risk would be as follows: if unit risk = 2 x 10"6 |ig/m3, 2 excess tumors may develop per
1,000,000 people if exposed daily for a lifetime to a concentration of 1 jig of the chemical in 1
m3 of air.
Intake - The process by which a substance crosses the outer boundary of an organism without
passing an absorption barrier, e.g., through ingestion or inhalation.
Intake Rate - Rate of inhalation, ingestion, and dermal contact depending on the route of
exposure.
Integrated Risk Information System (IRIS) - An EPA database which contains information on
human health effects that may result from exposure to various chemicals in the environment.
IRIS was initially developed for EPA staff in response to a growing demand for consistent
information on chemical substances for use in risk assessments, decision-making and regulatory
activities. The information in IRIS is intended for those without extensive training in toxicology,
but with some knowledge of health sciences.
Internal Dose - In exposure assessment, the amount of a substance penetrating the absorption
barriers (e.g., skin, lung tissue, gastrointestinal tract) of an organism through either physical or
biological processes.
Inversion - Subsidence Inversion - A temperature inversion that develops aloft as a result of air
gradually sinking over a wide area and being warmed by adiabatic compression, usually
associated with subtropical high pressure areas.
Inversion - Advection Inversion - Associated with the horizontal flow of warm air. Warm air
moves over a cold surface, and the air nearest the surface cools, causing a surface-based
inversion.
Inversion - Radiation Inversion - A thermally produced, surface-based inversion formed by
rapid radiational cooling of the Earth's surface at night. It does not usually extend above the
lower few hundred feet. Conditions which are favorable for this type of inversion are long
nights, clear skies, dry air, little or no wind, and a cold or snow covered surface. It is also called
a Nocturnal Inversion.
Iterative Process - Replication of a series of actions to produce successively better results, or to
accommodate new and different critical information or scientific inferences.
Isopleths - A delineated line or area on a map that represent equal values of a variable.
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Laboratory Studies - Research carried out in a laboratory (e.g., testing chemical substances,
growing tissues in cultures, or performing microbiological, biochemical, hematological,
microscopical, immunological, parasitological tests).
Leaching - The process by which soluble constituents are dissolved and filtered through the soil
by a percolating fluid (usually rainwater).
Life Stage - A phase in the life cycle of an organism.
Line Source - A theoretical one-dimensional source from which releases may occur (e.g.,
roadways are often modeled as a one-dimensional line).
Lofting - In pollution studies, a pattern of flow that occurs when the top of a plume from a
chimney stack disperses into slightly turbulent or neutral airflow conditions, while the lower part
of the plume is prevented from dispersing down toward the surface by a stable boundary layer,
especially at night. [Smith, J. [ed], 2001: The Facts on File Dictionary of Weather and Climate.]
Low-dose Extrapolation - An estimation of the dose-response relationship at doses less than the
lowest dose studied experimentally.
Lowest Observed Adverse Effect Level (LOAEL) - The lowest exposure level in a study or
group of studies at which there are statistically or biologically significant increases in frequency
or severity of adverse effects between the exposed population and its appropriate control group.
Also referred to as lowest-effect level (LEL).
M
Major Source - Under the Clean Air Act, a stationary source that emits more than 10 tons or
more per year of a single hazardous air pollutant (HAP) or 25 or more tons per year of all HAPs.
Margin of exposure (MOE) - The point of departure divided by the actual or projected
environmental exposure of interest.
Mass-Balance Estimate - An estimate of release of a chemical based on, generally, a
comparison of the amount of chemical in raw materials entering a process versus the amount of
chemical going out in products.
Maximum Achievable Control Technology (MACT) - Under the Clean Air Act, a group of
technology based standards, applicable to both major and some area sources of air toxics, that
are aimed at reducing releases of air toxics to the environment. MACT standards are established
on a source category by source category basis.
Maximum Exposed Individual (MEI) - The MEI represents the highest estimated risk to an
exposed individual, regardless of whether people are expected to occupy that area.
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Maximum Individual Risk (MIR) - An MIR represents the highest estimated risk to an
exposed individual in areas that people are believed to occupy.
Metric (or Measure) of Exposure - The quantitative outcome of the exposure assessment. For
air toxics risk assessments, personal air concentration (or adjusted exposure concentration) is
the metric of exposure for the inhalation route of exposure and intake rate is the metric of
exposure for the ingestion route of exposure.
Measurement - In air toxics assessment, a physical assessment (usually of the concentration of a
pollutant) taken in an environmental or biological medium, normally with the intent of relating
the measured value to the exposure of an organism.
Measurement Endpoint - A measurable ecological characteristic that is related to the valued
characteristic chosen as the assessment endpoint. Also known as "measure of effect."
Mechanical Turbulence - Random irregularities of fluid motion in air caused by buildings or
other nonthermal, processes.
Mechanistic Model - A model that uses information about a chemical or other agent's
mechanism(s) of action - how it interacts with and harms the target organs - to predict the dose-
response curve or other applications.
Media Concentrations - The amount of a given substance in a specific amount of
environmental medium. For air, the concentration is usually given as micrograms (jig) of
substance per cubic meter (m3) of air; in water as jig of substance per L of water; and in soil as
mg of substance per kg of soil.
Metabolism - Generally, the biochemical reactions by which energy is made available for the
use of an organism. Metabolism includes all chemical transformations occurring in an organism
from the time a substance enters, until it has been utilized and the waste products eliminated. In
toxicology, metabolism of a toxicant consists of a series of chemical transformations that take
place within an organism. A wide range of enzymes act on toxicants, that may increase water
solubility, and facilitate elimination from the organism. In some cases, however, metabolites
may be more toxic than their parent compound.
Meteorology - The science of the atmosphere, including weather.
Microcosm Studies - Studies of the effects of stressors on multiple species found in multiple
media which are conducted in enclosed experimental systems.
Microscale Assessment - An air monitoring network designed to assess concentrations in air
volumes associated with area dimensions ranging from several meters up to about 100 meters.
Microenvironment - A small 3-dimensional space (e.g., an office, a room in a home) that can be
treated as homogeneous (or well characterized) with regard to exposure concentration of a
chemical.
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Middle Scale Assessment - An air monitoring network designed to assess concentrations typical
of areas up to several city blocks in size with dimensions ranging from about 100 meters to 0.5
kilometer.
Minimal Risk Levels (MRL) - Derived by ATSDR, an MRL is defined as an estimate of daily
human exposure to a substance that is likely to be without an appreciable risk of adverse effects
(noncancer) over a specified duration of exposure. MRLs can be derived for acute, intermediate,
and chronic duration exposures by the inhalation and oral routes.
Mixed (Mixing) Layer - In the atmosphere, that part of the turbulent boundary layer that is
dominated by turbulent diffusion caused by eddies generated by friction with the surface and
thermals arising from surface heat sources. Surface heating during the day and the absence of
temperature inversions allow components of the air within the planetary boundary layer to
exhibit mainly random vertical movements. Such movements may become more organized into
gusts of wind and dust devils during the afternoon. Despite being random, the turbulent
movements allow the transfer of atmospheric properties, such as heat, water vapor, momentum,
and air pollutants, from the near surface up through the planetary boundary layer.
Mixing Height - The depth through which atmospheric pollutants are typically mixed by
dispersive processes.
Mixtures - Any set of multiple chemical substances occurring together in an environmental
medium.
Mobile Source Air Toxics - Air toxics that are emitted from non-stationary objects that release
pollution. Mobile sources include cars, trucks, buses, planes, trains, motorcycles and
gasoline-powered lawn mowers. Another example is a portable generator.
Model - A mathematical representation of a natural system intended to mimic the behavior of the
real system, allowing description of empirical data, and predictions about untested states of the
system.
Model Uncertainty - Uncertainty due to necessary simplification of real-world processes, mis-
specification of the model structure, model misuse, or use of inappropriate surrogate variables or
inputs.
Modeling - An investigative technique using a mathematical or physical representation of a
system or theory that accounts for all or some of its known properties.
Modeling Node - In air quality modeling, the location where impacts are predicted.
Monitoring - Periodic or continuous physical surveillance or testing to determine pollutant
levels in various environmental media or in humans, plants, and animals.
Monte Carlo Technique- A repeated random sampling from the distribution of values for each
of the parameters in a generic exposure or risk equation to derive an estimate of the distribution
of exposures or risks in the population.
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Multipathway Assessment - An assessment that considers more than one exposure pathway.
For example, evaluation of exposure through both inhalation and ingestion would be a
multipathway assessment. Another example would be evaluation of ingestion of contaminated
soil and ingestion of contaminated food.
Multipathway Exposure - When an organism is exposed to pollutants through more than one
exposure pathway. One example would be exposure through both inhalation and ingestion.
Another example would be ingestion of contaminated soil and ingestion of contaminated food.
Multipathway Risk - The risk resulting from exposure to pollutants through more than one
pathway.
Multistage Model - A mathematical function used to extrapolate the probability of cancer from
animal bioassay data, using the form:
P(d) = l-e
where:
P(d) = probability of cancer from a continuous, lifetime exposure rate d;
q; = fitted dose coefficients of model; i = 0, 1, . . ., k; and
k = number of stages selected through best fit of the model, no greater than one less
than the number of available dose groups.
Mutagen - A chemical that causes a permanent genetic change in a cell other than that which
occurs during normal growth.
Mutagenicity - The capacity of a chemical or physical agent to cause permanent genetic change
in a cell other than that which occurs during normal growth.
N
National Ambient Air Quality Standards (NAAQS) - Maximum air pollutant standards that
EPA has set under the Clean Air Act for attainment by each state. Standards are set for each of
the criteria pollutants.
National Air Toxics Assessment (NATA) - EPA's ongoing comprehensive evaluation of air
toxics in the U.S. Activities include expansion of air toxics monitoring, improving and
periodically updating emission inventories, improving national- and local-scale modeling and
risk characterization, continued research on health effects and exposures to both ambient and
indoor air, and improvement of assessment tools.
National Emissions Inventory (NEI) - EPA's primary emissions inventory of HAPs.
National Emissions Standards for Hazardous Air Pollutants (NESHAPs) - Emissions
standards set by EPA for hazardous air pollutants. Also commonly referred to as the MACT
standards.
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National Emissions Trends (NET) Database - The NET database is an emission inventory that
contains data on stationary and mobile sources that emit criteria air pollutants and their
precursors. The database also includes estimates of annual emissions of these pollutants from
point, area, and mobile sources. The NET is developed every three years (e.g., 1996 and 1999)
by EPA, and includes emission estimates for all 50 States, the District of Columbia, Puerto Rico,
and the Virgin Islands.
Natural Source - Non-manmade emission sources, including biological (biogenic sources such
as plants) and geological sources (such as volcanoes), and windblown dust.
Neighborhood Scale Assessment - An air monitoring network designed to assess concentrations
within some extended area of the city that has relatively uniform land use with dimensions in the
0.5 to 4.0 kilometers range.
Neurotoxicity - Ability to damage nervous system tissue or adversely effect nervous system
function.
New Source Review - A Clean Air Act requirement that State Implementation Plans must
include a permit review that applies to the construction and operation of new and modified
stationary sources in nonattainment areas to ensure attainment of national ambient air quality
standards.
New Source Performance Standards - Uniform national EPA air emission standards which
limit the amount of pollution allowed from new sources or from modified existing sources.
Noncarcinogenic Effect - Any health effect other than cancer. Note that, while not all
noncancer toxicants cause cancer, all carcinogens exhibit noncarcinogenic effects.
No Observable Adverse Effect Level (NOAEL) - An highest exposure level at which there are
no statistically or biologically significant increases in the frequency or severity of adverse effect
between the exposed population and its appropriate control; some effects may be produced at
this level, but they are not considered adverse, nor precursors to adverse effects.
Nonpoint Source (NEI sense) - Diffuse pollution sources that are not assigned a single point of
origin (e.g., multiple dry cleaners in a county which are only described in an inventory in the
aggregate).
Nonroad Mobile Sources - Sources such as farm and construction equipment, gasoline-powered
lawn and garden equipment, and power boats and outdoor motors that emit pollutants.
Non-Threshold Effect - An effect (usually an adverse health effect) for which there is no
exposure level below which the effect is not expected to occur.
Non-Threshold Toxicant - A chemical for which there is no exposure level below which an
adverse health outcome is not expected to occur. Such substances are considered to pose some
risk of harm at any level of exposure.
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Non Steady-state Model - A dynamic model; a mathematical formulation describing and
simulating the physical behavior of a system or a process and its temporal variability.
North American Industry Classification System (NAICS) - NAICS replaced the Standard
Industrial Classification (SIC) beginning in 1997. This industry-wide classification system has
been designed as the index for statistical reporting of all economic activities of the U.S., Canada,
and Mexico. NAICS industries are identified by a 6-digit code. The international NAICS
agreement fixes only the first five digits of the code. The sixth digit, where used, identifies
subdivisions of NAICS industries that accommodate user needs in individual countries.
o
Octanol/Water Partition Coefficient (K,,w) - The ratio of a chemical's solubility in n-octanol to
its solubility in water at equilibrium. This measure is often used as an indication of a chemical's
ability to bioconcentrate in organisms.
Office of Air and Radiation (OAR) - EPA's Office responsible for providing information about
air pollution, clean air, air quality and radiation. OAR develops national programs, technical
policies, and regulations for controlling air pollution and radiation exposure. OAR is concerned
with pollution prevention, indoor and outdoor air quality, industrial air pollution, pollution from
vehicles and engines, radon, acid rain, stratospheric ozone depletion, and radiation protection.
Office of Air Quality, Planning, and Standards (OAQPS) - An EPA Office within OAR
whose primary mission is to preserve and improve air quality in the United States. As part of
this goal, OAQPS monitors and reports on air quality, air toxics, and emissions. They also
respond to visibility issues, as they relate to the level of air pollution. In addition, OAQPS is
tasked by the EPA with providing technical information for professionals involved with
monitoring and controlling air pollution, creating governmental policies, rules, and guidance
(especially for stationary sources), and educating the public about air pollution and what can be
done to control and prevent it.
OAQPS Toxicity Table - The EPA Office of Air and Radiation recommended default chronic
toxicity values for hazardous air pollutants. They are generally appropriate for screening-level
risk assessments, including assessments of select contaminants, exposure routes, or emission
sources of potential concern, or to help set priorities for further research. For more complex,
refined risk assessments developed to support regulatory decisions for single sources or
substances, dose-response data may be evaluated in detail for each "risk driver" to incorporate
appropriate new toxicological data, (http://www.epa. gov/ttn/atw/toxsource/summary.html)
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Office of Radiation and Indoor Air (ORIA) - An EPA Office within OAR whose mission is to
protect the public and the environment from the risks of radiation and indoor air pollution. The
Office develops protection criteria, standards, and policies; works with other programs within
EPA and other agencies to control radiation and indoor air pollution exposures; provides
technical assistance to states through EPA's regional offices, and to other agencies having
radiation and indoor air protection programs; directs an environmental radiation monitoring
program; responds to radiological emergencies; and evaluates and assesses the overall risk and
impact of radiation and indoor air pollution.
Office of Transportation and Air Quality (OTAQ) - An EPA Office within OAR whose
mission is to reconcile the transportation sector with the environment by advancing clean fuels
and technology, and working to promote more liveable communities. OTAQ is responsible for
carrying out laws to control air pollution from motor vehicles, engines, and their fuels. Mobile
sources include: cars and light trucks, large trucks and buses, farm and construction equipment,
lawn and garden equipment, marine engines, aircraft, and locomotives.
Onroad Mobile Source - Any mobile source of air pollution such as cars, trucks, motorcycles,
and buses that travels on roads and highways.
Open Pit Source - Large, open pits, such as surface coal mines and rock quarries.
Operating Permit Program - A program required by the Clean Air Act; requires existing
industrial sources to obtain an"operating permit". The operating permit program is a national
permitting system that consolidates all of the air pollution control requirements into a single,
comprehensive "operating permit" that covers all aspects of a source's year-to-year air pollution
activities.
Particle-bound - Reversibly absorbed or condensed onto the surface of particles.
Particulates/Particulate Matter (PM) - Solid particles or liquid droplets suspended or carried
in the air.
Partitioning - The separation or division of a substance into two or more compartments.
Environmental partitioning refers to the distribution of a chemical into various media (soil, air,
water, and biota).
Partitioning Model - Models consisting of mathematical equations that estimate how chemicals
will divide (i.e., partition) among abiotic and biotic media in a given environment based on
chemical- and site- specific characteristics.
Passive Monitor - A type of air toxics monitor that collects airborne pollutants by absorption
onto a reactive material (for example, sorbent tube, filter) for subsequent laboratory analysis. No
pump is used to draw the air across the reactive material. This type of monitor is usually used
for personal exposure monitoring or work space monitoring.
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Pathway Specific Risk - The risk associated with exposure to a chemical agent or a mixture of
chemicals via a specific pathway (e.g., inhalation of outdoor air).
Persistent, Bioaccumulative, and Toxic (PBT) Chemicals - Highly toxic, long-lasting
substances that can build up in the food chain to levels that are harmful to human and ecosystem
health. They are associated with a range of adverse health effects, including effects on the
nervous system, reproductive and developmental problems, cancer, and genetic impacts.
Percentile - Any one of the points dividing a distribution of values into parts each of which
contain 1/100 of the values. For example, the 75th percentile is a value such that 75 percent of
the values are less than or equal to it.
Persistence - Refers to the length of time a compound stays in the environment, once introduced.
A compound may persist for very short amounts of time (e.g., fractions of a second) or for long
periods of time (e.g., hundreds of years).
Persistent Organic Pollutants (POPs) - Highly stable organic compounds used as pesticides or
in industry. They are also generated unintentionally as the byproduct of combustion and
industrial processes. POPs are a special problem because they persist in the environment,
accumulate in the tissues of living organisms, and are toxic to humans and wildlife. POPs with
these characteristics are typically semi-volatile, enabling them to move long distances and
condense over colder regions of the earth. These properties lead to increased concern for the
toxic effects that they can exert on a range of biota, in particular on top-of-the-food chain
species, even at extremely low levels in the ambient environment.
Personal Air Monitoring Device - Unlike a passive air toxics monitor, this device uses a pump
to draw the air sample through to measure exposure in the immediate vicinity of an individual.
The air sample can be drawn across a reactive material (to be analayzed in a laboratory), or it can
be drawn through a direct-read detector.
Personal Monitoring - A measurement collected from an individual's immediate environment
using active or passive devices to collect the samples.
Pervious Surface - A surface that can be penetrated (usually in reference to water; e.g., crop
land).
Pharmacodynamics - Process of interaction of pharmacologically active substances with target
sites, and the biochemical and physiological consequences leading to therapeutic or adverse
effects.
Pharmacokinetics - The study of the absorption, distribution, metabolism, and excretion of
chemicals in living organisms and the genetic, nutritional, behavioral, and environmental factors
that modify these parameters.
Photolysis - The breakdown of a material by sunlight; an important mechanism for the
degradation of contaminants in air, surface water, and the terrestrial environment.
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Physical Factors - Manmade and/or natural characteristics or features that influence the
movement of pollutants in the environment (e.g., settling velocity, terrain effects).
Physiologically Based Pharmacokinetic (PBPK) Model - A computer model that describes
what happens to a chemical in the body of a human or laboratory animal. It describes how the
chemical gets into the body, where it goes in the body, how it is changed by the body, and how it
leaves the body.
Piscivorous - A species feeding preferably on fish.
Planning and Scoping - The process of determining the purpose, scope, players, expected
outcomes, analytical approach, schedule, deliverables, QA/QC, resources, and document
requirements for the risk assessment.
Plume - The visible or measurable presence of a contaminant in the atmosphere, once released
from a given point of origin (e.g., a plume of smoke from a forest fire).
Plume Height - The elevation to which a plume travels (i.e., the sum of the release height and
plume rise).
Plume Rise - The height to which a plume rises in the atmosphere from the point of release.
Plume Transport - The movement of a plume through the atmosphere and across land and
water features.
Plume Washout - The removal of a substance from the atmosphere via a precipitation event.
PM-10/PM-2.5. PM-10 or PM10 refers to particles in the atmosphere with a diameter of less
than ten or equal to 10 micrometers. PM-2.5 or PM25 refers to smaller particles in the air (i.e.,
less than or equal to 2.5 micrometers in diameter).
Point of Departure (PoD) - The dose-response point that marks the beginning of a low-dose
extrapolation. This point can be the lower bound on dose for an estimated incidence or a change
in response level from a dose-response model (BMD), or a NOAEL or LOAEL for an observed
incidence, or change in level of response.
Point of Exposure - The location of potential contact between an organism and a chemical or
physical agent.
Point of Release - Location of release to the environment.
Point Source (NEI sense) - A source of air pollution which can be physically located on a map.
Point Source (non-NEI sense) - A stack, vent, duct, pipe or other confined air stream from
which chemicals may be released to the air.
Pollutant Release and Transfer Registries (PRTRs) - The international equivalent to the
Toxics Release Inventory (TRI). PRTRs are data banks of recorded information of the releases
April 2004 Page 29
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and transfers of toxic chemicals from industries, such as manufacturers, mining facilities,
processors, or government-owned and operated facilities.
Population Risk or Hazard - Population risk refers to an estimate of the extent of harm for the
population or population segment being addressed. It often refers to an analysis of the number of
people living at a particular risk or hazard level.
Potential Risk - Estimated likelihood, or probability, of injury, disease, or death resulting from
exposure to a potential environmental hazard.
Potential Dose - The amount of a compound contained in material swallowed, breathed, or
applied to the skin.
Practical Quantitation Limit - The lowest level of quantitation that can be reliably achieved
within specified limits of precision and accuracy during routine laboratory operating conditions.
Precision - A measure of the reproducibility of a measured value under a given set of
circumstances.
Present Scenario - Risk characterizations using present scenarios to estimate risks to individuals
(or populations) that currently reside in areas where potential exposures may occur (e.g., using
an existing population within some specified area).
Prevailing Wind - Direction from which the wind blows most frequently.
Prevention of Significant Deterioration (PSD) - An EPA program in which state and/or federal
permits are required in order to restrict emissions from new or modified sources in places where
air quality already meets or exceeds primary and secondary ambient air quality standards.
Primary Standard - A pollution limit based on health effects. Primary standards are set for
criteria air pollutants.
Probabilistic - A type of statistical modeling approach used to assess the expected frequency
and magnitude of a parameter by running repetitive simulations using statistically selected inputs
for the determinants of that parameter (e.g., rainfall, pollutants, flows, temperature).
Probabilistic Risk Assessment/Analysis - Calculation and expression of health risks using
multiple risk descriptors to provide the likelihood of various risk levels. Probabilistic risk results
approximate a full range of possible outcomes and the likelihood of each, which often is
presented as a frequency distribution graph, thus allowing uncertainty or variability to be
expressed quantitatively.
April 2004 Page 30
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Probability Density Function (PDF) - The PDF is alternatively referred to in the literature as
the probability function or the frequency function. For continuous random variables, that is, the
random variables which can assume any value within some defined range (either finite or
infinite), the probability density function expresses the probability that the random variable falls
within some very small interval. For discrete random variables, that is, random variables which
can only assume certain isolated or fixed values, the term probability mass function (PMF) is
preferred over the term probability density function. PMF expresses the probability that the
random variable takes on a specific value.
Problem Formulation (in Ecological Risk Assessment) - The initial stage of a risk assessment
where the purpose of the assessment is articulated, assessment endpoints and a conceptual model
are developed, and a plan for analyzing and characterizing risk is determined.
Problem Statement - A statement of the perceived problem to be studied by the risk assessment.
Problem statements often also include statements about how the problem is going to be studied.
Public Health Consultation (Public Health Assessment) - See health consultation
Public Health Assessment (PHA) - An evaluation of hazardous substances, health outcomes,
and community concerns at a hazardous waste site or other potential source of pollutants to
determine whether people could be harmed from coming into contact with those substances. The
PHA also lists actions that need to be taken to protect public health.
Public Health Advisory (in Public Health Assessment) - A statement made by a regulatory
agency that a release of hazardous substances or contamination by microbial pathogens poses an
immediate threat to human health. The advisory includes recommended measures to reduce
exposure and reduce the threat to human health.
Public Health Hazard Category (in Public Health Assessment) - Statements about whether
people could be harmed by conditions present at the site in the past, present, or future. One or
more hazard categories might be appropriate for each site. ATSDR's five public health hazard
categories are no public health hazard, no apparent public health hazard, indeterminate public
health hazard, public health hazard, and urgent public health hazard.
Q
Qualitative Uncertainty Estimate - A detailed examination, using qualitative information, of
the systematic and random errors of a measurement or estimate.
Quality Assurance Project Plan - A document describing in comprehensive detail the
necessary quality assurance, quality control, and other technical activities that must be
implemented to ensure that the results of the work performed will satisfy the stated performance
criteria.
Quality Assurance - An integrated system of activities involving planning, quality control,
quality assessment, reporting and quality improvement to ensure that a product or service meets
defined standards of quality with a stated level of confidence.
April 2004 Page 31
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Quality Control - The overall system of technical activities whose purpose is to measure and
control the quality of a product or service so that it meets the needs of its users. The aim is to
provide data quality that is satisfactory, adequate, and dependable.
R
Random Variable - A quantity which can take on any number of values but whose exact value
cannot be known before a direct observation is made. For example, the outcome of the toss of a
pair of dice is a random variable, as is the height or weight of a person selected at random from a
city phone book.
Receptor (modeling sense) - In fate/transport modeling, the location where impacts are
predicted.
Receptor (non-modeling sense) - The entity which is exposed to an environmental stressor.
Red Book - 1983 NRC publication entitled Risk Assessment in the Federal Government:
Managing the Process.
Reference Concentration (RfC) - An estimate (with uncertainty spanning perhaps an order of
magnitude) of a continuous inhalation exposure to the human population (including sensitive
subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime.
Reference Dose (RfD) - An estimate (with uncertainty spanning perhaps an order of magnitude)
of a daily oral exposure to the human population (including sensitive subgroups) that is likely to
be without an appreciable risk of deleterious effects during a lifetime.
Reference Media Evaluation Guides (RMEG) - A type of comparison value derived by
ATSDR to protect the most sensitive populations. They do not consider carcinogenic effects,
chemical interactions, multiple route exposure, or other media-specific routes of exposure, and
are very conservative concentration values designed to protect sensitive members of the
population.
Regional/National Scale Assessment - An air monitoring network designed to assess from tens
to hundreds of kilometers, up to the entire nation.
Relative Potency Factor - The ratio of the toxic potency of a given chemical to that of an index
chemical.
Release Parameters - The specific physical characteristics of the release (e.g., stack diameter,
stack height, release flow rate, temperature).
Representativeness - The degree to which one or a few samples are characteristic of a larger
population about which the analyst is attempting to make an inference.
April 2004 Page 32
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Reproductive Toxicity - The occurrence of biologically adverse effects on the reproductive
systems of females or males that may result from exposure to environmental agents. The toxicity
may be expressed as alterations to the female or male reproductive organs, the related endocrine
system, or pregnancy outcomes. The manifestation of such toxicity may include, but not be
limited to, adverse effects on onset of puberty, gamete production and transport, reproductive
cycle normality, sexual behavior, fertility, gestation, parturition, lactation, developmental
toxicity, premature reproductive senescence, or modifications in other functions that are
dependent on the integrity of the reproductive systems.
Residual Risk - The extent of health risk from air pollutants remaining after application of the
Maximum Achievable Control Technology (MACT).
Resources - Money, time, equipment, and personnel available to perform the assessment.
Risk (in the context of human health) - The probability of injury, disease, or death from
exposure to a chemical agent or a mixture of chemicals. In quantitative terms, risk is expressed
in values ranging from zero (representing the certainty that harm will not occur) to one
(representing the certainty that harm will occur). (Compare with hazard.)
Risk Assessor(s) - The person or group of people responsible for conducting a qualitative and
quantitative evaluation of the risk posed to human health and/or the environment by
environmental pollutants.
Risk Assessment - For air toxics, the scientific activity of evaluating the toxic properties of a
chemical and the conditions of human or ecological exposure to it in order both to ascertain the
likelihood that exposed humans or ecological receptors will be adversely affected, and to
characterize the nature of the effects they may experience.
Risk Assessment Forum - A standing committee of senior EPA scientists which was
established to promote Agency-wide consensus on difficult and controversial risk assessment
issues and to ensure that this consensus is incorporated into appropriate Agency risk assessment
guidance.
Risk Assessment Work Plan - A document that outlines the specific methods to be used to
assess risk, and the protocol for presenting risk results. The risk assessment workplan may
consist of one document or the compilation of several workplans that, together, constitute the
overall risk assessment workplan.
Risk Characterization - The last phase of the risk assessment process in which the information
from the toxicity and exposure assessment steps are integrated and an overall conclusion about
risk is synthesized that is complete, informative and useful for decision-makers. In all cases,
major issues and uncertainty and variability associated with determining the nature and extent of
the risk should be identified and discussed. The risk characterization should be prepared in a
manner that is clear, transparent, reasonable and consistent.
Risk Communication - The exchange of information about health or environmental risks among
risk assessors and managers, the general public, news media, and other stakeholders.
April 2004 Page 33
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Risk Management - The decision-making process that uses the results of risk assessment to
produce a decision about environmental action. Risk management includes consideration of
technical, scientific, social, economic, and political information.
Risk Manager(s) - The person or group responsible for evaluating and selecting alternative
regulatory and non-regulatory responses to risk.
Root Uptake - The uptake of compounds available in the soil and their transfer to the above
ground portions of the plant.
Route-to-Route Extrapolation - Calculations to estimate the dose-response relationship of an
exposure route for which experimental data do not exist or are inadequate, and which are based
on existing experimental data for other route(s) of exposure.
Runoff - That part of precipitation, snow melt, or irrigation water that runs off the land into
streams or other surface water. It can carry pollutants from the air and land into receiving
waters.
Sample - A small portion of something designed to evaluate the nature or quality of the whole
(for example, one or several samples of air used to evaluate air quality generally).
Sampling and Analysis Plan - An established set of procedures specifying how a sample is to
be collected, handled, analyzed, and the data validated and reported.
Sampling Frequency - The time interval between the collection of successive samples.
Science Advisory Board (SAB) - A group of recognized, non-EPA experts who advise EPA on
science and science policy.
Scenario Uncertainty - Uncertainty due to descriptive errors, aggregation errors, errors in
professional judgment, or incomplete analysis.
SCREENS - An air dispersion model developed to obtain conservative estimates of air
concentration for use in screening level assessments through the use of conservative algorithms
and meteorology.
Screening-level Risk Assessment - A risk assessment performed with few data and many
conservative assumptions to identify exposures that should be evaluated more carefully for
potential risk.
Secondary Production/Pollutant - Formation of pollutants in the atmosphere by chemical
transformation of precursor compounds.
Secondary Standard - A pollution limit based on environmental effects (e.g., damage to
property, plants, visibility). Secondary standards are set for criteria air pollutants.
April 2004 Page 34
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Sensitive Subgroups - Identifiable subsets of the general population that, due to differential
exposure or susceptibility, are at greater risk than the general population to the toxic effects of a
specific air pollutant (e.g., depending on the pollutant and the exposure circumstances, these may
be groups such as subsistence fishers, infants, asthmatics, or the elderly).
Settling Velocity/Rate - The maximum speed at which a particle will fall in still air. It is a
function of its size, density, and shape.
Silage - Stored vegetation used as feed for cattle.
Simulation - A representation of a problem, situation in mathematical terms, especially using a
computer.
Soil Volumetric Water Content - The soil-water content expressed as the volume of water per
unit bulk volume of soil.
Soil Dry Bulk Density - The mass of dry soil per unit bulk volume.
Soil Erosion - Detachment and movement of topsoil or soil material from the upper part of the
soil profile, by the action of wind or running water, especially as a result of changes brought
about by human activity, such as unsuitable or mismanaged agriculture.
Solar Radiation - Energy from the sun. Of importance to the climate system, solar radiation
includes ultra-violet radiation, visible radiation, and infrared radiation.
Solubility - The amount of mass of a compound that will dissolve in a unit volume of solution.
Aqueous solubility is the maximum concentration of a chemical that will dissolve in pure water
at a reference temperature.
Source - Any place or object from which pollutants are released.
Source Category - A group of similar industrial processes or industries that are contributors to
releases of hazardous air pollutants. The 1990 amendments to the Clean Air Act (CAA) requires
that the EPA publish and regularly update a listing of all categories and subcategories of major
and area sources that emit hazardous air pollutants.
Source Characterization - The detailed description of the source (e.g., location, source of
pollutant releases, pollutants released, release parameters).
Spatial Variability - The magnitude of difference in contaminant concentrations in samples
separated by a known distance.
SPECIATE - EPA's repository of Total Organic Compound (TOC) and Paniculate Matter (PM)
speciated profiles for a variety of sources for use in source apportionment studies. The profiles
in the system are provided as a library of available profiles for source-receptor and source
apportionment type models, such as Chemical Mass Balance 8 (CMB8).
April 2004 Page 35
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Stable Conditions (in the Atmosphere) - Air with little or no tendency to rise, that is usually
accompanied by clear dry weather. Stable air holds, instead of dispersing, pollutants. [National
Weather Service, Southern Region Headquarters' Jetstream Weather School,
http://www.srh.weather.gov/jetstream/append/glossary.htm and EPA, 1997: Terms of
Environment, http://www.epa. gov/OCEPAterms/.]
Stack - A chimney, smokestack, or vertical pipe that discharges used air.
Stack Release - The release of a chemical through a stack.
Stack Testing - The monitoring, by testing, of chemicals released from a stack.
Stakeholder(s) - Any organization, governmental entity, or individual that has a stake in or may
be impacted by a given approach to environmental regulation, pollution prevention, energy
conservation, etc.
Standard Industrial Classification (SIC) - A method of grouping industries with similar
products or services and assigning codes to these groups.
Standard Operating Procedure (SOP) - A established set of written procedures adopted and
used to guide the work of for a specific project. For example, an air monitoring study would
include SOPs on sample collection and handling and SOPs on analytical requirements and data
validation and reporting.
Standing Crop - The quantity of plant biomass in a given area, usually expressed as density (dry
mass per unit area) or energy content per unit area.
Stationary Source - A source of pollution that is fixed in space.
Steady-state Model - Mathematical model of fate and transport that uses constant values of
input variables to predict constant values of receiving media concentrations.
Stochastic - Involving or containing a random variable; involving probability or chance.
Stressor - Any physical, chemical, or biological entity that can induce adverse effects on
ecosystems or human health.
Stressor-response Profile or Relationship (in Ecological Risk Assessment] - The product of
characterization of ecological effects in the analysis phase of ecological risk assessment. The
stressor-response profile/relationship summarizes the data on the effects of a stressor and the
relationship of the data to the assessment endpoint.
April 2004 Page 36
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Structure-activity Relationship (SAR) - Mathematical or qualitative expression of the
relationships between biological activity or toxicity of a chemical to its chemical structure or
substructure. Ideally, such relationships can be formulated as Quantitative Structure Activity
Relationships (QSARs), in which some degree of predictive capability is present. [Air Risk
Information Support Center, OAQPS, March 1989: Glossary of Terms Related to Health,
Exposure, and Risk Assessment. EPA/450/3-88/016.]
Support Center for Regulatory Models (SCRAM) - An EPA website that is a source of
information on atmospheric dispersion models (e.g., ISCST3, SCREEN 3, and ASPEN) that
support regulatory programs required by the Clean Air Act. Documentation and guidance for
these computerized models are a major feature of this website. This site also contains computer
code, data, and technical documents that deal with mathematical modeling for the dispersion of
air pollutants.
Synergistic Effect - A situation in which the overall effect of two chemicals acting together is
greater than the simple sum of their individual effects.
Target Organ - The biological organ(s) most adversely affected by exposure to a chemical
substance (e.g., the site of the critical effect).
Target Organ Specific Hazard Index (TOSHI) - The sum of hazard quotients for individual
air toxics that affect the same organ/organ system or act by similar toxicologic processes
Temporal Variability - The difference in contaminant concentrations observed in samples taken
at different times.
Teratogenesis - The introduction of nonhereditary birth defects in a developing fetus by
exogenous factors such as physical or chemical agents acting in the womb to interfere with
normal embryonic development.
Terrain Effects - The impact on the airflow as it passes over complex land features such as
mountains.
Terrestrial Radiation - The total infrared radiation emitted by the earth and its atmosphere in
the temperature range of approximately 200 to 300 Kelvin. Terrestrial radiation provides a
major part of the potential energy changes necessary to drive the atmospheric wind system and is
responsible for maintaining the surface air temperature within limits of livability.
Thermal Turbulence - Turbulent vertical motions that result from surface heating and the
subsequent rising and sinking of air.
Threshold Dose/Threshold - The lowest dose of a chemical at which a specified measurable
effect is observed and below which it is not observed.
April 2004 Page 37
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Threshold Effect - An effect (usually an adverse health effect) for which there is an exposure
level below which the effect is not expected to occur.
Threshold Toxicant - A chemical for which there is an exposure level below which an adverse
health outcome is not expected to occur.
Tiered Analysis - An analysis arranged in layers/steps. Risk assessments/analyses are often
conducted in consecutive layers/steps that begin with a reliance on conservative assumptions and
little data (resulting in less certain, but generally conservative answers) and move to more study-
area specific data and less reliance on assumptions (resulting in more realistic answers). The
level of effort and resources also increases with the development of more realistic data.
Time-integrated Sample - Samples are collected over a period of time. Only the total pollutant
collected is measured, and so only the average concentration during the sampling period can be
determined.
Time-trend Study - Samples spaced in time to capture systematic temporal trends (e.g., a
facility might change its production methods or products over time).
Time-weighted Sum of Exposures - Used in inhalation exposure modeling. Provides a total
exposure from all different microenvironments in which a person spends time.
Toxic Air Pollutants - see hazardous air pollutant.
Toxicity - The degree to which a substance or mixture of substances can harm humans or
environmental receptors.
Toxicity Assessment - Characterization of the toxicological properties and effects of a chemical,
with special emphasis on establishment of dose-response characteristics.
Toxicity Test - Biological testing (usually with an cell system, invertebrate, fish, or small
mammal) to determine the adverse effects of a compound.
Toxicology - The study of harmful interactions between chemicals and biological systems.
Toxic Release Inventory (TRI) - Annual database of releases to air, land, and water, and
information on waste management in the United States of over 650 chemicals and chemical
compounds. This data is collected under Section 313 of the Emergency Planning and
Community Right to Know Act.
Trajectory - The track taken by a parcel of air as it moves within the atmosphere over a given
period.
Transformation - The change of a chemical from one form to another.
Transparency - Conducting a risk assessment in such a manner that all of the scientific
analyses, uncertainties, assumptions, and science policies which underlie the decisions made
throughout the risk assessment are clearly stated (i.e., made readily apparent).
April 2004 Page 38
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Turbulence - Irregular motion of the atmosphere, as indicated by gusts and lulls in the wind.
u
Uncertainty - Uncertainty represents a lack of knowledge about factors affecting
exposure/toxicity assessments and risk characterization and can lead to inaccurate or biased
estimates of risk and hazard. Some of the types of uncertainty include scenario uncertainty,
parameter uncertainty, and model uncertainty.
Uncertainty analysis - A detailed examination of the systematic and random errors of a
measurement or estimate (in this case a risk or hazard estimate); an analytical process to provide
information regarding the uncertainty.
Uncertainty Factor (UF) - One of several, generally 10-fold factors, used in operationally
deriving the RfD and RfC from experimental data. UFs are intended to account for (1) the
variation in sensitivity among the members of the human population; (2) the uncertainty in
extrapolating animal data to humans, i.e., interspecies variability; (3) the uncertainty in
extrapolating from data obtained in a study with less-than-lifetime exposure to lifetime exposure,
i.e., extrapolating from subchronic to chronic exposure; (4) the uncertainty in extrapolating from
a LOAEL rather than from a NOAEL; and (5) the uncertainty associated with extrapolation from
animal data when the data base is incomplete.
Universal Soil Loss Equation - An equation used to predict the average annual soil loss per unit
area per year.
Unit Risk Estimate (URE) - The upper-bound excess lifetime cancer risk estimated to result
from continuous exposure to an agent at a concentration of 1 |i g/L in water, or 1 |ig/m3 in air.
The interpretation of unit risk would be as follows: if the water unit risk = 2 x 10"6 |ig/L, 2 excess
tumors may develop per 1,000,000 people if exposed daily for a lifetime to 1 jig of the chemical
in 1 liter of drinking water.
Unstable Conditions (in the Atmosphere) - An atmospheric state in which warm air is below
cold air. Since warm air naturally rises above cold air (due to warm air being less dense than
cold air), vertical movement and mixing of air layers can occur.
Uptake - The process by which a substance crosses an absorption barrier and is absorbed into
the body.
Urban Scale Assessment - An air monitoring network designed to assess the overall, citywide
conditions with dimensions on the order of 4 to 50 kilometers. This scale would usually require
more than one site for definition.
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Vapor - The gas given off by substances that are solids or liquids at ordinary atmospheric
pressure and temperatures.
Variability - Refers to the observed differences attributable to true heterogeneity or diversity in
a population or exposure parameter. Examples include human physiological variation (e.g.,
natural variation in body weight, height, breathing rate, drinking water intake rate), weather
variability, variation in soil types and differences in contaminant concentrations in the
environment. Variability is usually not reducible by further measurement of study, but it can be
better characterized.
Volatilization/Vapor Release - The conversion of a liquid or solid into vapors.
Volume Source - In air dispersion modeling, a three dimensional volume from which a release
may occur (e.g., a gas station modeled as a box from which chemicals are emitted).
w
Watershed - The land area that drains into a stream; the watershed for a major river may
encompass a number of smaller watersheds that ultimately combine at a common point.
Weight-of-Evidence (WOE) - A system for characterizing the extent to which the available data
support the hypothesis that an agent causes an adverse health effect in humans. For example,
under EPA's 1986 cancer risk assessment guidelines, the WOE was described by categories "A
through E," Group A for known human carcinogens through Group E for agents with evidence
of noncarcinogenicity. The approach outlined in EPA's proposed guidelines for carcinogen risk
assessment (1996 and updates) considers all scientific information in determining whether and
under what conditions an agent may cause cancer in humans, and provides a narrative approach
to characterize carcinogenicity rather than categories.
White Book - 1996 Presidential Commission on Risk Assessment and Risk Management
(CRARM) publication entitled Risk Assessment and Risk Management in Regulatory Decision-
Making.
Wind Rose - A graphical display showing the frequency and strength of winds from different
directions over some period of time.
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Appendix A Listing of All HAPs
-------
-------
Appendix A. Listing of HAPs
CAS Number
75-07-0
60-35-5
75-05-8
98-86-2
53-96-3
107-02-8
79-06-1
79-10-7
107-13-1
107-05-1
92-67-1
62-53-3
90-04-0
1332-21-4
71-43-2
92-87-5
98-07-7
100-44-7
92-52-4
117-81-7
542-88-1
75-25-2
106-99-0
156-62-7
133-06-2
63-25-2
75-15-0
56-23-5
463-58-1
120-80-9
133-90-4
57-74-9
7782-50-5
79-11-8
532-27-4
108-90-7
510-15-6
67-66-3
107-30-2
126-99-8
1319-77-3
Chemical Name
Acetaldehyde
Acetamide
Acetonitrile
Acetophenone
2-Acetylaminofluorene
Acrolein
Acrylamide
Acrylic acid
Acrylonitrile
Allyl chloride
4-Aminobiphenyl
Aniline
o-Anisidine
Asbestos
Benzene (including benzene from gasoline)
Benzidine
Benzotrichloride
Benzylchloride
Biphenyl
Bis (2-ethylhexyl) phthalate
Bis(chloromethyl )ether
Bromoform
1 ,3-Butadiene
Calcium cyanamide
Captan
Carbaryl
Carbon disulfide
Carbon tetrachloride
Carbonyl sulfide
Catechol
Chloramben
Chlordane
Chlorine
Chloroacetic acid
2-Chloroacetophenone
Chlorobenzene
Chlorobenzilate
Chloroform
Chloromethyl methyl ether
Chloroprene
Cresol/Cresylic acid (mixed isomers)
Common Name
DEHP
CAA HAP
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
TRI Chemical
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Urban HAP
X
X
X
X
X
X
X
Mobile
Source Air
Toxic
X
X
X
X
April 2004
Page A-1
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Appendix A. Listing of HAPs
CAS Number
95-48-7
108-39-4
106-44-5
98-82-8
N/A
72-55-9
334-88-3
132-64-9
96-12-8
84-74-2
106-46-7
91-94-1
111-44-4
542-75-6
62-73-7
111-42-2
64-67-5
119-90-4
60-11-7
121-69-7
119-93-7
79-44-7
68-12-2
57-14-7
131-11-3
77-78-1
N/A
51-28-5
121-14-2
123-91-1
122-66-7
106-89-8
106-88-7
140-88-5
100-41-4
51-79-6
75-00-3
106-93-4
107-06-2
107-21-1
151-56-4
Chemical Name
o-Cresol
m-Cresol
p-Cresol
Cumene
2,4-Dichlorophenoxyacetic Acid (including salts and esters)
1 ,1 -dichloro-2,2-bis(p-chlorophenyl)ethylene
Diazomethane
Dibenzofuran
1 ,2-Dibromo-3-chloropropane
Dibutyl phthalate
1 ,4-Dichlorobenzene
3,3'-Dichlorobenzidine
Dichloroethylether
1 ,3-Dichloropropene
Dichlorvos
Diethanolamine
Diethyl sulfate
3,3'-Dimethoxybenzidine
4-Dimethylaminoazobenzene
N,N-Dimethylaniline
3,3'-Dimethylbenzidine
Dimethylcarbamoyl chloride
N,N-Dimethylformamide
1 ,1-Dimethylhydrazine
Dimethyl phthalate
Dimethyl sulfate
4,6-Dinitro-o-cresol (including salts)
2,4-Dinitrophenol
2-4-Dinitrotoluene
1 ,4-Dioxane
1 ,2-Diphenylhydrazine
Epichlorohydrin
1 ,2-Epoxybutane
Ethyl acrylate
Ethylbenzene
Ethyl carbamate
Ethyl chloride
Ethylene dibromide
Ethylene dichloride
Ethylene glycol
Ethyleneimine
Common Name
2-4-D
DDE
Bis[2-chloroethyl]ether
1 ,4-Diethyleneoxide
l-Chloro-2,3-epoxypropane
Urethane
Chloroethane
Dibromoethane
1 ,2-Dichloroethane
Aziridine
CAA HAP
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
TRI Chemical
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Urban HAP
X
X
X
Mobile
Source Air
Toxic
X
April 2004
PageA-2
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Appendix A. Listing of HAPs
CAS Number
75-21-8
96-45-7
75-34-3
50-00-0
76-44-8
118-74-1
87-68-3
N/A
77-47-4
67-72-1
822-06-0
680-31-9
110-54-3
302-01-2
7647-01-0
7664-39-3
123-31-9
78-59-1
108-31-6
67-56-1
72-43-5
74-83-9
74-87-3
71-55-6
78-93-3
60-34-4
74-88-4
108-10-1
624-83-9
80-62-6
1634-04-4
101-14-4
75-09-2
101-68-8
101-77-9
91-20-3
98-95-3
92-93-3
100-02-7
79-46-9
684-93-5
Chemical Name
Ethylene oxide
Ethylene thiourea
Ethylidene dichloride
Formaldehyde
Heptachlor
Hexachlorobenzene
Hexachlorobutadiene
1 ,2,3,4,5,6-Hexachlorocyclohexane (all stereoisomers-including lindane)
Hexachlorocyclopentadiene
Hexachloroethane
Hexamethylene diisocyanate
Hexamethylphosphoramide
Hexane
Hydrazine
Hydrochloric acid
Hydrogen fluoride
Hydroquinone
Isophorone
Maleic anhydride
Methanol
Methoxychlor
Methyl bromide
Methyl chloride
Methyl chloroform
Methyl ethyl ketone
Methyl hydrazine
Methyl iodide
Methyl isobutyl ketone
Methyl isocyanate
Methyl methacrylate
Methyl tert-butyl ether
4,4'-Methylenebis
Methylene chloride
4-4'-Methylenediphenyl diisocyanate
4-4'-Methylenedianiline
Naphthalene
Nitrobenzene
4-Nitrobiphenyl
4-Nitrophenol
2-Nitropropane
N-Nitroso-N-methylurea
Common Name
1-1-Dichloroethane
Hydrogen Chloride
Hydrofluoric acid
Bromomethane
Chloromethane
1-1-1-Trichloroethane
2-Butanone
lodomethane
Hexone
MTBE
2-chloroaniline
Dichloromethane
MDI
CAA HAP
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
TRI Chemical
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Urban HAP
X
X
X
X
X
Mobile
Source Air
Toxic
X
X
X
X
April 2004
PageA-3
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Appendix A. Listing of HAPs
CAS Number
62-75-9
59-89-2
56-38-2
82-68-8
87-86-5
108-95-2
106-50-3
75-44-5
7803-51-2
7723-14-0
85-44-9
1336-36-3
1120-71-4
57-57-8
123-38-6
114-26-1
78-87-5
75-56-9
75-55-8
91-22-5
106-51-4
100-42-5
96-09-3
1746-01-6
79-34-5
127-18-4
7550-45-0
108-88-3
95-80-7
584-84-9
95-53-4
8001-35-2
120-82-1
79-00-5
79-01-6
95-95-4
88-06-2
121-44-8
1582-09-8
540-84-1
108-05-4
Chemical Name
N-Nitrosodimethylamine
N-Nitrosomorpholine
Parathion
Pentachloronitrobenzene
Pentachlorophenol
Phenol
p-Phenylenediamine
Phosgene
Phosphine
Phosphorus
Phthalic anhydride
Polychlorinated biphenyls
1-3-Propanesultone
beta-Propiolactone
Propionaldehyde
Propoxur
Propylene dichloride
Propylene oxide
1-2-Propylenimine
Quinoline
Quinone
Styrene
Styrene oxide
2,3,7,8-Tetrachlorodibenzo-p-dioxin
1 ,1 ,2,2-Tetrachloroethane
Tetrachloroethylene
Titanium tetrachloride
Toluene
Toluene-2,4-diamine
2,4-Toluene diisocyanate
o-Toluidine
Toxaphene
1 ,2,4-Trichlorobenzene
1,1,2-Trichloroethane
Trichloroethylene
2-4-5-Trichlorophenol
2-4-6-Trichlorophenol
Triethylamine
Trifluralin
2,2,4-Trimethylpentane
Vinyl acetate
Common Name
Quintobenzene
Aroclors
Baygon
1 ,2-Dichloropropane
2-Methylaziridine
p-Benzoquinone
Perchloroethylene
chlorinated camphene
CAA HAP
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
TRI Chemical
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Urban HAP
X
X
X
X
X
X
X
Mobile
Source Air
Toxic
X
X
X
April 2004
PageA-4
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Appendix A. Listing of HAPs
CAS Number
593-60-2
75-01-4
75-35-4
1330-20-7
95-47-6
108-38-3
106-42-3
Chemical Name
Vinyl bromide
Vinyl chloride
Vinylidene chloride
Xylenes (mixed isomers)
o-Xylene
m-Xylene
p-Xylene
Antimony Compounds
Arsenic Compounds (inorganic including arsine)
Beryllium Compounds
Cadmium Compounds
Chromium Compounds
Cobalt Compounds
Coke Oven Emissions
Cyanide Compounds 1
Glycol ethers 2
Lead Compounds
Manganese Compounds
Mercury Compounds
Fine mineral fibers 3
Nickel Compounds
Polycyclic Organic Matter 4
Radionuclides (including radon) 5
Selenium Compounds
Common Name
1 ,1-Dichloroethylene
CAA HAP
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
TRI Chemical
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Urban HAP
X
X
X
X
X
X
X
X
X
X
X
Mobile
Source Air
Toxic
X
X
X
X
X
X
X
X
1 X'CN where X=H or any other group where a formal dissociation may occur. For example KCN or CA(CN)2.
2 Includes mono- and di- ethers of ethylene glycol, diethylene glycol, triethylene glycol R-(OCH2CH2)n-OR where n= 1 ,2, or 3; R= alkyl or aryl groups; R' = R, H or groups which, when
removed, yield glycol ethers with the structure: R-(OCH2CH)n-OH. Polymers are excluded from the glycol category.
3 Includes mineral fiber emissions from facilities manufacturing or processing glass, rock or slag fibers (or other mineral derived fibers) or average diameter 1 micrometer or less.
4 Includes organic compounds with more than one benzene ring, and which have a boiling point greater than or equal to 100 degrees C.
5 A type of atom which spontaneously undergoes radioactive decay.
April 2004
PageA-5
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Appendix B Guide to Federal Agencies that Oversee
Air Toxics
This appendix contains descriptions and contacts of the primary EPA organizations that routinely
deal with air toxics risk related regulations and information. Additional governmental offices
that also deal with air toxics information are also listed. This listing is not meant to be either
comprehensive or static and updates and suggestions for additions are welcome (email to
mitchell.ken(5),epa. gov).
The listing is arranged first by EPA headquarters offices and contacts that deal specifically with
air toxics risk related issues. EPA Regional air toxics contacts and other governmental agencies
that provide health and risk assessment information complete the listing.
1. EPA Headquarters Offices that Work Directly on Air Toxics Issues
a. Office of Air and Radiation. The Office of Air and Radiation (OAR) develops national
programs, technical policies, and regulations for controlling air pollution and radiation
exposure. OAR is concerned with energy conservation and pollution prevention, indoor
and outdoor air quality, industrial air pollution, pollution from vehicles and engines,
radon, acid rain, stratospheric ozone depletion, and radiation protection.
http ://www. epa. gov/air
There are three main offices within OAR that work on air toxics issues - OAQPS, OTAQ,
and ORIA.
i. Office of Air Quality Planning and Standards (OAQPS). OAQPS primary
mission is to preserve and improve air quality in the United States. OAQPS, as part of
this goal, monitors and reports on air quality, air toxics, and emissions. They also
watch for visibility issues, as they relate to the level of air pollution. In addition,
OAQPS is tasked by the EPA with providing technical information for professionals
involved with monitoring and controlling air pollution, creating governmental
policies, rules, and guidance for professionals and government, and educating the
public about air pollution and what can be done to control and prevent it.
http ://www. epa. gov/air/oaqps/index .html
ii. Office of Transportation and Air Quality (OTAQ). OTAQ protects public health
and the environment by controlling air pollution from motor vehicles, engines, and
the fuels used to operate them, and by encouraging travel choices that minimize
emissions. These "mobile sources" include cars and light trucks, large trucks and
buses, nonroad recreational vehicles (such as dirt bikes and snowmobiles), farm and
construction equipment, lawn and garden equipment, marine engines, aircraft, and
locomotives, http://www.epa.gov/otaq/
iii. Office of Radiation and Indoor Air (ORIA). The mission of ORIA is to protect the
public and the environment from the risks of radiation and indoor air pollution. The
April 2004 Page B-l
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programs within EPA and other agencies to control radiation and indoor air pollution
exposures; provides technical assistance to states through EPA's regional offices, and
to other agencies having radiation and indoor air protection programs; directs an
environmental radiation monitoring program; responds to radiological emergencies;
and evaluates and assesses the overall risk and impact of radiation and indoor air
pollution, http://www.epa.gov/air/oria.html
b. Office of Pollution Prevention and Toxics (OPPT). OPPT has the primary
responsibility for administering the Toxic Substances Control Act (TSCA) and the
Pollution Prevention Act of 1990. It also manages the Chemical Right-to-Know
Initiative and the New and Existing Chemicals programs; the Design for the Environment
(DFE), Green Chemistry, and Environmentally Preferable Products (EPP) programs; and
the Lead, Asbestos, and Polychlorinated Biphenyls (PCBs) program.
http ://www. epa. gov/opptintr/.
c. Office of Research and Development (ORD). The U.S. Environmental Protection
Agency (EPA) relies on sound science to safeguard both human health and the
environment. The Office of Research and Development (ORD) is the scientific research
arm of EPA. ORD's leading-edge research helps provide the solid underpinning of
science and technology for the Agency. ORD conducts research on ways to prevent
pollution, protect human health, and reduce risk. The work at ORD laboratories, research
centers, and offices across the country helps improve the quality of air, water, soil, and
the way we use resources. Applied science at ORD builds our understanding of how to
protect and enhance the relationship between humans and the ecosystems of Earth.
www. epa. gov/ord
i. Office of Science Policy (OSP). The OSP integrates and communicates scientific
information generated by or for ORD's laboratories and centers, as well as ORD's
expert advice on the use of scientific information. EPA and the scientific community
at large use this information to ensure that EPA's decisions and environmental
policies are informed by sound science, http://www.epa.gov/osp/
ii. The National Center for Environmental Assessment (NCEA). NCEA is EPA's
national resource center for human health and ecological risk assessment. NCEA
conducts risk assessments, carries out research to improve the state-of-the-science of
risk assessment, and provides guidance and support to risk assessors.
www. epa. gov/ncea
iii National Exposure Research Laboratory (NERL). NERL is comprised of several
divisions with diversified research specialties. NERL conducts research and
development that leads to improved methods, measurements and models to assess and
predict exposures of humans and ecosystems to harmful pollutants and other
conditions in air, water, soil, and food, www.epa.gov/nerl/
iv. National Health and Environmental Effects Research Laboratory (NHEERL).
NHEERL is the Agency's focal point for scientific research on the effects of
contaminants and environmental stressors on human health and ecosystem integrity.
Its research mission and goals help the Agency to identify and understand the
April 2004 Page B-2
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processes that affect our health and environment, and helps the Agency to evaluate
the risks that pollution poses to humans and ecosystems. The impact of NHEERL's
efforts can be felt far beyond the EPA, by enabling state and local governments to
implement effective environmental programs, assisting industry in setting and
achieving environmental goals, and collaborating with international governments and
organizations on issues of environmental importance, http://www.epa. gov/nheerl/
v. National Risk Management Research Laboratory (NRMRL). NRMRL conducts
research into ways to prevent and reduce pollution risks that threaten human health
and the environment. The laboratory investigates methods to prevent and control
pollution of air, land, and water, and to restore ecosystems. The goals of this research
are to develop and promote technologies that protect and improve the environment;
develop scientific and engineering information to support regulatory and policy
decisions; and provide technical support and information transfer to ensure
implementation of environmental regulations and strategies at the national and
community levels. In addition, NRMRL collaborates with both public and private
sector partners to anticipate emerging problems and to foster technologies that reduce
the cost of compliance, http://www.epa.gov/ORD/NRMRL/
2. EPA Headquarters Offices that Work on Specific Air Toxics Risk Issues
a. OAQPS Risk and Exposure Assessment Group (REAG). The REAG maintains the
scientific and analytical expertise necessary to conduct human and ecological air toxics
risk assessments and develop new assessment methodologies, guidelines, and policies for
air toxics risk assessments, risk characteristics, and risk communication. The Group also
serves as a center of air toxics health risk information for Regional, State, and local
agencies, http://www.epa. gov/oar/oaqps/organization/esd/reag.html
b. OAQPS Air Quality Modeling Group (AQMG). The Air Quality Modeling Group is
responsible for providing leadership and direction on the full range of atmospheric
dispersion models and other mathematical simulation techniques used in assessing source
impacts and control strategies. The Group serves as the focal point on modeling
techniques for other EPA headquarters staff, Regional Offices, and State and local
agencies. It coordinates with ORD on the development of new models and techniques, as
well as wider issues of atmospheric research. Finally, the Group conducts modeling
analyses to support policy/regulatory decisions in OAQPS.
http://www.epa.gov/air/oaaps/organization/emad/aqmg.html
c. OAQPS Emission Factors and Inventories Group (EFIG). Emission inventories are
the basis for numerous efforts including trends analysis, regional, and local scale air
quality modeling, regulatory impact assessments, and human exposure modeling. These
inventories are used in analyses by EPA, State and local agencies, as well as the public.
As a central depository for emission facts, inventory data and factor and inventory
development references, the EFIG is responsible for providing technical assistance to
Regional, State, and local clients. Through this working relationship, inventories are
April 2004 Page B-3
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developed to meet the emerging needs of all their users.
http://www.epa.gov/air/oaqps/organization/emad/efig.html
d. OAQPS Monitoring and Quality Assurance Group (MQAG). MQAG is responsible
for identifying ambient monitoring needs based on OAQPS' data requirements, and for
developing the monitoring program and quality assurance infrastructure to support these
requirements with the highest quality ambient air data.
http://www.epa.gov/air/oaqps/organization/emad/mqag.html
OAQPS Policy, Planning, and Standards Group (PPSG). The PPSG, which is in the
Emissions Standards Division of OAQPS, facilitates planning and development of
Division activities and integration of Division programs with other OAQPS and EPA
programs. The group is responsible for developing and implementing national emission
standards, new source performance standards, control techniques guidelines, regulatory
review programs, and other technical documents for specific categories of stationary
sources of hazardous and criteria air pollutants. Finally, the Group performs
comprehensive analyses of hazardous and criteria air pollutant emissions and control
measures for the specified categories of stationary sources. Such analyses typically form
the basis for national emission standards or technical guidance documents.
http://www.epa.gov/oar/oaqps/organization/esd/ppsg.html
OTAQ Air Toxics Center. The Air Toxics Center is OTAQ's resource on mobile
source air toxics and other mobile source-related human health and welfare issues. The
Center provides expertise on mobile source air toxic emissions, exposure and risk to the
Agency. It helps regulators and the public understand the risk from mobile source air
toxics to human health and welfare. It also develops mobile source-related air toxics
regulations, and addresses air toxics impacts of all mobile source control programs. In
addition, it develops information, tools and resources to empower states, communities
and individuals to make and implement their own decisions about air toxics. Finally, the
Center works to influence the toxics research agenda and strategies of parties internal and
external to EPA in order to advance OTAQ's mission, www.epa.gov/otaq/toxics.htm
April 2004 Page B-4
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3. EPA Regional Air Toxics Contacts
Region 1
FUNCTION
Maximum Achievable Control
Technology (MACT)
Toxics Emissions Inventory
Air Deposition
Air Dispersion/ Deposition
Modeling
Monitoring
Community Assessments
Risk Assessment
Mobile Sources
Indoor Air
NAME
Susan Lancey
Bob McConnell
Ian Cohen
Brian Hennessey
Peter Kahn
Marybeth Smuts
Marybeth Smuts
Robert Judge
Eugene Benoit
TELEPHONE
617-918-1656
617-918-1046
617-918-1655
617-918-1654
781-860-4392
617-918-1512
617-918-1512
617-918-1045
617-918-1639
April 2004
Page B-5
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Region 2
FUNCTION
Maximum Achievable Control
Technology (MACT)
Toxics Emissions Inventory
Air Deposition
Air Dispersion/ Deposition
Modeling
Monitoring
Community Assessments
Risk Assessment
Mobile Sources
Indoor Air
NAME
Umesh Dholakia
Raymond Forde
Bob Kelly
Bob Kelly
Mazeeda Khan
Avi Teitz
Carol Bellizzi
Marlon Gonzales
Gina Ferreira
Carol Bellizzi
Reema Persaud
Larainne Koehler
TELEPHONE
212-637-4023
212-637-3716
212-637-3709
212-637-3709
212-637-3715
732-906-6160
212-637-3712
212-637-3769
212-637-3768
212-637-3712
212-637-3760
212-637-4005
April 2004
Page B-6
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Region 3
FUNCTION
Maximum Achievable Control
Technology (MACT)
Air Deposition
Air Dispersion/Deposition
Modeling
Monitoring
Community Assessments
Risk Assessment
Mobile Sources
Indoor Air
NAME
Ray Chalmers
Al Cimorelli
Al Cimorelli
Ted Erdman
Helene Drago
Alvaro Alvarado
Brian Rehn
Fran Dougherty
Cristina Schulingkamp
TELEPHONE
215-814-2061
215-814-2189
215-814-2189
215-814-2766
215-814-5796
215-814-2109
215-814-2176
215-814-2083
215-814-2086
April 2004
Page B-7
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Region 4
FUNCTION
Maximum Achievable Control
Technology (MACT)
Toxics Emissions Inventory
Air Deposition
Air Dispersion/Deposition
Modeling
Monitoring
Community Assessments
Risk Assessment
Mobile Sources
Indoor Air
NAME
Lee Page
Leonardo Ceron
Dr. John Ackermann
Latoya Miller
Stan Krivo
Rick Gillam
Van Shrieves
Danny France
Paul Wagner
Dr. Kenneth Mitchell (human
health/ecological)
Dr. Solomon Pollard (human health)
Ofia Hodoh (human health)
Dr. John Ackermann (ecological)
Latoya Miller (ecological)
Dale Aspy
Henry Slack
TELEPHONE
404-562-9131
404-562-9129
404-562-9063
404-562-9885
404-562-9123
404-562-9049
404-562-9089
706-355-8738
404-562-9100
404-562-9065
404-562-9180
404-562-9176
404-562-9063
404-562-9885
404-562-9041
404-562-9143
April 2004
Page B-8
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Region 5
FUNCTION
Maximum Achievable Control
Technology (MACT)
Toxics Emissions Inventory
Air Deposition
Air Dispersion/ Deposition
Modeling
Monitoring
Community Assessments
Risk Assessment
Mobile Sources
Indoor Air
NAME
Bruce Varner
Suzanne King
Erin Newman
Randy Robinson
Phuong Nguyen
Motria Caudill
Jackie Nwia
Michele Palmer
George Bollweg
Margaret Sieffert
Jaime Julian
Suzanne King
Jack Barnette
Sheila Batka
TELEPHONE
312-886-6793
312-886-6054
312-886-4587
312-353-6713
312-886-6701
312-886-0267
312-886-6081
312-886-0387
312-353-5598
312-353-1151
312-886-9402
312-886-6054
312-886-6175
312-886-6053
April 2004
Page B-9
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Region 6
FUNCTION
Maximum Achievable Control
Technology (MACT)
Toxics Emissions Inventory
Air Deposition
Air Dispersion/ Deposition
Modeling
Monitoring
Community Assessments
Risk Assessment
Mobile Sources
Indoor Air
NAME
Jeff Robinson
Herb Sherrow
Phil Crocker
Quang Nguyen
Kuenja Chung
Ruben Casso
JeffYurk
Sandra Rennie
Mike Miller
TELEPHONE
214-665-6435
214-665-7237
214-665-7373
214-665-7238
214-665-8345
214-665-6763
214-665-8309
214-665-7367
214-665-7550
April 2004
Page B-10
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Region 7
FUNCTION
Maximum Achievable Control
Technology (MACT)
Toxics Emissions Inventory
Air Deposition
Air Dispersion/ Deposition
Modeling
Monitoring
Community Assessments
Risk Assessment
Mobile Sources
Indoor Air
NAME
Richard Tripp
Michael Jay
Michael Jay
Richard Daye
Michael Davis
Marcus Rivas
James Hirtz
James Hirtz
Robert Dye
TELEPHONE
913-551-7566
913-551-7460
913-551-7460
913-551-7619
913-551-7096
913-551-7669
913-551-7472
913-551-7472
913-551-7605
April 2004
Page B-11
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Region 8
FUNCTION
Maximum Achievable Control
Technology (MACT)
Toxics Emissions Inventory
Air Deposition
Air Dispersion/ Deposition
Modeling
Monitoring
Community Assessments
Risk Assessment
Mobile Sources
Indoor Air
NAME
Deldi Reyes
Daniel Webster
Anne-Marie Patrie
Victoria Parker-Christensen
Michael Copeland
Victoria Parker-Christensen
Anne-Marie Patrie
Victoria Parker-Christensen
Anne-Marie Patrie
Jeff Kimes
Ron Schiller
TELEPHONE
303-312-6055
303-312-6446
303-312-6524
303-312-6441
303-312-6010
303-312-6441
303-312-6524
303-312-6441
303-312-6524
303-312-6445
303-312-6017
April 2004
Page B-12
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Region 9
FUNCTION
Maximum Achievable Control
Technology (MACT)
Toxics Emissions Inventory
Air Deposition
Air Dispersion/ Deposition
Modeling
Monitoring
Community Assessments
Risk Assessment
Indoor Air
Mobile Sources
NAME
Mae Wang
John Brock
Larry Biland
Pam Tsai
Barbara Toole-O'Neil
Carol Bohnenkamp
Scott Bohning
Catherine Brown
Mike Bandrowski
Pam Tsai
Arnold Den
Barbara Spark
Sylvia Dugre
David Jesson
TELEPHONE
415-947-4124
415.947.3999
415-947-4132
415-947-4196
415-972-3991
415-947-4130
415-947-4127
415-947-4137
415-947-4194
415-947-4196
415-947-4191
415-947-4189
415-947-4149
415-947-4150
April 2004
Page B-13
-------
Region 10
FUNCTION
Maximum Achievable Control
Technology (MACT)
Toxics Emissions Inventory
Air Deposition
Air Dispersion/ Deposition
Modeling
Monitoring
Community Assessments
Risk Assessment
Mobile Sources
Indoor Air
NAME
Lucita Valiere
Madonna Narvaez
Madonna Narvaez
Mahbubul Islam
Keith Rose
Peter Murchie
Lisa McArthur
Julie Wroble
Wayne Elson
Ann Wawrukiewicz
TELEPHONE
206-553-8087
206-553-2117
206-553-2117
206-553-6985
206-553-1949
503-326-6554
206-553-1814
206-553-1079
206-553-1463
206-553-2589
April 2004
Page B-14
-------
4. Other Federal Agencies
a. Agency for Toxics Substances and Disease Registry (ATSDR). The mission of the
Agency for Toxic Substances and Disease Registry (ATSDR), as an agency of the U.S.
Department of Health and Human Services, is to serve the public by using the best
science, taking responsive public health actions, and providing trusted health information
to prevent harmful exposures and disease related to toxic substances. ATSDR is directed
by congressional mandate to perform specific functions concerning the effect on public
health of hazardous substances in the environment. These functions include public health
assessments of waste sites, health consultations concerning specific hazardous
substances, health surveillance and registries, response to emergency releases of
hazardous substances, applied research in support of public health assessments,
information development and dissemination, and education and training concerning
hazardous substances, http://www.atsdr.cdc.gov/about.html
b. National Center for Environmental Health (NCEH). CDC's National Center for
Environmental Health (NCEH) strives to promote health and quality of life by preventing
or controlling those diseases or deaths that result from interactions between people and
their environment, http ://www.cdc. gov/nceh/
c. National Cancer Institute (NCI). The NCI is a component of the National Institutes of
Health (NIH), one of eight agencies that compose the Public Health Service (PHS) in the
Department of Health and Human Services (DHHS). The NCI, established under the
National Cancer Act of 1937, is the Federal Government's principal agency for cancer
research and training. The National Cancer Act of 1971 broadened the scope and
responsibilities of the NCI and created the National Cancer Program. Over the years,
legislative amendments have maintained the NCI authorities and responsibilities and
added new information dissemination mandates as well as a requirement to assess the
incorporation of state-of-the-art cancer treatments into clinical practice. The National
Cancer Institute coordinates the National Cancer Program, which conducts and supports
research, training, health information dissemination, and other programs with respect to
the cause, diagnosis, prevention, and treatment of cancer, rehabilitation from cancer, and
the continuing care of cancer patients and the families of cancer patients.
www. cancer, gov
d. National Library of Medicine (NLM). The National Library of Medicine (NLM), on
the campus of the National Institutes of Health in Bethesda, Maryland, is the world's
largest medical library. The Library collects materials in all areas of biomedicine and
health care, as well as works on biomedical aspects of technology, the humanities, and
the physical, life, and social sciences. The collections stand at more than 6 million items-
-books, journals, technical reports, manuscripts, microfilms, photographs and images.
Housed within the Library is one of the world's finest medical history collections of old
and rare medical works. The Library's collection may be consulted in the reading room
or requested on interlibrary loan. NLM is a national resource for all U.S. health science
libraries through a National Network of Libraries of Medicine®.
http://www.nlm.nih.gov/nlmhome.html
April 2004 Page B-15
-------
National Institute of Environmental Health Sciences (NIEHS). Human health and
human disease result from three interactive elements: environmental factors, individual
susceptibility and age. The mission of the National Institute of Environmental Health
Sciences (NIEHS) is to reduce the burden of human illness and dysfunction from
environmental causes by understanding each of these elements and how they interrelate.
The NIEHS achieves its mission through multidisciplinary biomedical research programs,
prevention and intervention efforts, and communication strategies that encompass
training, education, technology transfer, and community outreach.
http://www.niehs.nih.gov/external/welcome.htm
April 2004 Page B-16
-------
Appendix C Recommended Dose-Response Values
for HAPs
This appendix presents tabulated dose-response assessments that the Office of Air Quality
Planning and Standards (OAQPS) uses for risk assessments of hazardous air pollutants. A
description of the derivation of these values, along with any updates can be found at the
following website: http://www.epa.gov/ttn/atw/toxsource/summary.html.
-------
Table 1. Prioritized Dose-Response Values (10/28/03)
CHEMICAL NAME
Acetaldehyde
Acetamide
Acetonitrile
Acetophenone
Acrolein
Acrylamide
Acrylic acid
Acrylonitrile
Allyl chloride
Aniline
Antimony compounds
Antimony pentoxide
Antimony potassium tartrate
Antimony tetroxide
Antimony trioxide
Arsenic compounds
Arsine
Benzene
Benzidine
Benzotrichloride
Benzyl chloride
Beryllium compounds
Biphenyl
Bis(2-ethylhexyl)phthalate
Bis(chloromethyl)ether
Bromoform
1,3-Butadiene
Cadmium compounds
Captan
Carbaryl
Carbon disulfide
Carbon tetrachloride
Chloramben
Chlordane
Chlorine
Chloroacetic acid
2-Chloroacetophenone
Chlorobenzene
Chlorobenzilate
Chloroform
Chloroprene
Chromium (III) compounds
Chromium (VI) compounds
CAS NO.1
75-07-0
60-35-5
75-05-8
98-86-2
1 07-02-8
79-06-1
79-10-7
107-13-1
107-05-1
62-53-3
7440-36-0
1314-60-9
304-61-0
1332-81-6
1309-64-4
7440-38-2
7784-42-1
71-43-2
92-87-5
98-07-7
1 00-44-7
7440-41-7
92-52-4
117-81-7
542-88-1
75-25-2
1 06-99-0
7440-43-9
1 33-06-2
63-25-2
75-15-0
56-23-5
1 33-90-4
57-74-9
7782-50-5
79-11-8
532-27-4
1 08-90-7
510-15-6
67-66-3
126-99-8
16065-83-1
18540-29-9
MAP
NO.2
1
2
3
4
6
7
8
9
10
12
173
173
173
173
173
174
174
15
16
17
18
175
19
20
21
22
23
176
26
27
28
29
32
33
34
35
36
37
38
39
41
177
177
WOE3 for
Cancer
EPA
B2
D
D
B2
B1
C
B2
A
A
A
B2
B2
B1
D
B2
A
B2
A
B1
B2
B2
B2
D
B2
B2
D
A
IARC
2B
2B
3
2A
2A
3
3
2B
1
1
2B
2B
1
2B
1
3
2A
1
3
2B
2B
2B
1
CHRONIC INHALATION
NONCANCER CANCER
mg/m3
0.009
0.06
0.00002
0.0007
0.001
0.002
0.001
0.001
0.0002
0.00003
0.00005
0.03
0.01
0.00002
0.01
0.002
0.00002
0.7
0.04
0.0007
0.0002
0.00003
1
0.098
0.007
0.0001
SOURCE
IRIS
IRIS
IRIS
P-CAL
IRIS
IRIS
IRIS
IRIS
IRIS
CAL
IRIS
IRIS
P-CAL
IRIS
CAL
IRIS
CAL
IRIS
CAL
IRIS
CAL
IRIS
CAL
ATSDR
HEAST
IRIS
1/(ug/m3)
2.2E-06
2.0E-05
1 .3E-03
6.8E-05
6.0E-06
1 .6E-06
4.3E-03
7.8E-06
6.7E-02
3.7E-03
4.9E-05
2.4E-03
2.4E-06
6.2E-02
1.1E-06
3.0E-05
1 .8E-03
1 .OE-06
1 .5E-05
1 .OE-04
7.8E-05
1 .2E-02
SOURCE
IRIS
CAL
IRIS
IRIS
CAL
CAL
IRIS
IRIS
IRIS
Conv. Oral
CAL
IRIS
CAL
IRIS
IRIS
IRIS
IRIS
Conv. Oral
IRIS
IRIS
HEAST
IRIS
CHRONIC ORAL
NONCANCER CANCER
mg/kg/d
0.0005
0.0005
SOURCE
IRIS
IRIS
1/(ma/ka/d> SOURCE
3.5E-01 IRIS
April 2004
Page C-1
-------
Table 1. Prioritized Dose-Response Values (10/28/03)
CHEMICAL NAME CAS NO.1
Chromium (VI) trioxide, chromic acid mist 1111 5-74-5
Cobalt compounds 7440-48-4
Coke Oven Emissions 8007-45-2
m-Cresol 1 08-39-4
o-Cresol 95-48-7
p-Cresol 1 06-44-5
Cresols (mixed) 1319-77-3
Cumene 98-82-8
Cyanazine 21725-46-2
Cyanide compounds 57-12-5
Acetone cyanohydrin 75-86-5
Calcium cyanide 592-01-8
Copper cyanide 544-92-3
Cyanogen 460-19-5
Cyanogen bromide 506-68-3
Cyanogen chloride 506-77-4
Ethylene cyanohydrin 109-78-4
Hydrogen cyanide 74-90-8
Potassium cyanide 151-50-8
Potassium silver cyanide 506-61-6
Silver cyanide 506-64-9
Sodium cyanide 143-33-9
Thiocyanic acid, 2-(benzothiazolylthio) methyl est 21564-17-0
Zinc cyanide 557-21-1
2,4-D, salts and esters 94-75-7
DDE 72-55-9
1 ,2-Dibromo-3-chloropropane 96-1 2-8
Dibutylphthalate 84-74-2
p-Dichlorobenzene 106-46-7
3,3'-Dichlorobenzidine 91-94-1
Dichloroethyl ether 111-44-4
1,3-dichloropropene 542-75-6
Dichlorvos 62-73-7
Diesel engine emissions DIESEL EMIS.
Diethanolamine 111-42-2
3,3'-Dimethoxybenzidine 119-90-4
p-Dimethylaminoazobenzene 60-1 1-7
3,3'-Dimethylbenzidine 119-93-7
Dimethyl formamide 68-12-2
N,N-dimethylaniline 121-69-7
1,1-Dimethylhydrazine 57-14-7
2,4-dinitrophenol 51-28-5
2,4-Dinitrotoluene 121-14-2
MAP
NO.2
177
178
179
44
43
45
42
46
180
180
180
180
180
180
180
180
180
180
180
180
180
180
180
180
47
48
51
52
53
54
55
56
57
190
58
61
62
63
65
59
66
70
71
WOE3 for
Cdnc6r
EPA IARC
A 1
A
C
C
C
C
D
C
D
B2
B2
D
C 2B
B2 2B
B2
B2 2B
B2 2B
B1
B2 2B
2B
B2
2B
3
B2 2B
B2 2B
CHRONIC INHALATION
NONCANCER CANCER
mg/m3 SOURCE
0.000008 IRIS
0.0001 ATSDR
0.6 CAL
0.4 IRIS
0.01 HEAST
0.003 IRIS
0.0002 IRIS
0.8 IRIS
0.02 IRIS
0.0005 IRIS
0.005 IRIS
0.003 CAL
0.03 IRIS
0.007 P-CAL
1/(ug/m3) SOURCE
6.2E-04 IRIS
2.4E-04 Conv. Oral
9.7E-05 Conv. Oral
2.0E-03 CAL
1.1E-05 CAL
3.4E-04 CAL
3.3E-04 IRIS
4.0E-06 IRIS
8.3E-05 Conv. Oral
4.0E-06 Conv. Oral
1 .3E-03 CAL
2.6E-03 Conv. Oral
8.9E-05 CAL
CHRONIC ORAL
NONCANCER CANCER
mg/kg/d SOURCE
1/(mg/kg/d) SOURCE
3.4E-01 IRIS
April 2004
Page C-2
-------
Table 1. Prioritized Dose-Response Values (10/28/03)
CHEMICAL NAME
2,4/2,6-Dinitrotoluene (mixture)
1,4-Dioxane
1 ,2-Diphenylhydrazine
Epichlorohydrin
1,2-Epoxybutane
Ethyl aery I ate
Ethyl benzene
Ethyl carbamate
Ethyl chloride
Ethylene dibromide
Ethylene dichloride
Ethylene glycol
Ethylene oxide
Ethylene thiourea
Ethylidene dichloride
Formaldehyde
Diethylene glycol monobutyl ether
Diethylene glycol monoethyl ether
Ethylene glycol butyl ether
Ethylene glycol ethyl ether
Ethylene glycol ethyl ether acetate
Ethylene glycol methyl ether
Ethylene glycol methyl ether acetate
Heptachlor
Hexachlorobenzene
Hexachlorobutadiene
Hexachlorocyclopentadiene
Hexachlorodibenzo-p-dioxin, mixture
Hexachloroethane
Hexamethylene-1 ,6-diisocyanate
n-Hexane
Hydrazine
Hydrochloric acid
Hydrofluoric acid
Hydroquinone
Isophorone
Lead compounds
Tetraethyl lead
Lindane (gamma-HCH)
alpha-Hexachlorocyclohexane (a-HCH)
beta-Hexachlorocyclohexane (b-HCH)
technical Hexachlorocyclohexane (HCH)
Maleic anhydride
CAS NO.1
25321-14-6
123-91-1
122-66-7
1 06-89-8
1 06-88-7
140-88-5
100-41-4
51-79-6
75-00-3
1 06-93-4
1 07-06-2
107-21-1
75-21-8
96-45-7
75-34-3
50-00-0
112-34-5
111-90-0
111-76-2
110-80-5
111-15-9
109-86-4
1 1 0-49-6
76-44-8
118-74-1
87-68-3
77-47-4
19408-74-3
67-72-1
822-06-0
1 1 0-54-3
302-01-2
7647-01-0
7664-39-3
123-31-9
78-59-1
7439-92-1
78-00-2
58-89-9
319-84-6
319-85-7
608-73-1
108-31-6
MAP
NO.2
71
72
73
74
75
76
77
78
79
80
81
82
84
85
86
87
181
181
181
181
181
181
181
88
89
90
91
187
92
93
95
96
97
98
99
100
182
182
101
101
101
101
102
WOE3 for
Cancer
EPA
B2
B2
B2
B2
B2
D
B2
B2
B1
B2
C
B1
C
B2
B2
C
E
B2
C
B2
C
B2
B2
C
B2
IARC
2B
2B
2A
2B
2B
2A
2B
1
2B
2A
2B
2B
3
3
2B
2B
2B
2B
2B
2B
CHRONIC INHALATION
NONCANCER CANCER
mg/m3
3
0.001
0.02
1
10
0.0008
2.4
0.4
0.03
0.003
0.5
0.0098
0.02
13
0.2
0.3
0.02
0.09
0.003
0.09
0.0002
0.08
0.00001
0.2
0.0002
0.02
0.03
2
0.0015
0.0003
0.02
0.002
0.0007
SOURCE
CAL
IRIS
IRIS
IRIS
IRIS
CAL
ATSDR
CAL
CAL
P-CAL
HEAST
ATSDR
HEAST
IRIS
IRIS
CAL
IRIS
CAL
P-CAL
P-CAL
IRIS
P-CAL
IRIS
IRIS
CAL
IRIS
CAL
CAL
EPA OAQPS
P-CAL
P-CAL
P-CAL
CAL
1/(ug/m3)
1 .9E-04
3.1E-06
2.2E-04
1 .2E-06
1 .4E-05
2.9E-04
2.2E-04
2.6E-05
8.8E-05
1 .3E-05
1 .6E-06
5.5E-09
1 .3E-03
4.6E-04
2.2E-05
1.3E+00
4.0E-06
4.9E-03
2.7E-07
3.1E-04
1 .8E-03
5.3E-04
5.1E-04
SOURCE
Conv. Oral
Conv. Oral
IRIS
IRIS
Conv. Oral
CAL
IRIS
IRIS
CAL
CAL
CAL
EPA OAQPS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
Conv. Oral
CAL
IRIS
IRIS
IRIS
CHRONIC ORAL
NONCANCER CANCER
mg/kg/d
SOURCE
0.0005
0.0008
0.0000001
0.0003
0.008
IRIS
IRIS
IRIS
IRIS
ATSDR
1/(mg/kg/d) SOURCE
4.5E+00 IRIS
1.6E+00 IRIS
6.2E+03 IRIS
1.1E+00 CAL
6.3E+00 IRIS
1.8E+00 IRIS
1.8E+00 IRIS
April 2004
Page C-3
-------
Table 1. Prioritized Dose-Response Values (10/28/03)
CHEMICAL NAME
Manganese compounds
Mercuric chloride
Mercury (elemental)
Methyl mercury
Phenylmercuric acetate
Methanol
Methoxychlor
Methyl bromide
Methyl chloride
Methyl ethyl ketone
Methyl isobutyl ketone
Methyl isocyanate
Methyl methacrylate
Methyl tert-butyl ether
4,4'-Methylene bis(2-chloroaniline)
Methylene chloride
Methylene diphenyl diisocyanate
4,4'-Methylenedianiline
Naphthalene
Nickel compounds
Nickel oxide
Nickel refinery dust
Nickel subsulfide
Nitrobenzene
2-Nitropropane
Nitrosodimethylamine
N-Nitrosomorpholine
Parathion
Polychlorinated biphenyls
Aroclor 1016
Aroclor 1254
Pentachloronitrobenzene
Pentachlorophenol
Phenol
p-Phenylenediamine
Phosgene
Phosphine
Phosphorus, white
Phthalic anhydride
Polybrominated Diphenyl Ethers
Acenaphthene
Acenaphthylene
Anthracene
CAS NO.1
7439-96-5
7487-94-7
7439-97-6
22967-92-6
62-38-4
67-56-1
72-43-5
74-83-9
74-87-3
78-93-3
108-10-1
624-83-9
80-62-6
1634-04-4
101-14-4
75-09-2
101-68-8
101-77-9
91-20-3
7440-02-0
1313-99-1
NI_DUST
12035-72-2
98-95-3
79-46-9
62-75-9
59-89-2
56-38-2
1336-36-3
12674-11-2
11097-69-1
82-68-8
87-86-5
1 08-95-2
1 06-50-3
75-44-5
7803-51-2
7723-14-0
85-44-9
PBDE
83-32-9
206-96-8
120-12-7
MAP
NO.2
183
184
184
184
184
103
104
105
106
108
111
112
113
114
115
116
117
118
119
186
186
186
186
120
123
125
126
127
136
136
136
128
129
130
131
132
133
134
135
187
187
187
187
WOE3 for
Cancer
EPA
D
C
D
C
D
D
D
E
B2
B2
D
C
A
A
A
D
B2
B2
C
B2
C
B2
D
D
D
D
D
D
IARC
3
2A
2B
2B
2B
2B
2B
2A
2B
3
2A
3
2B
3
3
CHRONIC INHALATION
NONCANCER CANCER
mg/m3
0.00005
0.00009
0.0003
4
0.005
0.09
5
3
0.001
0.7
3
1
0.0006
0.02
0.003
0.0002
0.0001
0.03
0.02
0.1
0.2
0.0003
0.0003
0.00007
0.02
SOURCE
IRIS
CAL
IRIS
CAL
IRIS
IRIS
IRIS
IRIS
CAL
IRIS
IRIS
ATSDR
IRIS
CAL
IRIS
ATSDR
CAL
P-CAL
IRIS
P-CAL
CAL
P-CAL
IRIS
P-CAL
CAL
1/(ug/m3) SOURCE
4.3E-04 CAL
4.7E-07 IRIS
4.6E-04 CAL
2.4E-04 IRIS
4.8E-04 IRIS
5.6E-06 EPA OAQPS
1 .4E-02 IRIS
1 .9E-03 CAL
1.0E-04 IRIS
7.4E-05 Conv. Oral
5.1E-06 CAL
CHRONIC ORAL
NONCANCER CANCER
mg/kg/d SOURCE
0.0003 IRIS
0.0001 IRIS
0.00008 IRIS
0.005 IRIS
0.00007 IRIS
0.00002 IRIS
0.007 ATSDR
0.06 IRIS
0.3 IRIS
1/(mg/kg/d) SOURCE
2.0E+00 IRIS
April 2004
Page C-4
-------
Table 1. Prioritized Dose-Response Values (10/28/03)
CHEMICAL NAME
Benzo(a)anthracene
Benzo(b)fluoranthene
Benzo[j]fluoranthene
Benzo(k)fluoranthene
Benzo(g,h,i)perylene
Benzo(a)pyrene
Benzo(e)pyrene
Carbazole
beta-Chloronaphthalene
Chrysene
Dibenz[a,h]acridine
Dibenz[aj]acridine
Dibenz(a,h)anthracene
7H-Dibenzo[c,g]carbazole
Dibenzo[a,e]pyrene
Dibenzo[a,h]pyrene
Dibenzo[a,i]pyrene
Dibenzo[a,l]pyrene
7, 1 2-Dimethylbenz(a)anthracene
1,6-Dinitropyrene
1,8-Dinitropyrene
Fluoranthene
Fluorene
lndeno(1 ,2,3-cd)pyrene
3-Methylcholanthrene
5-Methylchrysene
1-Methylnaphthalene
5-Nitroacenaphthene
6-Nitrochrysene
2-Nitrofluorene
1-Nitropyrene
4-Nitropyrene
Phenanthrene
Pyrene
1,3-Propane sultone
Propoxur
Propylene dichloride
Propylene oxide
Quinoline
Selenium compounds
Hydrogen selenide
Selenious acid
Selenourea
CAS NO.1
56-55-3
205-99-2
205-82-3
207-08-9
191-24-2
50-32-8
1 92-97-2
86-74-8
91-58-7
218-01-9
226-36-8
224-42-0
53-70-3
1 94-59-2
1 92-65-4
1 89-64-0
1 89-55-9
191-30-0
57-97-6
42397-64-8
42397-65-9
206-44-0
86-73-7
1 93-39-5
56-49-5
3697-24-3
90-12-0
602-87-9
7496-02-8
607-57-8
5522-43-0
57835-92-4
85-01-8
129-00-0
1120-71-4
114-26-1
78-87-5
75-56-9
91-22-5
7782-49-2
7783-07-5
7783-00-8
630-10-4
MAP
NO.2
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
187
137
140
141
142
144
189
189
189
189
WOE3 for
Cancer
EPA
B2
B2
B2
D
B2
B2
B2
B2
D
D
B2
D
D
B2
B2
B2
B2
D
D
IARC
2A
2B
2B
2B
3
2A
3
3
3
2B
2B
2A
2B
2B
2B
2B
2B
2B
2B
3
3
2B
2B
2B
2B
2B
2B
2B
2B
2B
CHRONIC INHALATION
NONCANCER CANCER
mg/m3
SOURCE
0.004
0.03
0.02
0.00008
IRIS
IRIS
CAL
CAL
1/(ug/m3)
1.1E-04
1.1E-04
1.1E-04
1.1E-04
1.1E-03
5.7E-06
1.1E-05
1.1E-04
1.1E-04
1 .2E-03
1.1E-03
1.1E-03
1.1E-02
1.1E-02
1.1E-02
7.1E-02
1.1E-02
1.1E-03
1.1E-04
6.3E-03
1.1E-03
3.7E-05
1.1E-02
1.1E-05
1.1E-04
1.1E-04
6.9E-04
1 .9E-05
3.7E-06
SOURCE
CAL
CAL
CAL
CAL
CAL
Conv. Oral
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
Conv. Oral
IRIS
CHRONIC ORAL
NONCANCER CANCER
mg/kg/d
0.08
0.04
0.04
0.07
0.03
SOURCE
IRIS
IRIS
IRIS
ATSDR
IRIS
1/(mg/kg/d)
1.2E+00
1.2E+00
1.2E+00
1.2E+00
7.3E+00
2.0E-02
1.2E-01
1.2E+00
1.2E+00
4.1E+00
1.2E+01
1.2E+01
1.2E+02
1.2E+02
1.2E+02
2.5E+02
1.2E+02
1.2E+01
1.2E+00
2.2E+01
1.2E+01
1.3E-01
1.2E+02
1.2E-01
1.2E+00
1.2E+00
SOURCE
CAL
CAL
CAL
CAL
IRIS
HEAST
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
CAL
April 2004
Page C-5
-------
Table 1. Prioritized Dose-Response Values (10/28/03)
CHEMICAL NAME CAS NO.1
Styrene 100-42-5
Styrene oxide 96-09-3
2,3,7,8-Tetrachlorodibenzo-p-dioxin 1746-01-6
1,1,2,2-Tetrachloroethane 79-34-5
Tetrachloroethene 127-18-4
Titanium tetrachloride 7550-45-0
Toluene 108-88-3
2,4-Toluene diamine 95-80-7
2,4/2,6-Toluene diisocyanate mixture (TDI) 26471-62-5
o-Toluidine 95-53-4
Toxaphene 8001-35-2
1,2,4-Trichlorobenzene 120-82-1
1,1,2-Trichloroethane 79-00-5
1,1,1-Trichloroethane 71-55-6
Trichloroethylene 79-01-6
2,4,5-Trichlorophenol 95-95-4
2,4,6-Trichlorophenol 88-06-2
Triethylamine 121-44-8
Trifluralin 1582-09-8
Uranium compounds 7440-61-1
Uranium, soluble salts URANSOLS
Vinyl acetate 1 08-05-4
Vinyl bromide 593-60-2
Vinyl chloride 75-01-4
Vinylidene chloride 75-35-4
m-Xylene 1 08-38-3
o-Xylene 95-47-6
Xylenes (mixed) 1330-20-7
HAP
NO.2
146
147
148
149
150
151
152
153
154
155
156
157
158
107
159
160
161
162
163
188
188
165
166
167
168
171
170
169
WOE3 for
C3P
EPA
B2
C
B2-C
D
B2
B2
B2
D
C
D
B2-C
B2
C
B2
A
C
1 Chemical Abstracts Services number for the compound.
2Position of the compound on the HAP list in the Clean Air Act (1 1 2[b][2])
IUCI
IARC
2B
2A
3
2A
3
2B
2B
2B
3
2A
3
2B
2A
1
CHRONIC INHALATION
NONCANCER CANCER
mg/m3 SOURCE
1 IRIS
0.006 P-CAL
4E-08 CAL
0.27 ATSDR
0.0001 ATSDR
0.4 IRIS
0.00007 IRIS
0.2 HEAST
0.4 P-CAL
1 CAL
0.6 CAL
0.007 IRIS
0.0003 ATSDR
0.2 IRIS
0.003 IRIS
0.1 IRIS
0.2 IRIS
0.1 IRIS
1/(ug/m3) SOURCE
3.3E+01 EPA ORD
5.8E-05 IRIS
5.9E-06 CAL
1.1E-03 CAL
1.1E-05 CAL
5.1E-05 CAL
3.2E-04 IRIS
1.6E-05 IRIS
2.0E-06 CAL
3.1E-06 IRIS
2.2E-06 Conv. Oral
3.2E-05 HEAST
8.8E-06 IRIS
CHRONIC ORAL
NONCANCER CANCER
mg/kg/d SOURCE
1 E-09 ATSDR
0.0075 IRIS
1/(mg/kg/d) SOURCE
1 .5E+05 EPA ORD
1.1E+00 IRIS
7.7E-03 IRIS
3Weight-of-evidence. See http://www.epa/iris/carcino.htm, http://193.51.164.11/monoeval/grlist.html.
April 2004
Page C-6
-------
Table 2. Acute Dose-Response Values (10/22/03)
CHEMICAL NAME
Acetaldehyde
Acetonitrile
Acrolein
Acrylamide
Acrylic acid
Acrylonitrile
Allyl chloride
Aniline
Anisidine
Antimony compounds
Arsenic compounds
Arsine
Benzene
Benzyl chloride
Beryllium compounds
Bis(chloromethyl)ether
Bromoform
1 ,3-Butadiene
Cadmium compounds
Carbaryl
Carbon disulfide
Carbon tetrachloride
Chlordane
Chlorine
Chloroacetic acid
Chlorobenzene
Chloroform
Chloromethyl methyl ether
Chloroprene
Chromium (VI) compounds
Chromium (VI) trioxide, chromic acid mist
Cobalt compounds
m-Cresol
o-Cresol
p-Cresol
Cresols (mixed)
Cumene
Cyanide compounds
Acetone cyanohydrin
Cyanogen chloride
Hydrogen cyanide
2,4-D, salts and esters
CAS NO.
75-07-0
75-05-8
1 07-02-8
79-06-1
79-1 0-7
1 07-1 3-1
1 07-05-1
62-53-3
90-04-0
7440-36-0
7440-38-2
7784-42-1
71-43-2
1 00-44-7
7440-41-7
542-88-1
75-25-2
1 06-99-0
7440-43-9
63-25-2
75-15-0
56-23-5
57-74-9
7782-50-5
79-1 1 -8
1 08-90-7
67-66-3
1 07-30-2
1 26-99-8
1 8540-29-9
11115-74-5
7440-48-4
1 08-39-4
95-48-7
1 06-44-5
1319-77-3
98-82-8
57-12-5
75-86-5
506-77-4
74-90-8
94-75-7
HAP NO.
1
3
6
7
8
9
10
12
13
173
174
174
15
18
175
21
22
23
176
27
28
29
33
34
35
37
39
40
41
177
177
178
44
43
45
42
46
180
180
180
180
47
AEGL-1 AEGL-2 AEGL-3
mg/m3
0.069 p
2.9'
30 f
12P
75 '
1.51
2.9 p
2.2'
mg/m3
0.23 p
140 !
46 f
0.54 f
2600 p
500 p
350 '
5.8'
26 p
430 p
0.2 !
19P
7.8 f
mg/m3
3.2 p
530 !
57 f
1.6'
13000P
1500P
11001
58 ''
8300 p
3.1 '
52 p
17f
ERPG-1 ERPG-2 ERPG-3
mg/m3
18
0.23
5.9
22
9.4
160
5.2
22
3.1
130
2.9
mg/m3
360
1.1
150
77
130
1.6
480
52
0.025
0.47
440
160
630
8.7
240
3.3
1
11
mg/m3
1800
6.9
2200
170
940
4.8
3200
130
0.1
2.4
11000
1600
4700
58
24000
33
10
28
IDLH/10
mg/m3
360
84
0.46
6
19
78
38
5
5
0.5
0.96
160
52
0.4
880
440
9
10
160
130
10
2.9
460
240
110
1.5
1.5
2
110
110
110
110
440
2.5
5.5
10
MRL
mg/m3
0.00011
0.22
0.16
1.3
0.49
REL
mg/m3
0.00019
6
0.00019
0.16
1.3
0.24
6.2
1.9
0.21
0.15
0.34
April 2004
Page C-7
-------
Table 2. Acute Dose-Response Values (10/22/03)
CHEMICAL NAME
Dibutylphthalate
p-Dichlorobenzene
Dichloroethyl ether
Dichlorvos
Dimethyl formamide
Dimethyl phthalate
Dimethyl sulfate
N,N-dimethylaniline
1,1-Dimethylhydrazine
4,6-Dinitro-o-cresol
2,4-Dinitrotoluene
1 ,4-Dioxane
Epichlorohydrin
Ethyl acrylate
Ethyl benzene
Ethyl chloride
Ethylene dibromide
Ethylene dichloride
Ethylene glycol
Ethylene imine (aziridine)
Ethylene oxide
Ethylidene dichloride
Formaldehyde
Ethylene glycol butyl ether
Ethylene glycol ethyl ether
Ethylene glycol ethyl ether acetate
Ethylene glycol methyl ether
Heptachlor
Hexachlorobutadiene
Hexachloroethane
n-Hexane
Hydrazine
Hydrochloric acid
Hydrofluoric acid
Hydroquinone
Lead compounds
Tetraethyl lead
Tetramethyl lead
Lindane (gamma-HCH)
Maleic anhydride
Manganese compounds
Mercury (elemental)
CAS NO.
84-74-2
1 06-46-7
111-44-4
62-73-7
68-12-2
131-11-3
77-78-1
121-69-7
57-14-7
534-52-1
121-14-2
123-91-1
1 06-89-8
1 40-88-5
100-41-4
75-00-3
1 06-93-4
1 07-06-2
107-21-1
151-56-4
75-21 -8
75-34-3
50-00-0
111-76-2
110-80-5
111-15-9
1 09-86-4
76-44-8
87-68-3
67-72-1
110-54-3
302-01-2
7647-01-0
7664-39-3
123-31-9
7439-92-1
78-00-2
75-74-1
58-89-9
108-31-6
7439-96-5
7439-97-6
HAP NO.
52
53
55
57
65
67
68
59
66
69
71
72
74
76
77
79
80
81
82
83
84
86
87
181
181
181
181
88
90
92
95
96
97
98
99
182
182
182
101
102
183
184
AEGL-1 AEGL-2 AEGL-3
mg/m3
61 p
19P
0.49 p
0.131
2.7 '
0.82 '
mg/m3
270 p
7.4f
1200P
91 p
8.1 ''
81 '
17P
171
33 '
20'
mg/m3
540 p
27 f
2700 p
270 p
171
360 '
61 p
46 ''
150 '
36 '
ERPG-1 ERPG-2 ERPG-3
mg/m3
6
7.6
0.041
200
1.2
32
0.65
4.5
1.6
mg/m3
300
76
120
810
90
12
110
6.5
30
16
1.6
mg/m3
600
380
1200
810
900
31
320
39
220
41
16
IDLH/10
mg/m3
400
90
58
10
150
200
3.6
50
3.7
0.5
5
180
28
1400
350
1000
77
20
140
1200
2.5
340
180
3.5
390
6.5
7.5
2.5
5
10
4
4
5
1
50
MRL
mg/m3
4.8
0.018
40
1.3
0.049
29
58
0.025
REL
mg/m3
3
1.3
0.094
14
0.37
0.14
0.093
2.1
0.24
0.0018
April 2004
Page C-8
-------
Table 2. Acute Dose-Response Values (10/22/03)
CHEMICAL NAME
Mercury compounds
Methyl mercury
Methanol
Methoxychlor
Methyl bromide
Methyl chloride
Methyl ethyl ketone
Methyl hydrazine
Methyl iodide
Methyl isocyanate
Methyl methacrylate
Methyl tert-butyl ether
Methylene chloride
Methylene diphenyl diisocyanate
Naphthalene
Nickel carbonyl
Nickel compounds
Nitrobenzene
2-Nitropropane
Parathion
Pentachlorophenol
Phenol
Phosgene
Phosphine
Phosphorus, white
Phthalic anhydride
Propylene dichloride
Propylene oxide
1 ,2-Propyleneimine
Quinone
Selenium compounds
Hydrogen selenide
Styrene
1 ,1 ,2,2-Tetrachloroethane
Tetrachloroethene
Titanium tetrachloride
Toluene
2,4-Toluene diisocyanate
o-Toluidine
1 ,1 ,2-Trichloroethane
1,1,1-Trichloroethane
Trichloroethylene
CAS NO.
HG_CMPDS
22967-92-6
67-56-1
72-43-5
74-83-9
74-87-3
78-93-3
60-34-4
74-88-4
624-83-9
80-62-6
1 634-04-4
75-09-2
101-68-8
91-20-3
1 3463-39-3
7440-02-0
98-95-3
79-46-9
56-38-2
87-86-5
1 08-95-2
75-44-5
7803-51-2
7723-14-0
85-44-9
78-87-5
75-56-9
75-55-8
106-51-4
7782-49-2
7783-07-5
1 00-42-5
79-34-5
1 27-1 8-4
7550-45-0
1 08-88-3
584-84-9
95-53-4
79-00-5
71-55-6
79-01 -6
HAP NO.
184
184
103
104
105
106
108
109
110
112
113
114
116
117
119
186
186
120
123
127
129
130
132
133
134
135
141
142
143
145
189
189
146
149
150
151
152
154
155
158
107
159
AEGL-1 AEGL-2 AEGL-3
mg/m3
690 !
290 p
171
140 !
240 !
0.54 p
750 '
0.141
13001
700 p
mg/m3
2700 !
5000 p
3.6 f
0.161
0.25 !
58 '
1.2'
2.8 !
690 !
28 '
2.4 p
16001
7.8 p
19001
0.59 '
3300 !
2400 p
mg/m3
100001
12000P
11f
0.47 !
1.1 '
180 !
3f
51
14001
54 '
7.3 p
81001
44 P
110001
3.6 '
21 000 !
20000 p
ERPG-1 ERPG-2 ERPG-3
mg/m3
260
150
0.058
690
0.2
38
120
210
680
5
190
0.071
1900
540
mg/m3
1300
190
830
290
1.2
2600
2
190
0.81
0.7
590
0.66
1100
1400
20
1100
3800
2700
mg/m3
6500
780
2100
730
12
14000
25
770
4
7
1800
6.6
4300
6800
100
3800
19000
27000
IDLH/10
mg/m3
1
0.2
790
500
97
410
7.2
58
0.7
410
800
7.5
130
1.4
1
100
36
1
0.25
96
0.81
6
180
95
10
0.1
0.33
300
69
100
190
1.8
22
55
380
MRL
mg/m3
0.19
1
7.2
2.1
0.02
0.23
1.4
3.8
11
11
REL
mg/m3
28
3.9
13
14
0.006
5.8
0.004
3.1
0.005
21
20
37
68
April 2004
Page C-9
-------
Table 2. Acute Dose-Response Values (10/22/03)
CHEMICAL NAME
Triethylamine
Uranium compounds
Uranium hexafluoride
Vinyl acetate
Vinyl chloride
m-Xylene
o-Xylene
p-Xylene
Xylenes (mixed)
CAS NO.
121-44-8
7440-61-1
7783-81-5
1 08-05-4
75-01 -4
1 08-38-3
95-47-6
1 06-42-3
1 330-20-7
HAP NO.
162
188
188
165
167
171
170
172
169
AEGL-1 AEGL-2 AEGL-3
mg/m3
52'
640 p
560 p
mg/m3
140'
3100P
1900P
mg/m3
520'
12000"
4000 p
ERPG-1 ERPG-2 ERPG-3
mg/m3
5
18
mg/m3
15
260
mg/m3
30
1800
IDLH/10
mg/m3
1
390
390
390
390
MRL
mg/m3
1.3
4.3
REL
mg/m3
2.8
180
22
AEGLs: f = final, I = interim, p = proposed
April 2004
Page C-10
-------
Appendix D Methodology for Identifying PB-HAP
Compounds
-------
-------
This Appendix provides and justifies a list of hazardous air pollutants that have sufficient
persistence and bioaccumulation potential to make them candidates for multipathway risk
assessments. The list was selected in two stages.
The first stage was to determine which HAPs are already listed as persistent, bioaccumulative,
and toxic (PBT) substances by the following EPA programs:
1. Priority PBT Profiles (Pollution Prevention program): http://www.epa.gov/pbt/cheminfo.htm.
2. Great Waters Pollutants of Concern:
http://www.epa.gov/oar/oaqps/gr8water/3rdrpt/execsum.html.
3. Toxics Release Inventory: http://www.epa.gov/tri/chemical/pbt_chem_list.htm.
All substances that are both HAPs pursuant to the CAA and listed by at least one of these
programs are shown in Exhibit 1.
The second stage was to determine if, based on their toxicity and bioaccumulation potential, any
additional substances should be assessed for multipathway risk by the air toxics program. This
determination was made by calculating two indexes for all HAPs for which data could be
obtained. One index (intended to estimate relative carcinogenic potential by oral exposure) was
the product of the oral carcinogenic potency slope and the bioconcentration factor (obtained
from the EPA PBT Profiler, http://www.pbtprofiler.net/). The other index (intended to estimate
relative noncarcinogenic hazard by oral exposure) was the ratio of the same bioconcentration
factor to the oral reference dose. The cancer and noncancer indexes were normalized to a scale
of 1 and combined by averaging (with chemicals with no data not averaged, rather than averaged
as zero).
The HAPs were then ranked in descending order of the combined index, and the substances that
comprised 99.9999% of the total of all substances were selected as potential candidates for
multipathway risk assessment. Results of the ranking exercise are shown in Exhibit 1.
Of the 26 substances that comprised 99.9999% of the aggregate index for all HAPs, 19 are
classified as polycyclic organic matter under the Clean Air Act. These were combined into a
single category in the table. Metals could not be ranked because the PBT Profiler does not
contain data for inorganic pollutants, but were included in the table because of their presence on
the other lists. Three other substances shown as "NA" fell outside the 99.9999% aggregate limit.
In summary, no substance not already on at least one existing list emerged in this analysis as a
significant potential PBT substance. Therefore, based on our current estimates of toxicity and
bioaccumulation potential, the 14 substances in the table represent a conservative list for
multipathway risk assessments in the air toxics program.
April 2004 Page D-l
-------
Exhibit 1. Identity and Ranking of Potential PB-HAP Compounds
PB-HAP Compound
Cadmium compounds
Chlordane
Chlorinated dibenzodioxins and furans
DDE
Heptachlor
Hexachlorobenzene
Hexachlorocyclohexane (all isomers)
Lead compounds
Mercury compounds
Methoxychlor
Polychlorinated biphenyls
Polycyclic organic matter
Toxaphene
Trifluralin
OAQPS
Rank
NA(1)
7
1
8
4
6
NA(4)
NA«
NA«
NA(4)
3
2(6)
5
NA(4)
Pollution
Prevention
Priority
PBTs
X
X(2)
X
X
X(5)
X
X
X(7)
X
Great Waters
Pollutants of
Concern
X
X
X
X
X
X
X
X
X
X
X
TRI PBT
Chemicals
X
X(3)
X
X
X
X
X
X
x(8)
X
X
(1) Not ranked because the PBT Profiler lacks data for inorganic compounds
(2) "Dioxins and furans" (denotes the phraseology of the source list)
(3) "Dioxin and dioxin-like compounds"
(4) Did not fall within 99.9999% of cumulative index
(5) Alkyllead
(6) 19 POM compounds that fell within the top 26 substances were assigned the rank of
7,12-dimethylbenz(a)anthracene, the highest-ranked compound
(7) Benzo[a]pyrene
(8) "Polycyclic aromatic compounds" and benzo[g,h,i]perylene
April 2004
Page D-2
-------
Appendix E Overview of Air Toxics Emission
Sources
This appendix provides general information on the types of air toxics commonly associated with
various types of sources. The table begins with the regulated major source categories and is
followed by mobile sources, indoor sources, and miscellaneous sources. This table is not meant
to be a comprehensive listing of all chemicals that may be emitted from a given source or group
of sources in a particular location.
-------
-------
Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Commercial / Industrial Sources
Halogenated Solvent
Cleaners (1614)
methylene chloride;
perchloroethylene;
trichloroethylene;
1,1,1 -trichloroethane;
carbon tetrachloride;
chloroform*0'
SIC: 33,34, 36,37
NAICS: 332,333,
334, 335,336, 447
MACT/GACT, see 40 CFR Part
63 Subpart T
U.S. EPA. 1995. Profile of the Iron and
Steel Industry. Office of Compliance Sector
Notebook Project, Washington, D.C.,
September 1995. EPA/310-R-95-005.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/iron
.html
Acetal Resins
Production (1301)
SIC:2869
NAICS: 325199
MACT, see 40 CFR Part 63 YY
(General MACT)
U.S. EPA. 1997. Profile of the Plastic
Resins and Man-made Fibers Industry.
Office of Compliance Sector Notebook
Project, Washington, D.C., September 1997.
EPA/310-R-97-008. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/plas
tic .html
Acrylic /M oda crylic
Fibers Production
(1001)
SIC:2869
NAICS: 325199
MACT, see 40 CFR Part 63 YY
U.S. EPA. 1997. Profile of the Plastic
Resins and Man-made Fibers Industry.
Office of Compliance Sector Notebook
Project, Washington, D.C., September 1997.
EPA/310-R-97-008. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/plas
tic .html
April 2004
PageE-l
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Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Acrylonitrile-
Butadiene-Styrene
Production (1302)
styrene; acrylonitrile;
butadiene; ethylene
glycol; methane 1;
acetaldehyde;
dioxane
SIC:2821,2822
NAICS: 325211,
325212
MACT, see 40 CFR Part 63 JJJ
U.S. EPA. 2001. Polymers and Resins IV
Inspection Tool. Adopt-a-MACT
Compliance Tool, Washington, D.C.,
September 2001. Available at:
http://www.epa.gOV/ttn/atw/pr4/privinspect.h
tml
USEPA. 1997. Profile of the Plastic Resins
and Man-made Fibers Industry. Office of
Compliance Sector Notebook Project,
Washington, D.C., September 1997.
EPA/310-R-97-008. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/plas
tic .html
Aerospace Industries
(0701)
chromium; cadmium;
methylene; chloride;
toluene; xylene;
methyl ethyl ketone;
ethylene glycol;
glycol ethers
SIC: 3720,3721,
3724, 3728,3760,
3761,3764,3769
NAICS: 336411,
336412, 336413,
336414, 336419,
481111,481112
MACT, see 40 CFR Part 63
Subpart GG
U.S. EPA. 1998. Profile of the Aerospace
Industry. Office of Compliance Sector
Notebook Project, Washington, D.C.,
November 1998. EPA/310-R-98-001.
Available at:
http://www.epa.gOv/compliance/resources/p
ublications/assistance/sectors/notebooks/aero
space.html
Amino/Phenolic Resins
Production (1347)
formaldehyde,
methanol, phenol,
xylene, toluene
SIC:2821
NAICS: 325211
MACT, see 40 CFR Part 63
Subpart OOO
U.S. EPA. 1997. Profile of the Plastic
Resins and Man-made Fibers Industry.
Office of Compliance Sector Notebook
Project, Washington, D.C., September 1997.
EPA/310-R-97-006. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/plas
tic .html
U.S. EPA. 1998. Hazardous Air Pollutant
Emissions from the Manufacture of Amino
and Phenolic Resins: Basis and Purpose
Document for Proposed Standards.
Emission Standards Division, Washington,
D.C., May 1998. Available at:
http://www.epa.gOV/ttn/atw/amiao/p r3bpd.
wpd
April 2004
PageE-2
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Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Ammonium Sulfate -
Cap ro lac tarn By-
Product Plants (1401)
toluene; methanol;
xylene; methyl ethyl
ketone; ethyl
benzene; methyl
isobutyl ketone;
hydrogen chloride;
vinyl acetate
NAICS: 3251,3252,
3253,3254,3255,
3256,3259
MACT, see 40 CFR Part 63
Subpart FFFF
U.S. EPA. 2002. Profile of the Organic
Chemical Industry. Office of Compliance
Sector Notebook Project, Washington, D.C.,
November 2002. EPA/310-R-02-001.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/org
anic.html
Asphalt Roofing and
Processing (0418)
formaldehyde;
hexane; hydrogen
chloride; phenol;
polycyclic organic
matter; toluene
SIC:2911,2952
NAICS: 32411,
324122
MACT, see 40 CFR Part 63
Subpart LLLLL
U.S. EPA. 1995. Profile of the Stone, Clay,
Glass and Concrete Industry. Office of
Compliance Sector Notebook Project,
Washington, D.C., September 1995.
EPA/310-R-95-017. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/ston
e.html
April 2004
PageE-3
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Source Name'"'
Asphalt/Coal Tar
Application - Metal
Pipes (0402)
Typical Pollutants
xylenes; toluene;
methyl ethyl ketone;
phenol;
cresols/cresylic acid;
glycol ethers
(including ethylene
glycol monobutyl
ether); styrene;
methyl iso butyl
ketone; ethyl
benzene
Typical Industries
(SIC)
NAICS: 335312,
336111, 336211,
336312, 33632,
33633, 33634,33637,
336399, 331316,
331524, 332321,
332323, 33312,
333611, 333618,
332312, 332722,
332813, 332991,
332999, 334119,
336413, 339999,
33612, 336211,
331319, 331422,
335929, 332311,
33242, 81131,
322214, 326199,
331513, 332439,
331111, 331513,
33121, 331221,
331511, 33651,
336611, 482111,
3369, 331316,
336991, 336211,
336112, 336213,
336214, 336399,
326291, 326299,
332311, 332312,
336212, 336999,
33635, 56121,8111,
56211
Regulatory and Control
Programs
MACT, see 40 CFR Part 63
Sub part MMMM
References and Other Information
U.S. EPA. 1995. Profile of the Fabricated
Metal Products Industry. Office of the
Compliance Sector Notebook Project,
Washington, D.C., September 1995.
EPA/310-R-95-007. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/fabr
ic .html
U.S. EPA. 1995. Profile of the Stone, Clay,
Glass and Concrete Industry. Office of
Compliance Sector Notebook Project,
Washington, D.C., September 1995.
EPA/310-R-95-017. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/ston
e.html
April 2004
PageE-4
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Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Auto & Light Duty
Truck (Surface
Coating) (0702)
toluene; xylene;
glycol ethers; methyl
ethyl ketone; methyl
isobutyl ketone;
ethylbenzene;
methane 1
NAICS: 336111,
336112,336211
MACT, see 40 CFR Part 63
Subpart IIII
U.S. EPA. 1995. Profile of the Motor
Vehicle Assembly Industry. Office of
Compliance Sector Notebook Project,
Washington, D.C., September 1995.
EPA/310-R-95-009. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/mot
or.html
U.S. EPA. 2002. Regulatory Impact
Analysis for the Proposed Automobile and
Light Duty Truck Coating NESHAP. Final
Report, Washington, D.C., October 2002.
EPA-452/R-01-013. Available at:
http://www.epa.gov/ttn/atw/auto/autoriap.pd
f
U.S. EPA. 1997. U.S. Auto Assembly Plants
and Their Communities — Environmental,
Econom ic, and Demographic Profile.
Common Sense Initiative Automobile
Manufacturing Sector. Washington, D.C.,
December 1997. Available at:
http://www.epa.gov/oar/opar/auto/
Boat Manufacturing
(1305)
styrene; methyl
methacrylate;
methylene chloride
(dichloromethane);
toluene; xylene; n-
hexane; methyl ethyl
ketone; methyl
isobutyl ketone;
methyl chloroform
(1,1,1-
trichloroethane)
SIC: 3731,3732
NAICS: 336612
MACT, see 40 CFR Part 63
Subpart VVVV
U.S. EPA. 1997. Profile of the Shipbuilding
and Repair Industry. Office of Compliance
Sector Notebook Project. Washington, D.C.,
November 1997. EPA/310-R-97-008.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/ship
.html
April 2004
PageE-5
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Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Brick and Structural
Clay Products
Manufacturing (0414)
hydrogen fluoride;
hydrogen chloride;
antimony; arsenic;
beryllium; cadmium;
chromium; cobalt;
mercury; manganese;
nickel; lead;
selenium
SIC: 3251,3253,3259
NAICS: 327121,
327122,327123
MACT, see 40 CFR Part 63
Subpart JJJJJ
U.S. EPA. 1995. Profile of the Stone, Clay,
Glass and Concrete Industry. Office of
Compliance Sector Notebook Project.
Washington, D.C., September 1995.
EPA/310-R-95-017. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/ston
e.html
Butyl Rubber
Production (1307)
n-hexane; 1,3-
butadiene;
acrylonitrile; methyl
chloride; hydrogen
chloride; carbon
tetrachloride;
chloroprene; toluene
SIC:2821,2822
NAICS: 325211,
325212
MACT, see 40 CFR Part 63
Subpart U
U.S. EPA. 1995. Profile of the Rubber and
Plastics Industry. Office of Compliance
Sector Notebook Project, Washington, D.C.,
September 1995. EPA/310-R-95-016.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/rub
ber.html
Carbon Black
Production (1415)
cyanide compounds;
acrylonitrile;
acetonitrile; carbonyl
sulfide; carbon
disulfide; benzene;
1,3 butadiene;
toluene; 2,4 toluene
diisocyanate
SIC:2895
NAICS: 325182
General MACT, see 40 CFR
Part 63 YY
U.S. EPA. 2002. Profile of the Organic
Chemical Industry. Office of Compliance
Sector Notebook Project, Washington, D.C.,
November 2002. EPA/310-R-02-001.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/org
anic.html
Carbonyl Sulfide
(COS) Production
(1604)
toluene; methanol;
xylene; hydrogen
chloride; methylene
chloride
NAICS: 3251,3252,
3253,3254,3255,
3256,3259
MACT, see 40 CFR Part 63
FFFF
(General MACT)
U.S. EPA. 2002. Profile of the Organic
Chemical Industry, Second Edition (2002).
Office of Compliance Sector Notebook
Project, Washington, D.C., November 2002.
EPA/310-R-02-001. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/org
anic.html
April 2004
PageE-6
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Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Cellulose Products
Manufacturing (1349)
carbon disulfide;
carbonyl sulfide;
ethylene oxide;
methanol; methyl
chloride; propylene
oxide; toluene
SIC: 2819,2821,
2823,2869,3089
NAICS: 325188,
325199,325211,
325221,326121,
326199
MACT, see 40 CFR Part 63
uuuu
U.S. EPA. 2002. Profile of the Pulp and
Paper Industry, 2nd Edition. Office of
Compliance Sector Notebook Project,
Washington, D.C., November 2002.
EPA/310-R-02-002. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/pul
p.html
U.S. EPA. 1997. Pro file of the Plastic
Resins and Man-made Fibers Industry.
Office of Compliance Sector Notebook
Project, Washington, D.C., September 1997.
EPA/310-R-97-008. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/plas
tic.html
Mercury Cell Chlor-
Alkali Plants (Formerly
Chlorine Production)
SIC: chlorine 2812
EPA proposes not to regulate
chlorine and hydrochloric acid
(HC1) emissions for the Chlorine
Production source category.
U.S. EPA. 1995. Profile of the Inorganic
Chemical Industry. Office of Compliance
Sector Notebook Project, Washington, D.C.,
September 1995. EPA/310-R-95-004.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/inor
ganic.html
Chromic Acid
Anodizing (1607)
chromium
NAICS: 332,333,
334,335,336
MACT, see 40 CFR Part 63
Subpart N
U.S. EPA. 1993. Chromium Emissions from
Chromium Electroplating and Chromic Acid
Anodizing Operations. Background
Information for Proposed Standards,
Washington, D.C., July 1993. EPA 453/R-
93-03Oa and EPA 453/r-93-030b, Volumes 1
and 2. Available at:
http://www.epa.gov/ttn/atw/chrome/chromep
g.html
April 2004
Page E-7
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Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Clay Ceramics
Manufacturing (0415)
hydrogen flouride;
hydrogen chloride;
antimony; arsenic;
beryllium; cadmium;
chromium; cobalt;
mercury; manganese;
nickel; lead;
selenium
SIC:3253,3261
NAICS: 327122,
327111
MACT, see 40 CFR Part 63
Subpart KKKKK
U.S. EPA. 1995. Profile of the Stone, Clay,
Glass and Concrete Industry. Office of
Compliance Sector Notebook Project.
Washington, D.C., September 1995.
EPA/310-R-95-017. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/ston
e.html
Coke Ovens:
Charging, Top Side,
and Door Leaks (0302)
coal tar (benzene,
toluene, and xylene);
creosote; coal tar
pitch; polycyclic
aromatic
hydrocarbons
(benzo(a)pyrene,
benzanthracene,
chrysene,
phenanthrene)
NAICS: 331111,
324199
MACT, see 40 CFR Part 63
Subpart L
U.S. EPA. 1995. Profile of the Petroleum
Refining Industry. Office of Compliance,
Sector Notebook Project. Washington, D.C.,
September 1995. EPA/310-R-95-013.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/petr
oleum.html
Coke Ovens: Pushing,
Quenching, & Battery
Stacks (0303)
polycyclic organic
matter; polynuclear
aromatic
hydrocarbons;
benzene; toluene;
xylene
NAICS: 331111,
324199
MACT, see 40 CFR Part 63
Subpart CCCCC
U.S. EPA. 1995. Profile of the Petroleum
Refining Industry. Office of Compliance,
Sector Notebook Project. Washington, D.C.,
September 1995. EPA/310-R-95-013.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/petr
oleum.html
Commercial
Sterilization Facilities
(1609)
ethylene oxide
NAICS: 3391
MACT, see 40 CFR Part 63
Subpart O
U.S. EPA. 1997. Ethylene Oxide
Commercial Sterilization and Fumigation
Operations. NESHAP Implementation
Document. Washington, D.C., September,
1997. EPA-456/R-004. Available at:
http://www.epa.gov/ttn/atw/eo/eoguide.pdf
April 2004
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Source Name'"'
Cyanide Chemicals
Manufacturing (1405)
Decorative Chromium
Electroplating (1610)
Dry Cleaning:
Perchloroethylene
(1643)
Typical Pollutants
cyanide compounds;
acrylonitrile;
acetonitrile; carbonyl
sulfide; carbon
disulfide; benzene;
1,3 butadiene;
toluene; 2,4 toluene
diisocyanate
chromium
perchloroethylene
Typical Industries
(SIC)
SIC: 2819,2869
NAICS: 325188,
325199
NAICS: 332,333,
334, 335,336
NAICS: 8123
Regulatory and Control
Programs
MACT, see 40 CFR Part 63 YY
(General MACT)
MACT, see 40 CFR Part 63
Subpart N
MACT, see 40 CFR Part 63
Subpart M
References and Other Information
U.S. EPA. 1995. Profile of the Dry Cleaning
Industry. Office of Compliance Sector
Notebook Project, Washington, D.C.,
September 1995. EPA/310-R-95-001.
Available at:
http://www.epa.gOv/compliance/resources/p
ublications/assistance/sectors/notebooks/drv.
html
April 2004
PageE-9
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Source Name'"'
Engine Test Facilities
(0101)
Ep ichloro hydrin
Elastomers Production
(1311)
Typical Pollutants
toluene; benzene;
mixed xylenes; 1,3-
butadiene
n-hexane; 1,3-
butadiene;
acrylonitrile; methyl
chloride; hydrogen
chloride; carbon
tetrachloride;
chloroprene; toluene
Typical Industries
(SIC)
SIC: 3511,3519,
3523, 3524,3531,
3559, 3566,3599,
3621, 3711,3714,
3721, 3724,3761,
3764, 4226,4512,
4581, 5541,7538,
7539, 7699,8299,
8711, 8731,8734,
8741, 9661,9711
NAICS: 54171,
92711, 92811,332212
333111, 333112,
333120, 333319,
333611, 333612,
333618, 335312,
336111, 336112,
336120, 336312,
336350, 336399,
336411, 336412,
336414, 336415,
336992, 481111,
488190, 541380,
611692, 811111,
811118, 811310,
811411
SIC: 2821,2822
NAICS: 325211,
325212
Regulatory and Control
Programs
MACT, see 40 CFR Part 63
Subpart PPPPP
MACT, see 40 CFR Part 63
Subpart U
References and Other Information
April 2004
Page E-10
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Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Epoxy Resins
Production (1312)
epichlorohydrin,
methanol,
hydrochloric acid
SIC: 2821,2823, 2824
MACT, see 40 CFR Part 63
Subpart W
U.S. EPA. 1997. Profile of the Plastic Resins
and Man-made Fibers Industry. Office of
Compliance Sector Notebook Project,
Washington, DC, September 1997.
EPA/310-R-97-008. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/plas
tic.html
Ethylene Processes
(1635)
cyanide compounds;
acrylonitrile;
acetonitrile; carbonyl
sulfide; carbon
disulfide; benzene;
1,3 butadiene;
toluene; 2,4 toluene
diisocyanate
SIC:2869
NAICS: 325110
MACT, see 40 CFR Part 63 YY
U.S. EPA. 1997. Profile of the Plastic Resins
and Man-made Fibers Industry. Office of
Compliance Sector Notebook Project,
Washington, DC. EPA/310-R-97-006.
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/plas
tic.html
Ethylene-Propylene
Rubber Production
(1313)
n-hexane; 1,3-
butadiene;
acrylonitrile; methyl
chloride; hydrogen
chloride; carbon
tetrachloride;
chloroprene; toluene
SIC:2821,2822
NAICS: 325211,
325212
MACT, see 40 CFR Part 63
Subpart U
U.S. EPA. 1995. Profile of the Rubber and
Plastics Industry. Office of Compliance
Sector Notebook Project, Washington, DC,
September 1995. EPA/310-R-95-016.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/rub
ber.html
Ferroalloys Production
(0304)
ferromanganese;
silicomanganese;
nickel compounds
SIC: 3313
MACT, see 40 CFR Part 63
Subpart XXX
Flexible Polyurethane
Foam Fabrication
Operations (1341)
hydrochloric acid;
2,4-toluene
diisocyanate;
hydrogen cyanide;
methylene chloride
SIC: 3086
NAICS: 32615
MACT, see 40 CFR Part 63
Subpart MMMMM
U.S. EPA. 1995. Profile of the Wood
Furniture and Fixtures Industry. Office of
Compliance Sector Notebook Project,
Washington, D.C., September 1995.
EPA/310-R-95-003.
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/woo
d.html
April 2004
Page E-11
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Source Name'"'
Flexible Polyurethane
Foam Production
(1314)
Friction Products
Manufacturing (1636)
Fumed Silica
Production (1406)
Gasoline Distribution
(Stage I) (0601)
Hard Chromium
Electroplating (1615)
Typical Pollutants
methylene chloride;
2,4-toluene
diisocyanate; methyl
chloroform;
methylene diphenyl
diisocyanate;
propylene oxide;
diethano lamine ;
methyl ethyl ketone;
methanol; toluene
n-hexane; toluene;
trichloroethylene
hydrochloric acid;
chlorine
benzene; toluene;
hexane; ethyl
benzene;
naphthalene;
cumene; xylenes; n-
hexane; 2, 2, 4-
trimethylpentane;
methyl tert-butyl
ether
chromium
Typical Industries
(SIC)
SIC: 3086
NAICS: 32615
NAICS: 33634,
327999, 333613
SIC: 2819,2821, 2869
NAICS: 325188,
325211, 325199
SIC: 2911,4226,
4613, 5171
NAICS: 324110,
493190, 486910,
422710
NAICS: 332,333,
334, 335,336
Regulatory and Control
Programs
MACT, see 40 CFR Part 63
Subpart III
MACT, see 40 CFR Part 63
QQQQQ
MACT, see 40 CFR Part 63
Subpart NNNNN
MACT, see 40 CFR Part 63
Subpart R
MACT, see 40 CFR Part 63
Subpart N
References and Other Information
U.S. EPA. 1995. Profile of the Wood
Furniture and Fixtures Industry. Office of
Compliance Sector Notebook Project,
Washington, D.C., September 1995.
EPA/310-R-95-003. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/woo
d.html
U.S. EPA. 1995. Profile of the Petroleum
Refining Industry. Office of Compliance
Sector Notebook Project, Washington, D.C.,
September 1995. EPA/310-R-95-013.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/petr
oleum.html.
April 2004
Page E-12
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Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Hazardous Waste
Incineration (0801)
chlorinated dioxins
and furans;
particulate matter (as
a surrogate for
antimony, cobalt,
manganese, nickel,
and selenium);
carbon monoxide;
mercury; lead;
cadmium; arsenic;
beryllium;
chromium; hydrogen
chloride and chlorine
gas (combined);
hydrocarbons
MACT, see 40 CFR Parts 63,
261 and 270
U.S. EPA. Hazardous Waste Combustion
NESHAP Toolkit.
Available at:
http://www.epa.gov/epaoswer/hazwaste/com
bust/to olkit/index.htm
Hydrochloric Acid
Production (1407)
hydrochloric acid;
chlorine
SIC:2819,2821, 2869
NAICS: 325188,
325211,325199
MACT, see 40 CFR Part 63
SubpartNNNNN
None found at this writing.
Hydrogen Fluoride
Production (1409)
SIC:2819
NAICS: 325188
MACT, see 40 CFR Part 63 YY
(General MACT)
U.S. EPA. Profile of the Plastic Resins and
Man-made Fibers Industry. Office of
Compliance Sector Notebook Project,
Washington, D.C., September 1997.
EPA/310-R-97-006 . Available at:
http://www.epa.gOv/compliance/resources/p
ublications/assistance/sectors/notebooks/plas
tic.html
Hypalon(TM)
Production (1315)
n-hexane; 1,3-
butadiene;
acrylonitrile; methyl
chloride; hydrogen
chloride; carbon
tetrachloride;
chloroprene; toluene
SIC:2821,2822
NAICS: 325211,
325212
MACT, see 40 CFR Part 63
Subpart U
None found at this writing.
April 2004
Page E-13
-------
Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Indu strial/Co mm ercial/
Institutional Boilers &
Process Heaters (0107)
arsenic; cadmium;
chromium; hydrogen
chloride; hydrogen
fluoride; lead;
manganese; mercury;
nickel
SIC: 13,24, 26,28,
29, 30,33, 34,37, 49,
80, 82
NAICS: 211,221,
316, 321,322, 324,
325, 326,331, 332,
336, 339,611, 622
MACT, see 40 CFR Part 63
Subpart DDDDD
U.S. EPA. 1999. Profile of Oil and Gas
Extraction Industry. Office of Compliance
Sector Notebook Project, Washington, D.C.,
October 2000. EPA/310-R-99-006.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/oil.
html.
Also see Profile of Lumber and Wood
Products Industry, Profile of Organic and
Inorganic Chemical Manufacturing Industry,
Profile of Petroleum Refining Industry, and
Profile of Rubber and Plastic Industry.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/index.html
Industrial Cooling
Towers (1619)
chromium
compounds
MACT, see 40 CFR Part 63
Subpart Q
U.S. EPA. 1995. Profile of the Petroleum
Refining Industry. Office of Compliance,
Sector Notebook Project. Washington, D.C.,
September 1995. EPA/310-R-95-013.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/petr
oleum.html
U.S. EPA. 2001. Profile of the Organic
Chemical Industry. Office of Compliance
Assistance and Sector Programs Division.
Washington, D.C., September 2001.
EPA/310/R-O2-001. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/org
anic.html
April 2004
Page E-14
-------
Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Integrated Iron & Steel
Manufacturing (0305)
metals (primarily
manganese and lead);
polycyclic organic
matter; benzene;
carbon disulfide
SIC: 3312
NAICS: 331111
MACT, see 40 CFR Part 63
Subpart FFFFF
U.S. EPA. 1995. Profile of the Iron and
Steel Industry. Office of Compliance Sector
Notebook Project, Washington, D.C.,
September 1995. EPA/310-R-95-005.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/iron
.html
Iron Foundries (0308)
lead; manganese;
cadmium; chromium;
nickel;
acetophenone;
benzene; cumene;
dibenzofurans;
dioxins;
formaldehyde;
methanol;
naphthalene; phenol;
pyrene; toluene;
triethylamine; xylene
NAICS: 331511
MACT, see 40 CFR Part 63
Subpart EEEEE
U.S. EPA. 1995. Profile of the Iron and
Steel Industry. Office of Compliance Sector
Notebook Project, Washington, D.C.,
September 1995. EPA/310-R-95-005.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/iron
.html
Large Appliance
(Surface Coating)
(0704)
glycol ethers;
methylene diphenyl
diisocyanate; methyl
ethyl ketone; toluene;
xylene
NAICS: 333312,
333319, 333415,
335221, 335222,
335224,335228
MACT, see 40 CFR Part 63
Subpart NNNN
U.S. EPA. 1995. Profile of the Dry Cleaning
Industry. Office of Compliance Sector
Notebook Project, Washington, D.C.,
September 1995. EPA/310-R-95-001.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/drv.
html.
Leather Tanning &
Finishing Operations
(1634)
glycol ethers;
toluene; xylene
SIC: 3111
NAICS: 3161
MACT, see 40 CFR Part 63
Subpart TTTT
None found as of this writing
April 2004
Page E-15
-------
Source Name'"'
Light Weight
Aggregate
Manufacturing (0417)
Lime Manufacturing
(0408)
Magnetic Tapes
(Surface Coating)
(0705)
Manufacture of
Nutritional Yeast
(1101)
Typical Pollutants
toluene; methanol;
methyl ethyl ketone;
xylenes; phenol;
methylene chloride;
ethylene glycol;
glycol ethers;
hexane; methyl
isobutyl ketone;
cresols and cresylic
acid;
dimethylformamide;
vinyl acetate;
formaldehyde; ethyl
benzene
hydrogen chloride;
antimony; arsenic;
beryllium; cadmium;
chromium; lead;
manganese; mercury;
nickel; selenium
methyl ethyl ketone;
toluene; methyl
isobutyl ketone;
toluene diisocyanate;
ethylene glycol;
methanol; xylenes;
ethyl benzene;
acetaldehyde;
chromium; cobalt
acetaldehyde
Typical Industries
(SIC)
NAICS: 322211,
322212, 322221,
322222, 322223,
322224, 322225,
322226, 322299,
323111, 323116,
325992, 326111,
326112, 326113,
32613, 326192,
32791, 332999,
339944
NAICS: 32741,
33111, 3314
SIC: 3695,2675
SIC: 2099
NAICS: 311999
Regulatory and Control
Programs
See MACT in 40 CFR Part 63
Subpart JJJJ
MACT, see 40 CFR Part 63
Subpart AAAAA
MACT, see 40 CFR Part 63
Subpart EE
MACT, see 40 CFR Part 63
Subpart CCCC
References and Other Information
None found as of this writing
None found at this writing.
April 2004
Page E-16
-------
Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Marine Vessel Loading
Operations (0603)
benzene; toluene;
hexane
MACT, see 40 CFR Part 63
Subpart Y
U.S. EPA. 1997. Profile of the Water
Transportation Industry (Shipping and
Barging). Office of Compliance Sector
Notebook Project, Washington, D.C.,
September 1997. EPA/310-R-97-003.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/wat
er.html
Metal Can (Surface
Coating) (0707)
ethylene glycol
monobutyl ether;
other glycol ethers;
xylenes; hexane;
methyl iso butyl
ketone; methyl ethyl
ketone
NAICS: 332115,
332116,332431,
332812,332999
MACT, see 40 CFR Part 63
Subpart KKKK
U.S. EPA. 1995. Profile of the Metal
Fabrication Industry. Office of Compliance
Sector Notebook Project, Washington, D.C.,
September 1995. EPA/310-R-95-007.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/fabr
ic.html
Metal Coil (Surface
Coating) (0708)
methyl ethyl ketone;
glycol ethers;
xylenes (isomers and
mixtures); toluene;
isophorone.
SIC: 34
NAICS: 332812,
331319, 332312,
332322, 332323,
332311, 33637,
332813, 332999,
333293, 336399,
325992, 42183,
323122, 339991,
326113, 32613,
32614, 331112,
331221, 33121,
331312, 331314,
331315
MACT, see 40 CFR Part 63
Subpart SSSS
U.S. EPA. 1995. Profile of the Metal
Fabrication Industry. Office of Compliance
Sector Notebook Project, Washington, D.C.,
September 1995. EPA/310-R-95-007.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/fabr
ic.html
April 2004
Page E-17
-------
Source Name'"'
Metal Furniture
(Surface Coating)
(0709)
Methyl Methacrylate-
Acrylonitrile-
Butadiene-Styrene
Production (1317)
Methyl Methacrylate-
Butadiene-Styrene
Terpolymers
Production (1318)
Mineral Wool
Production (0409)
Miscellaneous Coatings
Manufacturing (1642)
Typical Pollutants
xylene; toluene;
ethylene glycol
monobutyl ether;
other glycol ethers;
ethylbenzene; methyl
ethyl ketone
styrene; acrylonitrile;
butadiene; ethylene
glycol; methane 1;
acetaldehyde;
dioxane
styrene; acrylonitrile;
butadiene; ethylene
glycol; methane 1;
acetaldehyde;
dioxane
carbonyl sulfide;
nine hazardous
metals;
formaldehyde;
phenol
toluene; xylene;
glycol ethers; methyl
ethyl ketone, and
methyl iso butyl
ketone
Typical Industries
(SIC)
NAICS: 81142,
337124, 337127,
337214, 337215,
339111
SIC: 2821,2822
NAICS: 325211,
325212
SIC: 2821,2822
NAICS: 325211,
325212
SIC: 3296
NAICS: 3255
Regulatory and Control
Programs
MACT, see 40 CFR Part 63
Subpart RRRR
MACT, see 40 CFR Part 63 JJJ
MACT, see 40 CFR Part 63 JJJ
MACT, see 40 CFR Part 63
ODD
MACT, see 40 CFR Part 63
Subpart HHHHH
References and Other Information
U.S. EPA. 1995. Profile of the Metal
Fabrication Industry. Office of Compliance
Sector Notebook Project, Washington, D.C.,
September 1995. EPA/310-R-95-007.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/fabr
ic .html
U.S. EPA. 2001. Polymers and Resins IV
Inspection Tool. Adopt-a-MACT
Compliance Tool, Washington, D.C.,
September 2001. Available at:
http://www.epa.gOV/ttn/atw/pr4/privinspect.h
tml
U.S. EPA. 2001. Polymers and Resins IV
Inspection Tool. Adopt-a-MACT
Compliance Tool, Washington, D.C.,
September 2001. Available at:
http://www.epa.gOV/ttn/atw/pr4/privinspect.h
tml
U.S. EPA. 1995. Profile of the Metal
Fabrication Industry. Office of Compliance
Sector Notebook Project. Washington, D.C.,
September 1995. EPA/310-R-95-007.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/fabr
ic.html
April 2004
Page E-18
-------
Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Miscellaneous Metal
Parts & Products
(Surface Coating)
(0710)
xylene; toluene;
methyl ethyl ketone;
phenol;
cresols/cresylic acid;
2-butoxyethanol;
styrene; methyl
isobutyl ketone; ethyl
benzene; glycol
ethers
NAICS: 335312,
336111, 336211,
336312, 33632,
33633,33634,33637,
336399,331316,
331524,332321,
332323,33312,
333611, 333618,
332312, 332722,
332813, 332991,
332999,334119,
336413,339999,
33612, 336211,
331319, 331422,
335929,332311,
33242, 81131,
322214, 326199,
331513, 332439,
331111, 331513,
33121, 331221,
331511, 33651,
336611, 482111,
3369, 331316,
336991, 336211,
336112, 336213,
336214, 336399,
326291, 326299,
332311,332312,
336212,336999,
33635,56121,8111,
56211
MACT, see 40 CFR Part 63
Sub part MMMM
U.S. EPA. 1995. Profile of the Metal
Fabrication Industry. Office of Compliance
Sector Notebook Project. Washington, D.C.,
September 1995. EPA/310-R-95-007.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/fabr
ic .html
April 2004
Page E-19
-------
Source Name'"'
Miscellaneous Organic
Chemical Products &
Processes (1641)
Municipal Landfills
(0802)
Natural Gas
Transmission &
Storage (0504)
Neoprene Production
(1320)
Typical Pollutants
toluene; methanol;
xylene; methyl ethyl
ketone; ethyl
benzene; methyl
isobutyl ketone;
hydrogen chloride;
vinyl acetate
vinyl chloride; ethyl
benzene; toluene;
benzene
benzene; toluene;
ethyl benzene; mixed
xylenes; n-hexane
n-hexane; 1,3-
butadiene;
acrylonitrile; methyl
chloride; hydrogen
chloride; carbon
tetrachloride;
chloroprene; toluene
Typical Industries
(SIC)
NAICS: 3251,3252,
3253, 3254,3255,
3256, 3259
SIC: 4953,9511
NAICS: 562212,
924110
SIC: 40,42,46,49,
1321
NAICS: 211112
Note: Condensate tank
batteries, glycol
dehydration units,
natural gas processing
plants, and natural gas
transmission and
storage facilities not
included.
SIC: 2821,2822
NAICS: 325211,
325212
Regulatory and Control
Programs
MACT, see 40 CFR Part 63
Subpart FFFF
MACT, see 40 CFR Part 63
Subpart AAAA
MACT, see 40 CFR Part 63
Subpart HHH
MACT, see 40 CFR Part 63
Subpart U
References and Other Information
U.S. EPA. 2002. Profile of the Organic
Chemical Industry, 2nd Edition. Office of
Compliance Sector Notebook Project.
Washington, DC., November 2002.
EPA/310-R-02-001. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/org
anic.html.
None found as of this writing
U.S. EPA. 1997. Profile of the Ground
Transportation Industry - Railroad,
Trucking, and Pipeline. Office of
Compliance Sector Notebook Project,
Washington, D.C., September 1997.
EPA/310-R-97-002. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/gro
und.html
U.S. EPA. 1997. Profile of Plastic Resins
and Man-Made Fibers Industry. Office of
Compliance Sector Notebook Project,
Washington, D.C., September 1997.
EPA/310-R-97-006. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/plas
tic. html
April 2004
Page E-20
-------
Source Name'"'
Nitrile Butadiene
Rubber Production
(1321)
Nitrile Resins
Production (1342)
Off- Site Waste and
Recovery Operations
(0806)
Oil & Natural Gas
Production (0501)
Typical Pollutants
n-hexane; 1,3-
butadiene;
acrylonitrile; methyl
chloride; hydrogen
chloride; carbon
tetrachloride;
chloroprene; toluene
Styrene, n-hexane,
1,3-
butadiene,
acrylonitrile, methyl
chloride, hydrogen
chloride, carbon
tetrachloride,
chloroprene, toluene
benzene, methylene
chloride
benzene; toluene;
ethyl benzene; mixed
xylenes; n-hexane
Typical Industries
(SIC)
SIC: 2821,2822
NAICS: 325211,
325212
SIC: 1311, 1321,
1381, 1382, 1389
NAICS: 211112
(Condensate tank
batteries, glycol
dehydration units,
natural gas processing
plants, and natural gas
transmission and
storage facilities.)
Regulatory and Control
Programs
MACT, see 40 CFR Part 63
Subpart U
MACT, see 40 CFR Part 63
Subpart U
MACT, see 40 CFR Part 63
Subpart DD
MACT, see 40 CFR Part 63 HH
References and Other Information
U.S. EPA. 1995. Profile of the Rubber and
Plastic Industry. Office of Compliance
Sector Notebook Project, Washington, D.C.,
September 1995. EPA/310-R-95-016.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/rub
ber.html
U.S. EPA. 1997. Profile of Plastic Resins
and Man-Made Fibers Industry. Office of
Compliance Sector Notebook Project,
Washington, D.C., September 1997.
EPA/310-R-97-006. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/plas
tic .html.
None found at this writing.
U.S. EPA. 1999. Profile of the Oil and Gas
Extraction Industry. Office of Compliance
Sector Notebook Project, Washington, D.C.
EPA/310-R-99-006. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/oil.
html
April 2004
Page E-21
-------
Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Organic Liquids
Distribution (Non-
Gasoline) (0602)
benzene;
ethylbenzene;
toluene; vinyl
chloride; xylenes
SIC: 2821,2865,
2869, 2911,4226,
4612,5169,5171
NAICS: 325211,
325192, 325188,
32411,49311,49319,
48611,42269,42271
MACT, see 40 CFR Part 63
Subpart EEEE
U.S. EPA. 1997. Profile of the Ground
Transportation Industry - Railroad,
Trucking and Pipeline. Office of
Compliance Sector Notebook Project.
Washington, D.C., September 1997.
EPA/310-R-97-002.
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/gro
und.html
U.S. EPA. 1995. Profile of the Petroleum
Refining Industry. Office of Compliance
Sector Notebook Project. Washington, D.C.,
September 1995. EPA/310-R-95-013.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/petr
oleum.html
U.S. EPA. 2002. Organic Chemical
Manufacturing Industry. Office of
Compliance Sector Notebook Project.
Washington, D.C., November 2002.
EPA/310-R-02-001. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/org
anic.html
April 2004
Page E-22
-------
Source Name'"'
Paper & Other Webs
(Surface Coating)
(0711)
Pesticide Active
Ingredient Production
(0911)
Petroleum Refineries -
Catalytic Cracking,
Catalytic Reforming, &
Sulfur Plant Units
(0502)
Typical Pollutants
toluene; methanol;
methyl ethyl ketone;
xylenes; phenol;
methylene chloride;
ethylene glycol;
glycol ethers;
hexane; methyl
isobutyl ketone;
cresols and cresylic
acid;
dimethylformamide;
vinyl acetate;
formaldehyde; ethyl
benzene
toluene; methanol;
methyl chloride;
hydrogen chloride
hydrogen fluoride;
hydrogen chloride;
2,2,4-
trimethylpentane;
methyl tert butyl
ether; benzene;
naphthalene;
cresols/cresylic acid;
phenol;
ethylbenzene;
toluene; hexane;
xylenes ; methyl ethyl
ketone
Typical Industries
(SIC)
NAICS: 322211,
322212, 322221,
322222, 322223,
322224, 322225,
322226, 322299,
323111, 323116,
325992, 326111,
326112, 326113,
32613, 326192,
32791, 332999,
339944
SIC: 2869,2879
NAICS: 32532,
325199
SIC: 2911
Regulatory and Control
Programs
MACT, see 40 CFR Part 63 JJJJ
MACT, see 40 CFR Part 63
MMM
MACT, see 40 CFR Part 63
Subpart CC
References and Other Information
MACT Sources: Profile of the Pulp and
Paper Industry, 2nd Edition (2002).
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/pul
p. html
U.S. EPA. 2000. Profile of the Agricultural
Chemical, Pesticide, and Fertilizer Industry .
Office of Compliance Sector Notebook
Project, Washington, D.C., September 2000.
EPA/310-R-00-003. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/che
mical.html
U.S. EPA. 1995. Profile of the Petroleum
Refining Industry. Office of Compliance
Sector Notebook Project, Washington, D.C.,
September 1995. EPA/310-R-95-013.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/petr
oleum.html
April 2004
Page E-23
-------
Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Petroleum Refineries
Other Sources Not
Distinctly Listed
(0503)
benzene, toluene,
ethyl benzene,
2,2,4 -trimethy Ip entan
e, cresols/cresylic
acid, ethylbenzene,
hexane, methyl ethyl
ketone
SIC:2911
MACT, see 40 CFR Part 63
Subpart CC
U.S. EPA. 1995. Profile of the Petroleum
Refining Industry. Office of Compliance
Sector Notebook Project. Washington, D.C.,
September 1995. EPA/310-R-95-013.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/petr
oleum.html.
Pharmac euticals
Production (1201)
methylene chloride;
methane 1; toluene;
hydrogen chloride;
dimethylformamide;
hexane
SIC:2833,2834
NAICS: 32541,
325412
MACT, see 40 CFR Part 63
GGG
U.S. EPA. 1997. Profile of the
Pharmaceutical Industry. Office of
Compliance Sector Notebook Project.
Washington, D.C., September 1997.
EPA/310-R-97-005. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/pha
rmaceutic al .html
Phosphate Fertilizers
Production (1410)
hydrogen fluoride;
arsenic; beryllium;
cadmium; chromium;
manganese; mercury;
nickel; methyl
isobutyl ketone
SIC:2874
NAICS: 325314
MACT, see 40 CFR Part 63 BB
U.S. EPA. 2000. Profile of the Agricultural
Chemical, Pesticide, and Fertilizer Industry.
Office of Compliance Sector Notebook
Project. Washington, D.C., September 2000.
EPA/310-R-00-003. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/che
mical.html
Phosphoric Acid
Manufacturng (1411)
hydrogen fluoride;
arsenic; beryllium;
cadmium; chromium;
manganese; mercury;
nickel; methyl
isobutyl ketone
SIC:2874
NAICS: 325314
MACT, see 40 CFR Part 63 AA
U.S. EPA. 2000. Profile of the Agricultural
Chemical, Pesticide, and Fertilizer Industry.
Office of Compliance Sector Notebook
Project. Washington, D.C., September 2000.
EPA/310-R-00-003. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/che
mical.html
April 2004
Page E-24
-------
Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Plastic Parts &
Products (Surface
Coating) (0712)
methyl ethyl ketone;
methyl iso butyl
ketone; toluene;
ethylene glycol
monobutyl ether;
other glycol ethers;
xylenes
NAICS: 32615,
32614,33422,33992,
326199, 333313,
336211, 336212,
336213, 336214,
336399, 336999,
337214, 339111,
339112,339999
MACT, see 40 CFR Part 63
Subpart PPPP
U.S. EPA. 1995. Profile of the Motor
Vehicle Assembly Industry. Office of
Compliance Sector Notebook Project.
Washington, D.C., September 1995.
EPA/310-R-95-009. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/mot
or.html
Plywood and
Composite Wood
Products (1624)
acetaldehyde;
acrolein;
formaldehyde;
methanol; phenol;
propionaldehyde
SIC: 2421,2435,
2436,2439,2493
NAICS: 321211,
321212, 321213,
321219,321999
MACT, see 40 CFR Part 63
Subpart DDDD
The Plywood and Composite Wood Products
MACT was proposed on January 9, 2003.
The comment period ended on March 10,
2003. The final rule will most likely be
promulgated in March 2004, with a
compliance date of March 2007.
Polybutadiene Rubber
Production (1325)
styrene; n-hexane;
1,3- butadiene;
acrylonitrile; methyl
chloride; hydrogen
chloride; carbon
tetrachloride;
chloroprene; toluene
SIC:2821,2822
NAICS: 325211,
325212
MACT, see 40 CFR Part 63
Subpart U
U.S. EPA. 1995. Profile of the Rubber and
Plastic Industry. Office of Compliance
Sector Notebook Project. Washington, D.C.,
September 1995. EPA/310-R-95-016.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/rub
ber.html
Polycarbonates
Production (1326)
TOC, organic HAPs
SIC:2869
NAICS: 325199
MACT, see 40 CFR Part 63 YY
(Generic MACT)
U.S. EPA. 1997. Profile of the Plastic Resins
and Man-made Fibers Industry. Office of
Compliance Sector Notebook Project.
Washington, D.C., September 1997.
EPA/310-R-97-006 . Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/plas
tic.html
Polyether Polyols
Production (1625)
ethylene oxide;
propylene oxide;
hexane; toluene
SIC:2843,2869
NAICS: 325199,
325613
MACT, see 40 CFR Part 63 PPP
None found at this writing.
April 2004
Page E-25
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Source Name'"'
Polyethylene
Terephthalate
Production (1328)
Polystyrene Production
(1331)
Polysulfide Rubber
Production (1332)
Polyvinyl Chloride &
Copolymers Production
(1336)
Typical Pollutants
styrene; acrylonitrile;
butadiene; ethylene
glycol; methane 1;
acetaldehyde;
dioxane
styrene; acrylonitrile;
butadiene; ethylene
glycol; methane 1;
acetaldehyde;
dioxane
styrene; n-hexane;
1,3- butadiene;
acrylonitrile; methyl
chloride; hydrogen
chloride; carbon
tetrachloride;
chloroprene; toluene
vinyl chloride;
vinylidene chloride
(1,1
dichloroethylene);
vinyl acetate
Typical Industries
(SIC)
SIC: 2821,2822
NAICS: 325211,
325212
SIC: 2821,2822
NAICS: 325211,
325212
SIC: 30
SIC: 2821
NAICS: 325211
Regulatory and Control
Programs
MACT, see 40 CFR Part 63 JJJ
MACT, see 40 CFR Part 63 JJJ
MACT, see 40 CFR Part 63
Subpart U
MACT, see 40 CFR Part 63 J
References and Other Information
U.S. EPA. 2001. Polymers and Resins IV
Inspection Tool. Adopt-a-MACT
Compliance Tool, Washington, D.C.,
September 2001. Available at:
http://www.epa.goV/ttn/atw/pr4/privinspect.h
tml
U.S. EPA. 2001. Polymers and Resins IV
Inspection Tool. Adopt-a-MACT
Compliance Tool, Washington, D.C.,
September 2001. Available at:
http://www.epa.gOV/ttn/atw/pr4/privinspect.h
tml
U.S. EPA. 1995. Profile of the Rubber and
Plastic Industry. Office of Compliance
Sector Notebook Project. Washington, D.C.,
September 1995. EPA/310-R-95-016.
Available at:
http://www.epa.gOV/compliance/resources/p
ublications/assistance/sectors/notebooks/rub
ber.html
None found as of this writing
April 2004
Page E-26
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Source Name'"'
Portland Cement
Manufacturing (0410)
Primary Aluminum
Production (0201)
Primary Copper
Smelting (0203)
Primary Lead Smelting
(0204)
Primary Magnesium
Refining (0207)
Typical Pollutants
acetaldehyde;
arsenic; benzene;
cadmium; chromium;
chlorobenzene;
dibenzofurans;
formaldehyde;
hexane; hydrogen
chloride; lead;
manganese; mercury;
naphthalene; nickel;
phenol; polycyclic
organic matter;
selenium; styrene;
2,3,7,8-
tetrachlorodibenzo-p-
dioxin; toluene;
xylenes
hydrogen flouride;
polycyclic aromatic
hydrocarbons
antimony; arsenic;
beryllium; cadmium;
cobalt; lead;
manganese; nickel;
selenium
arsenic; antimony;
cadmium
chlorine;
hydrochloric acid;
dioxin/furan; trace
amounts of several
HAP metals
Typical Industries
(SIC)
SIC: 3241
NAICS: 32731
NAICS: 331312
SIC: 3339
SIC: 3339
NAICS: 331419
Regulatory and Control
Programs
MACT, see 40 CFR Part 63
Subpart LLL
MACT, see 40 CFR Part 63
Subpart LL
MACT, see 40 CFR Part 63
Subpart QQQ
MACT, see 40 CFR Part 63
Subpart TTT
MACT, see 40 CFR Part 63
Subpart TTTTT
References and Other Information
U.S. EPA. 1995. Profile of the Stone, Clay,
Glass and Concrete Industry. Office of
Compliance Sector Notebook Project.
Washington, D.C., September 1995.
EPA/310-R-95-017.
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/ston
e.html
U.S. EPA. 1995. Profile of the Nonferrous
Metals Industry . Office of Compliance
Sector Notebook Project. Washington, D.C.,
September 1995. EPA/310-R-95-010.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/non
ferrous.html
None found at this writing.
None found at this writing.
None found at this writing.
April 2004
Page E-27
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Source Name'"'
Printing, Coating &
Dyeing Of Fabrics
(0713)
Printing/Publishing
(Surface Coating)
(0714)
Publicly Owned
Treatment Works
(POTW) Emissions
(0803)
Pulp & Paper
Production -
Combustion (Kraft,
Soda, Sulfite, & Semi-
Chemical) (1626-2)
Typical Pollutants
toluene; methyl ethyl
ketone; methane 1;
xylenes ; methyl
isobutyl ketone;
methylene chloride;
n-hexane;
trichloroethylene;
n,n-dim ethyl
formamide.; 1,1,1-
trichloroethane;
naphthalene; ethyl
benzene; glycol
ethers (ethylene
glycol); biphenyl;
styrene
xylene; toluene;
ethylbenzene; methyl
ethyl ketone; methyl
isobutyl ketone;
methanol; ethylene
glycol; certain glycol
ethers
xylenes; methylene
chloride; toluene;
ethyl benzene;
chloroform;
tetrachloroethylene;
benzene; naphthalene
Typical Industries
(SIC)
NAICS: 31321,
31322, 313241,
NAICS: 313311,
313312, 313320,
314110
SIC: 2671,2711,
2721, 2754,2759
SIC: 4952
NAICS: 22132
SIC: 2611,2621,2631
NAICS: 32211,
32212, 32213
Regulatory and Control
Programs
MACT, see 40 CFR Part 63
Subpart OOOO
MACT, see 40 CFR Part 63
Subpart KK
MACT, see 40 CFR Part 63
Subpart VVV
MACT, see 40 CFR Part 63
Subpart S
References and Other Information
U.S. EPA. 1997. Profile of the Textiles
Industry. Office of Compliance Sector
Notebook Project, Washington, D.C.,
September 1997. EPA/310-R-97-009.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/text
iles.html
U.S. EPA. 1995. Profile of the Printing
Industry. Office of Compliance Sector
Notebook Project, Washington, D.C.,
September 1995. EPA/310-R-95-014.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/prin
ting.html
None found at this writing.
U.S. EPA. 2002. Profile of the Pulp and
Paper Industry, 2nd Edition. Office of
Compliance Sector Notebook Project,
Washington, D.C., November 2002.
EPA/310-R-95-015. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/pul
p. html
April 2004
Page E-28
-------
Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Pulp & Paper
Production - Non-
Combustion (1626-1)
SIC 26
MACT, see 40 CFR Part 63
Subpart S
U.S. EPA. 2002. Profile of the Pulp and
Paper Industry, 2nd Edition. Office of
Compliance Sector Notebook Project,
Washington, D.C., November 2002.
EPA/310-R-95-015. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/pul
p.html
Refractories Products
Manufacturing (0406)
ethylene glycol;
formaldehyde;
hydrogen fluoride;
hydrochloric acid;
methanol; phenol;
polycyclic organic
matter
NAICS: 327124,
327125
MACT, see 40 CFR Part 63
Subpart SSSSS
None found at this writing.
Reinforced Plastic
Composites Production
(1337)
styrene; methyl
methacrylate;
methylene chloride
(dichloromethane)
SIC: 2821,3084,
3087, 3088,3089,
3281, 3296,3431,
3531, 3612,3613,
3621, 3663,3711,
3713,3714,3716,
3728, 3743,3792,
3799
NAICS: 33312,
33612,33651,33653,
35313, 325211,
325991, 326122,
326191, 327991,
327993, 332998,
333422,335311,
335312, 336112,
336211, 336213,
336214, 336399,
336413
MACT, see 40 CFR Part 63
Subpart WWWW
None found at this writing.
April 2004
Page E-29
-------
Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Rocket Engine Test
Firing (1627)
toluene, benzene,
mixed xylenes, 1,3-
butadiene
SIC: 3724,3761,
3764,9661,9711
NAICS: 336412,
336414 , 336415,
54171,92711,92811
MACT, see 40 CFR Part 63
Subpart PPPPP
U.S. EPA. 1997. Profile of the Air
Transportation Industry. Office of
Compliance Sector Notebook Project,
Washington, D.C., February 1998.
EPA/310-R-97-001. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/air.
html
Rubber Tire Production
(1631)
toluene; hexane
SIC:2296,3011,7534
NAICS: 314992,
326211,326212
MACT, see 40 CFR Part 63
Subpart XXXX
U.S. EPA. Profile of the Rubber and Plastic
Industry. Office of Compliance Sector
Notebook Project, Washington, D.C.,
September 1995. EPA/310-R-95-016.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/rub
ber.html
Secondary Aluminum
Production (0202)
hydrogen chloride,
hydrogen fluoride,
chlorine,
2,3,7,8-tetrachlorodi
benzo-p-dioxin,
organic HAPs,
particulate HAP
metals
SIC: 3341,3334,
3353,3354,3355,
3363, 3365
NAICS: 331314,
331312, 331315,
331316, 331319,
331521,331524
MACT, see 40 CFR Part 63
Subpart RRR
None found at this writing.
Secondary Lead
Smelting (0205)
lead compounds;
arsenic compounds;
1,3-butadiene
NAICS: 331492
MACT, see 40 CFR Part 63
Subpart X
None found at this writing.
Semiconductor
Manufacturing (1629)
hydrochloric acid;
hydrogen flouride;
methanol; glycol
ethers; xylene
SIC: 3674
NAICS: 334413
MACT, see 40 CFR Part 63
Subpart BBBBB
U.S. EPA. 2001. National Emission
Standards for Hazardous Air Pollutants:
Semiconductor Manufacturing-Background
Information for Proposed Standards. Office
of Air Quality Planning and Standards,
Research Triangle Park, NC, February 2001.
Available at:
http://www.epa.gov/ttn/atw/semicon/smatr b
id.pdf
April 2004
Page E-30
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Source Name'"'
Shipbuilding & Ship
Repair (Surface
Coating) (0715)
Site Remediation
(0805)
Solvent Extraction for
Vegetable Oil
Production (1103)
Spandex Production
(1003)
Stationary Combustion
Turbines (0108)
Stationary Reciprocal
Internal Combustion
Engines (0105)
Typical Pollutants
xylene; toluene;
ethylbenzene; methyl
ethyl ketone; methyl
isobutyl ketone;
ethylene glycol;
glycol ethers
benzene; ethyl
benzene; toluene;
vinyl chloride;
xylenes; other
volatile organic
compounds
n-hexane
cyanide compounds;
acrylonitrile;
acetonitrile; carbonyl
sulfide; carbon
disulfide; benzene;
1,3 butadiene;
toluene; 2,4 toluene
diisocyanate
formaldehyde;
toluene; benzene;
acetaldehyde
formaldehyde;
acrolein; methanol;
acetaldehyde
Typical Industries
(SIC)
SIC: 3731
NAICS: 325211,
325192, 325188,
32411, 49311,49319,
48611, 42269,42271
SIC: 2076,2079
NAICS: 311223
SIC: 2824
NAICS: 325222
SIC: 1311, 1321,
4911, 4922,4931
NAICS: 221,2211,
211111, 211112,
486210
SIC: 1311, 1321,
4911, 4922,9711
NAICS: 2211,48621,
92811, 211111,
211112
Regulatory and Control
Programs
MACT, see 40 CFR Part 63
Subpart II
MACT, see 40 CFR Part 63
Subpart GGGGG
MACT, see 40 CFR Part 63
Subpart GGGG
MACT, see 40 CFR Part 63 YY
MACT, see 40 CFR Part 63
YYYY
MACT, see 40 CFR Part 63
Subpart ZZZZ
References and Other Information
U.S. EPA. 1997. Profile of the Shipbuilding
and Repair Industry. Office of Compliance
Sector Notebook Project, Washington, D.C.,
November 1997. EPA/310-R-97-008.
Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/ship
.html
None found at this writing.
U.S. EPA. 1997. Profile of the Plastic Resins
and Man-made Fibers Industry. Office of
Compliance Sector Notebook Project,
Washington, D.C., September 1997.
EPA/310-R-97-006. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/plas
tic. html
April 2004
Page E-31
-------
Source Name'"'
Steel Pickling - HCL
Process (0310)
Styrene Acrylonitrile
Production (1338)
Styrene-Butadiene
Rubber & Latex
Production (1339)
Synthetic Organic
Chemical
Manufacturing (HON)
(1501)
Taconite Iron Ore
Processing (0411)
Typical Pollutants
hydrochloric acid
styrene; acrylonitrile;
butadiene; ethylene
glycol; methane 1;
acetaldehyde;
dioxane
styrene; n-hexane;
1,3- butadiene;
acrylonitrile; methyl
chloride; hydrogen
chloride; carbon
tetrachloride;
chloroprene; toluene
toluene, methanol,
xylene, hydrogen
chloride, and
methylene chloride
metal compounds
(such as manganese,
arsenic, lead, nickel,
chromium, and
mercury); products
of incomplete
combustion
(including
formaldehyde);
hydrogen chloride;
hydrogen fluoride
Typical Industries
(SIC)
SIC: 3312,3315, 3317
SIC: 2821,2822
NAICS: 325211,
325212
SIC: 2821,2822
NAICS: 325211,
325212
NAICS: 3251,3252,
3253, 3254,3255,
3256, 3259
NAICS: 21221
Regulatory and Control
Programs
MACT, see 40 CFR Part 63
Subpart CCC
MACT, see 40 CFR Part 63 JJJ
MACT, see 40 CFR Part 63
Subpart U
MACT, see 40 CFR Part 63
Subpart FFFF
and Miscellaneous Organic
NESHAP
MACT, see 40 CFR Part 63
Subpart RRRRR
References and Other Information
U.S. EPA. 2001. Polymers and Resins IV
Inspection Tool. Adopt-a-MACT
Compliance Tool, Washington, D.C.,
September 2001. Available at:
http://www.epa.gOV/ttn/atw/pr4/privinspect.h
tml
U.S. EPA. 1995. Profile of the Rubber and
Plastic Industry. Office of Compliance
Sector Notebook Program, Washington,
D.C., September 1995. EPA/310-R-95-016.
Available at:
http://www.epa.gOV/compliance/resources/p
ublications/assistance/sectors/notebooks/rub
ber.html
None found at this writing.
April 2004
Page E-32
-------
Source Name'"'
Utility Boilers: Coal
(1808-1)
Utility Boilers: Natural
Gas (1808-2)
Utility Boilers: Oil
(1808-3)
Wet-Formed Fiberglass
Mat Production (0413)
Wood Building
Products (Surface
Coating) (0703)
Typical Pollutants
arsenic; cadmium;
chromium; hydrogen
chloride; hydrogen
fluoride; lead;
manganese; mercury;
nickel
arsenic; cadmium;
chromium; hydrogen
chloride; hydrogen
fluoride; lead;
manganese; mercury;
nickel
arsenic; cadmium;
chromium; hydrogen
chloride; hydrogen
fluoride; lead;
manganese; mercury;
nickel
formaldehyde;
methanol; vinyl
acetate
xylenes; toluene;
ethyl benzene;
ethylene glycol
monobutyl ether;
other glycol ethers'
methyl ethyl ketone;
methyl iso butyl
ketone; methanol;
styrene;
formaldehyde
Typical Industries
(SIC)
SIC: 29
NAICS: 324
SIC: 13,49
NAICS: 211,221
SIC: 24,29
NAICS: 321,324
SIC: 3229325
NAICS: 327212
SIC: 2421,2426,
2431, 2435,2436,
2493, 2499
NAICS: 321211,
321212 321219
321911, 321918,
321999
Note: The subcategory
of the SIC and NAICS
code depends on the
final end use of the
product.
Regulatory and Control
Programs
See 40 CFR Part 63 Subpart
DDDDD
See 40 CFR Part 63 Subpart
DDDDD
See 40 CFR Part 63 Subpart
DDDDD
MACT, see 40 CFR Part 63
Subpart HHHH
MACT, see 40 CFR Part 63
Subpart QQQQ
References and Other Information
None found at this writing.
None found at this writing.
None found at this writing.
None found at this writing.
U.S. EPA. 1995. Profile of the Wood
Furniture and Fixtures Industry. Office of
Compliance Sector Notebook Project,
Washington, D.C., September 1995.
EPA/310-R-95-003 Available at'
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/woo
d.html
April 2004
Page E-33
-------
Source Name'"'
Wood Furniture
(Surface Coating)
(0716)
Wool Fiberglass
Manufacturing (0412)
Typical Pollutants
toluene; xylene;
methanol; methyl
ethyl ketone; methyl
isobutyl ketone;
glycol ethers;
formaldehyde
arsenic,
chromium, lead,
formaldehyde,
phenol, and
methanol
Typical Industries
(SIC)
SIC: 2511,2512,
2517, 2519,2521,
2531, 2541
SIC: 3296
Regulatory and Control
Programs
MACT, see 40 CFR Part 63
Subpart JJ
MACT, see 40 CFR Part 63
Subpart NNN
References and Other Information
U.S. EPA. 1995. Profile of the Wood
Furniture and Fixtures Industry. Office of
Compliance Sector Notebook Project,
Washington, D.C., September 1995.
EPA/310-R-95-003. Available at:
http://www.epa.goV/compliance/resources/p
ublications/assistance/sectors/notebooks/woo
d.html
None found at this writing.
Mobile Sources
Mobile sources
acetaldehyde,
acrolein, arsenic
compounds, benzene,
1,3-butadiene,
chromium
compounds, diesel
particulate matter,
diesel exhaust
organic gases,
dioxin/ furans,
ethylbenzene,
formaldehyde ,
n-hexane, lead
compounds,
manganese
compounds, mercury
compounds, MTBE,
naphthalene, nickel
compounds,
polycyclic organic
matter, styrene,
toluene, xylene
N/A
Various, see
http://www.epa.gov/otaq/
EPA's Office of Transportation Air Qualtiy
provides information on mobile source air
toxics at http://www.epa.gov/otaq/toxics.htm
In-depth information on desiel engine
exhaust can be found at
http://cfpub.epa.gOV/ncea/cfm/recordisplay.c
fm?deid=29060&CFID=12048081&CFTOK
EN=92457493
The Health Effects Institute is an
independent, nonprofit corporation chartered
in 1980 to provide high-quality, impartial,
and relevant science on the health effects of
pollutants from motor vehicles and from
other sources in the environment (see
www.healtheffects.org).
April 2004
Page E-34
-------
Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Indoor Sources
Tobacco smoke
Many, including
benzene, toluene,
formaldehyde,
acrolein, N-
nitrosdimethyl-
amine, polycyclic
organic matter,
methyl chloride, 1,3-
butadiene, phenol,
catechol,
hydroquinone,
aniline, o-toluidine,
quinoline,
polychlorinated
dibenzo -p-dioxins,
nickel, cadmium,
polonium-210
N/A
Voluntary programs to protect
children from the effects of
secondhand smoke
U.S. EPA. 1992. Respiratory Health Effects
of Passive Smoking: Lung Cancer and Other
Disorders. Office of Research and
Development and Office of Air and
Radiation, Washington, D.C., December
1992. EPA/600/6-90/006F. Available at:
http://cfpub.epa.gOV/ncea/cfm/recordisplay.c
fm?deid=2835
Smoke-Free Homes Campaign:
http://www.epa.gov/smokefree/
Consumer and
commercial products
Many organic
chemicals and
metals, including
benzene, toluene,
xylenes, aldehydes
and ketones,
chlorinated solvents,
ethylene glycol and
glycol ethers,
phthalates, pesticides
N/A
Voluntary programs to control
exposures/risks
Sources of VOCs indoors:
http://www.epa.gov/iaq/voc.html
Pesticides:
http://www.epa.gov/iaq/pesticid.html
April 2004
Page E-35
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Source Name'"'
Building materials
Typical Pollutants
Many, including
formaldehyde from
pressed wood
products; chemicals
(see consumer and
commercial
products) from
caulks and sealants,
paints and wall
coverings, floor
coverings, etc.; and
asbestos and lead in
older buildings
Typical Industries
(SIC)
N/A
Regulatory and Control
Programs
Voluntary programs to control
exposures/risks
References and Other Information
Formaldehyde:
http://www.epa.gov/iaq/formalde.html
Asbestos:
http://www.epa.gov/asbestos/ashome.html
Lead:
http://www.epa.gov/iaq/lead.html
Natural Sources
Forest fires
Radon
Various volatile and
semivolatile organic
compounds (e.g.,
dioxins, PAHs)
radon
N/A
N/A
No federal programs currently
exist
Voluntary programs to control
exposures/risks
See tables 32-34 in:
http://www.epa.gov/ttn/chief/ap42/chl3/relat
ed/firerept.pdf. Also see the documentation
for the Preliminary 2002 National Emissions
Inventory (NEI), pages A58-A70:
ftp://ftp.epa.gov/pub/EmisInventory/prelim2
002 nei/nonpoint/documentation/2 002 prelim
neinonpt_032004.pdf. and and the 1999 final
NEI, (pages A56-A60:
ftp://ftp.epa.gov/EmisInventorv/finalnei99ve
r3/haps/documentation/nonpoint/nonpt99ver
3_aug2003.pdf
Radon in indoor air:
http://www.epa.gov/radon
April 2004
Page E-36
-------
Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
Other Sources
Long-range transport
aldrin, chlordane,
DDT, dieldrin,
dioxins and furans,
endrin, mirex,
heptachlor,
hexachlorobenzene,
mercury, PCBs,
toxaphene
N/A
N/A
Information on mercury as a global pollutant
can be found on the United Nations
Environment Programme website, which
also provides in-depth information and
assessment of the issue of global mercury
(see http://www.chem .unep .ch/mercury/).
General information about the health and
environmental impacts of persistent organic
pollutants (POPs) can be found at
http://www.epa.gov/international/toxics/broc
hure.html. This site describes what actions
the United States and some other countries
have already taken to address these
pollutants, and to describe the
actions set into motion by the Stockholm
Convention on POPs to address
ths issue globally. More in-depth
information on global POPs can be found in
The Foundation for Global Action on
Persistent Organic Pollutants: a United
States Perspective, Office of Research and
Development, U.S. EPA, Research Triangle
Park, NC, EPA/600/P-01/003F, 2002
(http://cfpub.epa.gov/ncea/cfm/recordisplay.
cfm?deid=51746). General reference
websites with information on the issue of
long range transport are EPA's Great Lakes
National Program Office (GLNPO;
www.epa.gov/glnpo/). the Binational Toxics
Strategy (www.epa.gov/glnpo/bns/). and the
Artie Monitoring and Assessment
Programme (http://www.amap.no/).
April 2004
Page E-37
-------
Source Name'"'
Typical Pollutants
Typical Industries
(SIC)
Regulatory and Control
Programs
References and Other Information
(a) HAP Source Category names are followed by MACT source category codes used for source classification in the National Toxics Inventory (see
http://www.epa.gov/ttn/chief/codes/index.htmlffmact). Except for mobile and natural sources, and sources of indoor air toxics, the table does not include
sources of criteria pollutants and TRI chemicals that are not also MACT HAP sources.
(b) Very limited information is available about emissions and risks associated with the many non-HAP compounds used in solvent cleanings since the MACT
rule was promulgated. These compounds are not listed in the table.
(c'The estimate of air toxics emissions from halogenated solvent cleaning is from background analyses conducted for the MACT rule. The estimate is based
on estimates and assumptions about the national number of cleaning machines, the types of cleaning machines and processes in use, control equipment and
work practice standards in use before and after the MACT rule, solvents used and solvent use rates, and emissions factors for the various machine types and
control equipment combinations. A sample of MACT compliance reports collected from states and EPA regions for a residual risk assessment suggest that
(1) the population of cleaning machines estimated for the MACT rule may have been substantially overestimated and/or (2) many cleaning machines have
been removed from service or changed to solvents not covered by the MACT.
April 2004
Page E-38
-------
Appendix F Specific HAPs Included in the National
Emissions Inventory (NEI)
-------
-------
Appendix F. Specific HAPs Included in the NEI
EPAChemRegistryName
1,1,1-Trichloroethane
1 ,1 ,2,2-Tetrachloroethane
1,1,2-Trichloroethane
1,1'-Biphenyl, chloro derivs.
1,1-Dichloroethane
1,1-Dichloroethylene
1 ,1-Dimethylhydrazine
1,2,3,4,6,7,8,9-Octachlorodibenzofuran
1,2,3,4,6,7,8,9-Octachlorodibenzo-p-dioxin
1,2,3,4,6,7,8-Heptachlorodibenzofuran
1,2,3,4,6,7,8-Heptachlorodibenzo-p-dioxin
1,2,3,4,7,8,9-Heptachlorodibenzofuran
1,2,3,4,7,8-Hexachlorodibenzofuran
1,2,3,4,7,8-Hexachlorodibenzo-p-dioxin
1,2,3,6,7,8-Hexachlorodibenzofuran
1,2,3,6,7,8-Hexachlorodibenzo-p-dioxin
1,2,3,7,8,9-Hexachlorodibenzofuran
1,2,3,7,8,9-Hexachlorodibenzo-p-dioxin
1,2,3,7,8-Pentachlorodibenzofuran
1,2,3,7,8-Pentachlorodibenzo-p-dioxin
NEI HAP Category
Methyl Chloroform (1,1,1-
Trichloroethane)
1 ,1 ,2,2-Tetrachloroethane
1,1,2-Trichloroethane
Polychlorinated Biphenyls (Aroclors)
Ethylidene Dichloride (1,1-
Dichloroethane)
Vinylidene Chloride (1,1-
Dichloroethylene)
1 ,1-Dimethylhydrazine
Dioxins/Furans as 2,3,7,8-TCDD TEQs
Dioxins/Furans as 2,3,7,8-TCDD TEQs
Dioxins/Furans as 2,3,7,8-TCDD TEQs
Dioxins/Furans as 2,3,7,8-TCDD TEQs
Dioxins/Furans as 2,3,7,8-TCDD TEQs
Dioxins/Furans as 2,3,7,8-TCDD TEQs
Dioxins/Furans as 2,3,7,8-TCDD TEQs
Dioxins/Furans as 2,3,7,8-TCDD TEQs
Dioxins/Furans as 2,3,7,8-TCDD TEQs
Dioxins/Furans as 2,3,7,8-TCDD TEQs
Dioxins/Furans as 2,3,7,8-TCDD TEQs
Dioxins/Furans as 2,3,7,8-TCDD TEQs
Dioxins/Furans as 2,3,7,8-TCDD TEQs
NEI Pollutant Name
Methyl Chloroform
1 ,1 ,2,2-Tetrachloroethane
1,1,2-Trichloroethane
Polychlorinated Biphenyls
Ethylidene Dichloride (1,1-
Dichloroethane)
Vinylidene Chloride
1,1-Dimethyl Hydrazine
Octachlorodibenzofuran
Octachlorodibenzo-p-Dioxin
1,2,3,4,6,7,8-
Heptachlorodibenzofuran
1,2,3,4,6,7,8-Heptachlorodibenzo-p-
Dioxin
1,2,3,4,7,8,9-
Heptachlorodibenzofuran
1,2,3,4,7,8-
Hexachlorodibenzofuran
1,2, 3,4,7, 8-Hexachlorodibenzo-p-
Dioxin
1,2,3,6,7,8-
Hexachlorodibenzofuran
1,2, 3,6,7, 8-Hexachlorodibenzo-p-
Dioxin
1,2,3,7,8,9-
Hexachlorodibenzofuran
1,2, 3,7,8, 9-Hexachlorodibenzo-p-
Dioxin
1,2,3,7,8-Pentachlorodibenzofuran
1 , 2,3,7, 8-Pentachlorodibenzo-p-
Dioxin
CASRN
71-55-6
79-34-5
79-00-5
1336-36-3
75-34-3
75-35-4
57-14-7
39001-02-0
3268-87-9
67562-39-4
35822-46-9
55673-89-7
70648-26-9
39227-28-6
57117-44-9
57653-85-7
72918-21-9
19408-74-3
57117-41-6
40321-76-4
April 2004
Page F-l
-------
Appendix F. Specific HAPs Included in the NEI
EPAChemRegistryName
1 ,2,4-Trichloro benzene
1 ,2-Butylene oxide
1 ,2-Dibromo-3-chloropropane
1,2-Dichloroethane
1,2-Dichloropropane
1 ,2-Diphenylhydrazine
1,3-Butadiene
1,3-Dichloropropene
1,3-Propane sultone
1,4-Dichlorobenzene
1 ,4-Dioxane
1 ,6-Dinitropyrene
1 ,8-Dinitropyrene
1 2-Methylbenz[a]anthrancene
1 -Methylnaphthalene
1 -Methylphenanthrene
1-Methylpyrene
1-Nitropyrene
2,2,4-Trimethylpentane
2,3,4,6,7,8-Hexachlorodibenzofuran
2,3,4,7,8-Pentachlorodibenzofuran
2,3,7,8-Tetrachlorodibenzofuran
2,3,7,8-Tetrachlorodibenzo-p-dioxin
2,3,7,8-Tetrachlorodibenzo-p-dioxin, TEQ
2,4,5-Trichlorophenol
2,4,6-Trichlorophenol
2,4-D
2,4-Dinitrophenol
NEI HAP Category
1 ,2,4-Trichlorobenzene
1 ,2-Epoxybutane
1 ,2-Dibromo-3-Chloropropane
Ethylene Dichloride (1,2-
Dichloroethane)
Propylene Dichloride (1 ,2-
Dichloropropane)
1 ,2-Diphenylhydrazine
1 ,3-Butadiene
1,3-Dichloropropene
1 ,3-Propane Sultone
1,4-Dichlorobenzene
p-Dioxane
Polycyclic Organic Matter
Polycyclic Organic Matter
Polycyclic Organic Matter
Polycyclic Organic Matter
Polycyclic Organic Matter
Polycyclic Organic Matter
Polycyclic Organic Matter
2,2,4-Trimethylpentane
Dioxins/Furans as 2,3,7,8-TCDD TEQs
Dioxins/Furans as 2,3,7,8-TCDD TEQs
Dioxins/Furans as 2,3,7,8-TCDD TEQs
Dioxins/Furans as 2,3,7,8-TCDD TEQs
Dioxins/Furans as 2,3,7,8-TCDD TEQs
2,4,5-Trichlorophenol
2,4,6-Trichlorophenol
2,4-D (2,4-Dichlorophenoxyacetic
Acid)(lncluding Salts And Esters)
2,4-Dinitrophenol
NEI Pollutant Name
1 ,2,4-Trichlorobenzene
1 ,2-Epoxybutane
1 ,2-Dibromo-3-Chloropropane
Ethylene Dichloride
Propylene Dichloride
1 ,2-Diphenylhydrazine
1,3-Butadiene
1,3-Dichloropropene
1,3-Propanesultone
1,4-Dichlorobenzene
p-Dioxane
1 ,6-Dinitropyrene
1 ,8-Dinitropyrene
1 2-Methylbenz(a)Anthracene
1 -Methylnaphthalene
1 -Methylphenanthrene
1-Methylpyrene
1-Nitropyrene
2,2,4-Trimethylpentane
2,3,4,6,7,8-
Hexachlorodibenzofuran
2,3,4,7,8-Pentachlorodibenzofuran
2,3,7,8-Tetrachlorodibenzofuran
2,3,7,8-Tetrachlorodibenzo-p-
Dioxin
2,3,7,8-TCDD TEQ
2,4,5-Trichlorophenol
2,4,6-Trichlorophenol
2,4-Dichlorophenoxy Acetic Acid
2,4-Dinitrophenol
CASRN
120-82-1
106-88-7
96-12-8
107-06-2
78-87-5
122-66-7
106-99-0
542-75-6
1120-71-4
106-46-7
123-91-1
42397-64-8
42397-65-9
2422-79-9
90-12-0
832-69-9
2381-21-7
5522-43-0
540-84-1
60851-34-5
57117-31-4
51207-31-9
1746-01-6
No CAS Number
95-95-4
88-06-2
94-75-7
51-28-5
April 2004
Page F-2
-------
Appendix F. Specific HAPs Included in the NEI
EPAChemRegistryName
2,4-Dinitrotoluene
2,4-Toluenediamine
2-Acetylaminofluorene
2-Chloroacetophenone
2-Chloronaphthalene
2-Ethoxyethanol
2-Methoxyethanol
2-Methoxyethyl oleate
2-Methylnaphthalene
2-Nitrofluorene
2-Nitropropane
2-Propoxyethanol acetate
3,3'-Dichlorobenzidine
3,3'-Dimethoxybenzidine
3,3'-Dimethylbenzidine
3-Butoxy-1 -propanol
3-Methylcholanthrene
4,4'-Methylenebis(2-chloroaniline)
4,4'-Methylenedi(phenyl isocyanate)
4,4'-Methylenedianiline
4,6-Dinitro-o-cresol
4-Aminobiphenyl
4-Dimethylaminoazobenzene
4-Nitrobiphenyl
4-Nitrophenol
5-Methylchrysene
6-Nitrochrysene
7,12-Dimethylbenz[a]anthracene
9-Methylanthracene
Acenaphthene
Acenaphthylene
Acetaldehyde
Acetamide
Acetonitrile
Acetophenone
NEI HAP Category
2,4-Dinitrotoluene
Toluene-2,4-Diamine
2-Acetylaminofluorene
2-Chloroacetophenone
Polycyclic Organic Matter
Glycol Ethers
Glycol Ethers
Glycol Ethers
Polycyclic Organic Matter
Polycyclic Organic Matter
2-Nitropropane
Glycol Ethers
3,3'-Dichlorobenzidene
3,3'-Dimethoxybenzidine
3,3'-Dimethylbenzidine
Glycol Ethers
Polycyclic Organic Matter
4,4'-Methylenebis(2-Chloroaniline)
4,4'-Methylenediphenyl Diisocyanate
(MDI)
4,4'-Methylenedianiline
4,6-Dinitro-o-Cresol (Including Salts)
4-Aminobiphenyl
4-Dimethylaminoazobenzene
4-Nitrobiphenyl
4-Nitrophenol
Polycyclic Organic Matter
Polycyclic Organic Matter
Polycyclic Organic Matter
Polycyclic Organic Matter
Polycyclic Organic Matter as 1 5-PAH
Polycyclic Organic Matter as 1 5-PAH
Acetaldehyde
Acetamide
Acetonitrile
Acetophenone
NEI Pollutant Name
2,4-Dinitrotoluene
Toluene-2,4-Diamine
2-Acetylaminofluorene
2-Chloroacetophenone
2-Chloronaphthalene
Cellosolve Solvent
Ethylene Glycol Methyl Ether
Methoxyethyl Oleate
2-Methylnaphthalene
2-Nitrofluorene
2-Nitropropane
2-Propoxyethyl Acetate
3,3'-Dichlorobenzidene
3,3'-Dimethoxybenzidine
3,3'-Dimethylbenzidine
3-Butoxy-1 -Propanol
3-Methylcholanthrene
4,4'-Methylenebis(2-Chloraniline)
4,4'-Methylenediphenyl
Diisocyanate
4,4'-Methylenedianiline
4,6-Dinitro-o-Cresol
4-Aminobiphenyl
4-Dimethylaminoazobenzene
4-Nitrobiphenyl
4-Nitrophenol
5-Methylchrysene
6-Nitrochrysene
7,12-Dimethylbenz[a]Anthracene
9-Methylbenz(a)Anthracene
Acenaphthene
Acenaphthylene
Acetaldehyde
Acetamide
Acetonitrile
Acetophenone
CASRN
121-14-2
95-80-7
53-96-3
532-27-4
91-58-7
110-80-5
109-86-4
111-10-4
91-57-6
607-57-8
79-46-9
20706-25-6
91-94-1
119-90-4
119-93-7
10215-33-5
56-49-5
101-14-4
101-68-8
101-77-9
534-52-1
92-67-1
60-11-7
92-93-3
100-02-7
3697-24-3
7496-02-8
57-97-6
779-02-2
83-32-9
208-96-8
75-07-0
60-35-5
75-05-8
98-86-2
April 2004
Page F-3
-------
Appendix F. Specific HAPs Included in the NEI
EPAChemRegistryName
Acrolein
Acrylamide
Acrylic acid
Acrylonitrile
Alkylated lead
Allyl chloride
Ammonium dichromate (VI)
Aniline
Anthracene
Antimonate(l-), hexafluoro-, sodium, (OC-6-11)-
Antimony
Antimony and compounds
Antimony oxide (unspecified)
Antimony pentafluoride
Antimony trichloride
Antimony trioxide
Antimony trisulfide
Arsenic
Arsenic acid
Arsenic acid (H3AsO4), lead(2+) salt (1:1)
Arsenic compounds (inorganic including arsine)
Arsenic(lll) trioxide
Arsenic(V) pentoxide
Arsenous acid, triethyl ester
Arsine
Asbestos
Aurate(l-), bis(cyano-. kappa. C)-, potassium
Aurate(l-), bis(cyano-. kappa. C)-, potassium
NEI HAP Category
Acrolein
Acrylamide
Acrylic Acid
Acrylonitrile
Lead Compounds
Allyl Chloride
Chromium Compounds
Aniline
Polycyclic Organic Matter as 1 5-PAH
Antimony Compounds
Antimony Compounds
Antimony Compounds
Antimony Compounds
Antimony Compounds
Antimony Compounds
Antimony Compounds
Antimony Compounds
Arsenic Compounds(lnorganic Including
Arsine)
Arsenic Compounds(lnorganic Including
Arsine)
Lead Compounds
Arsenic Compounds(lnorganic Including
Arsine)
Arsenic Compounds(lnorganic Including
Arsine)
Arsenic Compounds(lnorganic Including
Arsine)
Arsenic Compounds(lnorganic Including
Arsine)
Arsenic Compounds(lnorganic Including
Arsine)
Asbestos
Cyanide Compounds
Cyanide Compounds
NEI Pollutant Name
Acrolein
Acrylamide
Acrylic Acid
Acrylonitrile
Alkylated Lead
Allyl Chloride
Ammonium Dichromate
Aniline
Anthracene
Sodium hexafluoroantimenate
Antimony
Antimony & Compounds
Antimony Oxide
Antimony Pentafluoride
Antimony Trichloride
Antimony Trioxide
Antimony Trisulfide
Arsenic
Arsenic Acid
Lead Arsenate
Arsenic & Compounds (Inorganic
Including Arsine)
Arsenic Trioxide
Arsenic Pentoxide
Arsenous Acid
Arsine
Asbestos
Gold (I) Potassium Cyanide
Gold Potassium Cyanide
CASRN
107-02-8
79-06-1
79-10-7
107-13-1
No CAS Number
107-05-1
7789-09-5
62-53-3
120-12-7
16925-25-0
7440-36-0
No CAS Number
1327-33-9
7783-70-2
10025-91-9
1309-64-4
1345-04-6
7440-38-2
7778-39-4
7784-40-9
No CAS Number
1327-53-3
1303-28-2
3141-12-6
7784-42-1
1332-21-4
13967-50-5
13967-50-5
April 2004
Page F-4
-------
Appendix F. Specific HAPs Included in the NEI
EPAChemRegistryName
Aziridine
Benz[a]anthracene
Benz[a]anthracene mixt. with chrysene
Benzene
Benzene soluble organics
Benzeneacetonitrile
Benzidine
Benzo(b)fluoranthene
Benzo[a]fluoranthene
Benzo[a]pyrene
Benzo[b]fluoranthene mixt. with
benzo[k]fluoranthene
with benzo[k]fluoranthene
Benzo[c]phenanthrene
Benzo[e]pyrene
Benzo[ghi]fluoranthene
Benzo[ghi]perylene
Benzo[j]fluoranthene
Benzo[k]fluoranthene
Benzofluoranthene
Benzotrichloride
Benzyl chloride
Beryllium
Beryllium and compounds
Beryllium difluoride
Beryllium oxide
beta-Propiolactone
Biphenyl
Bis(2-(2-butoxyethoxy)ethyl) phthalate
Bis(2-chloroethyl) ether
Bis(chloromethyl) ether
Borate(l-), tetrafluoro-, lead(2+) (2:1)
NEI HAP Category
Ethyleneimine (Aziridine)
Polycyclic Organic Matter as 7-PAH
Polycyclic Organic Matter as 7-PAH
Benzene (Including Benzene From
Gasoline)
Coke Oven Emissions
Cyanide Compounds
Benzidine
Polycyclic Organic Matter as 7-PAH
Polycyclic Organic Matter
Polycyclic Organic Matter as 7-PAH
Polycyclic Organic Matter as 7-PAH
Polycyclic Organic Matter
Polycyclic Organic Matter
Polycyclic Organic Matter
Polycyclic Organic Matter as 15-PAH
Polycyclic Organic Matter
Polycyclic Organic Matter as 7-PAH
Polycyclic Organic Matter as 7-PAH
Benzotrichloride
Benzyl Chloride
Beryllium Compounds
Beryllium Compounds
Beryllium Compounds
Beryllium Compounds
Beta-Propiolactone
Biphenyl
Glycol Ethers
Dichloroethyl Ether (Bis[2-
Chloroethyl]Ether)
Bis(Chloromethyl) Ether
Lead Compounds
NEI Pollutant Name
Ethyleneimine
Benz[a]Anthracene
Benz(a)Anthracene/Chrysene
Benzene
Benzene Soluble Organics (BSO)
Benzyl Cyanide
Benzidine
Benzo[b]Fluoranthene
Benzo(a)fluoranthene
Benzo[a]Pyrene
Benzo[b+k]Fluoranthene
Benzo(c)phenanthrene
Benzo[e]Pyrene
Benzo(g,h,i)Fluoranthene
Benzo[g,h,i,]Perylene
B[j]Fluoranthen
Benzo[k]Fluoranthene
Benzofluoranthenes
Benzotrichloride
Benzyl Chloride
Beryllium
Beryllium & Compounds
Beryllium Fluoride
Beryllium Oxide
Beta-Propiolactone
Biphenyl
Di(Ethylene Glycol Monobutyl
Ether) Phthalate
Dichloroethyl Ether
Bis(Chloromethyl)Ether
Lead Fluoroborate
CASRN
151-56-4
56-55-3
No CAS Number
71-43-2
No CAS Number
140-29-4
92-87-5
205-99-2
203-33-8
50-32-8
No CAS Number
195-19-7
192-97-2
203-12-3
191-24-2
205-82-3
207-08-9
56832-73-6
98-07-7
100-44-7
7440-41-7
No CAS Number
7787-49-7
1304-56-9
57-57-8
92-52-4
16672-39-2
111-44-4
542-88-1
13814-96-5
April 2004
Page F-5
-------
Appendix F. Specific HAPs Included in the NEI
EPAChemRegistryName
C.I. Pigment Blue 28
Cadmium
Cadmium and compounds
Cadmium dichloride
Cadmium iodide
Cadmium nitrate
Cadmium oxide
Cadmium sulfide
Captan
Carbaryl
Carbon disulfide
Carbon tetrachloride
Carbonic acid, lead(2+) salt (1 :1)
Carbonic acid, nickel(2+) salt (1:1)
Carbonyl sulfide
Catechol
Ceramic fibers, man-made
Chloramben
Chlordane
Chlorinated dibenzo-p-dioxins
Chlorinated dibenzo-p-dioxins
Chlorine
Chloroacetic acid
Chlorobenzene
Chlorobenzilate
Chlorodibenzofurans
Chlorodibenzofurans
Chloroethane
Chloroform
Chloromethane
Chloromethyl methyl ether
Chloroprene
NEI HAP Category
Cobalt Compounds
Cadmium Compounds
Cadmium Compounds
Cadmium Compounds
Cadmium Compounds
Cadmium Compounds
Cadmium Compounds
Cadmium Compounds
Captan
Carbaryl
Carbon Disulfide
Carbon Tetrachloride
Lead Compounds
Nickel Compounds
Carbonyl Sulfide
Catechol
Fine Mineral Fibers
Chloramben
Chlordane
Dioxins/Furans (total, non TEQ)
Dioxins/Furans (total, non TEQ)
Chlorine
Chloroacetic Acid
Chlorobenzene
Chlorobenzilate
Dioxins/Furans (total, non TEQ)
Dioxins/Furans (total, non TEQ)
Ethyl Chloride
Chloroform
Methyl Chloride (Chloromethane)
Chloromethyl Methyl Ether
Chloroprene
NEI Pollutant Name
Cobalt Aluminate
Cadmium
Cadmium & Compounds
Cadmium Chloride
Cadmium Iodide
Cadmium Nitrate
Cadmium Oxide
Cadmium Sulfide
Captan
Carbaryl
Carbon Disulfide
Carbon Tetrachloride
Lead Carbonate
Nickel Carbonate
Carbonyl Sulfide
Catechol
Ceramic Fibers (Man-Made)
Chloramben
Chlordane
Dioxins, Total, w/o Individ. Isomers
Reported {PCDDs}
Polychlorinated Dibenzo-p-Dioxins,
Total
Chlorine
Chloroacetic Acid
Chlorobenzene
Chlorobenzilate
Dibenzofurans (Chlorinated)
{PCDFs}
Polychlorinated Dibenzofurans,
Total
Ethyl Chloride
Chloroform
Methyl Chloride
Chloromethyl Methyl Ether
Chloroprene
CASRN
1345-16-0
7440-43-9
No CAS Number
10108-64-2
7790-80-9
10325-94-7
1306-19-0
1306-23-6
133-06-2
63-25-2
75-15-0
56-23-5
598-63-0
3333-67-3
463-58-1
120-80-9
No CAS Number
133-90-4
57-74-9
136677-09-3
136677-09-3
7782-50-5
79-11-8
108-90-7
510-15-6
136677-10-6
136677-10-6
75-00-3
67-66-3
74-87-3
107-30-2
126-99-8
April 2004
Page F-6
-------
Appendix F. Specific HAPs Included in the NEI
EPAChemRegistryName
Chlorpyrifos
Chromic acid (H2CrO4), barium salt (1 :1)
Chromic acid (H2CrO4), calcium salt (1 :1)
Chromic acid (H2CrO4), lead(2+) salt (1:1)
Chromic acid (H2CrO4), strontium salt (1 :1)
Chromic acid, mixt. with sulfuric acid
Chromic(VI) acid
Chromic(VI) acid
Chromium
Chromium and compounds
Chromium chloride, hexahydrate
Chromium difluoride dioxide
Chromium oxide (CrO2)
Chromium zinc oxide (Cr2ZnO4)
Chromium zinc oxide (unspecified)
Chromium(lll)
Chromium(lll) acetylacetonate
Chromium(lll) hydroxide
Chromium(lll) oxide
Chromium(VI)
Chromium(VI) dioxychloride
Chromium(VI) trioxide
Chrysene
Coal tar
Cobalt
Cobalt and compounds
Cobalt hydrocarbonyl
Cobalt naphthenate
Cobalt tetraoxide
Cobalt(ll) oxide
Cobalt(ll) sulfide
Cobalt, tetracarbonylhydro-
Coke oven emissions
Copper(l) cyanide
Cresol
NEI HAP Category
Phosphorus Compounds
Chromium Compounds
Chromium Compounds
Lead Compounds
Chromium Compounds
Chromium Compounds
Chromium Compounds
Chromium Compounds
Chromium Compounds
Chromium Compounds
Chromium Compounds
Chromium Compounds
Chromium Compounds
Chromium Compounds
Chromium Compounds
Chromium Compounds
Chromium Compounds
Chromium Compounds
Chromium Compounds
Chromium Compounds
Chromium Compounds
Chromium Compounds
Polycyclic Organic Matter as 7-PAH
Coke Oven Emissions
Cobalt Compounds
Cobalt Compounds
Cobalt Compounds
Cobalt Compounds
Cobalt Compounds
Cobalt Compounds
Cobalt Compounds
Cobalt Compounds
Coke Oven Emissions
Cyanide Compounds
Cresol/Cresylic Acid (Mixed Isomers)
NEI Pollutant Name
Phosphorothioic Acid
Barium Chromate
Calcium Chromate
Lead Chromate
Strontium Chromate
Chromic Sulfuric Acid
Chromic Acid
Chromic Acid (VI)
Chromium
Chromium & Compounds
Chromium Chloride
Chromyl Fluoride
Chromium Dioxide
Chromium Zinc Oxide
Zinc Chromite
Chromium III
Chromium (III)-AA
Chromium Hydroxide
Chromic Oxide
Chromium (VI)
Chromyl Chloride
Chromium Trioxide
Chrysene
Coal Tar
Cobalt
Cobalt & Compounds
Cobalt Hydrocarbonyl
Cobalt Naphtha
Cobalt Oxide (1 1, 1 1 1)
Cobalt Oxide
Cobalt Sulfide
Cobalt Carbonate
Coke Oven Emissions
Copper Cyanide
Cresol
CASRN
2921-88-2
10294-40-3
13765-19-0
7758-97-6
7789-06-2
No CAS Number
7738-94-5
7738-94-5
7440-47-3
No CAS Number
10060-12-5
7788-96-7
12018-01-8
12018-19-8
50922-29-7
16065-83-1
21679-31-2
1308-14-1
1308-38-9
18540-29-9
14977-61-8
1333-82-0
218-01-9
8007-45-2
7440-48-4
No CAS Number
16842-03-8
61789-51-3
1308-06-1
1307-96-6
1317-42-6
16842-03-8
No CAS Number
544-92-3
1319-77-3
April 2004
PageF-7
-------
Appendix F. Specific HAPs Included in the NEI
EPAChemRegistryName
Cresol
Cumene
Cyanamide, calcium salt (1:1)
Cyanide
Cyanide and compounds
Cyclonaphthenes
Di(2-ethylhexyl) phthalate
Diazomethane
Dibenz[a,h]anthracene
Dibenz[a,j]acridine
Dibenzo[a,e]pyrene
Dibenzo[a,h]pyrene
Dibenzo[a,i]pyrene
Dibenzo[a,l]pyrene
Dibenzofuran
Dibenzo-p-dioxin
Dibutyl phthalate
Dichlorvos
Diethanolamine
Diethyl sulfate
Diethylene glycol dibenzoate
Diethylene glycol diethyl ether
Diethylene glycol diglycidyl ether
Diethylene glycol dimethyl ether
Diethylene glycol dinitrate
Diethylene glycol ethyl methyl ether
Diethylene glycol mono-2-cyanoethyl ether
Diethylene glycol mono-2-methylpentyl ether
Diethylene glycol monobutyl ether
Diethylene glycol monobutyl ether acetate
NEI HAP Category
Cresol/Cresylic Acid (Mixed Isomers)
Cumene
Calcium Cyanamide
Cyanide Compounds
Cyanide Compounds
Polycyclic Organic Matter
Bis(2-Ethylhexyl)Phthalate(Dehp)
Diazomethane
Polycyclic Organic Matter as 7-PAH
Polycyclic Organic Matter
Polycyclic Organic Matter
Polycyclic Organic Matter
Polycyclic Organic Matter
Polycyclic Organic Matter
Dibenzofuran
Dioxins/Furans (total, non TEQ)
Dibutyl Phthalate
Dichlorvos
Diethanolamine
Diethyl Sulfate
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
NEI Pollutant Name
Cresols (Includes o, m, &
p)/Cresylic Acids
Cumene
Calcium Cyanamide
Cyanide
Cyanide & Compounds
Naphthenes (Cyclo)
Bis(2-Ethylhexyl)Phthalate
Diazomethane
Dibenzo[a,h]Anthracene
Dibenzo[a,j]Acridine
Dibenzo[a,e]Pyrene
Dibenzo[a,h]Pyrene
Dibenzo[a,i]Pyrene
Dibenzo[a,l]Pyrene
Dibenzofuran
Dibenzo-p-Dioxin
Dibutyl Phthalate
Dichlorvos
Diethanolamine
Diethyl Sulfate
Diethylene Glycol Dibenzoate
Diethylene glycol diethyl ether
Diethylene Glycol Diglycidyl Ether
Diethylene Glycol Dimethyl Ether
Diethylene Glycol Dinitrate
Diethylene Glycol Ethyl Methyl
Ether
Diethylene Glycol Mono-2-
Cyanoethyl Ether
Diethyleneglycol-Mono-2-Methyl-
Pentyl Ether
Diethylene Glycol Monobutyl Ether
Butyl Carbitol Acetate
CASRN
1319-77-3
98-82-8
156-62-7
57-12-5
No CAS Number
No CAS Number
117-81-7
334-88-3
53-70-3
224-42-0
192-65-4
189-64-0
189-55-9
191-30-0
132-64-9
262-12-4
84-74-2
62-73-7
111-42-2
64-67-5
120-55-8
112-36-7
4206-61-5
111-96-6
693-21-0
1002-67-1
10143-54-1
10143-56-3
112-34-5
124-17-4
April 2004
Page F-8
-------
Appendix F. Specific HAPs Included in the NEI
EPAChemRegistryName
Diethylene glycol monoethyl ether
Diethylene glycol monoethyl ether acetate
Diethylene glycol monohexyl ether
Diethylene glycol monoisobutyl ether
Diethylene glycol monomethyl ether
Diethylene glycol monovinyl ether
Dimethyl mercury
Dimethyl phthalate
Dimethyl sulfate
Dimethylcarbamoyl chloride
Dioxins
Epichlorohydrin
Ethanol, 2-(phenylmethoxy)-
Ethene, [2-(2-ethoxyethoxy)ethoxy]-
Ethene, 1,1'-[oxybis(2,1-ethanediyloxy)]bis-
Ethyl acrylate
Ethylbenzene
Ethylene dibromide
Ethylene glycol
Ethylene glycol bis(2,3-epoxy-2-methylpropyl)
ether
Ethylene glycol diallyl ether
Ethylene glycol diethyl ether
Ethylene glycol dimethyl ether
Ethylene glycol mono-2,6,8-trimethyl-4-nonyl
ether
Ethylene glycol mono-2-methylpentyl ether
Ethylene glycol monobutyl ether
NEI HAP Category
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Mercury Compounds
Dimethyl Phthalate
Dimethyl Sulfate
Dimethylcarbamoyl Chloride
Dioxins/Furans (total, non TEQ)
Epichlorohydrin (1-Chloro-2,3-
Epoxypropane)
Glycol Ethers
Glycol Ethers
Glycol Ethers
Ethyl Acrylate
Ethylbenzene
Ethylene Dibromide (Dibromoethane)
Ethylene Glycol
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
NEI Pollutant Name
Diethylene Glycol Monoethyl Ether
Carbitol Acetate
N-Hexyl Carbitol
Diethylene Glycol Monoisobutyl
Ether
Diethylene Glycol Monomethyl
Ether
Diethylene Glycol Monovinyl Ether
Methyl Mercury
Dimethyl Phthalate
Dimethyl Sulfate
Dimethylcarbamoyl Chloride
Dioxins
1 -Chloro-2,3-Epoxypropane
Ethylene Glycol Monobenzyl Ether
Diethylene Glycol Ethylvinyl Ether
Diethylene Glycol Divinyl Ether
Ethyl Acrylate
Ethyl Benzene
Ethylene Dibromide
Ethylene Glycol
Ethylene Glycol Bis(2,3-Epoxy-2-
Methylpropyl) Ether
Ethylene Glycol Diallyl Ether
Ethylene Glycol Diethyl Ether
1 ,2-Dimethoxyethane
Ethyleneglycolmono-2,6,8-
Trimethyl-4-Nonyl Ether
Ethyleneglycol Mono-2-
Methylpentyl Ether
Butyl Cellosolve
CASRN
111-90-0
112-15-2
112-59-4
18912-80-6
111-77-3
929-37-3
593-74-8
131-11-3
77-78-1
79-44-7
No CAS Number
106-89-8
622-08-2
10143-53-0
764-99-8
140-88-5
100-41-4
106-93-4
107-21-1
3775-85-7
7529-27-3
629-14-1
110-71-4
10137-98-1
10137-96-9
111-76-2
April 2004
Page F-9
-------
Appendix F. Specific HAPs Included in the NEI
EPAChemRegistryName
Ethylene glycol monobutyl ether acetate
Ethylene glycol monoethyl ether acetate
Ethylene glycol monohexyl ether
Ethylene glycol monoisobutyl ether
Ethylene glycol monomethyl ether acetate
Ethylene glycol monomethyl ether acrylate
Ethylene glycol monophenyl ether
Ethylene glycol monophenyl ether propionate
Ethylene glycol monopropyl ether
Ethylene glycol mono-sec-butyl ether
Ethylene glycol monovinyl ether
Ethylene oxide
Ethylene thiourea
Ethylenebis(oxyethylenenitrilo)tetraacetic acid
Extractable organic matter (EOM)
Fine mineral fibers
Fine mineral fibers
Fine mineral fibers
Fine mineral fibers
Fluoranthene
Fluorene
Formaldehyde
Glycol ethers -CAA112B
Gold cyanide
Heptachlor
Heptachlorodibenzofuran
Heptachlorodibenzo-p-dioxin
Hexachlorobenzene
Hexachlorobutadiene
Hexachlorocyclopentadiene
NEI HAP Category
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Ethylene Oxide
Ethylene Thiourea
Glycol Ethers
Polycyclic Organic Matter
Fine Mineral Fibers
Fine Mineral Fibers
Fine Mineral Fibers
Fine Mineral Fibers
Polycyclic Organic Matter as 1 5-PAH
Polycyclic Organic Matter as 1 5-PAH
Formaldehyde
Glycol Ethers
Cyanide Compounds
Heptachlor
Dioxins/Furans (total, non TEQ)
Dioxins/Furans (total, non TEQ)
Hexachlorobenzene
Hexachlorobutadiene
Hexachlorocyclopentadiene
NEI Pollutant Name
2-Butoxyethyl Acetate
Cellosolve Acetate
2-(Hexyloxy)Ethanol
Isobutyl Cellosolve
Ethylene Glycol Monomethyl Ether
Acetate
Methyl Cellosolve Acrylate
Phenyl Cellosolve
Ethyleneglycol Monophenyl Ether
Propionate
Propyl Cellosolve
Ethylene Glycol Mono-Sec-Butyl
Ether
Ethylene Glycol Monovinyl Ether
Ethylene Oxide
Ethylene Thiourea
(Ethylenebis(Oxyethylenenitrilo))
Tetraacetic Acid
Extractable Organic Matter (EOM)
Fine Mineral Fibers
Glasswool (Man-Made Fibers)
Slagwool (Man-Made Fibers)
Rockwool (Man-Made Fibers)
Fluoranthene
Fluorene
Formaldehyde
Glycol Ethers
Gold Cyanide
Heptachlor
Total Heptachlorodibenzofuran
Total Heptachlorodibenzo-p-Dioxin
Hexachlorobenzene
Hexachlorobutadiene
Hexachlorocyclopentadiene
CASRN
112-07-2
111-15-9
112-25-4
4439-24-1
110-49-6
3121-61-7
122-99-6
23495-12-7
2807-30-9
7795-91-7
764-48-7
75-21-8
96-45-7
67-42-5
No CAS Number
No CAS Number
No CAS Number
No CAS Number
No CAS Number
206-44-0
86-73-7
50-00-0
No CAS Number
37187-64-7
76-44-8
38998-75-3
37871-00-4
118-74-1
87-68-3
77-47-4
April 2004
Page F-10
-------
Appendix F. Specific HAPs Included in the NEI
EPAChemRegistryName
Hexachlorodibenzofuran
Hexachlorodibenzo-p-dioxin
Hexachlorodibenzo-p-dioxin
Hexachloroethane
Hexamethylene-1 ,6-diisocyanate
Hexamethylphosphoramide
Hexane
Hexanoic acid, 2-ethyl-, cobalt(2+) salt
Hydrazine
Hydrochloric acid
Hydrofluoric acid
Hydrogen cyanide
Hydroquinone
lndeno[1 ,2,3-cd]pyrene
lodine-131
Isobutyronitrile
Isophorone
Lead
Lead acetate
Lead and compounds
Lead and compounds (other than inorganic)
Lead and compounds, inorganic
Lead arsenite (Pb(AsO2)2)
Lead chromate(VI) oxide
Lead dioxide
Lead dioxide
Lead monoxide
Lead naphthenate
Lead nitrate (Pb(NO3)2)
Lead oxide
Lead stearate
Lead tetraoxide
Lead titanium oxide (PbTiOS)
NEI HAP Category
Dioxins/Furans (total, non TEQ)
Dioxins/Furans (total, non TEQ)
Dioxins/Furans (total, non TEQ)
Hexachloroethane
Hexamethylene Diisocyanate
Hexamethylphosphoramide
Hexane
Cobalt Compounds
Hydrazine
Hydrochloric Acid (Hydrogen Chloride
[Gas Only])
Hydrogen Fluoride (Hydrofluoric Acid)
Cyanide Compounds
Hydroquinone
Polycyclic Organic Matter as 7-PAH
Radionuclides (Including Radon)
Cyanide Compounds
Isophorone
Lead Compounds
Lead Compounds
Lead Compounds
Lead Compounds
Lead Compounds
Lead Compounds
Lead Compounds
Lead Compounds
Lead Compounds
Lead Compounds
Lead Compounds
Lead Compounds
Lead Compounds
Lead Compounds
Lead Compounds
Lead Compounds
NEI Pollutant Name
Total Hexachlorodibenzofuran
Hexachlorodibenzo-p-Dioxin
Hexachlorodibenzo-p-Dioxins,
Total
Hexachloroethane
Hexamethylene Diisocyanate
Hexamethylphosphoramide
Hexane
Cobalt 2-ethylhexanoate
Hydrazine
Hydrochloric Acid
Hydrogen Fluoride
Hydrogen Cyanide
Hydroquinone
lndeno[1 ,2,3-c,d]Pyrene
lodine-131
2-Methyl-Propanenitrile
Isophorone
Lead
Lead Subacetate
Lead & Compounds
Lead Compounds (Other Than
Inorganic)
Lead Compounds (Inorganic)
Lead Arsenite
Lead Chromate Oxide
Lead Dioxide
Lead Dioxide, Unknown CAS #
Lead (II) Oxide
Lead Naphthenate
Lead Nitrate
Lead Oxide
Lead Stearate
Lead (II, IV) Oxide
Lead Titanate
CASRN
55684-94-1
34465-46-8
34465-46-8
67-72-1
822-06-0
680-31-9
110-54-3
136-52-7
302-01-2
7647-01-0
7664-39-3
74-90-8
123-31-9
193-39-5
10043-66-0
78-82-0
78-59-1
7439-92-1
1335-32-6
No CAS Number
No CAS Number
No CAS Number
10031-13-7
18454-12-1
1309-60-0
1309-60-0
1317-36-8
61790-14-5
10099-74-8
1335-25-7
7428-48-0
1314-41-6
12060-00-3
April 2004
Page F-11
-------
Appendix F. Specific HAPs Included in the NEI
EPAChemRegistryName
Lead titanium zirconium oxide (Pb(Ti,Zr)O3)
Lead (II) acetate
Lindane
Lithium chromate
Maleic anhydride
Manganese
Manganese and compounds
Manganese dioxide
Manganese naphthenate
Manganese tallate
Manganese tetraoxide
Manganese(ll) hypophosphite monohydrate
Manganese(lll) oxide
m-Cresol
Mercuric chloride
Mercury
Mercury
Mercury and compounds
Mercury, divalent
Mercury, divalent
Methanol
Methoxychlor
Methyl bromide
Methyl cellosolve acetyl ricinoleate
Methyl ethyl ketone
Methyl hydrazine
Methyl iodide
Methyl isobutyl ketone
Methyl isocyanate
Methyl methacrylate
Methyl tert-butyl ether
Methylanthracene
Methylbenzopyrene
NEI HAP Category
Lead Compounds
Lead Compounds
1 ,2,3,4,5,6-Hexachlorocyclyhexane (All
Stereo Isomers, Including Lindane)
Chromium Compounds
Maleic Anhydride
Manganese Compounds
Manganese Compounds
Manganese Compounds
Manganese Compounds
Manganese Compounds
Manganese Compounds
Manganese Compounds
Manganese Compounds
Cresol/Cresylic Acid (Mixed Isomers)
Mercury Compounds
Mercury Compounds
Mercury Compounds
Mercury Compounds
Mercury Compounds
Mercury Compounds
Methanol
Methoxychlor
Methyl Bromide (Bromomethane)
Glycol Ethers
Methyl Ethyl Ketone (2-Butanone)
Methylhydrazine
Methyl Iodide (lodomethane)
Methyl Isobutyl Ketone (Hexone)
Methyl Isocyanate
Methyl Methacrylate
Methyl Tert-Butyl Ether
Polycyclic Organic Matter
Polycyclic Organic Matter
NEI Pollutant Name
Lead Titanate Zircon
Lead Acetate
1,2,3,4,5,6-Hexachlorocyclyhexane
Lithium Chromate
Maleic Anhydride
Manganese
Manganese & Compounds
Manganese Dioxide
Manganese Napthenate
Manganese Tallate
Manganese Tetroxide
Manganesehypophosphi
Manganese Trioxide
m-Cresol
Mercuric Chloride
Elemental Gaseous Mercury
Mercury
Mercury & Compounds
Gaseous Divalent Mercury
Particulate Divalent Mercury
Methanol
Methoxychlor
Methyl Bromide
Methyl Cellosolve Acetylricinoleate
Methyl Ethyl Ketone
Methylhydrazine
Methyl Iodide
Methyl Isobutyl Ketone
Methyl Isocyanate
Methyl Methacrylate
Methyl Tert-Butyl Ether
Methylanthracene
Methylbenzopyrenes
CASRN
12626-81-2
301-04-2
58-89-9
14307-35-8
108-31-6
7439-96-5
No CAS Number
1313-13-9
1336-93-2
8030-70-4
1317-35-7
7783-16-6
1317-34-6
108-39-4
7487-94-7
7439-97-6
7439-97-6
No CAS Number
14302-87-5
14302-87-5
67-56-1
72-43-5
74-83-9
140-05-6
78-93-3
60-34-4
74-88-4
108-10-1
624-83-9
80-62-6
1634-04-4
26914-18-1
65357-69-9
April 2004
Page F-12
-------
Appendix F. Specific HAPs Included in the NEI
EPAChemRegistryName
Methylchrysene
Methylene chloride
Methylene chloride soluble organics
Methylmercury
m-Xylene
N,N-Dimethylaniline
N,N-Dimethylformamide
Naphthalene
Neodecanoic acid, lead salt
Nickel
Nickel and compounds
Nickel carbide
Nickel carbonyl
Nickel diacetate tetrahydrate
Nickel hydroxide (Ni(OH)2)
Nickel refinery dust
Nickel subsulfide
Nickel(ll) acetate
Nickel(ll) bromide
Nickel(ll) chloride
Nickel(ll) nitrate
Nickel(ll) oxide
Nickel(lll) oxide
Nickel-59
Nickelate(2-), tetrakis(cyano-. kappa. C)-,
dipotassium, (SP-4-1)-
Nickelocene
Nitric acid, manganese(2+) salt
Nitrobenzene
N-Nitrosodimethylamine
N-Nitrosomorpholine
N-Nitroso-N-methylurea
o-Anisidine
o-Cresol
NEI HAP Category
Polycyclic Organic Matter
Methylene Chloride (Dichloromethane)
Coke Oven Emissions
Mercury Compounds
Xylenes (Mixed Isomers)
N,N-Dimethylaniline
N,N-Dimethylformamide
Naphthalene
Lead Compounds
Nickel Compounds
Nickel Compounds
Nickel Compounds
Nickel Compounds
Nickel Compounds
Nickel Compounds
Nickel Compounds
Nickel Compounds
Nickel Compounds
Nickel Compounds
Nickel Compounds
Nickel Compounds
Nickel Compounds
Nickel Compounds
Nickel Compounds
Cyanide Compounds
Nickel Compounds
Manganese Compounds
Nitrobenzene
N-Nitrosodimethylamine
N-Nitrosomorpholine
N-Nitroso-N-Methylurea
o-Anisidine
Cresol/Cresylic Acid (Mixed Isomers)
NEI Pollutant Name
Methylchrysene
Methylene Chloride
Methylene Chloride Soluble
Organics (MCSO)
Mercury (Organic)
m-Xylene
N,N-Dimethylaniline
N,N-Dimethylformamide
Naphthalene
Lead Neodecanoate
Nickel
Nickel & Compounds
Nickel Carbide
Nickel Carbonyl
Nickel Diacetate TET
Nickel Hydroxide
Nickel Refinery Dust
Nickel Subsulfide
Nickel Acetate
Nickel Bromide
Nickel Chloride
Nickel Nitrate
Nickel Oxide
Nickel Peroxide
Nickel (Nl 059)
Potass Nickel Cyanid
Nickelocene
Manganese Nitrate
Nitrobenzene
N-Nitrosodimethylamine
N-Nitrosomorpholine
N-Nitroso-N-Methylurea
o-Anisidine
o-Cresol
CASRN
41637-90-5
75-09-2
No CAS Number
22967-92-6
108-38-3
121-69-7
68-12-2
91-20-3
27253-28-7
7440-02-0
No CAS Number
12710-36-0
13463-39-3
6018-89-9
12054-48-7
No CAS Number
12035-72-2
373-02-4
13462-88-9
7718-54-9
13138-45-9
1313-99-1
1314-06-3
14336-70-0
14220-17-8
1271-28-9
10377-66-9
98-95-3
62-75-9
59-89-2
684-93-5
90-04-0
95-48-7
April 2004
Page F-13
-------
Appendix F. Specific HAPs Included in the NEI
EPAChemRegistryName
o-Toluidine
o-Xylene
p,p'-DDE
Parathion
p-Cresol
Pentachlorodibenzofuran
Pentachlorodibenzo-p-dioxin
Pentachloronitrobenzene
Pentachlorophenol
Perylene
Phenanthrene
Phenol
Phenylmercury acetate
Phosgene
Phosphine
Phosphoric acid
Phosphoric acid, lead(2+) salt (2:3)
Phosphoric acid, monoammonium monosodium
salt
Phosphoric acid, reaction products with
aluminum hydroxide and chromium oxide
(CrO3)
Phosphoric acid, zinc salt (2:3)
Phosphorous acid
Phosphorus
Phosphorus and compounds
Phosphorus nitride (P3N5)
Phosphorus oxychloride
Phosphorus pentasulfide
Phosphorus pentoxide
Phosphorus trichloride
Phosphorus trioxide
Phthalic anhydride
NEI HAP Category
o-Toluidine
Xylenes (Mixed Isomers)
Dde (1,1-Dichloro-2,2-Bis(p-
Chlorophenyl) Ethylene)
Parathion
Cresol/Cresylic Acid (Mixed Isomers)
Dioxins/Furans (total, non TEQ)
Dioxins/Furans (total, non TEQ)
Pentachloronitrobenzene
(Quintobenzene)
Pentachlorophenol
Polycyclic Organic Matter
Polycyclic Organic Matter as 1 5-PAH
Phenol
Mercury Compounds
Phosgene
Phosphine
Phosphorus Compounds
Lead Compounds
Phosphorus Compounds
Phosphorus Compounds
Phosphorus Compounds
Phosphorus Compounds
Phosphorus Compounds
Phosphorus Compounds
Phosphorus Compounds
Phosphorus Compounds
Phosphorus Compounds
Phosphorus Compounds
Phosphorus Compounds
Phosphorus Compounds
Phthalic Anhydride
NEI Pollutant Name
o-Toluidine
o-Xylene
Dde(1,1-Dichloro-2,2-Bis(p-
Chlorophenyl) Ethylene)
Parathion
p-Cresol
Total Pentachlorodibenzofuran
Total Pentachlorodibenzo-p-Dioxin
Pentachloronitrobenzene
Pentachlorophenol
Perylene
Phenanthrene
Phenol
Mercury Acetato Phen
Phosgene
Phosphine
Phosphoric Acid
Lead Phosphate
Phosphorous Salt
Phosphoric Acid,Rx P
Zinc Phosphate
Phosphorous Acid
Phosphorus
Phosphorus & Compounds
Phosphorous Nitride
Phosphorus Oxychloride
Phosphorus Pentasulfide
Phosphorus Pentoxide
Phosphorus Trichloride
Phosphorus Trioxide
Phthalic Anhydride
CASRN
95-53-4
95-47-6
72-55-9
56-38-2
106-44-5
30402-15-4
36088-22-9
82-68-8
87-86-5
198-55-0
85-01-8
108-95-2
62-38-4
75-44-5
7803-51-2
7664-38-2
7446-27-7
13011-54-6
92203-02-6
7779-90-0
10294-56-1
7723-14-0
No CAS Number
12136-91-3
10025-87-3
1314-80-3
1314-56-3
7719-12-2
1314-24-5
85-44-9
April 2004
Page F-14
-------
Appendix F. Specific HAPs Included in the NEI
EPAChemRegistryName
Polycyclic aromatic hydrocarbons
Polycyclic aromatic hydrocarbons - 16-PAH
Polycyclic aromatic hydrocarbons - 7-PAH
Polycyclic organic matter- including 15-PAH
Potassium chromate (VI)
Potassium cyanide
Potassium dichromate
Potassium ferrocyanide
Potassium permanganate
Potassium zinc chromate hydroxide
(KZn2(Cr04)2(OH))
p-Phenylenediamine
Propionaldehyde
Propoxur
Propylene glycol monoisobutyl ether
Propylene oxide
Propyleneimine
p-Xylene
Pyrene
Quinoline
Quinone
Radionuclides (including radon)
Radionuclides (including radon)
Radon and its decay products
Selenious acid (H2SeO3)
Selenium
Selenium and compounds
Selenium dioxide
Selenium disulfide
Selenium hexafluoride
Selenium monosulfide
Selenium oxide
Silver cyanide
Sodium chromate (VI)
Sodium chromate(VI), tetrahydrate
Sodium cyanide
NEI HAP Category
Polycyclic Organic Matter as 7-PAH
Polycyclic Organic Matter
Polycyclic Organic Matter as 7-PAH
Polycyclic Organic Matter as 7-PAH
Chromium Compounds
Cyanide Compounds
Chromium Compounds
Cyanide Compounds
Manganese Compounds
Chromium Compounds
p-Phenylenediamine
Propionaldehyde
Propoxur (Baygon)
Glycol Ethers
Propylene Oxide
1 ,2-Propylenimine (2-Methylaziridine)
Xylenes (Mixed Isomers)
Polycyclic Organic Matter as 1 5-PAH
Quinoline
Quinone (p-Benzoquinone)
Radionuclides (Including Radon)
Radionuclides (Including Radon)
Radionuclides (Including Radon)
Selenium Compounds
Selenium Compounds
Selenium Compounds
Selenium Compounds
Selenium Compounds
Selenium Compounds
Selenium Compounds
Selenium Compounds
Cyanide Compounds
Chromium Compounds
Chromium Compounds
Cyanide Compounds
NEI Pollutant Name
PAH, Total
16-PAH
7-PAH
Polycyclic Organic Matter
Potassium Chromate
Potassium Cyanide
Potassium Dichromate
Potassium Ferrocyani
Potassium permanganate
Zinc Potassium Chromate
p-Phenylenediamine
Propionaldehyde
Propoxur
1 -lsobutoxy-2-Propanol
Propylene Oxide
1,2-Propylenimine
p-Xylene
Pyrene
Quinoline
Quinone
Radionuclides (Including Radon)
Radionuclides
Radon And Its Decay Products
Selenous Acid
Selenium
Selenium & Compounds
Selenium Dioxide
Selenium Disulfide
Selenium Hexafluoride
Selenium Monosulfide
Selenium Oxide
Silver Cyanide
Sodium Chromate
Sodium Chromate(VI)
Sodium Cyanide
CASRN
130498-29-2
No CAS Number
No CAS Number
No CAS Number
7789-00-6
151-50-8
7778-50-9
13943-58-3
7722-64-7
11103-86-9
106-50-3
123-38-6
114-26-1
23436-19-3
75-56-9
75-55-8
106-42-3
129-00-0
91-22-5
106-51-4
No CAS Number
No CAS Number
No CAS Number
7783-00-8
7782-49-2
No CAS Number
7446-08-4
7488-56-4
7783-79-1
7446-34-6
12640-89-0
506-64-9
7775-11-3
10034-82-9
143-33-9
April 2004
Page F-15
-------
Appendix F. Specific HAPs Included in the NEI
EPAChemRegistryName
Sodium dichromate
Sodium permanganate
Styrene
Styrene oxide
Sulfamic acid, nickel(2+) salt (2:1)
Sulfuric acid, beryllium salt (1 :1)
Sulfuric acid, cadmium salt (1 :1)
Sulfuric acid, chromium(3+) salt (3:2)
Sulfuric acid, cobalt(2+) salt (1:1)
Sulfuric acid, lead(2+) salt (1:1)
Sulfuric acid, manganese(2+) salt (1:1)
Sulfuric acid, nickel(2+) salt (1 :1)
Sulfuric acid, nickel(2+) salt (1:1), hexahydrate
Tetrachlorodibenzofuran
Tetrachlorodibenzo-p-dioxin
Tetrachloroethylene
Tetraethyl lead
Titanium tetrachloride
Toluene
Toluene-2,4-diisocyanate
Toxaphene
Tribromomethane
Trichloroethylene
Triethylamine
Triethylene glycol
Triethylene glycol dimethyl ether
Triethylene glycol monobutyl ether
Triethylene glycol monoethyl ether
Triethylene glycol monomethyl ether
Trifluralin
Trimethylene glycol monomethyl ether
Tri-o-cresyl phosphate
Triphenyl phosphate
NEI HAP Category
Chromium Compounds
Manganese Compounds
Styrene
Styrene Oxide
Nickel Compounds
Beryllium Compounds
Cadmium Compounds
Chromium Compounds
Cobalt Compounds
Lead Compounds
Manganese Compounds
Nickel Compounds
Nickel Compounds
Dioxins/Furans (total, non TEQ)
Dioxins/Furans (total, non TEQ)
Tetrachloroethylene (Perchloroethylene)
Lead Compounds
Titanium Tetrachloride
Toluene
2,4-Toluene Diisocyanate
Toxaphene (Chlorinated Camphene)
Bromoform
Trichloroethylene
Triethylamine
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Glycol Ethers
Trifluralin
Glycol Ethers
Phosphorus Compounds
Phosphorus Compounds
NEI Pollutant Name
Sodium Dichromate
Permanganic acid
Styrene
Styrene Oxide
Nickel Sulfamate
Beryllium Sulfate
Cadmium Sulfate
Chromic Sulfate
Cobalt Sulfate
Lead Sulfate
Manganese Sulfate
Nickel Sulfate
Nickel (II) Sulfate Hexahydrate
Total Tetrachlorodibenzofuran
Total Tetrachlorodibenzo-p-Dioxin
Tetrachloroethylene
Tetraethyl Lead
Titanium Tetrachloride
Toluene
2,4-Toluene Diisocyanate
Toxaphene
Bromoform
Trichloroethylene
Triethylamine
Triethylene glycol
Triethylene Glycol Dimethyl Ether
Triglycol Monobutyl Ether
Ethoxytriglycol
Methoxytriglycol
Trifluralin
3-Methoxy-1 -Propanol
Triorthocresyl Phosphate
Triphenyl Phosphate
CASRN
10588-01-9
10101-50-5
100-42-5
96-09-3
13770-89-3
13510-49-1
10124-36-4
10101-53-8
10124-43-3
7446-14-2
7785-87-7
7786-81-4
10101-97-0
30402-14-3
41903-57-5
127-18-4
78-00-2
7550-45-0
108-88-3
584-84-9
8001-35-2
75-25-2
79-01-6
121-44-8
112-27-6
112-49-2
143-22-6
112-50-5
112-35-6
1582-09-8
1589-49-7
78-30-8
115-86-6
April 2004
Page F-16
-------
Appendix F. Specific HAPs Included in the NEI
EPAChemRegistryName
NEI HAP Category
Triphenyl phosphite Phosphorus Compounds
Uranium-238 Radionuclides (Including Radon)
Urethane
Vinyl acetate
Vinyl bromide
Vinyl chloride
Xylene
Zinc chromate
Zinc chromate
Zinc cyanide
Ethyl Carbamate (Urethane) Chloride
(Chloroethane)
Vinyl Acetate
Vinyl Bromide
Vinyl Chloride
Xylenes (Mixed Isomers)
Chromium Compounds
Chromium Compounds
Cyanide Compounds
"ield Definitions :
• "EPAChemRegistryName" (EPA Chemical Registry Name) - the name EPA has selected as 1
EPA in referring to a chemical substance
• "NEI HAP Category" - Grouping of related NEI pollutants
• "NEI Pollutant Name" - HAP name for NEI pollutant
• '^CASRN" (Chemical Abstracts Service Registry Number)- the unique number assigned by Ch
Service (CAS) to a chemical substance
Table from:
3PA. 2003. 1999 NEI Final Version 3 for Hazardous Air Pollutants Point, non point, and inol
1999NEI Final Version 3 for Hazardous Air Pollutants. HAPs list with chemical ID standard J
\vailable at http://www.epa.gov/ttn/chief/net/1999inventorv.htinltfflnal3haps
"ield Definitions from:
1 999 NEI Final Version 3 for Hazardous Air Pollutants Point, non point, and mobile sources (Se
he 1999 NEI Final Version 3 for Hazardous Air Pollutants.Readme file for HAPs list with chen
>003. Available at http://www.epa.gov/ttn/chief/net/1999inventorv.htniltfflnal3haps
NEI Pollutant Name
Triphenyl Phosphite
Uranium
Ethyl Carbamate Chloride
CASRN
101-02-0
7440-61-1
51-79-6
Vinyl Acetate 108-05-4
Vinyl Bromide (593-60-2
Vinyl Chloride
75-01-4
Xylenes (Mixture of o, m, and p
Isomers) 1330-20-7
Zinc Chromate
Zinc Chromate
Zinc Cyanide
he name to be commonly used by
emical Abstracts
He sources. Documentation for the
i elds- August 2003 OAQPS.
^ptember 2003). Documentation for
lical ID standard fields - August
13530-65-9
13530-65-9
557-21-1
April 2004
Page F-17
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Appendix G Atmospheric and Meteorological
Concepts Relevant to Dispersal,
Transport, and Fate of Air Toxics
Table of Contents
1.0 Structure and Composition of the Atmosphere 1
2.0 Atmospheric Energy 1
2.1 Solar Radiation and Differential Heating 1
2.2 Effects of Topography 3.
3.0 Atmospheric Motions 4
3.1 Horizontal Air Motions 4
3.2 Vertical Air Motions 5
4.0 Meteorological Data £
4.1 Wind Speed and Direction £
4.2 Other Important Meteorological Data 9
4.3 Sources of Meteorological Data 1J_
References 12
-------
-------
This Appendix defines and discusses atmospheric and meteorological concepts relevant to
modeling dispersion, transport, and fate of air toxics. In addition, this appendix provides
information on sources of meteorological data that can be used for air toxics modeling. Much of
this information was obtained from EPA's primer on air pollution meteorology (see
http://www.epa.gov/oar/oaqps/eog/catalog/si409.html). Basic textbooks on meteorology provide
more detailed discussions of the material summarized in this Appendix.
1.0 Structure and Composition of the Atmosphere
The atmosphere consists of mixture of about 78 percent nitrogen, 21 percent oxygen and one
percent argon up to about 90 km. Within this region trace gases include carbon dioxide, neon,
helium, and water vapor. Although the water vapor content of the air is fairly small it is highly
variable. Water vapor absorbs six times more radiation energy than any other atmospheric
constituent and is therefore a very important component of the atmosphere. Similarly, carbon
dioxide is highly variable and is important gas because it absorbs and re-radiates back some of
the infrared radiation emitted by the earth.
The atmosphere has been divided into four regions (Exhibit 1) based on temperature changes
with height: the troposphere, stratosphere, mesosphere, and ionosphere. The troposphere
accounts for about three quarters of the mass of the atmosphere and contains nearly all of the
water in the atmosphere (in the forms of vapor, clouds, and precipitation). The depth of the
troposphere is on average about 16.5 km (54,000 ft) over the equator and about 8.5 km (28,000
ft) over the poles. The troposphere also tends to be thicker in summer (when the air is warmer)
than in the winter. The depth of the troposphere changes constantly due to changes in
atmospheric temperature. The troposphere is the most important layer of the atmosphere with
respect to air toxics, because this is the region in which most of the air toxics are released. Of the
other regions of the atmosphere only the stratosphere has a direct role for some air toxics. Some
air toxic emissions can be circulated into the lower stratosphere via weather system or directly
emitted from aircraft or volcanic eruption. Once air toxics reach the stratosphere they maybe
transported very long distances.
2.0 Atmospheric Energy
The troposphere is the most variable layer of the atmosphere and is the layer where weather
occurs. It is where air masses, weather fronts, and storms reside. Weather conditions are
governed by a number of factors, including solar radiation, atmospheric circulation, water vapor
and topography. However, the underlying driving force in all cases is the radiant energy from the
sun.
2.1 Solar Radiation and Differential Heating
The amount of incident sunlight influences the heating of the surface of the earth and the
overlying atmosphere. The radiation received directly from the sun is called solar radiation.
The amount of incoming solar radiation received at a particular time and location (insolation) on
the earth is governed by:
April 2004 Page G-l
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Exhibit 1. Structure of the Atmosphere
Ozone Layer
Tropopause
• The transparency of the atmosphere (for example, clouds reflect solar radiation);
• Hours of daylight; and
• The angle at which the sun's rays strike the earth.
The earth's surface absorbs short-wave solar radiation and emits longer wavelength terrestrial
radiation. In the atmosphere, clouds, water vapor, and to a lesser extent carbon dioxide absorb
terrestrial radiation, which causes the atmosphere to warm. The atmosphere absorbs much more
terrestrial radiation than solar radiation. The atmosphere also radiates energy to outer space and
back to the earth's surface. The earth-atmosphere system emits terrestrial radiation continuously.
The atmospheric absorption of terrestrial radiation benefits the earth by retaining energy that
would otherwise be radiated to space. This phenomenon explains how air temperatures are
generally warmer on nights when cloud cover is present. The greenhouse effect is the
descriptive name given to the result of the energy exchange process that causes the earth's
surface to be warmer than it would be if the atmosphere did not radiate energy back to earth.
Gases such as carbon dioxide and methane (and other similarly behaving gases often called
greenhouse gases) also increase the ability of the atmosphere to absorb radiation (Exhibit 2).
The amount of solar radiation reaching the earth's surface varies from place to place. In addition,
different types of earth surfaces (and man-made structures) vary in their ability to absorb and
store heat energy. For example, land masses absorb and store heat differently than water masses.
The color, shape, surface texture, vegetation and presence of buildings can all influence the
heating and cooling of the ground. Generally, dry surfaces heat and cool faster than moist
April 2004
Page G-2
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surfaces. Plowed fields, sandy beaches, and paved roads become hotter than surrounding
meadows and wooded areas. During the day, the air over a plowed field is warmer than over a
forest or swamp; during the night, the situation is reversed. The property of different surfaces
which causes them to heat and cool at different rates is referred to as differential heating.
Exhibit 2. The Greenhouse Effect
The Greenhouse Effect
ft
*7*
Some sdar radiation
re reflected dy the
earth and the
atmosphere
Some of he Infrared radiation passes
through the atmosphere, and some is
absorbed and re-emitted mall
directions by greenhouse gas
motecdes. The effect of tils is to warm
the earth's su rtace and the lower
atmosphere.
r/ost radiation is absorbed
by the earth's surface
and warms it
Source: EPA's "Global Warming Kids Site.
"(i)
Heat is transferred within the atmosphere by conduction, convection, and advection. These
processes affect the temperature of the atmosphere near the surface of the earth. Conduction is
the process by which heat is transferred through matter without movement of the matter itself.
For example, the handle of an iron skillet becomes hot due to the conduction of heat from the
stove burner. Conduction occurs from a warmer to a cooler object. Heat transfer also occurs due
to the movement of atmospheric gases. Meteorologists use the term convection to denote the
transfer of heat that occurs mainly by vertical motion. Air that is warmed by a heated land
surface will rise because it is lighter than the surrounding air. Likewise, cooler air aloft will sink
because it is heavier than the surrounding air. Meteorologists use the term advection to denote
heat transfer that occurs mainly by horizontal motion. All of these energy exchange processes,
particularly between the earth surface and the atmosphere, produce the complex atmospheric
motions of weather. As a result of these process air toxics maybe widely distributed far from
their location of origin.
2.2 Effects of Topography
The physical characteristics of the earth's surface are referred to as terrain features or
topography. Topography can be grouped into four general categories: flat, mountain/valley,
April 2004
Page G-3
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land/water, and urban. Topography also causes two types of turbulence in the atmosphere. As
noted above, topography causes thermal turbulence through differential heating. Topography
causes mechanical turbulence as the result of the wind flowing over different sizes and shapes
of objects. Physical features induce a frictional effect on wind speed and direction. For example,
urban settings with dense construction and tall buildings exert a strong frictional force on the
wind causing it to slow down, change direction, and become more turbulent.
Urban areas have a special effect on the atmosphere due to the high density of man-made
features. Building materials such as brick and concrete absorb and store heat more efficiently
than soil and vegetation found in rural areas. After sunset, the urban areas continue to radiate the
stored heat from buildings and paved surfaces. Air is warmed by this urban complex and rises to
create a dome (heat island) over an urban area. Large cities continue to emit heat throughout the
night and generally never completely cool down to the more stable surrounding conditions before
the sun rises and begins to heat the urban complex again. The overall effect of the urban
landscape is to increase the dispersion of air toxics through increased mixing.
3.0 Atmospheric Motions
The differential heating of the earth's surface causes imbalances in air pressure. The
atmospheric pressure at any point is due to the weight of the air pressing down from above due to
gravity. In any gas such as air, molecules are moving around in all directions at very high speeds.
The speed actually depends on the temperature of the gas. Air pressure is caused by the
molecules of atmospheric gases bumping into each other and other surfaces and bouncing off.
Air pressure is a function of the number of air molecules in a given volume and the speed at
which they are moving. When air is warmed, the molecules speed up, and air pressure increases.
As air cools, the molecules slow down, and air pressure decreases.
3.1 Horizontal Air Motions
Air moves in an attempt to equalize response to imbalances in pressure. The movement of air
(wind) tends to move from areas of high to low pressure. Wind is the basic element in the
general circulation of the atmosphere. Wind movements from small gusts to large air masses all
contribute to transport of heat, moisture and as well as air toxics around the earth. Winds are
always named by the direction from which they blow. Thus a "north wind" is a wind blowing
from the north to the south and a "westerly wind" blows from west to east. When wind blows
more frequently from one direction than from any other, the direction is termed the prevailing
wind. Section 4.1 provides further information on how meteorologists measure and describe
wind speed and direction.
Wind speed is heavily influenced by the presence or absence of friction ("drag") and increases
rapidly with height about the ground level. Wind is commonly not a steady current but is made
up of a succession of gusts, slightly variable in direction, separated by lulls. Close to the earth,
wind gustiness is caused by irregularities of the surface, which create eddies, which are
variations from the main current of wind flow. Larger irregularities are caused by convection
(vertical transport of heat). These and other forms of turbulence contribute to the movement of
heat, moisture, dust, and pollutants into the air. See Section 2.2 for additional information on
how topography affects air motions.
April 2004 Page G-4
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Air masses cover hundreds of thousands of square miles and extend upward for several miles.
They are relatively homogeneous volumes of air with regard to temperature and moisture, and
they acquire the characteristics of the region over which they form and travel. Pollutants released
into an air mass tend to travel and disperse within the air mass. Air masses develop more
commonly in some regions than in others. Air masses are classified as maritime or continental
according to their origin over ocean or land, and as arctic, polar, or tropical depending principally
on the latitude of origin. Continental polar air masses are similar to arctic air masses, but not as
cold and dry as arctic air masses. The chief air masses that affect the weather of North America
are continental polar, maritime polar, and maritime tropical.
Frontal patterns are formed by the interaction of adjacent air masses. A cold front is a transition
zone where a cold air mass is moving into the area previously occupied by a warm air mass. The
rise of warm air over an advancing cold front and the subsequent expansive cooling of this air
lead to cloud formation, and if sufficient moisture is available precipitation near the leading edge
of the front. A warm front is a transition zone where a warm air mass is moving into the area
previously occupied by a cold air mass. Precipitation commonly occurs in advance of a warm
front, as the warm air slowly rises above the cold air.
3.2 Vertical Air Motions
When air is displaced vertically, atmospheric behavior is a function of atmospheric stability. A
stable atmosphere resists vertical motion, and air that is displaced vertically in a stable
atmosphere tends to return to its original position. This atmospheric characteristic determines the
ability of the atmosphere to disperse pollutants. To understand atmospheric stability and the role
it plays in pollution dispersion, it is important to understand the mechanics of the atmosphere as
they relate to vertical atmospheric motion.
The degree of stability of the atmosphere is determined by the temperature difference between
an air parcel and the surrounding air. This difference can cause the parcel to rise or fall. There
are three general categories of atmospheric stability.
• In stable conditions, vertical movement tends not to occur. Stable conditions occur at
night when there is little or no wind. Air that is lifted vertically will remain cooler, and
therefore denser than the surrounding air. Once the lifting force is removed, the air that
has been lifted will return to its original position.
• Neutral conditions ("well mixed") neither encourage nor discourage air movement.
Neutral stability occurs on windy days or when there is cloud cover such that there is
neither strong heating nor cooling of the earth's surface. Air lifted vertically will
generally remain at the lifted height.
• In unstable conditions, the air parcel tends to move upward or downward and to continue
that movement. Unstable conditions most commonly develop on sunny days with low
wind speeds where strong solar radiation is present. The earth rapidly absorbs heat and
transfers some of it to the surface air layer. As warm air rises, cooler air moves
underneath. The cooler air, in turn, may be heated by the earth's surface and begin to
rise. Under such conditions, vertical motion in both directions is enhanced, and
considerable vertical mixing occurs.
April 2004 Page G-5
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Inversions occur whenever warm over-runs cold air and "traps" the cold air beneath. Within
these inversions there is little air motion, and the air becomes relatively stagnant. High air toxic
concentrations can occur within inversions due to the limited amount of mixing between the
"trapped" air and the surrounding atmosphere. Inversions can limit the volume of air into which
emissions are dispersed, even from tall stacks. Exhibit 3 illustrates the three major types of
inversions that are caused by different atmospheric interactions and can persist for different
amounts of time.
Most common is the radiation inversion, which occurs when the earth's surface cools rapidly.
As the earth cools, it also cools the layer of air close to the surface, which becomes trapped under
the layer of warmer air above. Radiation inversions usually occur in the late evening through the
early morning under clear skies with calm winds, when the cooling effect is greatest. In many
cases, solar radiation following sunrise results in vigorous vertical mixing, which breaks down
the inversion and disperses any trapped air pollutants. Under some conditions (e.g., thick fog),
the daily warming may not be strong enough to break down the inversion layer. Inversions
persisting for several days may lead to increased pollutant concentrations. This situation is most
likely to occur in an enclosed valley, where nocturnal, cool, downslope air movement can
reinforce a radiation inversion and encourage fog formation.
The subsidence inversion is almost always associated with high pressure systems. Air in a high
pressure system descends and flows outward in a clockwise rotation in the Northern Hemisphere.
As the air descends, the higher pressure present at lower altitudes enhances compression and
warming. The inversion layer thus formed is often elevated several hundred meters above the
ground surface during the day. At night, when the surface air cools, the base of the subsidence
inversion often descends, even to the ground. The clear, cloudless days characteristic of high
pressure systems encourage radiation inversions, so that there may be a surface inversion at night
and an elevated inversion during the day. Although the layer below the inversion may vary
diurnally, it will never become very deep. Subsidence inversions, unlike radiation inversions,
last a relatively long time. They are associated with both the semi permanent high pressure
systems centered on each ocean and the slow-moving high pressure systems that move generally
from west to east across the United States. When a high pressure system stagnates, pollutant
concentrations may become unusually high. The most severe air pollution episodes in the United
States have occurred either under a stagnant high pressure system (for example, New York in
November, 1966 and Pennsylvania in October, 1948) or under the eastern edge of the semi
permanent high pressure system associated with the Pacific Ocean (Los Angeles).
Advection inversions are associated with air masses moving across surfaces of different
temperatures than themselves. When warm air moves over a cold surface, the principles of
conduction and convection cool the air nearer to the surface, causing a surface-based inversion.
This inversion is most likely to occur in winter when warm air passes over snow cover or
extremely cold land. The same type of inversion can occur when air cooled by a cold surface,
such as the ocean, flows towards a warmer air mass, such as inland air in the summer.
April 2004 Page G-6
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Table 3. Types of Inversions
Radiation Inversion
Warmer air
Cooler air
Cool air becomes
trapped under a layer
of warm air.
Ground cools off at night;^
cools air next to It
r Heat transfers from air
y near ground to ground.
1
1
I
Large Scale Subsidence
Inversion
Warm air (inversion layer)
High pressure system
pushes air down. This
compression warms the
air and traps the cooler
air below it.
Trapped cool air
F
Air aloft sinks (subsides)
and warms from
compression
Advection Inversion
Example
Warm inland air
Cool air is more dense
than warm air, thus -
trapped under warm air
Cool ocean
April 2004
Page G-7
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4.0 Meteorological Data
Measuring and recording meteorological variables provides the necessary information to manage
the release of air contaminants into the atmosphere and to understand the transport and dispersion
of emitted air pollutants. The most useful data in air pollution studies are wind speed and
direction, ambient temperature and vertical temperature difference, solar radiation and mixing
height. For indirect exposure, precipitation data are needed as well. These same variables can be
used to make qualitative and quantitative predictions of ambient air toxic concentrations
resulting from the release of air toxics, and to conduct quantitative risk assessments.
4.1 Wind Speed and Direction
It is common to consider wind speed and wind direction as separate variables. Wind speed
determines the amount of initial dilution experienced by air toxics released into the atmosphere.
Wind speed also influences the height to which the toxics will rise after being released from an
elevated source - as wind increases, the air toxics are kept lower to the ground, allowing them to
impact the ground at shorter distances downwind.
Wind direction for meteorological purposes is defined as the direction from which the wind is
blowing. However, wind direction has both horizontal and vertical components. The horizontal
and vertical components of the wind direction can be measured with a bi-directional wind vane
or an anemometer.
Wind roses are often used to graphically depict the prevailing wind direction of an area. The
wind rose depicts the relative frequency of wind direction, typically on a 16-point compass, with
north, east, south, and west directions going clockwise. Each ring on the wind rose represents a
frequency of the total. The WINDROSE program, which calculates and prints a frequency
distribution for wind speed and wind direction for 36 (10 degree) sectors, can be obtained from
EPA.(2)
Exhibit 4 presents an example wind rose for Brownsville, Texas. The right hand shows that the
winds are predominantly from the south-southeasterly direction. The left hand side shows that
the strongest winds occur between 14 and 21 UTC (8 A.M. to 3 P.M. CST). On average, 2 P.M.
is the windiest time of day, averaging just over 15 knots (18 UTC). The shaded portion of the
bar shows the frequency of winds over 20 knots. At noon CST, winds are over 20 knots
approximately 15 percent of the time.
The distribution of pollutants is determined by the wind directions. A wind rose can provide
information regarding the percentage of time that the direction(s) and speed(s) associated with a
certain air quality can be expected over a time period. However, due to the influences of local
terrain, possible coastal effects, exposure of the instruments, and temporal variability of the wind,
the wind rose statistics from a nearby weather station may not always be representative of true
wind speed and direction for the area of concern.
April 2004 Page G-i
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Exhibit 4. Example of a Wind Rose
(yrs 61-90, 16,367 obs)
Z0±
15-
1 n -
Kt/% :
~i
—
r
r
r
r
r
f
mr
::::q
•
OOZ 03Z 06Z 09Z 12 Z 15Z 18Z 21Z
Mean hourly speed, freq of >2Qkt, and relative freq of dir.
Brownsville, TX
Source: Brownsville CLIMATE page at:
http://www.srh.noaa.gov/bro/roshelp.htm
Another tool useful for understanding the distribution of pollutants is wind trajectories, which
are aerial maps showing the path taken by a parcel of air over a period of time. Trajectories are
important for understanding the transport of air toxics and/or the potential geographic regions
from which sources of air toxics may emanate. Trajectories illustrate estimates of the general
path that air has traveled over a recent time period in order to arrive at a particular location, and
where it is likely to be going immediately afterward. The meteorological dynamics that cause air
to rise or fall, and that determine its path, can affect air quality by carrying air toxics many miles
from their sources. Exhibit 5 presents an example of a trajectory map for the Northeastern
United States.
4.2 Other Important Meteorological Data
Both ambient air temperatures at a single level (typically 1.5 to 2 m) and temperature
differences between two levels (typically 2 m and 10m) are useful in air pollution studies.
These temperature measurements are used in calculations of plume rise and can be used in
determining atmospheric stability.
Solar radiation is related to the stability of the atmosphere. Cloud cover and ceiling height
(height of the base of the cloud deck that obscures at least half the sky) data, taken routinely at
National Weather Service (NWS) stations, provide an indirect estimation of radiation effects,
and are used in conjunction with wind speed to derive an atmospheric stability category. If
representative information is not available from routine NWS observations, it may be appropriate
to measure solar radiation for use in determining atmospheric stability. For information on the
use of cloud cover and ceiling height data in air toxics modeling, refer to EPA's Guideline on
Air Quality Models.(3)
April 2004
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Exhibit 5. Example of a Trajectory Map
NOAA HYSPLIT MODEL source 10 m AGL
Forward trajectories starting at 11 UTC 22 Mar 04
12 UTC 22 Mar ETA Forecast Initialization
Source: National Oceanic and Atmospheric Administration (NOAA) HYSPLIT Model.(4)
The vertical depth of the atmosphere through which vertical mixing takes place is called the
mixing layer. The top of the mixing layer is referred to as the mixing height. The mixing
height is an important variable in air toxic studies, as it limits the vertical mixing of air toxics.
Daytime mixing heights may reach as high as several kilometers during the day. Although
mixing heights are not typically measured directly, they can be approximated from routine
upper-air and surface meteorological measurements. In the daytime the mixing height is
determined by the depth of the layer thorough which the sun's heating has established a well
mixed conditions. On clear nights, radiational cooling might be expected to establish an
inversions and reduce the mixing height to near zero. However, it has been found that in
metropolitan areas, the urban heat island effect keeps the mixing height between 100 and 200
meters. The mixing heights are used in air quality models as an upper boundary to which air
April 2004
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toxics can be mixed. The level of the mixing height is most important for elevated stacks and
much less so for ground level sources.
4.3 Sources of Meteorological Data
The principal federal sources for meteorological data include:
The National Climatic Data Center (NCDC) located in Asheville, NC.
• The National Weather Service (NWS) Forecast Centers
• The EPA Support Center for Regulatory Models (SCRAM) at Research Triangle Park,
NC.
State climatological offices are excellent sources of meteorological data. Data can often be
obtained in a text format, and can be used in conjunction with applications that are available as
downloads from federal and state data Internet sites. Commercial and university Internet sites are
also sources of current weather conditions.
The NCDC is the most extensive source of historical meteorological and climatological data.
EPA's SCRAM site has surface and mixing height data that can be used to create wind roses
and/or used in air dispersion models. These data are for the major NWS stations throughout the
United States. The data are mostly for the years 1984 through 1992 (for surface data) or 1991
(for upper air data used for mixing heights). Exhibit 6 presents a list of Internet sites where
meteorological data are available.
Exhibit 6. Internet Sites with Meteorological Data
National Climatic Data Center ( http:// www.ncdc.noaa.gov/oa/ncdc.html)
EPA SCRAM Site (http://www.epa.gov/scramOOI/)
Weather Underground (http://www.wunderground.com/)
UNSYSIS (http://weather.unisvs.com/)
NWS Pleasant Hill, MO (http://www.crh.noaa.gov/eax/)
Western Regional Climate Center (http://www.wrcc.dri.edu/)
Northeast Regional Climate Center
(http://met-www.cit. Cornell.edu/nrcc_home.html)
Midwest Regional Climate Center (http://mcc.sws.uiuc.edu/)
High Plains Regional Climate Center (http ://www.hprcc.unl. edu/)
Southern Regional Climate Center (http://www.srcc.lsu.edu/)
Southeast Regional Climate Center (http://www.sercc.com/)
WebMET.com (http://www.webmet.com/)
April 2004
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References
1. U.S. Environmental Protection Agency. 2004. Global Warming Kids Site. Greenhouse
Effect. Updated March 1, 2004. Available at:
http://www.epa.gov/globalwarming/kids/greenhouse.html. (Last accessed March 2004).
2. U.S. Environmental Protection Agency. 2004. Technology Transfer Network. Support Center
for Regulatory Air Models, Meteorological Data, Related Programs. Updated March 8, 2004.
Available at: http://www.epa.gov/scramOO 17tt24.htm#relatedpro grams (Last accessed March
2004).
3. U.S. Environmental Protection Agency. 2004. Technology Transfer Network. Support
Center for Regulatory Air Models, Guidance/Support, Modeling Guidance. Updated March
22, 2004. Available at http ://www. epa. gov/scramOO 17tt25 .htm#guidance (Last accessed
March 2004).
4. Rolph, G.D. 2003. Real-time Environmental Applications and Display sYstem (READY)
Website. Available at: http://www.arl.noaa.gov/ready/hysplit4.html. NOAA Air Resources
Laboratory, Silver Spring, MD. (Last accessed March 2004)
April 2004 Page G-12
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Appendix H Data Quality Evaluation
Table of Contents
1.0 Introduction j_
2.0 Step 1: Gather All Data Available from the Sampling Investigation and Sort by Medium 2
3.0 Step 2: Evaluate the Analytical Methods Used 4
4.0 Step 3: Evaluate the Quality of Data with Respect to Sample Quantitation Limits 5.
4.1 Sample Quantitation Limits (SQLs) That Are Greater Than Benchmark Concentrations
5
4.2 Unusually High SQLs 7
4.3 When Only Some Samples in a Medium Test Positive For a Chemical £
4.4 When SQLs Are Not Available 8
4.5 When Air Toxics Are Not Detected in Any Samples in a Medium £
5.0 Step 4: Evaluate the Quality of Data with Respect to Qualifiers and Codes £
5.1 Types of Qualifiers 9
5.2 Using the Appropriate Qualifiers L2
6.0 Step 5: Evaluate the Quality of Data with Respect to Blanks L3_
7.0 Step 6: Evaluate Tentatively Identified Compounds 14
8.0 Step 7: Compare Potential Contamination with Background 1_5
9.0 Step 8: Develop a Set of Data for Use in the Risk Assessment j/7
10.0 Step 9: Further Limit the Number of Chemicals to Be Carried Through the Risk Assessment, If
Appropriate j/7
10.1 Conduct Initial Activities lj$
10.2 Group Chemicals by Class lj$
10.3 Evaluate Frequency of Detection JjS
10.4 Use a Toxicity-Weighted or Risk-based Screening Analysis 12
11.0 Summarize and Present Data 12
11.1 Summarize Data Collection and Evaluation Results in Text 12
11.2 Summarize Data Collection and Evaluation Results in Tables and Graphics 2J_
References 22
-------
-------
1.0 Introduction
This appendix presents information for assembling the analytical data available after a
monitoring investigation has been completed and deciding which of the data are of sufficient
quality to be used in the risk assessment. Each sample may have been analyzed for the presence
of many different air toxics, and many of those substances may have been detected. The
following nine steps describe an approach to organize the data for use in a risk assessment. This
stepwise approach is modified from that described in Chapter 5 of EPA's Risk Assessment
Guidance for Superfundm Note that the application of this stepwise approach requires
considerable knowledge related to sampling and analysis methods and risk assessment and
therefore should be done in consultation with appropriate experts.
1
4.
7.
8
Acronyms for Appendix H
Contract Laboratory Program
Contract-Required Detection Limit
Contract-Required Quantitation Limit
Estimated Quantitation Limits
Detection Limit
Field Investigation Team
Instrument Detection Limit
Method Detection Limit
Non-detect
Performance Evaluation
Practical Quantitation Limit
Quality Assurance/Quality Control
Quantitation Limit
Inhalation Reference Concentration
Oral Reference Dose
Sample Quantitation Limit
Semivolatile Organic Chemical
Target Compound List
Tentatively Identified Compound
Total Organic Carbon
Total Organic Halogens
Volatile Organic Chemical
Gather all data available from the
sampling investigation and sort by
medium (Section 2);
Evaluate the analytical methods used
(Section 3);
Evaluate the quality of data with
respect to sample quantitation limits
(Section 4);
Evaluate the quality of data with
respect to qualifiers and codes
(Section 5);
Evaluate the quality of data with
respect to blanks (Section 6);
Evaluate tentatively identified
compounds (Section 7);
Compare potential contamination with
background (Section 8);
Develop a set of data for use in the
risk assessment (Section 9); and
9. Further limit the number of chemicals
to be carried through the risk
assessment, if appropriate (Section
10).
10. Summarize and present data (Section
11).
The outcome of this evaluation is (1) the identification of contaminants of potential concern
(COPC) that will be carried through the risk assessment and (2) reported concentrations that are
of acceptable quality for use in a quantitative risk assessment. If the nine data evaluation steps
are followed, the number of air toxics to be considered in the remainder of the risk assessment
usually will be less than the number of substances initially identified. A suggested process for
averaging acceptable data to develop chemical specific exposure concentrations is provided in
Appendix I.
CLP
CRDL
CRQL
EQL
DL
FIT
IDL
MDL
ND
PE
PQL
QA/QC
QL
RfC
RfD
SQL
SVOC
TCL
TIC
TOC
TOX
VOC
April 2004
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Definitions for Appendix H
Chemicals of Potential Concern. Air toxics that are evaluated in the risk assessment because they
have the potential to affect the risk management decision. The corresponding term for ecological risk
assessment are chemicals of potential ecological concern (COPEC). The risk assessment often finds
that most of the risk is associated with a subset of the COPC. The subset, which drives the risk
management decisions, is referred to as chemicals of concern (COC).
Common Laboratory Contaminants. Certain organic chemicals (e.g., acetone, 2-butanone,
methylene chloride, toluene, and the phthalate esters) that are commonly used in the laboratory and
thus may be introduced into a sample from laboratory cross-contamination.
Contract-required Quantitation Limit (CRQL). Chemical-specific levels that the laboratory must
be able to routinely and reliably detect and quantitate in specified sample matrices to meet pre-
specified data quality objectives. May or may not be equal to the reported quantitation limit of a given
chemical in a given sample. (This term is also used in the Superfund Program under their Contract
Laboratory Program.)
Detection Limit (DL). The lowest amount that can be distinguished from the normal "noise" of an
analytical instrument or method.
Non-detects (NDs). Chemicals that are not detected in a particular sample above a certain limit,
usually the quantitation limit for the chemical in that sample. Non-detects are often indicated by a "U"
data qualifier.
Positive Data. Analytical results for which measurable concentrations (i.e., above a quantitation
limit) are reported. May have data qualifiers attached (except a U, which indicates a non-detect).
Quantitation Limit (QL). The lowest level at which a chemical can be accurately and reproducibly
quantitated. Usually equal to the instrument detection limit multiplied by a factor of three to five, but
. varies for different chemicals and different samples.
X S
2.0 Step 1: Gather All Data Available from the Sampling Investigation and Sort by
Medium
Gather data, which may be from several different sampling periods and based on several
different analytical methods, from all available sources. Sort data by medium (i.e., air, water,
sediment, soil, and biota, if appropriate). Exhibit 1 illustrates a useful table format for presenting
data.
The data should be given to the risk assessor in a data summary report (or reports) that provides
information on a number of critical elements that allow the assessor to judge the adequacy of the
data to perform the risk analysis. Some of the critical elements include:
• Description of the study area,
• Sampling design and sampling locations,
• Procedures followed to ensure quality data (e.g., SOPs, QAPPs),
• Analytical methods and quantitation limits,
April 2004 Page H-2
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Chemical-specific results on a per sample basis,
Exhibit 1. Example of Output Format for Validated Data
Hypothetical Soil Sampling Results from Area X
Sample medium
Sample ID
Sample or
screen depth
Date collected
Soil
SRB-3-1
0-1'
12/14/99
Soil
SRB-3-1DU
0-1'
12/14/99
Soil
SRB-3-2
2-4'
12/14/99
Air Toxic
toxaphene
2,4,7,8-TCDD
lead
mercury
SQL(a)
80
20
160
60
Concen-
tration
80
10
120
30
Quali-
fier00
U
J
J
J
SQL(a)
80
20
160
60
Concen-
tration
80
8
110
44
Quali-
fier00
U
J
J
J
SQL(a)
80
200
400
300
Concen-
tration
40
200
360
300
Quali-
fier00
J
U/J
J
U/J
Note: All values other than qualifiers must be entered as numbers, not labels.
(a) Sample quantitation limit. Values for illustration only.
00 Refer to Section 5.1 (Exhibit 3) for an explanation of qualifiers.
• Field conditions, including meteorological conditions,
• Data validation reports (both by the laboratory and any secondary validation), and
• A description of any issues with field collection, transportation/storage, or analysis that
impact the veracity of the data.
The data reports provided to the risk assessor must be sufficient to allow the assessor to judge
the completeness, comparability, representativeness, precision, and accuracy of the data.
[A more thorough overview of the process for assessing the usability of data for risk assessment
purposes, including minimum data and documentation needs, is provided in reference 2. While
this document was developed for the Superfund program, it provides relevant information for the
evaluation of environmental monitoring data in a risk assessment context and, as such, is
referenced here. Assessors are strongly encouraged to review this document prior to planning
and scoping a assessment. This will help to ensure that all the information necessary to assess
the useability of data for risk assessment purposes will be developed during the sampling and
analysis phase of the assessment. (For example, assessing precision of sampling results is
usually performed by establishing duplicate monitors at one or more sampling stations. The
requirements for duplicate sampling must be written into the analytical plan during the planning
and scoping phase of the assessment.) Reference 2 may also be consulted for information on
assessing the useability of historical data for risk assessment.](2)
April 2004
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Evaluate data from different time periods to determine if concentrations of air toxics are similar
or if changes have occurred between sampling periods (e.g., during different seasons of the
year). If the methods used to analyze samples from different time periods are similar in terms of
the types of analyses conducted and the QA/QC procedures followed, then the data may be
combined for the purposes of quantitative risk assessment. Usually, this means averaging at
least one year's worth of data to develop an estimate of long term average concentration (see
Appendix I for a suggested methodology for combining results from air monitoring to estimate
exposure concentration for the inhalation pathway). If concentrations of air toxics change
significantly between sampling periods, it may be useful to also note temporal variation in the
risk characterization. If data are available that spans long periods of time (e.g., multiple years)
one could use only the most recent data in the quantitative risk assessment and evaluate older
data in a qualitative analysis of changes in concentrations over time. When data are eliminated
from a data set, justification for such elimination should be fully described in the risk assessment
report. (A good understanding of the risk management goals will help in deciding what data to
keep and how to combine data.)
3.0 Step 2: Evaluate the Analytical Methods Used
Group data according to the types of analyses conducted (e.g., Toxic Organic method,
semivolatiles analyzed by EPA methods for air) to determine which analytical method results are
appropriate for use in quantitative risk assessment.
Some types of data usually are not appropriate for use in quantitative risk assessment, even
though they may be available. For example, analytical results that are not specific for a
particular compound (e.g., total organic carbon [TOC], total organic halogens [TOX]), or results
from insensitive analytical methods (e.g., analyses using portable field instruments such as
organic vapor analyzers and other field screening methods) may be useful for identifying
potential monitoring locations and/or examining the potential fate and transport of contaminants.
These types of analytical results, however, generally are not appropriate for quantitative risk
assessment. In addition, the results of analytical methods associated with unknown, few, or no
QA/QC procedures are generally eliminated from further quantitative use. (Note that one of the
purposes of the data quality objectives (DQO) process described in Chapter 6 and elsewhere in
this manual is to avoid the use of sampling and analysis protocols that will not provide data that
are useable for the risk assessment). These types of results, however, may be useful for
qualitative discussions of risk.
The outcome of this step is a set of study-specific data that has been developed according to a
standard set of sensitive, chemical-specific methods (see Chapters 10 and 19 for links to
identified, standardized methods).
Note however that even when standardized, verified field and analytical procedures and
associated QA/QC have been used during sampling and analysis, there is no guarantee that all
analytical results are consistently of sufficient quality and reliability for use in quantitative risk
assessment. Instead, it is important to determine - according to the steps discussed below - the
limitations and uncertainties associated with the data, so that only data that are appropriate and
reliable for use in a quantitative risk assessment are carried through the process.
April 2004 Page H-4
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4.0 Step 3: Evaluate the Quality of Data with Respect to Sample Quantitation Limits
This step involves evaluation of quantitation limits (QLs) and detection limits (DLs) for all of
the air toxics assessed. This evaluation may lead to the re-analysis of some samples, the use of
"proxy" (or estimated) concentrations, and/or the elimination of certain air toxics from further
consideration (because they are believed to be absent in all samples). Types and definitions of
QLs and DLs are presented in the box on the next page. Before eliminating an air toxic because
they are not detected (or conducting any other manipulation of the data), the following points
should be considered:
The sample quantitation limit (SQL) for a specific air toxic may be greater than
corresponding standards, criteria, or concentrations against which the concentrations will be
compared (e.g., RfCs, RfDs, or ecological benchmark levels). In this situation, the
"undetected" air toxic may be present at levels greater than these benchmarks and their
exclusion from the risk assessment may result in an underestimate of risk.
• A particular SQL may be significantly higher than positively detected values in other
samples in a data set.
These two points are discussed in detail in the following two subsections. A third subsection
provides guidance for situations where only some of the samples for a given medium test
positive for a particular chemical. A fourth subsection addresses the special situation where
SQLs are not available. The final subsection addresses the specific steps involved with
elimination of air toxics from the quantitative risk assessment based on their QLs.
4.1 Sample Quantitation Limits (SQLs) That Are Greater Than Benchmark
Concentrations
QLs needed for the sampling and analysis investigation should be specified in the sampling plan.
For some air toxics, however, SQLs obtained from available analytical methods may exceed
certain concentrations of potential concern (e.g., RfCs, tissue sample concentrations that might
result in a dietary intake level that exceeds an RfD). Exhibits 10-10 and 10-11 identify some
known deficiencies in available air monitoring methods and some air toxics for which improved
monitoring methods are needed. Two points should be noted when considering this situation:
• Review of available information on sources and emissions, a preliminary determination of
COPC, and/or the results of fate and transport modeling prior to sample collection may
allow the risk assessor to identify when more sensitive sampling and/or analytical methods
may be needed before an investigation begins. This is the most efficient way to minimize the
problem of QLs exceeding levels of potential concern.
• Analytical laboratories may not be able to attain QLs in particular samples that meet data
quality requirements using standardized, verified procedures.
If an air toxic is not detected in any sample from a particular medium at the QL and a more
sensitive method is not available, then modeling data, as well as professional judgment, may be
used to evaluate whether the chemical may be present above the concentrations of potential
concern. If the available information indicates the chemical is not present, see Section 3.5 of this
April 2004 Page H-5
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Detection Limits and Quantitation Limits
Strictly interpreted, the detection limit (DL) is the lowest amount of a chemical that can be "seen"
above the normal, random noise of an analytical instrument or method. A chemical present below that
level cannot reliably be distinguished from noise. DLs are chemical-specific and instrument-specific
and are determined by statistical treatment of multiple analyses in which the ratio of the lowest amount
observed to the electronic noise level (i.e., the signal-to-noise ratio) is determined. On any given day
in any given sample, the calculated limit may not be attainable; however, a properly calculated limit
can be used as an overall general measure of laboratory performance.
Two types of DLs may be described: instrument DLs (IDLs) and method DLs (MDLs). The IDL is
generally the lowest amount of a substance that can be detected by an instrument; it is a measure only
of the DL for the instrument, and does not consider any effects that sample matrix, handling, and
preparation may have. The MDL, on the other hand, takes into account the reagents, sample matrix,
and preparation steps applied to a sample in specific analytical methods.
Due to the irregular nature of instrument or method noise, reproducible quantitation of a chemical is
not possible at the DL. Generally, a factor of three to five is applied to the DL to obtain a quantitation
limit (QL), which is considered to be the lowest level at which a chemical may be accurately and
reproducibly quantitated. DLs indicate the level at which a small amount would be "seen," whereas
QLs indicate the levels at which measurements of concentration can be "trusted."
Two types of QLs may be described: estimated quantitation limits (EQL - also sometimes referred to
as a practical quantitation limit or PQL) and sample QLs (SQLs). EPA's Superfund Program
maintains a Contract Laboratory Program (CLP) as a means to obtain reliable analytical results from
many different laboratories. To participate in the CLP, a laboratory must be able to meet EPA's EQL.
This EQL is established by contract and, thus, is called a contract required quantitation limit (CRQL).
CRQLs are chemical-specific and vary depending on the medium analyzed and the amount of
chemical expected to be present in the sample. As the name implies, CRQLs are not necessarily the
lowest detectable levels achievable, but rather are levels that a CLP laboratory should routinely and
reliably detect and quantitate in a variety of sample matrices. For most air toxics risk assessments,
SQLs, not CRQLs, will be the QLs of interest for most samples. In fact, for the same chemical, a
specific SQL may be higher than, lower than, or equal to SQL values for other samples. In addition,
preparation or analytical adjustments such as dilution of a sample for quantitation of an extremely high
level of only one compound could result in non-detects for all other compounds included as analytes
for a particular method, even though these compounds may have been present at trace quantities in the
environmental sample. Because SQLs take into account sample characteristics, sample preparation,
and analytical adjustments, these values are the most relevant QLs for evaluating non-detected
chemicals. Also note that because of the inability to accurately measure concentration at the MDL, the
SQL is used as he starting point for developing exposure concentrations where some of the samples in
a data set have detections of an analyte and others do not (see Appendix I).
April 2004 Page H-6
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appendix for guidance on eliminating chemicals. If there is some indication that the chemical is
present, the only choices are to:
• Use modeling results in the risk assessment;
• Re-analyze selected samples using a more sensitive analytical method (if feasible); or
• Address the chemical qualitatively in the risk assessment.
In determining which option is most appropriate for an analysis, it may be helpful to assume the
air toxic is present at the SQL for purposes of an initial (tier 1) screening risk assessment. In this
way, risks that would be posed if the chemical is present at the SQL can be compared with risks
posed by other air toxics in the analysis.
4.2 Unusually High SQLs
Due to one or more sample-specific problems (e.g., matrix interferences), SQLs for a particular
chemical in some samples may be unusually high, sometimes greatly exceeding the positive
results reported for the same chemical in other samples from the data set. Even if these SQLs do
not exceed health-based standards or criteria, they may still present problems. If the SQLs
cannot be reduced by re-analyzing the sample, consider excluding the samples from the
quantitative risk assessment if they cause the calculated exposure concentration to exceed the
maximum detected concentration for a particular sample set. Exhibit 2 presents an example of
how to address a situation with unusually high QLs.
Exhibit 2. Example of Unusually High Quantitation Limits
In this hypothetical example, ambient air concentrations of benzene in air have been determined
using the TO-1 method.
Concentration (ppb)
Chemical
benzene
Sample 1
50 U(a)
Sample 2
59
Sample 3
200 U
Sample 4
74
(a) U indicates that benzene was analyzed for, but not detected; the value presented (e.g., 50 U) is
the SQL.
The ambient air concentrations presented in this example (i.e., 50 to 200 ppb) vary widely from
sample to sample. Assume a more sensitive analytical method would not aid in reducing the
unusually high QL of 200 ppb noted in Sample 3. In this case, the result for benzene in Sample 3
would be eliminated from the quantitative risk assessment because it would cause the calculated
exposure concentrations to exceed the maximum detected concentration (in this case 74 ppb).
Thus the data set would be reduced to three samples: the non-detect in Sample 1 and the two
detected values in Samples 2 and 4.
April 2004 Page H-7
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4.3 When Only Some Samples in a Medium Test Positive For a Chemical
Most analytes are not positively detected in each sample collected and analyzed. Instead, for a
particular chemical the data set generally will contain some samples with positive results and
others with non-detected results. The non-detected results usually are reported as SQLs. These
limits indicate that the chemical was not measured above certain levels, which may vary from
sample to sample. The chemical may be present at a concentration just below the reported
quantitation limit, or it may not be present in the sample at all (i.e., the concentration in the
sample is zero). Appendix I provides a suggested methodology for combining the results of a
dataset where some of the samples test positive for an analyte and others do not.
4.4 When SQLs Are Not Available
In some cases, laboratory data summaries may not provide the SQLs. Instead, MDLs, CRQLs,
or even IDLs may have been substituted wherever a chemical was not detected. Sometimes, no
detection or quantitation limits may be provided with the data. As a first step in these situations,
always attempt to obtain the SQLs, because these are the most appropriate limits to consider
when evaluating non-detected air toxics (i.e., they account for sample characteristics, sample
preparation, or analytical adjustments that may differ from sample to sample). Good planning
and clearly articulated directions to the laboratory will help ensure that the appropriate
information is provided to the risk assessor. The problem associated with incorrectly reported
data should only be an issue when evaluating historical data for which there was no pre-
consultation with the laboratory about what is to be provided in the data package.
If SQLs cannot be obtained, the MDL may be used as the QL, with the understanding that in
most cases this will underestimate the SQL (because the MDL is a measure of detection limits
only and does not account for sample characteristics or matrix interferences). The IDL should
rarely be used for non-detected air toxics since it is a measure only of the detection limit for a
particular instrument and does not consider the effect of sample handling and preparation or
sample characteristics.
4.5 When Air Toxics Are Not Detected in Any Samples in a Medium
After considering the discussion provided in the above subsections, generally eliminate those air
toxics that have not been detected in any samples of a particular medium. If information exists
to indicate that the air toxics are present, they should not be eliminated from the analysis. The
outcome of this step is a data set that only contains air toxics for which positive data (i.e.,
analytical results for which measurable concentrations are reported) are available in at least one
sample from each medium. Unless otherwise indicated, assume at this point in the evaluation of
data that positive data to which no uncertainties are attached concerning either the assigned
identity of the chemical or the reported concentration (i.e., data that are not "tentative,"
"uncertain," or "qualitative") are appropriate for use in the quantitative risk assessment.
5.0 Step 4: Evaluate the Quality of Data with Respect to Qualifiers and Codes
Various qualifiers and codes (hereafter referred to as qualifiers) may be attached to certain data
by either the laboratories conducting the analyses or by persons performing data validation.
These qualifiers often pertain to QA/QC problems and generally indicate questions concerning
April 2004 Page H-8
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chemical identity, chemical concentration, or both. All qualifiers must be addressed before the
chemical can be used in quantitative risk assessment. Qualifiers used by the laboratory may
differ from those used by data validation personnel in either identity or meaning.
5.1 Types of Qualifiers
Exhibit 3 provides a list of the qualifiers that laboratories are permitted to use under the
Superfund CLP, along with their potential use in risk assessment. Exhibit 4 provides a similar
list addressing data validation qualifiers. (Note that the data qualifiers and their meanings
provided here are not consistent across all laboratories. In all cases, it is critical to discuss with
the lab what they mean by the data qualifiers they report.) In general, because the data
validation process is intended to assess the effect of QC issues on data usability, validation data
qualifiers are attached to the data after the laboratory qualifiers and supersede the laboratory
qualifiers. If data have both laboratory and validation qualifiers and they appear contradictory,
ignore the laboratory qualifier and consider only the validation qualifier. If qualifiers have been
attached to certain data by the laboratory and have not been removed, revised, or superseded
during data validation, then evaluate the laboratory qualifier itself. If it is unclear whether the
data have been validated, contact the appropriate data validation and/or laboratory personnel.
The type of qualifier and other site-specific factors determine how qualified data are to be used
in a risk assessment. As seen in Exhibits 3 and 4, the type of qualifier attached to certain data
often indicates how that data should be used in a risk assessment. For example, most of the
laboratory qualifiers for both inorganic chemical data and organic chemical data (e.g., J, E, N)
indicate uncertainty in the reported concentration of the chemical, but not in its assigned identity.
Therefore, these data can be used just as positive data with no qualifiers or codes. In general,
include data with qualifiers that indicate uncertainties in concentrations but not in identification.
Exhibit 3. Example of Data Qualifiers and Their Potential Use in
Quantitative Risk Assessment: Superfund Contract Laboratory Program (CLP)
Qualifier
Definition
Indicates:
Uncertain
Identity?
Uncertain
Concentration?
Include Data in
Quantitative
Risk
Assessment?
Inorganic Chemical Data(a)
B
U
E
M
Reported value is IDL.
Compound was analyzed for, but
not detected.
Value is estimated due to matrix
interferences.
Duplicate injection precision
criteria not met.
No
Yes
No
No
No
Yes
Yes
Yes
Yes
?
Yes
Yes
April 2004
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Exhibit 3. Example of Data Qualifiers and Their Potential Use in
Quantitative Risk Assessment: Superfund Contract Laboratory Program (CLP)
Qualifier
N
S
w
*
+
Definition
Spiked sample recovery not within
control limits.
Reported value was determined by
the Method of Standard Additions
(MSA).
Post-digestion spike for furnace
AA analysis is out of control
limits, while sample absorbance is
<50% of spike absorbance.
Duplicate analysis was not within
control limits.
Correlation coefficient for MSA
was<0.995.
Indicates:
Uncertain
Identity?
No
No
No
No
No
Uncertain
Concentration?
Yes
No
Yes
Yes
Yes
Include Data in
Quantitative
Risk
Assessment?
Yes
Yes
Yes
Yes
Yes
Organic Chemical Data*-1
U
J
c
B
E
D
A
Compound was analyzed for, but
not detected.
Value is estimated, either for a
tentatively identified compound
(TIC) or when a compound is
present (spectral identification
criteria are met, but the
value is
-------
Exhibit 3. Example of Data Qualifiers and Their Potential Use in
Quantitative Risk Assessment: Superfund Contract Laboratory Program (CLP)
Qualifier
X
Definition
Additional flags defined
separately.
Indicates:
Uncertain
Identity?
-(d)
Uncertain
Concentration?
~
Include Data in
Quantitative
Risk
Assessment?
~
(a) Source: U.S. EPA, 1988. Contract Laboratory Program Statement of Work for Inorganics Analysis: Multi-
media, Multi-concentration. Office of Emergency and Remedial Response. SOW No. 788.
(b) Source: U.S. EPA, 1988. Contract Laboratory Program Statement of Work for Organics Analysis: Multi-
media, Multi-concentration. Office of Emergency and Remedial Response. SOW No. 288.
©) See Section 6 for a discussion of blank contamination.
(d) Data will vary with laboratory conducting analyses.
Exhibit 4. Validation Data Qualifiers and Their Potential Use in
Quantitative Risk Assessment
Qualifier
Definition
Indicates:
Uncertain
Identity?
Uncertain
Concentration?
Include Data in
Quantitative
Risk
Assessment?
Inorganic and Organic Chemical Data1-3-1
U
J
R
Z
Q
N
The material was analyzed for, but
not detected. The associated
numerical value is the SQL.
The associated numerical value is
an estimated quantity.
Quality control indicates that the
data are unusable (compound may
or may not be present). Re-
sampling and/or re-analysis is
necessary for verification.
No analytical result (inorganic
data only).
No analytical result (organic data
only).
Presumptive evidence of
presence of material (tentative
identification)^
Yes
No
Yes
~
~
Yes
Yes
Yes
Yes
~
~
Yes
?
Yes
No
~
~
?
April 2004
Page H-11
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Exhibit 4. Validation Data Qualifiers and Their Potential Use in
Quantitative Risk Assessment
(a) Source: U.S. EPA. 1988. Laboratory Data Validation Functional Guidelines for Evaluating Inorganics
Analysis. Office of Emergency and Remedial Response.
U.S. EPA. 1988. Laboratory Data Validation Functional Guidelines for Evaluating Organics Analysis
(Functional Guidelines for Organics). Office of Emergency and Remedial Response.
(b) Organic chemical data only
Exhibit 5 provides examples showing the use of two commonly encountered data qualifiers: the
J qualifier, and the R qualifier. Basically, the suggestion is to use J-qualified concentrations the
same way as positive data that do not have this qualifier. If possible, note potential uncertainties
associated with the qualifier, so that if data qualified with a J contribute significantly to the risk,
then appropriate caveats can be attached. The R data qualifier indicates that the sample result
was rejected by the data validation personnel, and therefore this result should be eliminated from
the risk assessment.
Exhibit 5. Example Use of "J" and "R" Data Qualifiers
In this example, concentrations of benzene in an air monitor have been determined using a hypothetical
analytical method. Benzene was detected in these four samples at concentrations of 3,200 ug/1, 40
ug/1, and 20 ug/1; therefore, these concentrations - as well as the non-detect - should be used in
determining representative concentrations.
Chemical
Benzene
Sample 1
3,200 I(a)
Sample 2
40
Sample 3
30 U®
Sample 4
201
(a) J = The numerical value is an estimated quantity
(b) U = Compound was analyzed for, but not detected. Value presented (e.g., 30 U) is the SQL.
In this example, concentrations of lead in surface water have been determined using a hypothetical
analytical method. These data have been validated, and therefore the R qualifers indicate that the
person conducting the data validation rejected the data for lead in samples 2 and 3. The "UR" qualifier
means that lead was not detected in Sample 3; however, the data validator rejected the non-detected
result. Eliminate these two samples so that the data set now consists of only two samples (Samples 1
and 4).
Chemical
Lead
Sample 1
310
Sample 2
500 R(a)
Sample 3
30 UR00
Sample 4
500
(a) R = Quality control indicates that the data are unusable (compound may not be present)
(b) U = Compound was analyzed for, but not detected. Value presented (e.g., 30 UR) is the SQL.
5.2 Using the Appropriate Qualifiers
The information presented in Exhibits 3 and 4 is based on 1988 EPA guidance documents
concerning qualifiers. The types and definitions of qualifiers may be periodically updated within
any analytical program, and EPA regions, states, and local governments may have their own data
April 2004
Page H-12
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qualifiers and associated definitions. In general, the risk assessor should clearly understand the
specific data qualifiers used by a particular analytical program and use the resulting data
appropriately in the risk assessment. Make sure that definitions of data qualifiers used in the
data set for the analysis have been reported with the data and are current. Never guess about the
definition of qualifiers.
6.0 Step 5: Evaluate the Quality of Data with Respect to Blanks
Blank samples provide a measure of contamination that has been introduced into a sample set
either (1) in the field while the samples were being collected or transported to the laboratory, or
(2) in the laboratory during sample preparation or analysis. To prevent the inclusion of
non-site-related contaminants in the risk assessment, the concentrations of air toxics detected in
blanks must be compared with concentrations of the same air toxics detected in site samples.
Exhibit 6 provides detailed definitions of different types of blanks. Blank data should be
compared with results from samples with which the blanks are associated. It is often impossible,
however, to determine the association between certain blanks and data. In this case, compare the
blank data with results from the entire sample data set. EPA's Superfund Program has
developed guidelines for comparing sample concentrations with blank concentrations; note that
the requirements or practices for a given air toxic program may differ.
• Blanks containing common laboratory contaminants. As discussed in the EPA
documents cited in Exhibits 3 and 4, acetone, 2- butanone (or methyl ethyl ketone),
methylene chloride, toluene, and the phthalate esters are considered by EPA to be common
laboratory contaminants. If the blank contains detectable levels of common laboratory
contaminants, EPA guidance indicates that the sample results should be considered as
positive results only if the concentrations in the sample exceed ten times the maximum
amount detected in any blank. If the concentration of a common laboratory contaminant is
less than ten times the blank concentration, then EPA guidance indicates to conclude that the
chemical was not detected in the particular sample and consider the blank-related
concentrations of the chemical to be the quantitation limit for the chemical in that sample.
Note that if all samples contain levels of a common laboratory contaminant that are less than
ten times the level of contamination noted in the blank, then completely eliminate that
chemical from the set of sample results.
• Blanks containing chemicals that are not common laboratory contaminants. As
discussed in the previously referenced guidance, if the blank contains detectable levels of one
or more organic or inorganic chemicals that are not considered by EPA to be common
laboratory contaminants, then consider sample results as positive only if the concentration of
the chemical in the sample exceeds five times the maximum amount detected in any blank.
Treat samples containing less than five times the amount in any blank as non-detects, and
consider the blank-related chemical concentration to be the quantitation limit for the
chemical in that sample. Again, note that if all samples contain levels of a chemical that are
less than five times the level of contamination noted in the blank, then completely eliminate
that chemical from the set of sample results.
April 2004 Page H-13
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Exhibit 6. Types of Blanks
Blanks are analytical quality control samples analyzed in the same manner as site samples. They are
used in the measurement of contamination that has been introduced into a sample either (1) in the field
while the samples were being collected or transported to the laboratory or (2) in the laboratory during
sample preparation or analysis. Four types of blanks - trip, field, laboratory calibration, and laboratory
reagent (or method) - are described below. A discussion on the water used for the blank also is
provided.
Trip Blank. This type of blank is used to indicate potential contamination due to migration of volatile
organic chemicals (VOCs) from the air on the site or in sample shipping containers, through the septum
or around the lid of sampling vials, and into the sample. A trip blank consists of laboratory distilled,
deionized water in a 40-ml glass vial sealed with a teflon septum. The blank accompanies the empty
sample bottles to the field as well as the samples returning to the laboratory for analysis; it is not
opened until it is analyzed in the lab with the actual site samples. The containers and labels for trip
blanks should be the same as the containers and labels for actual samples, thus making the laboratory
"blind" to the identity of the blanks.
Field Blank. A field blank is used to determine if certain field sampling or cleaning procedures (e.g.,
insufficient cleaning of sampling equipment) result in cross-contamination of site samples. Like the
trip blank, the field blank is a sample of distilled, deionized water taken to the field with empty sample
bottles and is analyzed in the laboratory along with the actual samples. Unlike the trip blank, however,
the field blank sample is opened in the field and used as a sample would be (e.g., it is poured through
cleaned sampling equipment or it is poured from container to container in the vicinity of a gas-powered
pump). As with trip blanks, the field blanks' containers and labels should be the same as for actual
samples.
Laboratory Calibration Blank. This type of blank is distilled, deionized water injected directly into
an instrument without having been treated with reagents appropriate to the analytical method used to
analyze actual site samples. This type of blank is used to indicate contamination in the instrument
itself, or possibly in the distilled, deionized water.
Laboratory Reagent or Method Blank. This blank results from the treatment of distilled, deionized
water with all of the reagents and manipulations (e.g., digestions or extractions) to which site samples
will be subjected. Positive results in the reagent blank may indicate either contamination of the
chemical reagents or the glassware and implements used to store or prepare the sample and resulting
solutions. Although a laboratory following good laboratory practices will have its analytical processes
under control, in some instances method blank contamination cannot be entirely eliminated.
Water Used for Blanks. For all the blanks described above, results are reliable only if the water
comprising the blank was clean. For example, if the laboratory water comprising the trip blank was
contaminated with VOCs prior to being taken to the field, then the source of VOC contamination in the
trip blank cannot be isolated (see laboratory calibration blank).
7.0 Step 6: Evaluate Tentatively Identified Compounds
Both the identity and reported concentration of a tentatively identified compound (TIC) is
questionable (see Exhibit 7). Two options for addressing TICs exist, depending on the relative
number of TICs compared to non-TICs. If the risk assessment involves a regulatory decision,
the risk assessor is strongly encouraged to consult the appropriate regulatory authorities about
how to address TICs in the risk assessment.
April 2004 Page H-14
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When few TICs are present. When only a few TICs are present, and either (a) no
information indicates that either a particular TIC may indeed be present (e.g., it is not present
in emissions from the source(s) being evaluated or other nearby sources), or (b) the estimated
concentration is relatively low, and therefore, the risk estimate would likely not be
dominated by the TIC, then generally do not include the TICs in the risk assessment.
When Many TICs are present. If many TICs are present, or if TIC concentrations appear
high or site information indicates that TICs are indeed present, then further evaluation of
TICs is necessary. If sufficient time is available, use more sensitive analytical methods to
confirm the identity and to positively and reliably measure the concentrations of TICs prior
to their use in the risk assessment. If such methods are unavailable or impractical, then the
TICs should be included as COPC in the risk assessment and (usually) discussed
qualitatively in the risk characterization along with a discussion of the uncertainty in both
identity and concentration.
Exhibit 7. Tentatively Identified Compounds (TICs)
The set of compounds analyzed in a particular laboratory protocol may be a limited subset of the
organic air toxics that could actually be present in specific emissions being evaluated. Thus, a
laboratory analysis may indicate the presence of additional organic compounds not being specifically
evaluated. The presence of additional compounds may be indicated, for example, by"peaks" on a
chromatogram (a chromatogram is a paper representation of the response of the instrument to the
presence of a compound). The laboratory may be required to attempt to identify some of these
compounds (e.g., the highest peaks) using computerized searches of a library containing mass spectra
(essentially "fingerprints" for particular compounds). When the mass spectra match to a certain
degree, the compound (or general class of compound) is named; however, the assigned identity is in
most cases highly uncertain. These compounds are called tentatively identified compounds (TICs).
The analytical protocols being used by the laboratory may include procedures to obtain a rough
estimate of the concentrations of TICs. These estimates, however, generally are highly uncertain and
could be orders of magnitude higher or lower than the actual concentration. For TICs, therefore,
assigned identities may be inaccurate, and quantitation is certainly inaccurate. Due to these
uncertainties, TIC information often is not provided with data summaries. Additional sampling and
analysis using different or more sensitive methods may reduce the uncertainty associated with TICs
and, therefore, TIC information should be sought even if it is absent from data summaries.
8.0 Step 7: Compare Potential Contamination with Background
In some cases, a comparison of sample concentrations with background concentrations is useful
for identifying the relative contribution of the source(s) being evaluated and other potential
sources to the total concentrations to which a population may be exposed. Often, however, the
comparison of samples with background is unnecessary because the risk estimates resulting from
other sources are very low compared to those resulting from the source(s) being evaluated.
Information collected during the risk assessment can provide information on two types of
background chemicals: (1) naturally occurring chemicals that have not been influenced by
humans and (2) chemicals that are present due to anthropogenic sources. Either type of
background chemical can be either localized or widespread. Information on background
chemicals may have been obtained by the collection of background samples and/or from other
April 2004 Page H-15
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sources (e.g., County Soil Conservation Service surveys, United States Geological Survey
reports). Background concentrations should be from the vicinity of the location sampled. For
example, background air samples are generally collected upwind from the study area to estimate
concentrations of chemicals in the air mass that is moving into the study area. For water,
samples are taken upstream of the area where deposition (or erosion of contaminated soils) is
occurring.
Background samples collected during the monitoring effort should not be used if they were
obtained from areas influenced or potentially influenced by the source(s) being evaluated.
Instead, the literature sources mentioned in the previous paragraph may be consulted to
determine expected background levels of air toxics in the study area. Care must be taken in
using literature sources, because the data contained therein might represent nationwide variation
in a particular parameter rather than variation typical of the geographic region or geological
setting in which the site is located. For example, a literature source providing concentrations of
chemicals in soil on a national scale may show a wide range of concentrations that is not
representative of the variation in concentrations that would be expected within a particular study
area.
Both the concentration of the chemical in the study-area and the concentration in background
media should be clearly articulated in the risk assessment report. Background concentrations
should generally not be subtracted from study-area specific concentrations; rather, they should
be compared (e.g., as barcharts). Statistical analyses that indicate whether study-area and
background concentrations are different may also be presented. (In cases where background
comparisons will be made, the statistical methods that will be used to compare study-area
concentrations to background concentrations should be identified prior to the collection of
samples.)
As an example, chromium is present in air releases from a source in a study area and chromium
is also naturally occurring in study area soils. In this case, it may be necessary to include a
careful comparison of the relative magnitude of estimated exposure and risk due to background
vs. estimated exposure and risk from total (i.e., deposited chromium + background chromium) .
This can be done by the bar chart method mentioned above and may be augmented by statistical
analyses that attempt to answer the question about whether study area soil concentrations of
chromium are statistically different from background soils. Again, consultation with the
appropriate decision making authorities is strongly encouraged to ensure that they get the type of
information that they will need to make their risk management decisions. (Note that, in general,
comparison with naturally occurring levels is commonly performed primarily for inorganic
chemicals such as metals, because the majority of organic air toxics released to the environment
are not naturally occurring (even though they may be ubiquitous). Similar to naturally occurring
background concentrations, anthropogenic levels resulting from human sources (other than those
being evaluated in the air toxics risk assessment) may also be present. For example, an
assessment that is evaluating exposures to dioxin from a specific source may also have to
contend with dioxin that is also present in the study area that has resulted from numerous other
small sources in the area (and possibly also from naturally occurring sources such as forest fires
and some amount of longer range transport). Similar to naturally occurring chemicals, some
combination of background sampling, literature values, modeling, and statistical analysis can be
performed to try and sort out how much of the concentrations and risk are due to the source(s) in
question and how much is present due to other human (and non-human) influences.
April 2004 Page H-16
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9.0 Step 8: Develop a Set of Data for Use in the Risk Assessment
After the evaluation of data is complete as specified in previous sections, a list of the samples
(by medium) is made that will be used to estimate exposure concentrations. In addition, a list of
COPC (also by medium) will be needed for the quantitative risk assessment. This list should
include chemicals that were:
• Positively detected in at least one sample in a given medium, including (a) chemicals with no
qualifiers attached (excluding samples with unusually high detection limits), and (b)
chemicals with qualifiers attached that indicate known identities but unknown concentrations
(e.g., J-qualified data);
• Detected at levels significantly elevated above levels of the same chemicals detected in
associated blank samples;
• Only tentatively identified but either may be associated with emissions from the source(s)
being evaluated based on ancillary information or have been confirmed by additional
analysis; and/or
Transformation products of air toxics demonstrated to be present.
Air toxics that were not detected in samples from a given medium (i.e., non-detects) but that may
be present at the site also may be included in the risk assessment if an evaluation of the risks
potentially present at the detection limit is desired.
10.0 Step 9: Further Limit the Number of Chemicals to Be Carried Through the Risk
Assessment, If Appropriate
For certain assessments, the list of air toxics potentially related to emissions from the source(s)
being evaluated and remaining after quantitation limits, qualifiers, blank contamination, and
background have been evaluated may be lengthy. Note, however, that often a modeling
analysis can identify the subset of air toxics in the emissions being evaluated that are most
likely to contribute significantly to risk, and therefore limit the scope of any subsequent
sampling and analysis effort. Carrying a large number of chemicals through a quantitative risk
assessment may be complex, and it may consume significant amounts of time and resources.
The resulting risk assessment report may be difficult to read and understand, and it may distract
from the dominant risks. In these cases, the procedures discussed in this section - using
chemical classes, frequency of detection, essential nutrient information, and a concentration
toxicity screen - may be used to further reduce the number of COPC in each medium.
If conducting a risk assessment on a large number of chemicals is feasible (e.g., because of
adequate computer capability), then the procedures presented in this section may be omitted.
However, the most important chemicals (e.g., those presenting 99 percent of the risk) - identified
after the risk assessment - may be the focus of the main text of the report, and the remaining
chemicals could be presented in the appendices.
10.1 Conduct Initial Activities
April 2004 Page H-17
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There are several activities that are useful to conduct before implementing any of the procedures
described in this section. The risk assessor is strongly encouraged to consult with appropriate
decision making authorities prior to implementing these procedures to ensure that the resulting
processed data will meet the decision makers' needs. These remaining initial activities include:
• Considering how the rationale for the procedure should be documented. The rationale
for eliminating chemicals from the quantitative risk assessment based on the procedures
discussed below should be clearly stated in the risk assessment report. This documentation,
and its possible defense at a later date, could be fairly resource- intensive. If a continuing
need to justify this step is expected, then any plans to eliminate chemicals should be
reconsidered.
• Examining historical information about the source(s) being evaluated. Chemicals
reliably associated with emissions from the source(s) being evaluated based on historical
information generally should not be eliminated from the quantitative risk assessment (at least
during the initial tiers of analysis), even if the results of the procedures given in this section
indicate that such an elimination is possible.
Considering mobility, persistence, and bioaccumulation Three factors that should be
considered are the mobility, persistence, and bioaccumulation of the chemicals. For
example, a highly volatile (i.e., mobile) chemical such as benzene, a long-lived (i.e.,
persistent) chemical such as dioxin, or a readily bioaccumulated chemical such as the PB-
HAPs, probably should remain in the risk assessment. These procedures do not explicitly
include a mobility, persistence, or bioaccumulation component, and therefore the risk
assessor must pay special attention to these factors.
Considering special exposure routes. For some chemicals, certain exposure routes need to
be considered carefully before using these procedures. For example, some air toxics may
pose a significant risk in certain circumstances due to dermal contact. The procedures
described in this section may not account for exposure routes such as this.
10.2 Group Chemicals by Class
Some dose-response values used in characterizing risks are available only for certain chemicals
within a chemical class. For example, slope factors are available only for some of the poly cyclic
aromatic hydrocarbons (PAHs). In such cases, the information provided in Chapter 12 (toxicity
evaluation) and information provided on EPA's FERA website (http://www.epa.gov/ttn/fera/).
10.3 Evaluate Frequency of Detection
Chemicals that are infrequently detected may be artifacts in the data due to sampling, analytical,
or other problems, and therefore may not be related to the sources being evaluated. Consider the
chemical as a candidate for elimination from the quantitative risk assessment if: (1) it is detected
infrequently in one or perhaps two environmental media, (2) it is not detected in any other
sampled media or at high concentrations, and (3) there is no reason to believe that the chemical
may be present in emissions from the source(s) being evaluated. In particular, modeling results
may indicate whether monitoring data that show infrequently detected chemicals are
representative of only their sampling locations or of broader areas. Because chemical
April 2004 Page H-18
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concentrations within a broad assessment area are spatially variable, the risk assessor can use
modeling results to compare infrequently detected chemical concentrations to those estimated
over broader areas when determining whether the subject chemicals are relevant to the overall
risk assessment. Judicious use of modeling to supplement available monitoring data often can
minimize the need to resort to arbitrarily setting limits on inclusion of infrequently detected
chemicals in the risk assessment.
In addition to available monitoring data and modeling results, the risk assessor should consider
other relevant factors (e.g., presence of sensitive subpopulations) in recommending appropriate
site-specific limits on inclusion of risk assessment.
The reported or modeled concentrations and locations of chemicals should be examined to check
for "hotspots" (localized areas of particularly high concentrations), which may be especially
important for short-term exposures and which therefore should not be eliminated from the risk
assessment. For PB-HAPs, always consider detection of particular chemicals in all sampled
media because some media may be sources of contamination for other media. In addition,
infrequently detected chemicals with concentrations that greatly exceed reference concentrations
should not be eliminated.
10.4 Use a Toxicity-Weighted or Risk-based Screening Analysis
The objective of this screening procedure is to identify the chemicals in a particular analysis that,
based on concentration and toxicity, are most likely to contribute significantly to the resulting
risk estimates. These procedures are described, along, with examples, in Chapter 6.
11.0 Summarize and Present Data
The section of the risk assessment report summarizing the results of the data collection and
evaluation should be titled "Identification of COPC." Information in this section should be
presented in ways that readily support the calculation of exposure concentrations in the exposure
assessment portion of the risk assessment. Exhibits 8 and 9 present examples of tables to be
included in this section of the risk assessment report.
11.1 Summarize Data Collection and Evaluation Results in Text
In the introduction for this section of the risk assessment report, clearly discuss in bullet form the
steps involved in data evaluation. If the optional screening procedure described in Section 9 was
used in determining COPC, these steps should be included in the introduction. If both historical
data and current data were used in the data evaluation, state this in the introduction. Any special
site-specific considerations in collecting and evaluating the data should be mentioned. General
uncertainties concerning the quality associated with either the collection or the analysis of
samples should be discussed so that the potential effects of these uncertainties on later sections
of the risk assessment can be determined.
In the next part of the report, discuss the samples from each medium selected for use in
quantitative risk assessment. Provide information concerning the sample collection methods
used (e.g., grab, composite) as well as the number and location of samples. If any samples (e.g.,
field screening/analytical samples) were excluded specifically from the quantitative risk
April 2004 Page H-19
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assessment prior to evaluating the data, document this along with reasons for the exclusion.
Again, remember that such samples, while not used in the quantitative risk assessment, may be
useful for qualitative discussions and therefore should not be entirely excluded from the risk
assessment.
Discuss the data evaluation within the appropriate context for the risk assessment. For example,
the focus may be on a particular neighborhood within the assessment area; specific types of
modeled receptors; or specific geographic features such as a water body. For PB-HAPs, the
discussion should include those media (e.g., wastes, soils) that are potential sources of
contamination for other media (e.g., surface water/sediments). If no samples or data were
available for a particular medium, discuss this in the text. For soils data, discuss surface soil
results separately from those of subsurface soils. Discuss surface water/sediment results by the
specific surface water body sampled.
Exhibit 8. Example of Table Format for Presenting Air Toxics Sampled in Specific Media
Air Toxic
Chemical A
Chemical B00
Concentration in Medium X
Frequency of
Detection(a)
3/25
25/25
Range of Sample
Quantitation Limits (SQLs)
(units)
2-30
1 -32
Range of Detected
Concentrations
(units)
320 - 4600
17-72
Background
Levels
100 - 140
~
~ Not sampled
(a) Number of samples in which the chemical was positively detected over the number of samples available
^ Identified as a COPC based upon evaluation of data according to procedures described in text of report
For each medium, identify in the report the chemicals for which samples were analyzed, and list
the analytes that were detected in at least one sample. If any detected chemicals were eliminated
from the quantitative risk assessment based on evaluation of data (i.e., based on evaluation of
data quality, background comparisons, and the optional screening procedures, if used), provide
reasons for the elimination in the text (e.g., chemical was detected in blanks at similar
concentrations to those detected in samples or chemical was infrequently detected).
April 2004
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Exhibit 9. Example of Table Format for Summarizing COPC in All Media Sampled
Air Toxic
Chemical A
Chemical B
Chemical C
Chemical D
Concentration
Air
((ig/m3)
0.5-225
0.1 -22
0.01-2.2
3-854
Soils
(mg/kg)
5- 1,100
0.5-6.4
~
2- 12
Surface Water
(Mg/1)
2-30
~
50 - 440
~
Sediments
(Mg/1)
~
12-3650
100- 11,000
~ Not sampled
The final subsection of the text is a discussion of general trends in the data results. For example,
the text may mention (1) whether concentrations of COPC in most media were close to the
detection limits or (2) trends concerning chemicals detected in more than one medium or in more
than one operable unit at the site. In addition, the location of hot spots should be discussed, as
well as any noticeable trends apparent from sampling results at different times.
11.2 Summarize Data Collection and Evaluation Results in Tables and Graphics
As shown in Exhibit 8, a separate table that includes all chemicals detected in a medium can be
provided if appropriate. Chemicals that have been determined to be of potential concern based
on the data evaluation should be designated in the table with an asterisk to the left of the
chemical name.
For each chemical, present the frequency of detection in a certain medium (i.e., the number of
times a chemical was detected over the total number of samples considered) and the range of
detected or quantified values in the samples. Do not present the QL or similar indicator of a
minimum level (e.g., <10 mg/L, ND) as the lower end of the range; instead, the lower and upper
bound of the range should be the minimum and maximum detected values, respectively. The
range of reported QLs obtained for each chemical in various samples should be provided in a
separate column. Note that these QLs should be sample-specific; other types of
non-sample-specific values (e.g., MDLs or CRQLs) should be provided only when SQLs are not
available. Note that the range of QLs would not include any limit values (e.g., unusually high
QLs) eliminated based on the guidance in Section 3. Finally, naturally occurring concentrations
of chemicals used in comparing sample concentrations may be provided in a separate column.
The source of these naturally occurring levels should be provided in a footnote. List the identity
of the samples used in determining concentrations presented in the table in an appropriate
footnote.
The final table in this section is a list of the COPC presented by medium at the site or by medium
within each operable unit at the site. A sample table format is presented in Exhibit 9. Ths
isopleth is another useful type of presentation of chemical concentration data (not shown). This
April 2004
Page H-21
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graphic characterizes the monitored or modeled concentrations of chemicals at a site and
illustrates the spatial pattern of contamination.
References
1. U.S. Environmental Protection Agency. 1989. Risk Assessment Guidance for Superfund:
Volume I. Human Health Evaluation Manual (Part A). Office of Emergency and Remedial
Response. Washington, DC, EPA/541/1-89/002, available at:
http://www.epa.gov/superfund/programs/risk/ragsa/index.htm
2. U.S. Environmental Protection Agency. 1992. Guidance for Data Useability in Risk
Assessment (Part A). Office of Emergency and Remedial Response, Washington, DC.
Publication 92857-09A, PB92-93356, available at:
http://www.epa.gov/oerrpage/superfund/programs/risk/datause/parta.htm.
April 2004 Page H-22
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Appendix I Use of Air Monitoring Data to
Develop Estimates of Exposure
Concentration (Data Analysis and
Reduction)
Table of Contents
1.0 Introduction 1
2.0 Data Treatment and Handling of Non-Detects 2
3.0 Statistical Methods: Characterization of Concentration Data 4
References 8
-------
-------
1.0 Introduction
This appendix discusses the process of air monitoring data analysis and reduction, the goals of
which are to (1) extract and summarize air monitoring data needed for the risk assessment, (2)
use the data to develop estimates of exposure concentration (EC), and (3) present the results of
the air monitoring study in an informative and understandable format. In short, this Appendix
describes how to take the refined air monitoring data sets developed according to the processes
described in Appendix H and use them to develop estimates of exposure concentration. Standard
computer software packages, such as Microsoft Excel® or the Statistical Analysis System,® may
be used to generate summary statistics for each chemical and monitoring location. Summary
statistics should include:
Tentatively Identified Compounds (TICs)
As noted in Appendix H, TICs are chemicals
identified in the laboratory, but which cannot be
identified with complete accuracy. Given that there
is not certainty as to their identify (and because, there
often is no toxicity data for them), TICs are often
assess only qualitatively in the risk assessment. The
level of detail applied to TICs depends on their
tentative identification (are they known toxic
compounds), their concentration, known sources, and
frequency of detection. Depending on the answers to
these questions, the analyst may recommend that
re-sampling be performed to try to more accurately
determine the nature of the TICs. ,
The frequency of detection, or the
proportion of total valid
measurements collected which were
present at or above the respective
sample quantitation limit (SQL) and
including detections marked with
certain data qualifier (e.g., "J" values
see Appendix H);
The range of concentrations detected
(highest and lowest concentrations
measured for each chemical at each
monitoring site - including J values);
The statistical description of the data
(e.g., normally distributed,
log-normally distributed), based on standardized statistical tests;
• The range of sample quantitation limits (SQLs); and
• An arithmetic mean value, the standard deviation, the median value (i.e., 50th percentile),
and the 95th percentile upper confidence limit (95% UCL) of the arithmetic mean.
The mathematical formulas and procedures for calculating these summary statistics are provided
in Section 3 below.
Statistical analysis of air monitoring data may be conducted using standard methods such as
those outlined in EPA's Guidance for Data Quality Assessment - Practical Methods for Data
Analysis.(1) This manual provides a detailed description of the formulae that should be used in
estimating the parameters mentioned above, and reviews issues associated with data treatment
(e.g., treatment of non-detects, use of J-qualified data). EPA's Calculating Upper Confidence
Limits for Exposure Point Concentrations at Hazardous Waste Sites (2) is also an important
reference to consider when evaluating air monitoring data for exposure assessments. Readers are
encouraged to review both of these document prior to using monitoring data to calculate
exposure concentrations.
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Data Qualifiers
Having obtained a monitoring result, it is necessary to assign a qualifier to it so decision-makers can
understand the quality of the result and, hence, the role the result might play in decisions (a more
complete discussion of data qualifiers is provided in Appendix H).
• U Flag. If the value is below the MDL, the result should be flagged as
-------
In general, once it is clear that there are no issues with field duplicate samples, they should be
treated as a single sample by simply averaging their results. In cases where a chemical is
detected in one but not both duplicates (or the data is J-qualified), the chemical should be
assumed to be present and the two values should be averaged using the procedure for handling
non-detects as described below.
When a chemical is not detected in any sample at a monitor, that chemical can usually be
removed from further consideration if there are no known problems with the method, the method
meets DQOs, and there is no reason to suspect that the chemical should have been detected (e.g.,
there are no known sources, and the chemical was also not found at other monitors). In some
instances, the monitoring methodology (or interferences by other substances) do not allow for
the detection of a substance, even when it is present. The assessors must weigh these types of
evidence when deciding to drop a chemical from further consideration.
Various procedures have been used in risk
assessments to treat non-detects (i.e.,
samples in which the chemical
concentration is not present at or higher
than the sample quantification limit
(SQL)), ranging from the assumption that
the chemical is absent (i.e., the true
concentration is zero) to the assumption
that the chemical was present in a sample
at a level infmitesimally beneath the SQL
(i.e. very close to the SQL and so
essentially equal to the SQL). Some
algorithms differentiate assignment of
values to non-detects based upon the
frequency of a chemical's detection. For
example, if a chemical is detected in
almost all samples, a concentration equal
to (or some fraction of) the analytical
SQL is assigned to non-detects, but if the ^ '
chemical is detected in few or no samples,
a concentration of zero is assumed for non-detects. In general, the strategy described below may
be used to address the issue of non-detects. References 1 and 2 provide more information on this
subject and analysts are encouraged to become familiar with both of these documents prior to
beginning data analysis. Also note that the generic upon which the procedure described below is
based assumes approximately 30 or more samples collected over the course of a year are being
averaged to develop an estimate of long term exposure concentration; however, air toxics
monitoring sampling schemes usually collect samples on at least a one-in-six day schedule,
giving the analyst approximately 60 or more samples to work with. Sampling frequencies are
sometimes even greater.
• If less than 15% of the monitored concentrations of a given chemical at a given location are
below the SQL, then a value equal to 1A of the respective SQL is assigned to these
concentrations and these values are used in the calculation of summary statistics as described
below.
The MDL or the SQL: Which One Should I Use
for Risk Assessment?
When including non-detected data in the averaging
processes described on this page, one may either
include the non-detected sample as 1A the MDL or 1A
the SQL. The MDL is not appropriate for this task
because it is a statistical measure developed by each
lab for each analytical instrument and can fluctuate
from day to day. In other words, it is not a stable
measure of true detection "limit." In addition, many
labs that actually do detect a chemical in a sample at
levels less than the quantitation limit do not routinely
report the detection because they cannot accurately
quantitate its concentration). It is for these two
reasons that 1A the SQL is used when including
nondetected samples in the averaging process. This
holds even when the lab in question routinely reports
J-valued data.
April 2004
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• If greater than 90% of the monitored concentrations of a given chemical at a given location
are less than the respective SQL, no estimation of the statistical descriptors is undertaken
initially. If concentrations were only detected on a limited number of days (i.e., 1 to 3 days)
then an investigation may be undertaken to assess the potential sources for these chemicals
and the validity of the measurements. A knowledgeable statistician can help determine an
appropriate method for developing summary statistics from such a data set, if appropriate.
• If between 15% and 90% of the monitored concentrations of a given chemical at a given
location are greater than the respective SQL, then a value equal to /^ of the respective SQL is
assigned to these concentrations and these values are used in the calculation of summary
statistics as described below. For chemicals in this group that end up contributing
significantly to risk, a knowledgeable statistician may reevaluate the data according to the
procedures in appropriate guidance (e.g., those provided in references 1 and 2).
3.0 Statistical Methods: Characterization of Concentration Data
One method to estimate the long-term annual average concentration would be to calculate a
simple arithmetic mean for each analyte/monitor combination. The arithmetic mean, or average
is constructed from discrete sample measurements taken at the monitor over time. As noted
previously, constraints on resources almost always place limits on the amount of sampling
possible (e.g., air toxics samples usually cannot be collected every day). Instead, samples are
usually collected roughly one out of every six days and in a manner to eliminate obvious sources
of bias (e.g., samples are not uniformly collected on the same day of the week, or only on
weekdays or only on weekends). In addition, collecting samples for a year allows for an
evaluation of seasonal variability.
All factors being equal, one would expect the sampling results from such a monitoring program
to contain equal probabilities of sampling on days when pollutant concentrations may have been
relatively high as on days when pollutant concentrations may have been relatively low (or on
days when meteorological conditions were conducive to high ground-level concentrations and
days when they were not). Since samples are usually not collected every single day, however,
one cannot be absolutely certain that all possible conditions were sampled equally. The
arithmetic mean concentration is thus subject to uncertainty due to a number of factors,
including:
• Daily variability in concentrations;
• The ability to measure only a finite number of instances from the distribution of
concentrations over time; and
• Potential inaccuracy in individual measurements of concentrations.
This uncertainty produces a result in which the simple arithmetic mean of sampling results may
underestimate, approach, or overestimate the true annual average. (The example below
illustrates how three different monitoring data sets taken at the same monitor may result in an
average concentration that underestimates, overestimates, or is close to the true long term
average concentration.) Given this uncertainty in the use of the arithmetic mean concentration to
describe "average" exposure concentration, the 95% Upper Confidence Limit of the mean (95%
UCL) is commonly used as a public health protective estimate of the true annual average.
Proceeding in this manner is likely to overestimate the true long-term average exposure;
April 2004 Page 1-4
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however, this method virtually obviates the risk of underestimating the true exposure. EPA's
Superfund program has routinely used this procedure to evaluate exposures at hazardous sites
and this process has garnered long term acceptance as a public health protective approach, in
light of the uncertainties.
Example Showing How Simple Arithmetic Mean
Does Not Always Represent the True Annual Average
t
o
D
U
O
u
Sample Set A Sample Set B Sample Set C
95% VCL
\
Average of
Sample Set
True (but
Unknown)
Average
Distributional Analysis
To calculate the 95% UCL for a chemical data set from a monitor, it is necessary to understand
its underlying statistical distribution, including whether the sampling results are normally or
lognormally distributed. Once the analysis goes beyond these commonly understood
distributional types, the level of statistical sophistication can increase substantially. EPA's
Office of Air Quality Planning and Standards (OAQPS) has developed the following pragmatic
strategy to evaluate the distribution of monitoring data sets; however, other approaches are
available (see references 1 and 2). Specifically, EPA suggests the following procedure:
• Inspect each data set for normality using standard test procedures (e.g., Shapiro-Wilk Test,
Komolgorov-Smirnoff Test, or Filibens Test). If the assumption of normality holds, then the
summary descriptive statistics, including the 95% UCL, should be calculated as described
below with the equations based on the statistical assumption of a normal distribution.
• If the data are not normally distributed, then they are presumed to be lognormal and are
log-transformed by taking the natural logarithm of the measured concentrations. The
assumption of normality is then used to test the transformed data. If the assumption of
normality holds for the transformed data, the summary descriptive statistics, including he
April 2004
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95% UCL, are developed with the transformed data using the equations based on the
statistical assumption of a lognormal distribution.
• If the transformed data are not lognormal, they may be treated initially as lognormal. For
chemicals in this group that significantly contribute to risk, a knowledgeable statistician may
reevaluate the data (e.g., according to the procedures suggested in References 1 and 2).
The use of this simple and pragmatic approach to data analysis allows most scientists and
engineers with a basic background in statistics to perform these analyses without access to
advanced statistical analysis resources. Presuming a data set is lognormally distributed generally
results in a 95% UCL that is conservative and, thus, public health protective. Only those
chemicals that the initial risk characterization identifies as being significant risk drivers would
be reevaluated with more robust statistical procedures, depending on the needs of the risk
manager.
STATISTICAL FORMULAS
The following Exhibits provide the basic equations for developing the 95% UCL for chemical
data sets that are either normally distributed (Exhibits 1 and 2) or lognormally - or presumed to
be lognormally - distributed (Exhibits 3 and 4). The Students t and H statistics that are needed
to perform these calculations are available in Gilbert's 1987 book Statistical Methods for
Environmental Pollution Monitoring.^
Normally Distributed Data Sets
Exhibit 1. Directions for Computing UCL for the Mean of a Normal Distribution - Student's t
Let
STEPS:
, . . . , Xn represent the n randomly sampled concentrations.
—
STEP 1: Compute the sample mean X = — / ,
STEP 2: Compute the sample standard deviation s =
n-
_
t - JQ
Use atable of quantiles of the Student's t distribution to find the (l-oc)th quantile of the
Student's t distribution with n-\ degrees of freedom. For example, the value at the 0.05
level with 40 degrees of freedom is 1 .684. A table of Student's t values can be found in
Gilbert (1987, page 255, where the values are indexed by p = 1-oc, rather than a level).
The t value appropriate for computing the 95% UCL can be obtained in Microsoft Excel8
with the formula TINV ((1-0.95)*2, «-l).
STEP 4: Compute the one-sided (l-«) upper confidence limit on the mean
ta j s
April 2004
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Exhibit 2. An Example Computation of UCL for a Normal Distribution - Student's t
25 VOC samples were collected from an air monitoring station and analyzed for a specific chemical.
The values observed are 228, 552, 645, 208, 755, 553, 674, 151, 251, 315, 731, 466, 261, 240, 411,
368, 492, 302, 438, 751, 304, 368, 376, 634, and 810 (ig/m3. It seems reasonable that the data are
normally distributed, and the Shapiro-Wilk Wtest for normality fails to reject the hypothesis that they
are (W= 0.937). The UCL based on Student's t is computed as follows:
STEP 1: The sample mean of the n = 25 values is x = 451
STEP 2: The sample standard deviation of the values is s = 198
STEP 3: The /-value at the 0.05 level for 25-1 degrees of freedom is t0 05 2s-\ = 1.710
STEP 4: The one-sided 95% upper confidence limit on the mean is therefore:
95% UCL = 451+(1.710 x 198 / A/25) = 519
Lognormally Distributed Data
Exhibit 3. Directions for Computing UCL for the Mean of a Lognormal
Distribution - Land Method
Let
, . . . , Xn represent the n randomly sampled concentrations.
1
STEP 1: Compute the arithmetic mean of the log-transformed data In X = — /, ln( Xt)
Yl • i
STEP 2: Compute the associated standard deviation slnX =
n~
STEP 3: Look up the H^ statistic for sample size n and the observed standard deviation of the log-
transformed data. Tables of these values are given by Gilbert (1987, Tables A-10 and A-
12) and Land (1975).
STEP4: Compute the one-sided (1-a) upper confidence limit on the mean
April 2004
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Exhibit 4. An Example Computation of UCL for a lognormal Distribution - Land Method
31 VOC samples were collected from an air monitoring stations and analyzed for a specific chemical.
The values observed are 2.8, 22.9, 3.3, 4.6, 8.7, 30.4, 12.2, 2.5, 5.7, 26.3, 5.4, 6.1, 5.2, 1.8, 7.2, 3.4,
12.4,0.8, 10.3, 11.4,38.2,5.6, 14.1, 12.3,6.8,3.3,5.2,2.1, 19.7, 3.9, and 2.8 (ig/m3. Because of their
skewness, the data may be lognormally distributed. The Shapiro-Wilk Wtest for normality rejects the
hypothesis, at both the 0.05 and 0.01 levels, that the distribution is normal. The same test fails to reject
at either level the hypothesis that the distribution is lognormal. The UCL on the mean based on Land's
H statistic is computed as follows:
STEP 1: Compute the arithmetic mean of the log-transformed data In X = 1.8797
STEP 2: Compute the associated standard deviation slnX = 0.8995
STEP 3: The H statistic for « = 31 and slnX = 0.90 is 2.31
STEP4: The one-sided 95% upper confidence limit on the mean is therefore:
95% UCL = exp( 1.8797 + 0.89952 / 2 + 2.31 x 0.8995 / V31- 1) = 14.4
It is statistically possible for the 95% UCL confidence limit of the mean to exceed the maximum
measured concentration for a chemical. If this exceeding occurs, the maximum concentration of
the chemical is commonly used in place of the 95th percentile upper confidence limit as the
exposure concentration, with certain caveats (see reference 2).
References
1. U.S. Environmental Protection Agency. 1998. Guidance for Data Quality Assessment -
Practical Methods for Data Analysis. EPA/QA-G9, QA97 Version, EPA 600/R96/O84,
Washington, DC, January 1998; available atwww.epa.gov/swerustl/cat/epaqag9.pdf
2. U.S. Environmental Protection Agency. 2002. Calculating Upper Confidence Limits for
Exposure Point Concentrations at Hazardous Waste Sites. Office of Emergency and
Remedial Response, Washington, DC, December 2002. OSWER 9285.6-10, available at
http://www.epa.gov/superfund/programs/risk/ragsa/ucl.pdf
3. Gilbert, R.O. 1987'. Statistical Methods for Environmental Pollution Monitoring. John Wiley
& Sons, New York, NY.
April 2004 Page 1-8
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Appendix J Air Monitoring and Sampling
Methods
This appendix contains a summary of monitoring and sampling methods for a variety of organic
and inorganic compounds in ambient air. Each approach is described briefly, with a listing of
compounds for which it is appropriate, the detection limit, and a summary of advantages and
disadvantages in using the approach. Descriptions of the methods can be downloaded from the
EPA's Ambient Monitoring Technology Information Center (AMTIC) website
(www.epa.gov/ttn/amtic/airtox.htmn.
The measurement process generally relies on collecting a sample in the field, followed by a
return to the lab for analysis. A number of methods are used for initial collection of samples in
the field:
1. Sampling tubes, in which air is drawn through a tube containing a sorbent specific to the
compound being sampled, and the tube returned to the lab for analysis. Possible sorbents in
the tube are organic polymers; carbon (molecular, activated, etc); polyurethane foam; silica
gel; and dinitrophenylhydrazone (DNPH). Multi-sorbents also are available.
2. Filters, in which air is drawn through a fiber (often a glass fiber) filter, collecting the
sampled compound, and returned to the lab for analysis. In some methods, air is drawn over
an absorbent onto which the chemical sorbs. In some methods, a chemical reaction occurs
that converts the air toxics to another material that is then analyzed.
3. Cryogenic traps, in which air is drawn into a chamber at low temperature, condensing the
compound out of the air. The trap and condensate are returned to the lab for analysis.
4. Evacuated chambers, in which air is drawn into a chamber under vacuum. The chamber is
returned to the lab for analysis.
An important consideration in the use of such methods is the available time between collection
and analysis of samples. The compounds will degrade during the intervening holding period,
and so this holding period should not exceed maximum allowed times (holding times depend on
the method and compound (consult the AMTIC website for information on QA/QC for air
monitoring).
April 2004 Page J-l
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April 2004 Page J-2
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Method
Designation
TO-1
TO-2
TO-3
TO-4
TO-5
Applicable
Compounds
VOCs(80°to
200° C); e.g.
benzene,
toluene, xylenes.
Highly volatile
VOCs
(-15° to 120° C);
e.g. vinyl
chloride,
chloroform,
chlorobenzene.
Nonpolar VOCs
(-10°to200°C);
e.g. vinyl
chloride,
methylene
chloride,
acrylonitrile.
Pesticides and
PCBs; e.g.
PCBs, 4,4-DDE,
DDT, ODD.
Aldehydes and
Ketones; e.g.
formaldehyde,
acetaldehyde,
acrolein.
Approach
Ambient air is drawn through organic
polymer sorbent where certain
compounds are trapped. The cartridge is
transferred to the lab, thermally
desorbed and analyzed using GC/MS or
GC/FID.
Selected volatile organic compounds are
captured on carbon molecular sieve
absorbents. Compounds are thermally
desorbed and analyzed by GC/MS or
GC/FID techniques.
Vapor phase organic s are condensed in a
cryogenic trap. Carrier gas transfers the
condensed sample to a GC column.
Absorbed compounds are eluted from
the GC column and measured by FID or
ECD.
Pesticides/PCBs trap on filter and PUT
absorbent trap. Trap is returned to lab,
solvent extracted and analyzed by
GC/FID/ECD or GC/MS.
Air sample is drawn through DNPH
impinger solution using a low volume
pump. The solution is analyzed using
HPLC with a UV detector.
Detection
Limit
0.01 to 100 ppbv
0.1 to 200 ppbv
0.1 to 200 ppbv
0.2 pg/m3 to 200
ng/m3
1 to 50 ppbv
Advantages
Good data base; large sample
volume; water vapor not collected;
wide variety of compounds
collected; low detection limits;
standard procedures available;
practical for field use.
Trace levels of VOCs are collected
and concentrated; efficient
collection of polar compounds; wide
range of application; highly volatile
compounds are absorbed; easy to
use in field.
Collects a wide variety of VOCs;
standard procedures are available;
contaminants common to absorbent
materials are avoided; low blanks;
consistent recovery; large data base.
Low detection limits; effective for
broad range of pesticides and PCBs;
PLTF reusable; low blanks; excellent
collection and retention efficiencies
for common pesticides and PCBs.
Specific for aldehydes and ketones;
good stability for derivative
compounds formed in the impingers;
low detection limits.
Disadvantages
Highly volatile compounds and
certain polar compounds not
collected; rigorous clean-up of
absorbent required; no possibility of
multiple analyses; low breakthrough
volume for some compounds;
desorption of some compounds
difficult; interference from
structural isomers; possible
contamination of sorbent and blank;
artifact formation.
Some trace levels of organic species
are difficult to recover from sorbent;
interferences from structural
isomers; water is collected and can
de-activate absorption sites; thermal
desorption of some compounds
difficult.
Moisture levels in air can cause
freezing problems in cryogenic trap;
difficult to use in field; expensive;
integrated sampling is difficult;
compounds with similar retention
times interfere.
Breakdown of PUT absorbent may
occur with polar extraction solvents;
contamination of glassware may
increase detection limits; loss of
some semi-volatile organics during
storage; interference by extraneous
organics; difficulty in identifying
individual pesticides and PCBs if
ECD used.
Sensitivity limited by reagent purity;
potential for evaporation of liquid
over long term sampling; isomeric
aldehydes and ketones may be
unresolved by the HPLC system.
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Method
Designation
TO-6
TO-7
TO-8
TO-9A*
Applicable
Compounds
Phosgene
N-nitroso
dimethylamine
Cresol and
phenol
Dioxin, furan
and PCBs
Approach
Ambient air is drawn through a midget
impinger containing 10 ml of 2/98
aniline/toluene (v/v). Phosgene reacts
with aniline to form 1,3-diphenylurea
and is analyzed using reverse-phase
HPLC with a UV absorbance detector
operating at 254 nm.
Ambient air is drawn through a cartridge
containing Thermosorb/N absorbant to
trap N-nitrosodimethyl amine. The
cartridge is returned to the lab and
eluted with 5 ml of dichloromethane.
The cartridge then is eluted in reverse
direction with 2 ml of acetone. The N-
nitrosodimethylamine is determined by
GC/MS.
Ambient air is drawn through two
midget impingers. Phenols are trapped
as phenolates in NaOH solution, which
is returned to the lab and analyzed by
HPLC.
Ambient air is drawn through a glass
fiber filter and a polyurethane foam
(PLTF) absorbent cartridge with a high
volume sampler. The filter and PUT
cartridge are returned to the lab and
extracted using toluene. The extract is
concentrated using the Kudrena-Danish
technique, diluted with hexane, and
cleaned up using column
chromatography. The cleaned extract
then is analyzed by high resolution
GC/high resolution MS.
Detection
Limit
1 to 50 ppbv
1 to 50 ppbv
1 to 250 ppbv
0.25 to 5000
pg/m3
Advantages
Good specificity; good stability for
derivative compounds formed in the
impingers; low detection limits.
Good specificity; good stability for
derivative compounds formed on the
cartridge; low detection limit for n-
nitrosodimethylamine; placement of
sorbent as first compound in sample
train minimizes contamination;
sampling system portable and
lightweight.
4,6-dinitro-2-methylphenol specific
to class of compounds; good
stability; detects non- volatile as well
as volatile phenol compounds.
Cartridge is reusable; excellent
detection limits; easy to preclean
and extract; excellent collection and
retention efficiencies; brad database;
proven methodology.
Disadvantages
Chloroformates and acidic materials
may interfere; contamination of
aniline reagents may interfere; use
of midget impingers in field
application may not be practical.
Compounds with similar GC
retention times and detectable MS
ions may interfere; specificity is a
limiting factor if looking for other
organic amines.
Compounds having the same HPLC
retention times may interfere;
phenolic compounds of interest may
be oxidized; limited sensitivity.
Analytical interferences may occur
from PCBs, methoxybiphenyls,
chlorinated hydroxydiphenylethers,
napthalenes, DDE and DDT with
similar retention times and mass
fractions; inaccurate measurement
Ds/Fs are retained on particulate
matter and may chemically change
during sampling and storage;
analytical equipment required
(HRGC/HRMS) expensive and not
readily available; operator skill level
important; complex preparation and
analysis process; can't separate
particles from gas phase.
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Method
Designation
TO-10A
TO-11A
TO- 12
TO- 15
Applicable
Compounds
Pesticides; e.g.
heptachlor,
chlordane,
dieldrin, aldrin
Formaldehyde,
other aldehydes
and ketones; e.g.
formaldehyde,
acetaldehyde,
acrolein.
Non-methane
organic
compounds
(NMOC)
VOCs (polar and
non-polar);
methanol,
benzene, xylene,
nitrobenzene
Approach
A low volume sample (1-5 L/min) is
pulled through a PUF plug to trap
organochlorine pesticides. After
sampling, the plug is returned to the lab,
extracted and analyzed by GC coupled
to multi-detectors (ECID, PID, FID,
etc).
An ambient air sample is drawn through
a DNPH cartridge at a rate of 500 to
1200 ml/minute. The cartridge is
returned to the lab in screw-cap glass
vials. The cartridge then is removed
from the vial and washed with
acetonitrile by gravity feed elution. The
eluate is diluted volumetrically and an
aliquot is removed for determination of
the DNPH-formaldehyde derivative by
isocratic reverse phase HPLC with UV
detection at 350 nm.
Ambient air is drawn into a cryogenic
trap, where the non-methane organic
compounds (NMOCs) are concentrated.
The trap is heated to move the NMOCs
to the FID. Concentration of NMOCs is
determined by integrating under the
broad peak. Water correction is
necessary.
Whole air samples are collected in a
specifically -prepared canister. VOCs
are concentrated on a solid sorbent trap
or other arrangement, separated on a GC
column, and passed to an MS detector
for identifaction and quantification.
Detection
Limit
1 to 100 ng/m3
0.5 to lOOppbv
0.1 to 200
ppmvC
0.2 to 25 ppbv
Advantages
Easy field use; proven methodology;
easy to clean; effective for broad
range of compounds; portable; good
retention of compounds.
Placement of sorbent as first
element in the sampling train
minimizes contamination; large
database; proven technology;
sampling system is portable and
lightweight.
Standard procedures are available;
contaminants common to absorbent
materials are avoided; low blanks;
consistent recoveries; large data
base; good sensitivity; useful for
screening areas or samples; analysis
much faster than GC.
Incorporates a multi-sorbent/dry
purge technique to manage water;
has established methods
performance criteria; provides
enhanced provisions for QC; unique
water management approach allows
analysis of polar VOCs.
Disadvantages
ECD and other detectors (except
MS) are subject to responses from a
variety of compounds other than
target analytes; PCBs, dioxins and
furans may interfere; certain
organochlorine pesticides (e.g.
chlordane) are complex mixtures
and can make accurate
quantification difficult; may not be
sensitive enough for all target
analytes.
Isometric aldehydes and ketones and
other compounds with the same
HPLC retention time as
formaldehyde might interfere;
Carbonyls on the DNPH cartridge
may degrade if an ozone denuder is
not used; liquid water captured on
the DNPH cartridge during
sampling may interfere; ozone and
UV light deteriorates trapped
carbonyls on cartridge.
Moisture levels in air can cause
freezing problems; non-speciated
measurement; precision is limited.
Expensive analytical equipment;
depends critically on operator skill
level.
April 2004
Page J-5
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Method
Designation
TO-16
TO- 17
IO-1
IO-2
Applicable
Compounds
Polar and non-
polar VOCs; e.g.
alcohols,
ketones,
benzene,
toluene, o-
xylene,
chlorobenzene.
Polar and non-
polar VOCs; e.g.
alcohols,
ketones,
benzene,
toluene, o-
xylene,
chlorobenzene.
Suspended
particulate
matter (SPM);
continuous
measurement.
Suspended
particulate
matter (SPM);
integrated
measurement.
Approach
VOCs are monitored using real-time
long-path open-path Fourier transform
infrared spectroscopy (FTIR).
Ambient air is drawn through a multi-
bed sorbent tube where VOCs are
trapped. The cartridge is returned to the
lab, thermally desorbed and analyzed by
GC/MS or other methods.
Ambient air is drawn at a rate of
approximately 16 to 17 L/minute
through a virtual impact or cyclonic
flow filter. Particle build-up on a filter
tape is determined continuously either
through measurement of attenuation of
beta particles incident on the tape or
through an oscillating pendulum.
Ambient air is drawn through a filter
with a high volume sampler, with large
(> 10 micron) particles removed prior to
the filter. The filter is weighed before
and after sampling, with dessication to
remove water vapor. Mean particulate
concentration is determined from mass
gain and air flow rate.
Detection
Limit
25 to 500 ppbv
0.2 to 25 ppbv
3
micrograms/m3.
1 microgram/m3
Advantages
Open path analysis maintains
integrity of samples; multi-gas
analysis saves money and time;
path-integrated pollutant
concentration measurement
minimizes possible sample
contamination and provides real-
time pollutant concentration;
applicable for special survey
monitoring; monitoring at
inaccessible areas possible using
open-path FTIR.
Placement of the sorbent as the first
element minimizes contamination
from other sample train components;
large selection of sorbents to match
with target analyte list; includes
polar VOCs; better water
management using hydrophobic
sorbents than Compendium Method
TO-14A; large database; proven
technology; size and cost advantages
in sampling equipment.
Less sensitive to temperature,
pressure and humidity fluctuations
than other continuous methods.
Well established methodology;
relatively simply technique to
employ
Disadvantages
High levels of operator skill
required; requires spectra
interpretation; Limited spectral
library available; higher detection
limits than most alternatives; must
be skilled in computer operation;
substantial limitations from ambient
CO2 and humidity levels associated
with spectral analysis.
Distributed volume pairs required
for quality assurance; rigorous
clean-up of sorbent required; no
possibility of multiple analysis;
must purchase thermal desorption
unit for analysis; desorption of some
VOCs is difficult; contamination of
absorbent can be a problem.
Results can be biased by water
collection on the filter tape;
oscillator must be isolated from
external noise and vibrations.
Balance used in measurement must
be precise; subject to bias due to
collection of water vapor if
complete dessication is not
obtained;
April 2004
Page J-6
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Method
Designation
10-3
IO-4
10-5
Applicable
Compounds
Chemical
species analysis
of filter-
collected SPM.
Reactive acidic
and basic gases;
strong acidity of
atmospheric fine
particles.
HN03, NH3,
HCL, S02, NH4,
SO4, NO3
Atmospheric
mercury
Approach
Ambient air is drawn through a filter
with a high volume sampler, with large
(> 10 micron) particles removed prior to
the filter. The filter is weighed before
and after sampling, with dessication to
remove water vapor. The filter then is
subsampled and strips digested using a
microwave or hot acid extraction
technique. Specific extracts are
analyzed by the appropriate method.
Based on measurement of the fine
particle strong acidity component of the
atmosphere. Air is drawn through an
annular denuder followed by a 37 mm
Teflon filter to trap the fine particle acid
aerosol. The filter is returned to the lab
for extraction and analysis using an
aequeous solution of perchloric acid
followed by titration or pH
determination.
Low flow (for vapor phase) or higher
flow (for particulate phase) ambient air
stream is flowed over gold coated bead
traps and glass fiber filters. Mercury
content is determined by cold- vapor
atomic fluorescence spectrometry after
thermal desorption.
Detection
Limit
Depends on
compound
considered.
30 pg/m3
(particulate
phase) or 45
pg/m3 for vapor
phase.
Advantages
Advantages depend on chemical
species analyzed, but particle
collection has the advantages noted
in IO-2.
Simple method of analysis; well
established methodology.
No known positive interferences
using the 253.7 nm wavelength to
excite the mercury atoms.
Disadvantages
Disadvantages depend on chemical
species analyzed.
Without denuders employed to
remove ammounia and other acid
gases, interference can occur.
Possible interferences from PAHs
and water vapor; excessive water
quenches signal; free halogens can
degrade trap.
April 2004
Page J-7
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Appendix K Equations For Estimating
Concentrations of PB-HAP
Compounds in Food and Drinking
Water
Table of Contents
1.0 Introduction 1
2.0 Calculation of PB-HAP Compound Concentrations in Soil 1
2.1 Calculating Cumulative Soil Concentration (Cs) 2
2.2 Calculating the PB-HAP compound Soil Loss Constant (ks) 3.
2.2.1 PB-HAP compound Loss Constant Due to Biotic and Abiotic Degradation (ksg) 4
2.2.2 PB-HAP compound Loss Constant Due to Soil Erosion (kse) 5
2.2.3 PB-HAP compound Loss Constant Due to Runoff (for) 6
2.2.4 PB-HAP compound Loss Constant Due to Leaching (ksl) 6
2.2.5 PB-HAP compound Loss Constant Due to Volatilization (fov) 7
2.3 Calculating the Deposition Term (Ds) £
2.4 Universal Soil Loss Equation (USLE) 9
2.5 Site-Specific Parameters for Calculating Cumulative Soil Concentration 9
2.5.1 Soil Mixing Zone Depth (Zs) 9
2.5.2 Soil Dry Bulk Density (BD) 9
2.5.3 Available Water (P +1 - RO - Ev} K)
2.5.4 Soil Volumetric Water Content (0SW) K)
3.0 Calculation of PB-HAP Compound Concentrations in Produce K)
3.1 Aboveground Produce Concentration Due to Direct Deposition (Pd) H
3.1.1 Interception Fraction of the Edible Portion of Plant (Rp) 1_2
3.1.2 Plant Surface Loss Coefficient (kp) 12
3.1.3 Length of Plant Exposure to Deposition per Harvest of Edible Portion of Plant (Ip) . 1_2
3.1.4 Standing Crop Biomass (Productivity) (Yp) 1_2
3.2 Aboveground Produce Concentration Due to Air-to-Plant Transfer (Pv) 12
3.3 Produce Concentration Due to Root Uptake (Pr) 13
4.0 Calculation of PB-HAP Compound Concentrations in Beef and Dairy Products 14
-------
4.1 Forage and Silage Concentrations Due to Direct Deposition (Pd) 15
4.1.1 Interception Fraction of the Edible Portion of Plant (Rp) 1_5
4.1.2 Plant Surface Loss Coefficient (kp) 15
4.1.3 Length of Plant Exposure to Deposition per Harvest of the Edible Portion of Plant (Tp)
16
4.1.4 Standing Crop Biomass (Productivity) (Yp) 16
4.2 Forage and Silage Concentrations Due to Air-to-Plant Transfer (Pv) 16.
4.3 Forage, Silage, and Grain Concentrations Due to Root Uptake (Pr) 16.
4.4 Beef Concentration Resulting from Plant and Soil Ingestion (Abeej) 1/7
4.4.1 Fraction of Plant Type i Grown on Contaminated Soil and Eaten by the Animal
(Cattle)(F,) 17
4.4.2 Quantity of Plant Type i Eaten by the Animal (Cattle) Each Day (Qpt) 17
4.4.3 Concentration of PB-HAP compound in Plant Type i Eaten by the Animal (Cattle) (P,)
18
4.4.4 Quantity of Soil Eaten by the Animal (Cattle) Per Day (Qs) 18
4.4.5 Average Soil Concentration Over Exposure Duration (Cs) 18
4.4.6 Soil Bioavailability Factor (Bs) 18
4.4.7 Metabolism Factor (MF) 18
4.5 PB-HAP compound Concentration In Milk Due to Plant and Soil Ingestion (Amilk) 19.
4.5.1 Fraction of Plant Type i Grown on Contaminated Soil and Eaten by the Animal (Dairy
Cattle) (F) 19
4.5.2 Quantity of Plant Type i Eaten by the Animal (Dairy Cattle) Per Day (Qpt) 19
4.5.3 Concentration of PB-HAP compound in Plant Type i Eaten by the Animal (Dairy Cattle)
OP,) 20
4.5.4 Quantity of Soil Eaten by the Animal (Dairy Cattle) Per Day (Qs) 20
4.5.5 Average Soil Concentration Over Exposure Duration (Cs) 20
4.5.6 Soil Bioavailability Factor (Bs) 20
4.5.7 Metabolism Factor (MF) 20
5.0 Calculation of PB-HAP Compound Concentrations in Pork 20
5.1 Concentration of PB-HAP compound In Pork 20
5.1.1 Fraction of Plant Type i Grown on Contaminated Soil and Eaten by the Animal (Swine)
(F) 21
5.1.2 Quantity of Plant Type i Eaten by the Animal (Swine) Each Day (Qp;) 2J_
5.1.3 Concentration of PB-HAP compound in Plant Type i Eaten by the Animal (Swine) (P)
22
5.1.4 Quantity of Soil Eaten by the Animal (Swine) Each Day (Qs) 22
5.1.5 Average Soil Concentration Over Exposure Duration (Cs) 22
5.1.6 Soil Bioavailability Factor (Bs) 22
5.1.7 Metabolism Factor (MF) 22
6.0 Calculation of PB-HAP Compound Concentrations in Chicken and Eggs 22
-------
6.1 Concentration of PB-HAP compound in Chicken and Eggs 23.
6.1.1 Fraction of Plant Type i Grown on Contaminated Soil and Eaten by the Animal
(Chicken)(F,) 23
6.1.2 Quantity of Plant Type i Eaten by the Animal (Chicken) Each Day (Qp,) 23_
6.1.3 Concentration of PB-HAP compound in Plant Type i Eaten by the Animal (Chicken) (P,.)
24
6.1.4 Quantity of Soil Eaten by the Animal (Chicken) Each Day (Qs) 24
6.1.5 Average Soil Concentration Over Exposure Duration (Cs) 24
6.1.6 Soil Bioavailability Factor (Bs) 24
7.0 Calculation of PB-HAP Compound Concentrations in Drinking Water and Fish 24
7.1 Total PB-HAP compound Load to the Water Body (LT) 26
7.1.1 Total (Wet and Dry) Particle Phase and Vapor Phase PB-HAP compound Direct
Deposition Load to Water Body (LDEP) 26
7.1.2 Vapor Phase PB-HAP compound Diffusion Load to Water Body (Ldif) 27
7.1.3 Runoff Load from Impervious Surfaces (LRI) 27
7.1.4 Runoff Load from Pervious Surfaces (LR) 2£
7.1.5 Soil Erosion Load (LE) 29
7.2 Universal Soil Loss Equation - USLE 29
7.3 Sediment Delivery Ratio (SD) 30
7.4 Total Water Body PB-HAP compound Concentration (CMot) 30
7.4.1 Fraction of Total Water Body PB -HAP compound Concentration in the Water Column
(Q and Benthic Sediment
-------
-------
1.0 Introduction
This Appendix describes equations used by some multimedia models to estimate media
concentrations for the recommended exposure scenarios presented in Part IE. Most risk
assessments will use a multimedia fate and transport model to perform these calculations; the
particular equations used in a given model may differ slightly from those presented here, which
are taken largely from EPA's 1998 Peer Review Draft Human Health Risk Assessment Protocol
for Hazardous Waste Combustion Facilities, Volume I.m The equations, and descriptions of the
associated parameters, are presented here simply as a general reference, and are not intended to
imply a recommendation over other equations, methods, or values for describing these processes.
EPA's 1998 Risk Assessment Protocol for Hazardous Waste Combustion Facilities provides a
more detailed discussion of the origin and development of each of these equations and many of
their specific parameters. It should be noted that reference made throughout this chapter to
"particle phase" is generic and made without distinction between particle and particle-bound.
The remainder of this chapter is divided into seven sections:
• Section 2 describes the estimating media concentration equations for soils contaminated by
PB-HAP compounds.
• Section 3 describes the estimating media concentration equations used to determine PB-HAP
compound concentrations in produce.
• Sections 4 through 6 describe equations used to determine PB-HAP compound
concentrations in animal products (such as milk, beef, pork, poultry, and eggs) resulting from
animal ingestion of contaminated feed and soil.
• Section 7 describes equations used to determine PB-HAP compound concentrations in fish
through bioaccumulation (or, for some compounds, bioconcentration) from the water column,
dissolved water concentration, or bed sediment - depending on the PB-HAP compound.
• Section 8 describes equations for estimating the concentrations of doxins in breast milk.
2.0 Calculation of PB-HAP Compound Concentrations in Soil
PB-HAP compound concentrations in soil are calculated by summing the vapor phase and
particle phase deposition of PB-HAP compounds to the soil. Wet and dry deposition of particles
and vapors are considered, with dry deposition of vapors calculated from the vapor air
concentration and the dry deposition velocity. The calculation of soil concentration incorporates
a term that accounts for loss of PB-HAP compounds by several mechanisms, including leaching,
erosion, runoff, degradation (biotic and abiotic), and volatilization. These loss mechanisms all
lower the soil concentration associated with the deposition rate.
Soil concentrations may require many years to reach steady state. As a result, the equations used
to calculate the average soil concentration over the period of deposition were derived by
integrating the instantaneous soil concentration equation over the period of deposition. For
carcinogenic PB-HAP compounds, EPA (1998)(1) recommends using two variations of the
equation (average soil concentration over exposure duration). One form should be used if the
exposure duration is greater than or equal to the operating lifetime of the emission source(s), and
the other should be used if the exposure duration is less than the operating lifetime of the
emission source(s).
April 2004 Page K-l
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For noncarcinogenic PB-HAP compounds, EPA (1998)(1) recommends using the second form of
the carcinogenic equation to calculate the highest annual average PB-HAP compound soil
concentration occurring during the exposure duration. These equations are described in more
detail in Section 2.1.
Soil conditions such as pH, structure, organic matter content, and moisture content affect the
distribution and mobility of PB-HAP compounds. Loss of PB-HAP compounds from the soil is
modeled by using rates that depend on the physical and chemical characteristics of the soil.
These variables and their use are described in the following subsections, along with the
recommended equations.
2.1 Calculating Cumulative Soil Concentration (Cs)
EPA (1998)(1) recommends the use of Equations 1A, IB, and 1C to calculate the cumulative soil
concentration (Cs).
Carcinogens:
For T2 < tD
Cs =
Ds
tD+
exp(- Jb
(Equation 1A)
For T,
-------
EPA (1998)(1) recommends Equation 1C when an exposure duration that is less than or equal to
the operating lifetime of the emission source(s) (T2 < tD); when an exposure duration greater
than the operating lifetime of the emissions source(s) (T}< tD < T2), Equation IB is
recommended. For noncarcinogenic PB-HAP compounds, Equation 1C is recommended.
The PB-HAP compound soil concentration averaged over the exposure duration, represented by
Cs, can be used for carcinogenic compounds, where risk is averaged over the lifetime of an
individual. Because the hazard quotient associated with noncarcinogenic PB-HAP compounds is
based on a threshold dose rather than a lifetime exposure, the highest annual average PB-HAP
compound soil concentration occurring during the exposure duration period is recommended to
be used for noncarcinogenic PB-HAP compounds. The highest annual average PB-HAP
compound soil concentration, CstD, will typically occur at the end of the operating life of the
emission source(s).
EPA (1998) (1) recommends using the highest 1-year annual average soil concentration,
determined by using Equation 1C, to evaluate risk from noncarcinogenic PB-HAP compounds.
2.2 Calculating the PB-HAP compound Soil Loss Constant (ks)
Organic and inorganic PB-HAP compounds may be lost from the soil by several processes that
may or may not occur simultaneously. The rate at which a PB-HAP compound is lost from the
soil is known as the soil loss constant (ks). The constant ks is determined by using the soil's
physical, chemical, and biological characteristics to consider the loss resulting from leaching,
runoff, erosion, biotic and abiotic degradation, and volatilization. EPA (1998)(1) recommends
that Equation 2 be used to calculate the PB-HAP compound soil loss constant (ks).
ks - ksg + kse + for + M + kw (Equation 2)
where
ks = PB-HAP compound soil loss constant due to all processes (yr !)
ksg = PB-HAP compound loss constant due to biotic and abiotic degradation (yr !)
kse = PB-HAP compound loss constant due to soil erosion (yr !)
ksr = PB-HAP compound loss constant due to surface runoff (yr !)
ksl = PB-HAP compound loss constant due to leaching (yr !)
ksv = PB-HAP compound loss constant due to volatilization (yr !)
As highlighted in Section 2.1, the use of Equation 2 in Equations 1A and IB assumes that PB-
HAP compound loss can be defined by using first-order reaction kinetics. First-order reaction
rates depend on the concentration of one reactant.(2) The loss of a PB-HAP compound by a first-
order process depends only on the concentration of the PB-HAP compound in the soil, and a
constant fraction of the PB-HAP compound is removed from the soil over time. Those processes
that apparently exhibit first-order reaction kinetics without implying a mechanistic dependence
on a first-order loss rate are termed "apparent first-order" loss rates.(3) The assumption that PB-
HAP compound loss follows first-order reaction kinetics may be an oversimplification because -
at various concentrations or under various environmental conditions - the loss rates from soil
systems will resemble different kinetic expressions. However, at low concentrations, a
April 2004 Page K-3
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first-order loss constant may be adequate to describe the loss of the PB-HAP compound from soil
(EPA 1990)(4).
PB-HAP compound loss in soil can also follow zero or second-order reaction kinetics.
Zero-order reaction kinetics are independent of reactant concentrations (Bohn, McNeal, and
O'Connor 1985).(2) Zero-order loss rates describe processes in which the reactants are present at
very high concentrations. Under zero-order kinetics, a constant amount of a PB-HAP compound
is lost from the soil over time, independent of its concentration. Processes that follow
second-order reaction kinetics depend on the concentrations of two reactants or the concentration
of one reactant squared (Bohn, McNeal, and O'Connor 1985)(2). The loss constant of a PB-HAP
compound following a second-order process can be contingent on its own concentration, or on
both its concentration and the concentration of another reactant, such as an enzyme or catalyst.
Because PB-HAP compound loss from soil depends on many complex factors, it may be difficult
to model the overall rate of loss. In addition, because the physical phenomena that cause PB-
HAP compound loss can occur simultaneously, the use of Equation 2 may also overestimate loss
rates for each process (Valentine 1986).(5) When possible, the common occurrence of all loss
processes should be taken into account. Combined rates of soil loss by these processes can be
derived experimentally; values for some PB-HAP compounds are presented in EPA (1986).(6)
Sections 2.2.1 through 2.2.5 discuss issues associated with the calculation of the ksl, kse, ksr, ksg,
and ksv variables.
2.2.1 PB-HAP compound Loss Constant Due to Biotic and Abiotic Degradation (ksg)
Soil losses resulting from biotic and abiotic degradation (ksg) are determined empirically from
field studies and should be addressed in the literature (EPA 1990).(4) Lyman et al. (1982)(7) states
that degradation rates can be assumed to follow first order kinetics in a homogenous medium.
Therefore, the half-life of a compound can be related to the degradation rate constant. Ideally,
ksg is the sum of all biotic and abiotic rate constants in the soil media. Therefore, if the half-life
of a compound (for all of the mechanisms of transformation) is known, the degradation rate can
be calculated. However, literature sources do not provide sufficient data for all such
mechanisms, especially for soil. EPA (1994a)(8) recommends that ksg values for all PB-HAP
compounds other than polycyclic organic matter (specifically 2,3,7,8-TCDD) should be set equal
to zero. EPA (1998) (1)presents EPA recommended values for this compound-specific variable.
The rate of biological degradation in soils depends on the concentration and activity of the
microbial populations in the soil, the soil conditions, and the PB-HAP compound concentration
(Jury and Valentine 1986).(9) First-order loss rates often fail to account for the high variability of
these variables in a single soil system. However, the use of simple rate expressions may be
appropriate at low chemical concentrations (e.g., nanogram per kilogram soil) at which a
first-order dependence on chemical concentration maybe reasonable. The rate of biological
degradation is PB-HAP compound-specific, depending on the complexity of the PB-HAP
compound and the usefulness of the PB-HAP compound to the microorganisms. Some
substrates, rather than being used by the organisms as a nutrient or energy source, are simply
degraded with other similar PB-HAP compounds, which can be further utilized. Environmental
and PB-HAP compound-specific factors that may limit the biodegradation of PB-HAP
compounds in the soil environment (Valentine and Schnoor 1986)(10) include (1) availability of
April 2004 Page K-4
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the PB-HAP compound, (2) nutrient limitations, (3) toxicity of the PB-HAP compound, and (4)
inactivation or nonexistence of enzymes capable of degrading the PB-HAP compound.
Chemical degradation of organic compounds can be a significant mechanism for removal of PB-
HAP compounds in soil (EPA 1990).(4) Hydrolysis and oxidation-reduction reactions are the
primary chemical transformation processes occurring in the upper layers of soils (Valentine
1986).(5) General rate expressions describing the transformation of some PB-HAP compounds by
all non-biological processes are available, and these expressions are helpful when division into
component reactions is not possible.
Hydrolysis in aqueous systems is characterized by three processes: acid-catalyzed, base-
catalyzed, and neutral reactions. The overall rate of hydrolysis is the sum of the first-order rates
of these processes (Valentine 1986).(5) In soil systems, sorption of the PB-HAP compound can
increase, decrease, or not affect the rate of hydrolysis, as numerous studies cited in Valentine
(1986)(5) have shown. The total rate of hydrolysis in soil can be predicted by adding the rates in
the soil and water phases, which are assumed to be first-order reactions at a fixed pH (Valentine
1986).(5) Methods for estimating these hydrolysis constants are described by Lyman et al.
(1982).(7)
Organic and inorganic compounds also undergo oxidation-reduction (redox) reactions in the soil
(Valentine 1986).(5) Organic redox reactions involve the exchange of oxygen and hydrogen
atoms by the reacting molecules. Inorganic redox reactions may involve the exchange of atoms
or electrons by the reactants. In soil systems where the identities of oxidant and reductant species
are not specified, a first-order rate constant can be obtained for describing loss by redox reactions
(Valentine 1986).(5) Redox reactions involving metals may promote losses from surface soils by
making metals more mobile (e.g., leaching to subsurface soils).
2.2.2 PB-HAP compound Loss Constant Due to Soil Erosion (kse)
EPA (1998) (1) recommends that the constant for the loss of soil resulting from erosion (kse) is
recommended to be set equal to zero in most cases. If soil erosion is a significant issue in the
assessment area, EPA (1993b)(11) recommends the use of Equation 3 to calculate the constant for
soil loss resulting from erosion (kse).
Q.l.Xa.SD.ER &ds • BD (Equations)
kse = -
BD-Z
S sw
where
kse = PB-HAP compound soil loss constant due to soil erosion
0.1 = Units conversion factor (1,000 g-kg/1 0,000 cm2-m2)
Xe = Unit soil loss (kg/m2-yr)
SD = Sediment delivery ratio (unitless)
ER = Soil enrichment ratio (unitless)
Kds = Soil-water partition coefficient (mL water/g soil)
BD = Soil bulk density (g soil/cm3 soil)
Zs = Soil mixing zone depth (cm)
Qsw = Soil volumetric water content (mL water/cm3 soil)
April 2004 Page K-5
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Unit soil loss (Xe) is calculated by using the Universal Soil Loss Equation (USLE) (See Section
7.2). Soil bulk density (BD) is described in Section 2.4.2. Soil volumetric water content (0OT) is
described in Section 2.5.4.
For additional information on addressing kse, EPA (1998)(1) recommends consulting the
methodologies described in EPA NCEA document, Methodology for Assessing Health Risks
Associated with Multiple Pathways of Exposure to Combustor Emissions (EPA 1998)(12).
2.2.3 PB-HAP compound Loss Constant Due to Runoff (ksr)
EPA (1998)(1) recommends that Equation 4 be used to calculate the constant for the loss of soil
resulting from surface runoff (ksr).
RO 1 }
\ (Equation 4)
where
ksr = PB-HAP compound loss constant due to runoff (yr !)
RO = Average annual surface runoff from pervious areas (cm/yr)
Qsw = Soil volumetric water content (mL water/cm3 soil)
Zs = Soil mixing zone depth (cm)
Kds = Soil-water partition coefficient (mL water/g soil)
BD = Soil bulk density (g soil/cm3 soil)
Soil bulk density (BD) is described in Section 2.5.2. Soil volumetric water content (Qsw) is
described in Section 2.5.4.
2.2.4 PB-HAP compound Loss Constant Due to Leaching (ksl)
Losses of soil PB-HAP compounds due to leaching (ksl) depend on the amount of water available
to generate leachate and soil properties such as bulk density, soil moisture, soil porosity, and soil
sorption properties. EPA (1998)(1) recommends that Equation 5 be used to calculate the PB-HAP
compound loss constant due to leaching (ksl) to account for runoff.
P + I - RO + E.
V
ksl = r ( M (Equations)
where
ksl = PB-HAP compound loss constant due to leaching (yr !)
P = Average annual precipitation (cm/yr)
/ = Average annual irrigation (cm/yr)
RO = Average annual surface runoff from pervious areas (cm/yr)
Ev = Average annual evapotranspiration (cm/yr)
Qsw = Soil volumetric water content (mL water/cm3 soil)
April 2004 Page K-6
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Zs = Soil mixing zone depth (cm)
Kds = Soil-water partition coefficient (cm3 water/g soil)
ED = Soil bulk density (g soil/cm3 soil)
The average annual volume of water (P +1 - RO - Ev) available to generate leachate is the mass
balance of all water inputs and outputs from the area under consideration. These variables are
described in Section 2.5.3. Soil bulk density (BD) is described in Section 2.5.2. Soil volumetric
water content (Qsw) is described in Section 2.5.4.
2.2.5 PB-HAP compound Loss Constant Due to Volatilization (ksv)
Semi-volatile and volatile PB-HAP compounds emitted in high concentrations may become
adsorbed to soil particles and exhibit volatilization losses from soil. The loss of a PB-HAP
compound from the soil by volatilization depends on the rate of movement of the PB-HAP
compound to the soil surface, the chemical vapor concentration at the soil surface, and the rate at
which vapor is carried away by the atmosphere (Jury 1986).(13)
EPA (1998)(1) recommends that in cases where high concentrations of volatile organic
compounds are expected to be present in the soil that Equation 6A be used to calculate the
constant for the loss of soil resulting from volatilization (ksv).
ksv =
3.1536x
D
-BD)
1-
f BD'
'-•Psoil-'
(Equation 6A)
where
ksv
3. 1536
H
Z,
Kds
R
T
* a
BD
Psoil
107 =
PB-HAP compound loss constant due to volatization (yr !)
Units conversion factor (s/yr)
Henry's Law constant (atm-m3/mol)
Soil mixing zone depth (cm)
Soil-water partition coefficient (mL/g)
Universal gas constant (atm-m3/mol-K)
Ambient air temperature (K) = 298.1 K
Soil bulk density (g soil/cm3 soil) =1.5 g/cm3
Diffusivity of PB-HAP compound in air (cm2/s)
Soil volumetric water content (mL/cm3 soil) = 0.2 mL/cm3
Solids particle density (g/cm3) = 2.7 g/cm3
The gas-phase mass transfer coefficient, Kt, based on general soil properties, can also be written
as follows (Hillel 1980; Miller and Gardiner 1998)(14):
£>
(Equation 6B)
where
April 2004
PageK-7
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Kt = Gas phase mass transfer coefficient (cm/s)
Zs = Soil mixing zone depth (cm)
Da = Diffusivity of PB-HAP compound in air (cm2/s)
Qv = Soil void fraction (cmVcm3)
The soil void fraction (0V) is the volumetric fraction of a soil that does not contain solids or water
and can be expressed as:
(BD}
&v = 1 - - &sw (Equation 6C)
\PsoiV
where
0V = Soil void fraction (cmVcm3)
Qsw = Soil volumetric water content (mL water/cm3 soil) = 0.2 mL/cm3
BD = Soil bulk density (g/cm3) = 1.5 g/cm3
psoil = Solids particle density (g/cm3) = 2.7 g/cm3
The expression containing bulk density (BD) divided by solids particle density (psoil) gives the
volume of soil occupied by pore space or voids (Miller and Gardiner 1998).(14) Soil bulk density
is affected by the soil structure, such as looseness or compaction of the soil, depending on the
water and clay content of the soil (Hillel 1980)(14); a range of 0.83 to 1.84 was originally cited in
Hoffman and Baes (1979).(15) A default soil bulk density value of 1.5 g/cm3 is recommended
based on a mean value for loam soil from Carsel et al. (1988).(16) Blake and Hartge (1996)(17) and
Hillel (1980)(14) both suggests that the mean density of solid particles is about 2.7 gm/cm3. The
soil water content depends on both the available water and the soil structure of a particular soil.
Values for 0^, range from 0.03 to 0.40 mL/cm3 depending on soil type (Hoffman and Baes
1979).(15) The lower values are typical of sandy soils, which cannot retain much water; the
higher values are typical of soils such as clay or loam soils which can retain water. A mid-point
default value of 0.2 mL water/cm3 soil is recommended as a default in the absence of site-specific
information. However, since the soil water content of soil is unique for each soil type, site-
specific information is highly recommended.
2.3 Calculating the Deposition Term (Ds)
EPA (1998)(1) recommends that Equation 7 be used to calculate the deposition term (Ds).
100-e'
Ds =
Z. -3D
•[Fv-( Dydv + Dywv) + (Dydp + Dywp) • (l - Fv)] (Equation 7)
where
Ds = Deposition term (mg PB-HAP compound/kg soil/yr)
100 = Units conversion factor (mg-m2/kg-cm2)
£? = PB-HAP compound emission rate (g/s)
Zs = Soil mixing zone depth (cm)
April 2004 Page K-&
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ED = Soil bulk density (g soil/cm3 soil)
Fv = Fraction of PB-HAP compound air concentration in vapor phase (unitless)
Dydv = Unitized yearly average dry deposition from vapor phase (s/m2-yr)
Dywv = Unitized yearly average wet deposition from vapor phase (s/m2-yr)
Dydp = Unitized yearly average dry deposition from particle phase (s/m2-yr)
Dywp = Unitized yearly average wet deposition from particle phase (s/m2-yr)
2.4 Universal Soil Loss Equation (USLE)
EPA (1998)(1) recommends that the universal soil loss equation (USLE) be used to calculate the
unit soil loss (X). This equation is further described in Section 7.2.
2.5 Site-Specific Parameters for Calculating Cumulative Soil Concentration
Calculating average soil concentration over the exposure duration (Cs) requires the use of
site-specific parameters including the following:
• Soil mixing zone depth (Zs)
• Soil bulk density (BD)
• Available water (P +1 - RO - Ev)
• Soil volumetric water content (q^)
Determination of values for these parameters is further described in the following subsections.
2.5.1 Soil Mixing Zone Depth (Zs)
When exposures to PB-HAP compounds in soils are modeled, the depth of contaminated soils is
important in calculating the appropriate soil concentration. PB-HAP compounds deposited onto
soil surfaces may be moved into lower soil profiles by tilling, whether manually in a garden or
mechanically in a large field.
EPA (1998)(1) recommends the following values for the soil mixing zone depth (Zs):
• 2 cm for unfilled soils; and
• 20 cm for tilled soils.
The assumption made to determine the value of Zs may affect the outcome of the risk assessment,
because soil concentrations that are based on soil depth are used to calculate exposure via several
pathways: (1) ingestion of plants contaminated by root uptake; (2) direct ingestion of soil by
humans, cattle, swine, or chicken; and (3) surface runoff into water bodies.
2.5.2 Soil Dry Bulk Density (BD)
Soil dry bulk density (BD) is the ratio of the mass of soil to its total volume. EPA (1998)(1)
recommends the value of 1.50 g/cm3 for the soil dry bulk density (BD). EPA (1994c)(18)
recommended that wet soil bulk density be determined by weighing a thin-walled, tube soil
sample (e.g., a Shelby tube) of known volume and subtracting the tube weight (ASTM Method
April 2004 Page K-9
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D2937).(19) Moisture content can then be calculated (ASTM Method 2216)(20) to convert wet soil
bulk density to dry soil bulk density.
2.5.3 Available Water (P + I-RO-Ev)
The average annual volume of water available (P +1 - RO - Ev) for generating leachate is the
mass balance of all water inputs and outputs from the area under consideration. A wide range of
values for these site-specific parameters may apply in the various EPA regions.
The average annual precipitation (P), irrigation (7), runoff (RO), and evapotranspiration (Ev) rates
and other climatological data may be obtained from either data recorded on site or from the
Station Climatic Summary for a nearby airport.
Meteorological variables such as the evapotranspiration rate (Ev) and the runoff rate (RO) may
also be found in resources such as Geraghty, Miller, van der Leeden, and Troise (1973).(21)
Surface runoff may also be estimated by using the Curve Number Equation developed by the
U.S. Soil Conservation Service (EPA 1990).(4) EPA (1985)(22) cited isopleths of mean annual
cropland runoff corresponding to various curve numbers developed by Stewart, Woolhiser,
Wischmeier, Caro, and Frere (1975).(23) Curve numbers are assigned to an area on the basis of
soil type, land use or cover, and the hydrologic conditions of the soil (EPA 1990).(4)
Using these different references, however, introduces uncertainties and limitations. For example,
Geraghty, Miller, van der Leeden, and Troise (1973)(21) presented isopleths for annual surface
water contributions that include interflow and ground water recharge. As noted in EPA
(1994a)(8), these values are recommended to be adjusted downward to reflect surface runoff only.
EPA (1994a)(8) recommended that these values be reduced by 50 percent.
2.5.4 Soil Volumetric Water Content (0TO)
The soil volumetric water content (Qsw) depends on the available water and the soil structure. A
wide range of values for these variables may apply in the various EPA regions. EPA (1998)(1)
recommends a value for Qsw of 0.2 ml/cm3.
3.0 Calculation of PB-HAP Compound Concentrations in Produce
Indirect exposure resulting from ingestion of produce depends on the total concentration of PB-
HAP compounds in the leafy, fruit, and tuber portions of the plant. Because of general
differences in contamination mechanisms, consideration of indirect exposure separates produce
into two broad categories: aboveground produce and belowground produce. In addition,
aboveground produce can be further subdivided into exposed and protected aboveground produce
for consideration of contamination as a result of indirect exposure.
Aboveground Produce
Aboveground exposed produce is assumed to be contaminated by three possible mechanisms:
• Direct deposition of particles—wet and dry deposition of particle phase PB-HAP
compounds on the leaves and fruits of plants (Section 3.1).
April 2004 Page K-10
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• Vapor transfer—uptake of vapor phase PB-HAP compounds by plants through their foliage
(Section 3.2).
• Root uptake—root uptake of PB-HAP compounds available from the soil and their transfer
to the aboveground portions of the plant (Section 3.3).
The total PB-HAP compound concentration in aboveground exposed produce is calculated as a
sum of contamination occurring through all three of these mechanisms. However, edible
portions of aboveground protected produce, such as peas, corn, and melons, are covered by a
protective covering; hence, they are protected from contamination through deposition and vapor
transfer. Therefore, root uptake of PB-HAP compounds is the primary mechanism through
which aboveground protected produce becomes contaminated (Section 3.3).
Belowground Produce
For belowground produce, contamination is assumed to occur only through one mechanism -
root uptake of PB-HAP compounds available from soil (Section 3.3). Contamination of
belowground produce via direct deposition of particles and vapor transfer are not considered
because the root or tuber is protected from contact with contaminants in the vapor phase.
3.1 Aboveground Produce Concentration Due to Direct Deposition (Pd)
EPA (1998)(1) recommends the use of Equation 8 to calculate PB-HAP compound concentration
in exposed and aboveground produce due to direct deposition.
p j _ -'--- ^ \- -vf \_-s~r • v- " -v--I-VJ --i- 1-° exP[ ^'^pj\ (Equations)
Yp-kp
where
PJ = Plant (aboveground produce) concentration due to direct (wet and dry) deposition (mg
PB-HAP compound/kg DW)
1,000 = Units conversion factor (mg/g)
Q = PB-HAP compound emission rate (g/s)
Fv = Fraction of PB-HAP compound air concentration in vapor phase (unitless)
Dydp = Unitized yearly average dry deposition from particle phase (s/m2-yr)
Fw = Fraction of PB-HAP compound wet deposition that adheres to plant surfaces
(unitless)
Dywp = Unitized yearly wet deposition from particle phase (s/m2-yr)
Rp = Interception fraction of the edible portion of plant (unitless)
kp = Plant surface loss coefficient (yr !)
Tp = Length of plant exposure to deposition per harvest of the edible portion of the z'th
plant group (yr)
Yp = Yield or standing crop biomass of the edible portion of the plant (productivity) (kg
DW/m2)
April 2004 Page K-11
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3.1.1 Interception Fraction of the Edible Portion of Plant (Sp)
EPA (1998)(1) recommends the use of the weighted average Rp value of 0.39 as a default^?/? value
because it represents the most current parameters including standing crop biomass and relative
ingestion rates.
3.1.2 Plant Surface Loss Coefficient (kp)
EPA (1998)(1) recommends use of a plant surface loss coefficient (kp) value of 18. The primary
uncertainty associated with this variable is that the calculation of kp does not consider chemical
degradation processes. However, information regarding chemical degradation of contaminants
on plant surfaces is limited. The inclusion of chemical degradation processes would result in
decreased half-life values and thereby increase kp values. Note that effective plant concentration
decreases as kp increases. Therefore, use of a kp value that does not consider chemical
degradation processes is protective.
3.1.3 Length of Plant Exposure to Deposition per Harvest of Edible Portion of Plant (Tp)
This value represents the time required from when a plant first emerges until harvest. EPA
(1998)(1) recommends using a Tp value of 0.164 year as the best available default value. The
primary uncertainty associated with the use of this value is that it is based on the growing season
for hay rather than aboveground produce. The average period between successive hay harvests
(60 days) may not reflect the length of the growing season or the period between successive
harvests for aboveground produce at specific sites. To the extent that information documenting
the growing season or period between successive harvests for aboveground produce is available,
this information may be used to estimate a site-specific Tp value. Calculated plant
concentrations will be affected most if the site-specific value of Tp is significantly less than 60
days.
3.1.4 Standing Crop Biomass (Productivity) (Yp)
EPA (1998)(1) recommends the use of the weighted average Yp value of 2.24 as a default Yp
value based on this value representing the most complete and thorough information available.
The primary uncertainty associated with this variable is that the harvest yield (Yh) and area
planted (Ah) may not reflect site-specific conditions. To the extent to which site-specific
information is available, the magnitude of the uncertainty introduced by the default Yp value can
be estimated.
3.2 Aboveground Produce Concentration Due to Air-to-Plant Transfer (Pv)
The methodology used to estimate PB-HAP compound concentration in exposed and
aboveground produce due to air-to-plant transfer (Pv) considers limitations of PB-HAP
compounds concentrations to transfer from plant surfaces to the inner portions of the plant.
These limitations result from mechanisms responsible for inhibiting the transfer of the lipophilic
PB-HAP compound (e.g., the shape of the produce) and the removal of the PB-HAP compounds
from the edible portion of the produce (e.g., washing, peeling, and cooking). EPA (1998)(1)
recommends the use of Equation 9 to calculate aboveground produce concentration due to
air-to-plant transfer (Pv).
April 2004 Page K-12
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Cyv • Bvae
Pv = Q • Fv • (Equation 9)
Pa
where
Pv = Concentration of PB-HAP compound in the plant resulting from air-to-plant transfer
(|ig PB-HAP compound/g DW)
Q = PB-HAP compound emission rate (g/s)
Fv = Fraction of PB-HAP compound air concentration in vapor phase (unitless)
Cyv = Unitized yearly average air concentration from vapor phase (|ig-s/g-m3)
5vag = PB-HAP compound air-to-plant biotransfer factor ([mg PB-HAP compound/g DW
plant]/[mg PB-HAP compound/g air]) (unitless)
VGag = Empirical correction factor for aboveground produce (unitless)
pa = Density of air (g/m3)
As discussed below in Section 3.2.1, the parameter VGag is dependent on lipophilicity of the PB-
HAP compound, and assigned a value of 0.01 for lipophilic PB-HAP compounds (log Kow greater
than 4) or a value of 1.0 for PB-HAP compounds with a log Kow less than 4.
Empirical Correction Factor for Aboveground Produce (VGag)
The parameter VGag has been incorporated into Equation 9 to address the potential
overestimation for lipophilic PB-HAP compounds to be transferred to the inner portions of
bulky produce, such as apples. Because of the protective outer skin, size, and shape of bulky
produce, transfer of lipophilic PB-HAP compounds (log Kow greater than 4) to the center of the
produce is not as likely as for non-lipophilic PB-HAP compounds and, as a result, the inner
portions will be less affected. EPA (1998)(1) recommends the following empirical VGag values
for aboveground produce:
• 0.01 for lipophilic PB-HAP compounds (log Kow greater than 4); and
• 1.0 for PB-HAP compounds with a log Kow less than 4 (these PB-HAP compounds are
assumed pass more easily through the skin of produce).
Uncertainty may be introduced by the assumption of VGag values for leafy vegetables (such as
lettuce) and for legumes (such as snap beans). Underestimation maybe introduced by assuming
a VGag value of 0.01 for legumes and leafy vegetables because these species often have a higher
ratio of surface area to mass than other bulkier fruits and fruiting vegetables, such as tomatoes.
3.3 Produce Concentration Due to Root Uptake (Pr)
Root uptake of contaminants from soil may also result in PB-HAP compound concentrations in
aboveground exposed produce, aboveground protected produce, and belowground produce. EPA
(1998)(1) recommends the use of Equations 10A and 10B to calculate PB-HAP compound
concentration aboveground and belowground produce due to root uptake (Pr).
April 2004 Page K-13
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Exposed and protected aboveground produce:
Pr = Cs- Br (Equation 10A)
Belowground produce:
Cs • RCF • VG
•—-o iv-^i. k ^rootveg
= JFj— JUT (Equation 10B)
where
Pr = Concentration of PB-HAP compound in produce due to root uptake (mg/kg)
Br = Plant-soil bioconcentration factor for produce (unitless)
VGrootveg = Empirical correction factor for belowground produce (unitless)
Kds = Soil-water partition coefficient (L/kg)
Cs = Average soil concentration over exposure duration (mg PB-HAP compound/kg
soil)
RCF = Root concentration factor (unitless)
Equation 10A is appropriate for evaluation of exposed and protected aboveground produce;
however, it may not be appropriate for soil-to-belowground plant transfers. For belowground
produce, Equation 10B includes a root concentration factor (RCF) developed by Briggs et al.
(1982).(24) RCF is the ratio of PB-HAP compound concentration in the edible root to the PB-
HAP compound concentration in the soil water. Since Briggs et al. (1982)(24) conducted their
experiments in a growth solution, the PB-HAP compound soil concentration (Cs) must be
divided by the PB-HAP compound-specific soil-water partition coefficient (Kds ) (EPA
1994b).(25)
Similar to VGag and as discussed in Section 3.2.1, VGrootveg is based on the lipophilicity of the PB-
HAP compound. EPA (1998)(1) recommends the following empirical values for VGrootveg:
• 0.01 for lipophilic PB-HAP compounds (log Kow greater than 4) based on root vegetables like
carrots and potatoes; and
• 1.0 for PB-HAP compounds with a log Kow less than 4.
4.0 Calculation of PB-HAP Compound Concentrations in Beef and Dairy Products
PB-HAP compound concentrations in beef tissue and milk products are estimated on the basis of
the amount of PB-HAP compounds that cattle are assumed to consume through their diet. The
cattle's diet is assumed to consist of forage (primarily pasture grass and hay); silage (forage that
has been stored and fermented), and grain. Additional contamination may occur through the
cattle's ingestion of soil. The total PB-HAP compound concentration in the feed items (e.g.,
forage, silage, and grain) is calculated as a sum of contamination occurring through the following
mechanisms:
• Direct deposition of particles—wet and dry deposition of particle phase PB-HAP
compounds onto forage and silage (Section 4.1).
April 2004 Page K-14
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• Vapor transfer—uptake of vapor phase PB-HAP compounds by forage and silage through
foliage (Section 4.2).
• Root uptake—root uptake of PB-HAP compounds available from the soil and their transfer
to the aboveground portions of forage, silage, and grain (Section 4.3).
Feed items consumed by animals can be classified as exposed and protected, depending on
whether it has a protective outer covering. Because the outer covering on the protected feed acts
as a barrier, it is assumed that there is negligible contamination of protected feed through
deposition of particles and vapor transfer. In this analysis, grain is classified as protected feed.
As a result, grain contamination is assumed to occur only through root uptake. Contamination of
exposed feed items, including forage and silage, is assumed to occur through all three
mechanisms.
The amount of grain, silage, forage, and soil consumed is assumed to vary between dairy and
beef cattle. Sections 4.4 (beef) and 4.5 (dairy) describe methods for estimating consumption
rates and subsequent PB-HAP compound concentrations in cattle. EPA (1998)(1) recommends
that 100 percent of the plant materials eaten by cattle be assumed to have been grown on soil
contaminated by emission sources. Therefore, 100 percent of the feed items consumed are
assumed to be contaminated.
4.1 Forage and Silage Concentrations Due to Direct Deposition (Pd)
PB-HAP compound concentrations in forage and silage result from wet and dry deposition onto
exposed plant surfaces; similar to aboveground produce (Section 3.1). Equation 8, described in
Section 3.1, is recommended for calculation of PB-HAP compound concentrations resulting from
direct deposition onto plant surfaces of leafy plants and exposed produce (Pd). Therefore, EPA
(1998)(1) recommends that Equation 8 also be used in calculating forage and silage
concentrations due to direct deposition.
4.1.1 Interception Fraction of the Edible Portion of Plant (Rp)
EPA (1998)(1) recommends use of the Rp value of 0.5 for forage and the Rp value of 0.46 for
silage. Note that the empirical relationships used to develop the default values for silage may not
accurately represent site-specific silage types. However, the range of empirical constants used to
develop the default value for forage is fairly small, and therefore the use of the midpoint should
not significantly affect the Rp value and the resulting estimate of plant PB-HAP compound
concentration.
4.1.2 Plant Surface Loss Coefficient (kp)
Section 3.1.2 presents the recommended value for plant surface loss coefficient kp for
aboveground produce. The kp factor is derived in exactly the same manner for cattle forage and
silage, and the uncertainties of kp for cattle forage and silage are similar to its uncertainties for
aboveground produce.
April 2004 Page K-15
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4.1.3 Length of Plant Exposure to Deposition per Harvest of the Edible Portion of Plant
(Tp)
As discussed in Section 3.1.3, Tp is treated as a constant, based on the average period between
successive hay harvests. This periodrepresents the length of time that aboveground vegetation
(in this case, hay) would be exposed to particle deposition before being harvested. EPA (1998)(1)
recommends the following Tp values: 0.12 year for forage; and 0.16 year for silage. The primary
uncertainties associated with Tp are similar to those for aboveground produce, and are discussed
in Section 3.1.3.
4.1.4 Standing Crop Biomass (Productivity) (Yp)
As discussed in Section 3.1.4, the best estimate of Yp is productivity, requires consideration of
dry harvest yield (Yh) and area harvested (Ah). EPA (1998)(1) recommends that forage Yp be
calculated as a weighted average of the calculated pasture grass and hay Yp values. Weightings
are assumed to be 0.75 for forage and 0.25 for hay, based on the fraction of a year that cattle are
assumed to be pastured and eating grass (9 months per year) or not pastured and fed hay (3
months per year). The resulting value of 0.24 kg DW/m2 is recommended as the Yp for forage.
For silage, EPA (1998)(1) recommends that a production-weighted U.S. average Yp of 0.8 kg
DW/m2 be assumed. The primary uncertainty associated with this variable is that the harvest
yield (Yh) and area planted (Ah) may not reflect site-specific conditions. To the extent that
site-specific information is available, the magnitude of the uncertainty introduced by the default
Yp value can be estimated. In addition, the weightings assumed in this discussion for the amount
of time that cattle are pastured (and foraging) or stabled (and being fed silage) should be adjusted
to reflect site-specific conditions, as appropriate.
4.2 Forage and Silage Concentrations Due to Air-to-Plant Transfer (Pv)
PB-HAP compound concentration in aboveground produce resulting from air-to-plant transfer
(Pv), is calculated by using Equation 9 (Section 3.2). Pv is calculated for cattle forage and silage
similarly to the way that it is calculated for aboveground produce. A detailed discussion ofPv is
provided in Section 3.2. Differences in VGag values for forage and silage, as compared to the
values for aboveground produce described in Section 3.2.1, are presented below in Section 4.2.1.
Empirical Correction Factor for Forage and Silage (VGag)
EPA (1998)(1) recommends the use of VGag values of 1.0 for forage and 0.5 for silage. As
discussed, the primary uncertainty associated with this variable is the lack of specific information
on the proportions of each vegetation type of which silage may consist, leading to the default
assumption of 0.5.
4.3 Forage, Silage, and Grain Concentrations Due to Root Uptake (Pr)
PB-HAP compound concentration in aboveground and belowground produce resulting from root
uptake is calculated by using Equations 10A and 10B (Section 3.3). Pr is also calculated for
cattle forage, silage, and grain in exactly the same way that it is calculated for aboveground
produce. A detailed discussion describing calculation ofPr is provided in Section 3.3.
April 2004 Page K-16
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4.4 Beef Concentration Resulting from Plant and Soil Ingestion (Abeef)
EPA (1998)(1) recommends that PB-HAP compound concentration in beef tissue (Abeej) be
calculated by using Equationl 1 . Equation 1 1 calculates the daily amount of a PB-HAP
compound that is consumed by cattle through the ingestion of contaminated feed items (plant)
and soil. The equation includes biotransfer and metabolism factors to transform the daily animal
intake of a PB-HAP compound (mg/day) into an animal PB-HAP compound tissue concentration
(mg PB-HAP compound/kg tissue).
= (Z ( 3 • Qpr ^ ) + Qs • cs • BS) • Eabeif • MF
(Equation 1 1}
where
Abeef = Concentration of PB-HAP compound in beef (mg PB-HAP compound/kg FW tissue)
Ft = Fraction of plant type i grown on contaminated soil and ingested by the animal
(cattle) (unitless)
Qpt = Quantity of plant type i eaten by the animal (cattle) per day (kg DW plant/day)
P{ = Concentration of PB-HAP compound in each plant type i eaten by the animal (cattle)
(mg/kg DW)
Qs = Quantity of soil eaten by the animal (cattle) each day (kg/day)
Cs = Average soil concentration over exposure duration (mg PB-HAP compound/kg soil)
Bs = Soil bioavailability factor (unitless)
Babeef = PB-HAP compound biotransfer factor for beef (day/kg FW tissue)
MF = Metabolism factor (unitless)
The parameters Ft, Qpt, Pt, Qs, Cs, Bs, and MF are described in Sections 4.4.1 through 4.4.7,
respectively.
4.4.1 Fraction of Plant Type i Grown on Contaminated Soil and Eaten by the Animal
(Cattle)(F,)
EPA (1998)(1) recommends that 100 percent of the plant materials eaten by cattle be assumed to
have been grown on soil contaminated by the emission sources being evaluated and therefore
recommends a default value of 1.0 for 7%.
4.4.2 Quantity of Plant Type / Eaten by the Animal (Cattle) Each Day (gp,)
EPA (1998)(1) recommends the following beef cattle ingestion rates of forage, silage, and grain.
These values are based on the total daily intake rate of about 12 kg DW/day.
• Forage = 8 .8 kg DW/day;
• Silage = 2.5 kg DW/day; and
• Grain = 0.47 kg DW/day.
The principal uncertainty associated with Qpi is the variability between forage, silage, and grain
ingestion rates for cattle.
April 2004 Page K-17
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4.4.3 Concentration of PB-HAP compound in Plant Type i Eaten by the Animal (Cattle)
The total PB-HAP compound concentration in forage, silage, and grain are recommended to be
calculated by using Equation 12. Values for Pd, Pv, and Pr can be derived for each type of feed
by using Equations 8, 17, and 10, respectively.
R = J\.(Pd + Pv + Pr) m , 10,
! ^— 'A l (Equation 12)
where
Pi = Concentration of PB-HAP compound in each plant type i eaten by the animal (mg PB-
HAP compound/kg DW)
Pd = Plant concentration due to direct deposition (mg PB-HAP compound/kg DW)
Pv = Plant concentration due to air-to-plant transfer (mg PB-HAP compound/kg DW)
Pr = Plant concentration due to root uptake (mg PB-HAP compound/kg DW)
4.4.4 Quantity of Soil Eaten by the Animal (Cattle) Per Day (Qs)
Additional cattle contamination occurs through ingestion of soil. EPA (1998)(1) recommends a
value of 0.5 kg/day for the quantity of soil ingested by the animal (cattle).
4.4.5 Average Soil Concentration Over Exposure Duration (Cs)
PB-HAP compound concentration in soil is recommended to be calculated as discussed in
Section 2.1, by using Equations 1A, IB, and 1C.
4.4.6 Soil Bioavailability Factor (Bs)
The efficiency of transfer from soil may differ from efficiency or transfer from plant material for
some PB-HAP compounds. If the transfer efficiency is lower for soils, than this ratio would be
less than 1.0. If it is equal or greater than that of vegetation, the Bs value would be equal to or
greater than 1.0. Until more PB-HAP compound-specific data becomes available for this
parameter, EPA (1998)(1) recommends a default value of 1 for 5s.
4.4.7 Metabolism Factor (MF)
The metabolism factor (MF) represents the estimated amount of PB-HAP compound that remains
in fat and muscle. EPA (1998)(1) recommends aMF of 1.0 for all PB-HAP compounds.
Considering the recommended values for this variable, MF has no quantitative effect on Abeef.
MF applies only to mammalian species, including beef cattle, dairy cattle, and pigs. It does not
relate to metabolism in produce, chicken, or fish. In addition, since exposures evaluated in this
chapter are intake driven, the use of a metabolism factor applies only to ingestion of beef, milk,
and pork. In summary, use of a MF does not apply for direct exposures to soil or water, or to
ingestion of produce, chicken, or fish.
April 2004 Page K-18
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4.5 PB-HAP compound Concentration In Milk Due to Plant and Soil Ingestion (Amilk)
Equation 1 1 (Section 4.4) describes the calculation of PB-HAP compound concentrations in beef
cattle (Abee^. Equation 1 1 can be modified to calculate PB-HAP compound milk concentrations
(4»-»)> as follows:
MF (Equatlon 1 3)
where
•A mat = Concentration of PB-HAP compound in milk (mg PB-HAP compound/kg milk)
F{ = Fraction of plant type i grown on contaminated soil and ingested by the animal (dairy
cattle) (unitless)
Qpt = Quantity of plant type i eaten by the animal (dairy cattle) each day (kg DW plant/day)
Pi = Concentration of PB-HAP compound in plant type i eaten by the animal (dairy cattle)
(mg/kg DW)
Qs = Quantity of soil eaten by the animal (dairy cattle) each day (kg soil/ day)
Cs = Average soil concentration over exposure duration (mg PB-HAP compound/kg soil)
Bs = Soil bioavailability factor (unitless)
^amiik = PB-HAP compound biotransfer factor for milk (day/kg WW tissue)
MF = Metabolism factor (unitless)
EPA (1998)(1) recommends the use of Equation 13 to estimate dairy cattle milk PB-HAP
compound concentration (Amilk). The discussion in Section 4.4 of the variables Ft, Qpt, Pt, Qs, Cs,
and MF for beef cattle generally applies to the corresponding variables for dairy cattle. However,
there are some differences in assumptions made for dairy cattle; these differences are
summarized in the following subsections.
4.5.1 Fraction of Plant Type i Grown on Contaminated Soil and Eaten by the Animal
(Dairy Cattle) (F,)
The calculation ofF{ for dairy cattle is identical to that for beef cattle (Section 4.4.1).
4.5.2 Quantity of Plant Type / Eaten by the Animal (Dairy Cattle) Per Day (Qp,)
As discussed in Section 4.4.2, the daily quantity of forage, silage, and grain feed consumed by
cattle is estimated for each category of feed material. However, daily ingestion rates for dairy
cattle are estimated differently than for beef cattle. The daily quantity of feed consumed by cattle
is recommended to be estimated on a dry weight basis for each category of plant feed.
EPA (1998)(1) recommends a default total ingestion rate of 20 kg DW/day for dairy cattle,
divided among forage, silage, and grain, as follows:
• Forage = 1 3.2 kg DW/day;
• Silage = 4. 1 kg DW/day; and
• Grain =3. Okg DW/day
April 2004 Page K-19
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Uncertainties associated with the estimation of Qpi include the estimation of forage, grain, and
silage ingestion rates, which will vary from site to site. The assumption of uniform
contamination of plant materials consumed by cattle also introduces uncertainty.
4.5.3 Concentration of PB-HAP compound in Plant Type i Eaten by the Animal (Dairy
Cattle) (P,)
The estimation of Pi for dairy cattle is identical to that for beef cattle (Section 4.4.3).
4.5.4 Quantity of Soil Eaten by the Animal (Dairy Cattle) Per Day (Qs)
As discussed in Section 4.4.4, contamination of dairy cattle also results from the ingestion of
soil. EPA (1998)(1) recommends a soil ingestion rate of 0.4 kg/day for dairy cattle. Uncertainties
associated with Qs include the lack of current empirical data to support soil ingestion rates for
dairy cattle. The assumption of uniform contamination of soil ingested by cattle also adds
uncertainty.
4.5.5 Average Soil Concentration Over Exposure Duration (Cs)
The calculation of Cs for dairy cattle is the same as for beef cattle (Section 4.4.5).
4.5.6 Soil Bioavailability Factor (Bs)
The calculation ofBs for dairy cattle is the same as for beef cattle (Section 4.4.6).
4.5.7 Metabolism Factor (MF)
The recommended values for MF are identical to those recommended for beef cattle (Section
4.4.7).
5.0 Calculation of PB-HAP Compound Concentrations in Pork
PB-HAP compound concentrations in pork tissue are estimated on the basis of the amount of PB-
HAP compounds that swine are assumed to consume through their diet; assumed to consist of
silage and grain. Additional PB-HAP compound contamination of pork tissue may occur
through the ingestion of soil by swine.
5.1 Concentration of PB-HAP compound In Pork
Equation 11 (Section 4.4) describes the calculation of PB-HAP compound concentration in beef
cattle (Abeej). Equation 11 can be modified to calculate PB-HAP compound concentrations in
swine (Apork), as follows:
Bapork'MF (Equation 14)
where
April 2004 Page K-20
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Apork = Concentration of PB-HAP compound in pork (mg PB-HAP compound/kg FW tissue)
Fi = Fraction of plant type i grown on contaminated soil and ingested by the animal
(swine)(unitless)
Qpi = Quantity of plant type z eaten by the animal (swine) each day (kg DW plant/day)
PI = Concentration of PB-HAP compound in plant type i eaten by the animal (swine)
(mg/kg DW)
Qs = Quantity of soil eaten by the animal (swine) (kg/day)
Cs = Average soil concentration over exposure duration (mg PB-HAP compound/kg soil)
Bs = Soil bioavailability factor (unitless)
Bapork = PB-HAP compound biotransfer factor for pork (day/kg FW tissue)
MF = Metabolism factor (unitless)
EPA (1998)(1) recommends that Equation 14 be used to calculate PB-HAP compound pork
concentrations (Apork). The discussion in Section 4.5 of the variables Ft, Qpt, Pt, Qs, Cs and MF
for beef cattle generally applies to the corresponding variables for pork. However, different
assumptions are made for pork. These differences are summarized in the following subsections.
5.1.1 Fraction of Plant Type i Grown on Contaminated Soil and Eaten by the Animal
(Swine) (F,)
The calculation of Fi for pork is identical to that for beef cattle (Section 4.4.1).
5.1.2 Quantity of Plant Type i Eaten by the Animal (Swine) Each Day (QpJ
As discussed in Section 4.4.2, the daily quantity of forage, silage, and grain feed consumed by
beef cattle is estimated for each category of feed material. However, daily ingestion rates for
pork are estimated differently than for beef cattle. Because swine are not grazing animals, they
are assumed not to eat forage, and EPA (1998)(1) recommends that the daily quantity of plant
feeds (kilograms of DW) consumed by swine be estimated for each category of plant feed.
EPA (1990)(4) and NC DEHNR (1997)(26) did not differentiate between subsistence and typical
hog farmers as for cattle. EPA (1990)(4) and NC DEHNR (1997)(26) recommended grain and
silage ingestion rates for swine as 3.0 and 1.3 kg DW/day, respectively. NC DEHNR (1997)(26)
references EPA (1990)(4) as the source of these ingestion rates. EPA (1990)(4) reported total dry
matter ingestion rates for hogs and lactating sows as 3.4 and 5.2 kg DW/day, respectively. EPA
(1990)(4) cites Boone, Ng, and Palm (1981)(27) as the source of the ingestion rate for hogs, and
NAS (1987)(28) as the source of the ingestion rate for a lactating sow. Boone, Ng, and Palm
(1981)(27) reported a grain ingestion rate of 3.4 kg DW/day for a hog. NAS (1987)(28) reported an
average ingestion rate of 5.2 kg DW/day for a lactating sow. EPA (1990)(4) recommended using
the average of these two rates (4.3 kg DW/day). EPA (1990)(4) assumed that 70 percent of the
swine diet is grain and 30 percent silage to obtain the grain ingestion rate of 3.0 kg DW/day and
the silage ingestion rate of 1.3 kg DW/day. EPA (1990)(4) cited EPA (1982)(29) as the source of
the grain and silage dietary fractions. EPA (1995)(30) recommended an ingestion rate of 4.7
kg DW/day for a swine, referencing NAS (1987).(28) NAS (1987)(28) reported an average daily
intake of 4.36 kg DW/day for a gilt (young sow) and a average daily intake of 5.17 kg DW/day
for a sow, which averages out to 4.7 kg/DW/day. Assuming the 70 percent grain to 30 percent
silage diet noted above, estimated ingestion rates of 3.3 kg DW/day (grain) and 1.4 kg DW/day
(silage) are derived.
April 2004 Page K-21
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EPA (1998)(' recommends the use of the following Qpt values for pork:
• Grain = 3.3 kg DW/day; and
• Silage = 1.4 kg DW/day.
Uncertainties associated with this variable include the variability of actual grain and silage
ingestion rates from site to site. Site-specific data can be used to mitigate this uncertainty. In
addition, the assumption of uniform contamination of plant materials consumed by swine
produces some uncertainty.
5.1.3 Concentration of PB-HAP compound in Plant Type / Eaten by the Animal (Swine)
(Pi)
The calculation of Pt for pork is identical to that for beef cattle (Section 4.4.3).
5.1.4 Quantity of Soil Eaten by the Animal (Swine) Each Day (Qs)
As discussed in Section 4.4.4, additional contamination of swine results from ingestion of soil.
EPA (1998)(1) recommends the following soil ingestion rate for swine: 0.37 kg DW/day.
Uncertainties associated with this variable include the lack of current empirical data to support
soil ingestion rates for swine, and the assumption of uniform contamination of soil ingested by
swine.
5.1.5 Average Soil Concentration Over Exposure Duration (Cs)
The calculation of Cs for pork is the same as for beef cattle (Section 4.4.5).
5.1.6 Soil Bioavailability Factor (Bs)
The calculation ofBs for pork is the same as for beef cattle (Section 4.4.6)
5.1.7 Metabolism Factor (MF)
The recommended values for MF are identical to those recommended for beef cattle (Section
4.4.7).
6.0 Calculation of PB-HAP Compound Concentrations in Chicken and Eggs
Estimates of the PB-HAP compound concentrations in chicken and eggs are based on the amount
of PB-HAP compounds that chickens consume through ingestion of grain and soil. The uptake
of PB-HAP compounds via inhalation and via ingestion of water is assumed to be insignificant
relative to other pathways. Chickens are assumed to be housed in a typical manner that allows
contact with soil; and therefore, are assumed to consume 10 percent of their diet as soil. The
remainder of the diet (90 percent) is assumed to consist of grain. Grain ingested by chickens is
assumed to have originated from the exposure scenario location; therefore, 100 percent of the
grain consumed is assumed to be contaminated. The uptake of PB-HAP compounds via
ingestion of contaminated insects and other organisms (e.g., worms, etc.), which may also
April 2004 Page K-22
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contribute to the ingestion of PB-HAP compounds, is not accounted for in the equations and may
be a limitation depending on the site-specific conditions under which the chickens are raised.
The PB-HAP compound concentration in grain is estimated by using the algorithm for
aboveground produce described in Section 3. Grain is considered to be a feed item that is
protected from deposition of particles and vapor transfer. As a result, only contamination due to
root uptake of PB-HAP compounds is considered in the calculation of PB-HAP compound
concentration in grain.
6.1 Concentration of PB-HAP compound in Chicken and Eggs
EPA (1998)(1) recommends the use of Equation 15 to calculate PB-HAP compound
concentrations in chicken and eggs. It is recommended that PB-HAP compound concentrations
in chicken and eggs be determined separately.
. Bs • Baegg or Bashisken (Equation 15)
where
A ^ken = Concentration of PB-HAP compound in chicken (mg PB-HAP compound/kg FW
tissue)
Aegg = Concentration of PB-HAP compound in eggs (mg PB-HAP compound/kg FW
tissue)
Fi
Qpi
tissue;
= Fraction of plant type i (grain) grown on contaminated soil and ingested by the
animal (chicken)(unitless)
= Quantity of plant type i (grain) eaten by the animal (chicken) each day (kg DW
plant/day)
Pi = Concentration of PB-HAP compound in plant type i (grain) eaten by the animal
(chicken) (mg/kg DW)
Qs = Quantity of soil eaten by the animal (chicken) (kg/day)
Cs = Average soil concentration over exposure duration (mg PB-HAP compound/kg
soil)
Bs = Soil bioavailability factor (unitless)
Bo-chicken = PB-HAP compound biotransfer factor for chicken (day/kg FW tissue)
Baegg = PB-HAP compound biotransfer factor for eggs (day/kg FW tissue)
EPA (1998)(1) describes determination of compound specific parameters Bachicken and Baegg. The
remaining parameters are discussed in the following subsections.
6.1.1 Fraction of Plant Type i Grown on Contaminated Soil and Eaten by the Animal
(Chicken)(F.)
The calculation of Ft for chicken is identical to that for beef cattle (Section 4.4.1).
6.1.2 Quantity of Plant Type i Eaten by the Animal (Chicken) Each Day (Qp)
Because chickens are not grazing animals, they are assumed not to eat forage. Chickens £
assumed not to consume any silage. The daily quantity of plant feeds (kilograms of DW)
are
April 2004 Page K-23
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consumed by chicken only should be estimated for grain feed. EPA (1998)(1) recommends the
use of the following ingestion rate (Qpt): Grain = 0.2 kg DW/day. Uncertainties associated with
this variable include the variability of actual grain ingestion rates from site to site. In addition,
the assumption of uniform contamination of plant materials consumed by chicken produces some
uncertainty.
6.1.3 Concentration of PB-HAP compound in Plant Type / Eaten by the Animal
(Chicken) (P,)
The total PB-HAP compound concentration is the PB-HAP compound concentration in grain and
can be calculated by using Equation 16. Values for Pr can be derived by using Equation 10.
p. = Pr (Equation 16)
where
Pi = Concentration of PB-HAP compound in each plant type i eaten by the animal (mg PB-
HAP compound/kg DW)
Pr = Plant concentration due to root uptake (mg PB-HAP compound/kg DW)
6.1.4 Quantity of Soil Eaten by the Animal (Chicken) Each Day (Qs)
PB-HAP compound concentration in chickens also results from intake of soil. As discussed
earlier, chickens are assumed to consume 10 percent of their total diet as soil. EPA (1998)(1)
recommends the following soil ingestion rate for chicken: 0.022 kg DW/day. Uncertainties
associated with this variable include the lack of current empirical data to support soil ingestion
rates for chicken, and the assumption of uniform contamination of soil ingested by chicken.
6.1.5 Average Soil Concentration Over Exposure Duration (Cs)
The calculation of Cs for chicken is the same as for beef cattle (Section 4.4.5).
6.1.6 Soil Bioavailability Factor (Bs)
The calculation ofBs for chicken is the same as for beef cattle (Section 4.4.6)
7.0 Calculation of PB-HAP Compound Concentrations in Drinking Water and Fish
PB-HAP compound concentrations in surface water are calculated for all water bodies selected
for evaluation in the risk assessment; specifically, evaluation of the drinking water and/or fish
ingestion exposure pathways. Mechanisms considered for determination of PB-HAP compound
loading of the water column are:
(1) Direct deposition,
(2) Runoff from impervious surfaces within the watershed,
(3) Runoff from pervious surfaces within the watershed,
(4) Soil erosion over the total watershed,
(5) Direct diffusion of vapor phase PB-HAP compounds into the surface water, and
(6) Internal transformation of compounds chemically or biologically.
April 2004 Page K-24
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Other potential mechanisms may need consideration on a case-by-case basis (e.g., tidal
influences), however, contributions from other potential mechanisms are assumed to be
negligible in comparison with those being evaluated.
The USLE and a sediment delivery ratio are used to estimate the rate of soil erosion from the
watershed. In the ISCST3 model, surface water concentration algorithms include a sediment
mass balance, in which the amount of sediment assumed to be buried and lost from the water
body is equal to the difference between the amount of soil introduced to the water body by
erosion and the amount of suspended solids lost in downstream flow. As a result, the
assumptions are made that sediments do not accumulate in the water body over time, and an
equilibrium is maintained between the surficial layer of sediments and the water column. The
total water column PB-HAP compound concentration is the sum of the PB-HAP compound
concentration dissolved in water and the PB-HAP compound concentration associated with
suspended solids. Partitioning between water and sediment varies with the PB-HAP compound.
The total concentration of each PB-HAP compound is partitioned between the sediment and the
water column. The assumptions for other multimedia models may differ.
To evaluate the PB-HAP compound loading to a water body from its associated watershed, it is
recommended that the PB-HAP compound concentration in watershed soils be calculated. As
described in Section 2, the equation for PB-HAP compound concentration in soil includes a loss
term that considers the loss of contaminants from the soil after deposition. These loss
mechanisms all lower the soil concentration associated with a specific deposition rate.
The ISCST3 model approach for modeling PB-HAP compound loading to a water body
represents a simple steady-state model to solve for a water column in equilibrium with the upper
sediment layer. This approach may be limited in addressing the dynamic exchange of
contaminants between the water body and the sediments following changes in external loadings.
While appropriate for calculating risk under long-term average conditions, the evaluation of
complex water bodies or shorter term loading scenarios may be improved through the use of a
dynamic modeling framework [e.g., Exposure Analysis Modeling System (EXAMS)]. Although
typically more resource intensive, such analysis may offer the ability to refine modeling of
contaminant loading to a water body. Additionally, the computations may better represent the
exposure scenario being evaluated.
For example, EXAMS allows computations to be performed for each defined segment or
compartment of a water body or stream. These compartments are considered physically
homogeneous and are connected via advective and dispersive fluxes. Compartments can be
defined as littoral, epilimnion, hypolimnion, or benthic. Such resolution also makes it possible to
assign receptor locations specific to certain portions of a water body where evaluation of
exposure is of greatest interest.
Some considerations regarding the selection and use of a dynamic modeling framework or
simulation model to evaluate water bodies may include the following:
• Will a complex surface water modeling effort provide enhanced results over the use of the
more simplistic steady-state equations;
April 2004 Page K-25
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• Are the resources needed to conduct, as well as review, a more complex modeling effort
justified in comparison to the refinement to results provided;
• Has the model been used previously for regulatory purposes, and therefore, already has
available documentation to support such uses;
• Can the model conduct steady-state and dynamic analysis; and
• Does the model require calibration with field data, and if so, are there sufficient quantity and
quality of site-specific data available to support calibration.
7.1 Total PB-HAP compound Load to the Water Body (LT)
EPA (1998)(1) recommends the use of Equation 17 to calculate the total PB-HAP compound load
to a water body (LT).
r ^dif T ^RI T -H? T ^E T ^J (Equation 17)
where
Zr = Total PB-HAP compound load to the water body (including deposition, runoff, and
erosion) (g/yr)
LDEP = Total (wet and dry) particle phase and vapor phase PB-HAP compound direct
deposition load to water body (g/yr)
Ld. = Vapor phase PB-HAP compound diffusion load to water body (g/yr)
LRI = Runoff load from impervious surfaces (g/yr)
LR = Runoff load from pervious surfaces (g/yr)
LE = Soil erosion load (g/yr)
Lj = Internal transfer (g/yr)
Due to the limited data and uncertainty associated with the chemical or biological internal
transfer, LT, of compounds into daughter products, EPA (1998)(1) recommends a default value for
this variable of zero. However, if a permitting authority determines that site-specific conditions
indicate calculation of internal transfer may need to be considered, EPA (1998)(1) recommends
following the methodologies described in EPA NCEA document, Methodology for Assessing
Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions (EPA
1998).(12) Calculation of each of the remaining variables (LDEP, Ldif> LRI, LR, and LE) is discussed in
the following subsections.
7.1.1 Total (Wet and Dry) Particle Phase and Vapor Phase PB-HAP compound Direct
Deposition Load to Water Body (LDEP)
EPA (1998)(1) recommends Equation 18 to calculate the load to the water body from the direct
deposition of wet and dry particles and vapors onto the surface of the water body (LDEP).
DWP\-*r (Equation 18)
April 2004 Page K-26
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where
LDEP = Total (wet and dry) particle phase and vapor phase PB-HAP compound direct
deposition load to water body (g/yr)
Q = PB-HAP compound emission rate (g/s)
Fv = Fraction of PB-HAP compound air concentration in vapor phase (unitless)
Dytwv = Unitized yearly (water body or watershed) average total (wet and dry) deposition from
vapor phase (s/m2-yr)
Dytwp = Unitized yearly (water body or watershed) average total (wet and dry) deposition from
particle phase (s/m2-yr)
Aw = Water body surface area (m2)
7.1.2 Vapor Phase PB-HAP compound Diffusion Load to Water Body (Ldij)
EPA (1998)(1) recommends using Equation 19 to calculate the vapor phase PB-HAP compound
diffusion load to the water body (Ldij).
K-O- Fv • Cyvw• Aw • 1 x 10"6
-H—^ v- ^ ^ (Equation 19)
= H
where
L = Vapor phase PB-HAP compound diffusion load to water body (g/yr)
Kv = Overall PB-HAP compound transfer rate coefficient (m/yr)
Q = PB-HAP compound emission rate (g/s)
Fv = Fraction of PB-HAP compound air concentration in vapor phase (unitless)
Cywv = Unitized yearly (water body or watershed) average air concentration from vapor phase
(ug-s/g-m3)
Aw = Water body surface area (m2)
10~6 = Units conversion factor (g/ug)
H = Henry's Law constant (atm-mVmol)
R = Universal gas constant (atm-m3/mol-K)
Twk = Water body temperature (K)
The overall PB-HAP compound transfer rate coefficient (Kv) is calculated by using Equation 29
(see section 7.4.4). EPA (1998)(1) recommends a water body temperature (Twk) of 298 K (or
25°C).
7.1.3 Runoff Load from Impervious Surfaces (LRI)
In some watershed soils, a fraction of the total (wet and dry) deposition in the watershed will be
to impervious surfaces. This deposition may accumulate and be washed off during rain events.
EPA (1998)(1) recommends the use of Equation 20 to calculate impervious runoff load to a water
body (Lgj).
April 2004 Page K-2 7
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LRI =Q.[Fr. £>yrwv+ (l.O- Fv). Dytwp] . A, (Equatlon20)
where
Lm = Runoff load from impervious surfaces (g/yr)
Q = PB-HAP compound emission rate (g/s)
Fv = Fraction of PB-HAP compound air concentration in vapor phase (unitless)
Dytwv = Unitized yearly (water body or watershed) average total (wet and dry) deposition from
vapor phase (s/m2-yr)
Dytwp = Unitized yearly (water body or watershed) average total (wet and dry) deposition from
particle phase (s/m2-yr)
Aj = Impervious watershed area receiving PB-HAP compound deposition (m2)
Impervious watershed area receiving PB-HAP compound deposition (AT) is the portion of the
total effective watershed area that is impervious to rainfall (such as roofs, driveways, streets, and
parking lots) and drains to the water body.
7.1.4 Runoff Load from Pervious Surfaces (LR)
EPA (1998)(1) recommends the use of Equation 21 to calculate the runoff dissolved PB-HAP
compound load to the water body from pervious soil surfaces in the watershed (LR).
f , Cs-BD
LR = RO- (AL - Aj)- -Q-01 (Equation21)
where
LR = Runoff load from pervious surfaces (g/yr)
RO = Average annual surface runoff from pervious areas (cm/yr)
AL = Total watershed area receiving PB-HAP compound deposition (m2)
Aj = Impervious watershed area receiving PB-HAP compound deposition (m2)
Cs = Average soil concentration over exposure duration (in watershed soils) (mg PB-HAP
compound/kg soil)
BD = Soil bulk density (g soil/cm3 soil)
Qsw = Soil volumetric water content (mL water/cm3 soil)
Kds = Soil-water partition coefficient (cm3 water/g soil)
0. 01 = Units conversion factor (kg-cm2/mg-m2)
The calculation of the PB-HAP compound concentration in watershed soils (Cs) are discussed in
Section 2.1 . Soil bulk density (BD) is described in Section 2.5.2. Soil water content (0^,) is
described in Section 2.5.4.
April 2004 Page K-28
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7.1.5 Soil Erosion Load (LE)
EPA (1998)(1) recommends the use of Equation 22 to calculate soil erosion load (LE).
, , Cs- Kd, • BD
Lw = X • [A, - AT}• SD • ER 0.001 (Equation22)
z e V L /; &svf + Kd, + BD
where
LE = Soil erosion load (g/yr)
Xe = Unit soil loss (kg/m2-yr)
AL = Total watershed area (evaluated) receiving PB-HAP compound deposition (m2)
Aj = Impervious watershed area receiving PB-HAP compound deposition (m2)
SD = Sediment delivery ratio (watershed) (unitless)
ER = Soil enrichment ratio (unitless)
Cs = Average soil concentration over exposure duration (in watershed soils) (mg PB-HAP
compound/kg soil)
BD = Soil bulk density (g soil/cm3 soil)
Qsw = Soil volumetric water content (mL water/cm3 soil)
Kds = Soil-water partition coefficient (mL water/g soil)
0.001 = Units conversion factor (k-cm2/mg-m2)
Unit soil loss (Xe) is described in Section 7.2. Watershed sediment delivery ratio (SD) is
calculated as described in Section 7.3. PB-HAP compound concentration in soils (Cs) is
described in Section 2.1. Soil bulk density (BD) is described in Section 2.5.2. Soil water content
(0OT) is described in Section 2.5.4.
7.2 Universal Soil Loss Equation - USLE
EPA (1998)(1) recommends that the universal soil loss equation (USLE), Equation 22A, be used
to calculate the unit soil loss (XJ specific to each watershed.
907.18
Xe = RF • K- LS • C • PF • (Equation 22A)
*T 'JT" f
where
Xe = Unit soil loss (kg/m2-yr)
RF = USLE rainfall (or erosivity) factor (yr !)
K = USLE erodibility factor (ton/acre)
LS = USLE length-slope factor (unitless)
C = USLE cover management factor (unitless)
PF = USLE supporting practice factor (unitless)
907.18 = Units conversion factor (kg/ton)
4047 = Units conversion factor (m2/acre)
April 2004 Page K-29
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The US LE RF variable, which represents the influence of precipitation on erosion, is derived
from data on the frequency and intensity of storms. This value is typically derived on a storm-
by-storm basis, but average annual values have been compiled (U.S. Department of Agriculture
1982).(31) Information on determining site-specific values for variables used in calculating Xe is
provided in U.S. Department of Agriculture (U.S. Department of Agriculture 1997)(32) and EPA
guidance (EPA 1985).(22)
7.3 Sediment Delivery Ratio (SD)
EPA (1998)(1) recommends the use of Equation 23 to calculate sediment delivery ratio (SD).
SD = a ' (AL )"& (Equation 23)
where
SD = Sediment delivery ratio (watershed) (unitless)
a = Empirical intercept coefficient (unitless)
b = Empirical slope coefficient (unitless)
AL = Total watershed area (evaluated) receiving PB-HAP compound deposition (m2)
AL is the total watershed surface area evaluated that is affected by deposition and drains to the
body of water (see Chapter 2). In assigning values to the watershed surface area affected by
deposition, the following may be a consideration:
• Distance from the emission source;
• Location of the area affected by deposition fallout with respect to the point at which drinking
water is extracted or fishing occurs; and
• The watershed hydrology.
7.4 Total Water Body PB-HAP compound Concentration (Cwtot)
EPA (1998)(1) recommends the use of Equation 24 to calculate total water body PB-HAP
compound concentration (Cwtot). The total water body concentration includes both the water
column and the bed sediment.
J^m
(Equation 24)
where
Cwtot = Total water body PB-HAP compound concentration (including water column and bed
sediment) (g PB-HAP compound/m3 water body)
LT = Total PB-HAP compound load to the water body (including deposition, runoff, and
erosion) (g/yr)
Vfx = Average volumetric flow rate through water body (mVyr)
fwc = Fraction of total water body PB-HAP compound concentration in the water column
(unitless)
kwt = Overall total water body PB-HAP compound dissipation rate constant (yr !)
April 2004 Page K- 30
-------
Aw = Water body surface area (m2)
dwc = Depth of water column (m)
dhs = Depth of upper benthic sediment layer (m)
The total PB-HAP compound load to the water body (LT) - including deposition, runoff, and
erosion - is described in Section 7.1. The depth of the upper benthic layer (dbs), which represents
the portion of the bed that is in equilibrium with the water column, cannot be precisely specified;
however, EPA (1998)(1) recommends a default value of 0.03. Issues related to the remaining
parameters are summarized in the following subsections.
7.4.1 Fraction of Total Water Body PB-HAP compound Concentration in the Water
Column (fwc) and Benthic Sediment (fbs)
EPA (1998)(1) recommends using Equation 25 A to calculate fraction of total water body PB-HAP
compound concentration in the water column (fwc), and Equation 25B to calculate total water
body contaminant concentration in benthic sediment (fbs).
swwes m +. 0
-------
of 2 to 300 mg/L; with additional information on anticipated TSS values available in the EPA
NCEA document, Methodology for Assessing Health Risks Associated with Multiple Pathways of
Exposure to Combustor Emissions (EPA 1998).(12) If measured data are not available, or of
unacceptable quality, a calculated TSS value can be obtained for non- flowing water bodies using
Equation 25C.
X. • ( A r - A r ) • SD • 1 x 1 Q3 / . x
& V L ^ _ (Equation )25C
where
TSS = Total suspended solids concentration (mg/L)
Xe = Unit soil loss (kg/m2-yr)
AL = Total watershed area (evaluated) receiving PB-HAP compound deposition (m2)
Aj = Impervious watershed area receiving PB-HAP compound deposition (m2)
SD = Sediment delivery ratio (watershed) (unitless)
Vfx = Average volumetric flow rate through water body (value should be 0 for quiescent
lakes or ponds) (mVyr)
Dss = Suspended solids deposition rate (a default value of 1,825 for quiescent lakes or
ponds) (m/yr)
Aw = Water body surface area (m2)
1x1 0"3 = Units conversion factor (g/kg)
The default value of 1,825 m/yr provided for Dss is characteristic of Stake's settling velocity for
an intermediate (fine to medium) silt.
Also, to evaluate the appropriateness of watershed-specific values used in calculating the unit
soil loss (Xe), as described in Section 7.2, the water-body specific measured TSS value can be
compared to the calculated TSS value obtained using Equation 25C. If the measured and
calculated TSS values differ significantly, parameter values used in calculating Xe can be re-
evaluated. This re-evaluation of TSS and Xe can also be conducted if the calculated TSS value is
outside of the normal range expected for average annual measured values, as discussed above.
Bed sediment porosity (Qbs) can be calculated from the bed sediment concentration by using
Equation 26 (EPA 1993b)(11):
U g£
#& = 1 - - (Equation 26)
P*
where
Qbs = Bed sediment porosity (Lwater/Lsediment)
ps = Bed sediment density (kg/L)
CBS = Bed sediment concentration (kg/L)
April 2004 Page K-32
-------
EPA (1998)(1) recommends the default value of 0.6 Lwate/LSediment for bed sediment porosity (Qbs).
This assumes a bed sediment density (ps) of 2.65 kg/L and abed sediment concentration (CBS) of
l.Okg/L.
7.4.2 Overall Total Water Body PB-HAP compound Dissipation Rate Constant (kwt)
EPA (1998)(1) recommends the use of Equation 27 to calculate the overall dissipation rate of PB-
HAP compounds in surface water, resulting from volatilization and benthic burial.
*=-* +'* (Equation27)
where
k = Overall total water body dissipation rate constant (yr !)
fwc = Fraction of total water body PB-HAP compound concentration in the water column
(unitless)
kv = Water column volatilization rate constant (yr !)
fbs = Fraction of total water body PB-HAP compound concentration in benthic sediment
(unitless)
kb = Benthic burial rate constant (yr !)
The variables/,,, andfbs are discussed in Section 7.4.1, and Equations 25A and 25B.
7.4.3 Water Column Volatilization Rate Constant (kv)
EPA (1998)(1) recommends using Equation 28 to calculate water column volatilization rate
constant.
_ *, _
k = - 7 - 71 (Equation 28)
-
where
kv = Water column volatilization rate constant (yr !)
Kv = Overall PB-HAP compound transfer rate coefficient (m/yr)
d2 = Total water body depth (m)
Kd^ = Suspended sediments/surface water partition coefficient (L water/kg suspended
sediments)
TSS = Total suspended solids concentration (mg/L)
1 x 10~6 = Units conversion factor (kg/mg)
Total water body depth (dz), suspended sediment and surface water partition coefficient
and total suspended solids concentration (TSS), are described in Section 7.4.1. The overall
transfer rate coefficient (Kv) is described in Section 7.4.4.
April 2004 Page K-33
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7.4.4 Overall PB-HAP compound Transfer Rate Coefficient (Kv)
Volatile organic chemicals can move between the water column and the overlying air. The
overall transfer rate Kv, or conductivity, is determined by a two-layer resistance model that
assumes that two "stagnant films" are bounded on either side by well-mixed compartments.
Concentration differences serve as the driving force for the water layer diffusion. Pressure
differences drive the diffusion for the air layer. From balance considerations, the same mass
must pass through both films; the two resistances thereby combine in series, so that the
conductivity is the reciprocal of the total resistance.
EPA (1998)(1) recommends the use of Equation 29 to calculate the overall transfer rate
coefficient (Kv).
(Equation 29)
where
Kv = Overall PB-HAP compound transfer rate coefficient (m/yr)
KL = Liquid phase transfer coefficient (m/yr)
KG = Gas phase transfer coefficient (m/yr)
H = Henry's Law constant (atm-mVmol)
R = Universal gas constant (atm-mVmol-K)
^wk = Water body temperature (K)
0 = Temperature correction factor (unitless)
The value of the conductivity Kv depends on the intensity of turbulence in the water body and the
overlying atmosphere. As Henry's Law constant increases, the conductivity tends to be
increasingly influenced by the intensity of turbulence in water. Conversely, as Henry's Law
constant decreases, the value of the conductivity tends to be increasingly influenced by the
intensity of atmospheric turbulence.
The liquid and gas phase transfer coefficients, KL and KG, respectively, vary with the type of
water body. The liquid phase transfer coefficient (KL) is calculated by using Equations 30A and
30B (described in Section 7.4.5). The gas phase transfer coefficient (KG) is calculated by using
Equations 31A and 3 IB (described in Section 7.4.6).
Henry's Law constants generally increase with increasing vapor pressure of a PB-HAP
compound and generally decrease with increasing solubility of a PB-HAP compound. Henry's
Law constants are compound-specific and are presented in Appendix D. The universal ideal gas
constant, R, is 8.205 x 10~5 atm-m3/mol-K, at 20°C. The temperature correction factor (0), which
is equal to 1.026, is used to adjust for the actual water temperature. Volatilization is assumed to
occur much less readily in lakes and reservoirs than in moving water bodies.
April 2004 Page K-34
-------
7.4.5 Liquid Phase Transfer Coefficient (KL)
EPA (1998)(1) recommends using Equations 30A and 30B to calculate liquid phase transfer
coefficient. (KL).
K =
fl x 1CT4 ) .
. it
.3.1536xl0
(Equation 30A)
k
0.33
3.1536X 10J
(Equation SOB)
where
A^ = Liquid phase transfer coefficient (m/yr)
Dw = Diffusivity of PB-HAP compound in water (cm2/s)
u = Current velocity (m/s)
1 x 10~4 = Units conversion factor (m2/cm2)
dz = Total water body depth (m)
Cd = Drag coefficient (unitless)
W = Average annual wind speed (m/s)
pa = Density of air (g/cm3)
pw = Density of water (g/cm3)
k = von Karman's constant (unitless)
Az = Dimensionless viscous sublayer thickness (unitless)
|iw = Viscosity of water corresponding to water temperature (g/cm-s)
3.1536xl07 _ Units conversion factor (s/yr)
For a flowing stream or river, the transfer coefficients are controlled by flow-induced turbulence.
For these systems, the liquid phase transfer coefficient is calculated by using Equation 30A. For
a stagnant system (quiescent lake or pond), the transfer coefficient is controlled by wind-induced
turbulence, and the liquid phase transfer coefficient can be calculated by using Equation 3OB.
The total water body depth (dz) for liquid phase transfer coefficients is discussed in Section 7.4.1.
EPA (1998)(1) recommends the use of the following default values:
• A diffusivity of chemical in water ranging (£)w) from 1.0 x 10 5 to 8.5 x 10"2 cm2/s;
• A dimensionless viscous sublayer thickness (Az) of 4;
• A von Karman's constant (k) of 0.4;
• A drag coefficient (Q of 0.0011;
• An air density (pa) of 0.0012 g/cm3 at standard conditions (temperature = 20°C or 293 K,
pressure = 1 arm or 760 millimeters of mercury);
• A water density of(pw) of 1 g/cm3; and
• A water viscosity(|iw) of a 0.0169 g/cm-s corresponding to water temperature.
April 2004
Page K-35
-------
7.4.6 Gas Phase Transfer Coefficient (KG)
EPA (1998)(1) recommends using Equations 31A and 3 IB to calculate gas phase transfer
coefficient (KG).
For flowing streams or rivers:
= 36,5QQm/yr
(Equation 3 1 A)
For quiescent lakes or ponds:
K =
Q 33
3.1 536 x 10
(Equation 31B)
where
KG = Gas phase transfer coefficient (m/yr)
Cd = Drag coefficient (unitless)
W = Average annual wind speed (m/s)
k = von Karman's constant (unitless)
Az = Dimensionless viscous sublayer thickness (unitless)
|ia = Viscosity of air corresponding to air temperature (g/cm-s)
pa = Density of air corresponding to water temperature (g/cm3)
Da = Diffusivity of PB-HAP compound in air (cm2/s)
3.1536 x 107 = Units conversion factor (s/yr)
EPA (1998)(1) recommends 1.81 x 10~4 g/cm-s for the viscosity of air corresponding to air
temperature.
7.4.7 Benthic Burial Rate Constant (kb)
EPA (1998)(1) recommends using Equation 32 to calculate benthic burial rate (kh).
X
m . _.
(Equation 32)
where
kb
Xe
AL
SD
Vfx
15*5*
Aw
Benthic burial rate constant (yr !)
Unit soil loss (kg/m2-yr)
Total watershed area (evaluated) receiving deposition (m2)
Sediment delivery ratio (watershed) (unitless)
Average volumetric flow rate through water body (mVyr)
Total suspended solids concentration (mg/L)
Water body surface area (m2)
April 2004
Page K-36
-------
CBS = Bed sediment concentration (g/cm3)
dbs = Depth of upper benthic sediment layer (m)
1 x 10 6 _ Units conversion factor (kg/mg)
1 x 103 = Units conversion factor (g/kg)
The benthic burial rate constant (kb), can also be expressed in terms of the rate of burial (Wb)
(Equation 33):
Wb - kb -dbs (Equation 33)
where
Wb = Rate of burial (m/yr)
hh = Benthic burial rate constant (yr !)
dbs = Depth of upper benthic sediment layer (m)
EPA (1998)(1) recommends the following default value of 1.0 kg/L for bed sediment
concentration (CBS).
Section 7.2 discusses the unit soil loss (Xe). Section 7.3 discusses sediment delivery ratio (SD)
and watershed area evaluated receiving PB-HAP compound deposition (AL). Section 7.4
discusses the depth of the upper benthic sediment layer (dbs). Average volumetric flow rate
through the water body (Vfx) and water body surface area (Aw) are discussed further in EPA
(1998).(1) Section 7.4.1 discusses total suspended solids concentration (TSS).
The calculated value for hh is expected to range from 0 to 1.0; with low hh values expected for
water bodies characteristic of no or limited sedimentation (rivers and fast flowing streams), and
hh values closer to 1.0 expected for water bodies characteristic of higher sedimentation (lakes).
This range of values is based on the relation between the benthic burial rate and rate of burial
expressed in Equation 33; with the depth of upper benthic sediment layer held constant. For hh
values calculated as a negative (water bodies with high average annual volumetric flow rates in
comparison to watershed area evaluated), EPA (1998)(1) recommends assigning a hh value of 0
for use in calculating the total water body PB-HAP compound concentration (Cwtot) in
Equation 34 (see next section). If the calculated hh value exceeds 1.0, re-evaluation of the
parameter values used in calculating Xe is recommended to be conducted.
April 2004 Page K-37
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7.4.8 Total PB-HAP compound Concentration in Water Column (Cwctot)
EPA (1998)(1) recommends using Equation 34 to calculate total PB-HAP compound
concentration in water column (Cwctot).
"wi- "^ "&<:
C = f • C • -^ — (Equation 34)
wcfoi J we tvtot j
where
Cwctot = Total PB-HAP compound concentration in water column (mg PB-HAP compound/L
water column)
fwc = Fraction of total water body PB-HAP compound concentration in the water column
(unitless)
Cwtot = Total water body PB-HAP compound concentration, including water column and bed
sediment (mg PB-HAP compound/L water body)
dwc = Depth of water column (m)
dbs = Depth of upper benthic sediment layer (m)
Total water body PB-HAP compound concentration - including water column and bed sediment
(Cwtot) and fraction of total water body PB-HAP compound concentration in the water column
(fwc) - can be calculated by using Equation 34 and Equation 35 (see next section). Depth of
upper benthic sediment layer (dbs) is discussed in Section 7.4.1.
7.4.9 Dissolved Phase Water Concentration (Cdw)
EPA (1998)(1) recommends the use of Equation 35 to calculate the concentration of PB-HAP
compound dissolved in the water column (Cdw).
cwctof
, ,.nrt-6 (Equation 35)
where
Cdw = Dissolved phase water concentration (mg PB-HAP compound/L water)
Cwctot = Total PB-HAP compound concentration in water column (mg PB-HAP
compound/L water column)
Kdm = Suspended sediments/surface water partition coefficient (L water/kg suspended
sediment)
TSS = Total suspended solids concentration (mg/L)
1 x 10~6 = Units conversion factor (kg/mg)
The total PB-HAP compound concentration in water column (Cwctot) is calculated by using the
Equation 34. Section 7.4.1 discusses the surface water partition coefficient (Kdsw) and total
suspended solids concentration (TSS).
April 2004 Page K-38
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7.4.10 PB-HAP compound Concentration Sorbed to Bed Sediment (Csb)
EPA (1998)(1) recommends the use of Equation 36 to calculate PB-HAP compound
concentration sorbed to bed sediment (Csb).
{ Kdb } (d + db}
Ch = fh • C „ - - - - • — - - (Equation 36)
^sb J &s ^wtat / . j W
where
Csb = PB-HAP compound concentration sorbed to bed sediment (mg PB-HAP
compound/kg sediment)
fbs = Fraction of total water body PB-HAP compound concentration in benthic sediment
(unitless)
Cwtot = Total water body PB-HAP compound concentration, including water column and bed
sediment (mg PB-HAP compound/L water body)
Kdbs = Bed sediment/sediment pore water partition coefficient (L PB-HAP compound/kg
water body)
Qbs = Bed sediment porosity (Lpore wate/Lsediment)
CBS = Bed sediment concentration (g/cm3)
dwc = Depth of water column (m)
dhs = Depth of upper benthic sediment layer (m)
Bed sediment porosity (Qbs) and bed sediment concentration (CBS) are discussed in Section 7.4. 1 .
Depth of water column (dwc) and depth of upper benthic layer (dbs) are discussed in Section 7.4.
7.5 Concentration of PB-HAP compound in Fish (Cfish)
The PB-HAP compound concentration in fish is calculated using either a PB-HAP compound-
specific bioconcentration factor (BCF), a PB-HAP compound-specific bioaccumulation factor
(BAF), or a PB-HAP compound-specific biota-sediment accumulation factor (BSAF). For
compounds with a log Kow less than 4.0, BCFs are used. Compounds with a log Kow greater than
4.0 (except for extremely hydrophobic compounds such as poly cyclic organic matter and PCBs),
are assumed to have a high tendency to bioaccumulate, therefore, BAFs are used. While
extremely hydrophobic PB-HAP compounds are also assumed to have a high tendency to
bioaccumulate, they are expected to be sorbed to the bed sediments more than associated with the
water phase. Therefore, for polycyclic organic matter and PCBs, EPA (1998)(1) recommends
using BSAFs to calculate concentrations in fish.
BCF and BAF values are generally based on dissolved water concentrations. Therefore, when
BCF or BAF values are used, the PB-HAP compound concentration in fish is calculated using
dissolved water concentrations. BSAF values are based on benthic sediment concentrations.
Therefore, when BSAF values are used, PB-HAP compound concentration in fish is calculated
using benthic sediment concentrations. The equations used to calculate fish concentrations are
described in the subsequent subsections.
April 2004 Page K-39
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7.5.1 Fish Concentration (Cflsh) from Bioconcentration Factors Using Dissolved Phase
Water Concentration
EPA (1998)(1) recommends the use of Equation 37 to calculate fish concentration fromBCFs
using dissolved phase water concentration.
C1 - C1 • P.C'W (Equations?)
^•fish ~ ^dw £^-ffi$h ' 4 '
where
Cfish = Concentration of PB-HAP compound in fish (mg PB-HAP compound/kg FW
tissue)
Cdw = Dissolved phase water concentration (mg PB-HAP compound/L)
BCFfish = Bioconcentration factor for PB-HAP compound in fish (L/kg)
The dissolved phase water concentration (Cdw) is calculated by using Equation 35.
7.5.2 Fish Concentration (Cflsh) from Bioaccumulation Factors Using Dissolved Phase
Water Concentration
EPA (1998)(1) recommends the use of Equation 38 to calculate fish concentration fromBAFs
using dissolved phase water concentration.
(Equation 3 8)
where
Cfish = Concentration of PB-HAP compound in fish (mg PB-HAP compound/kg FW tissue)
Cdw = Dissolved phase water concentration (mg PB-HAP compound/L)
BAFfish = Bioaccumulation factor for PB-HAP compound in fish (L/kg FW tissue)
The dissolved phase water concentration (Cdw) is calculated by using Equation 35.
7.5.3 Fish Concentration (Cfish) from Biota-To-Sediment Accumulation Factors Using PB-
HAP compound Sorbed to Bed Sediment
EPA (1998)(1) recommends the use of Equation 39 to calculate fish concentration ftomBSAFs
using PB-HAP compound sorbed to bed sediment for very hydrophobic compounds (polycyclic
organic matter and PCBs).
(Equation 3 9)
^^sed
where
Cfish = Concentration of PB-HAP compound in fish (mg PB-HAP compound/kg FW tissue)
April 2004 Page K-40
-------
Csb = Concentration of PB-HAP compound sorbed to bed sediment (mg PB-HAP
compound/kg bed sediment)
fitpid = Fisn lipid content (unitless)
BSAF = Biota-to-sediment accumulation factor (unitless)
OCsed = Fraction of organic carbon in bottom sediment (unitless)
The concentration of PB-HAP compound sorbed to bed sediment (Csb) is calculated by using
Equation 36. EPA recommended default values for the fish lipid content (flipid) and for the
fraction of organic carbon in bottom sediment (OCsed) are given in EPA (1998).(1)
Values for the fraction of organic carbon in bottom sediment recommended by EPA (1993b)(11)
range from 0.03 to 0.05 (Ocsed). These values are based on an assumption of a surface soil OC
content of 0.01. This document states that the organic carbon content in bottom sediments is
higher than the organic carbon content in soils because (1) erosion favors lighter-textured soils
with higher organic carbon contents, and (2) bottom sediments are partially comprised of detritus
materials.
The fish lipid content (f,ipid) value is site-specific and dependent on the type of fish. As stated in
EPA (1998)(1), a default range of 0.03 to 0.07 is recommended specific to warm or cold water
fish species. EPA (2000)(33) provides information supporting a value of 0.03 (3 percent lipid
content of the edible portion). EPA (1993a)(34) recommended a default value of 0.04 for OC.
sedi
which is the midpoint of the specified range. EPA (1993b; 1993a)(11)(34) recommended the use of
0.07, which was originally cited in Cook et al. (1991).(35)
8.0 Concentrations of Dioxins in Breast Milk
EPA (1998)(1) recommends the use of Equation 40 to estimate the concentrations of dioxins in
breast milk.
m-lx 109
06932
where
(Equation 40)
Cmiitfat = Concentration of dioxin in milk fat of breast milk for a specific exposure scenario (pg
dioxin/kg milk fat)
m = Average maternal intake of dioxin for each adult exposure scenario (mg dioxin/kg
BW-day)
1 x 1 09 = Units conversion factor (pg/mg)
h = Half-life of dioxin in adults (days)
fj = Fraction of ingested dioxin that is stored in fat (unitless)
f2 = Fraction of mother's weight that is fat (unitless)
The values of m, /z,/;, andf2 are site-specific and dependent on the specific species of dioxin
present. EPA (1998)(1) recommends a default value of 2,555 days for h, a default value of 0.9 for
f], and a default value of 0.3 forf2 . Additional references for the derivation of this equation and
these default values are given in EPA (1998).(1)
April 2004 Page K-41
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Uncertainties associated with this equation include:
• The most significant uncertainties are associated with the variable m. Because m is
calculated as the sum of numerous potential intakes, estimates ofm incorporate uncertainties
associated with each exposure pathway. Therefore, m may be under- or over-estimated.
• This equation assumes that the concentration of dioxin in breast milk fat is the same as in
maternal fat. To the extent that this is not the case, uncertainty is introduced.
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