Office of Solid Waste 

and Emergency Response

(5305W)

EPA530-R-05-006

September 2005

www.epa.gov/osw

Human Health Risk

Assessment Protocol for

Hazardous Waste

Combustion Facilities

Final
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EPA530-R-05-006

September 2005

Human Health Risk Assessment Protocol for

Hazardous Waste Combustion Facilities

U.S. EPA, OFFICE OF SOLID WASTE

U.S. ENVIRONMENTAL PROTECTION AGENCY
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ii

DISCLAIMER

This document provides guidance to EPA regional and state RCRA hazardous waste programs, as well as

to facilities subject to RCRA requirements and the general public. More specifically, this guidance

document conveys how EPA generally intends to exercise its discretion in implementing RCRA statutory

and regulatory provisions concerning combustion facilities subject to RCRA. EPA designed this

guidance to explain and clarify national policy on issues related to EPA’s obligation to ensure that

operating permits granted to combustion facilities contain conditions necessary to protect human health

and the environment.

The statutory provisions and EPA regulations discussed in this handbook contain legally binding

requirements. This guidance itself does not substitute for those provisions, nor is it a regulation itself. 

Thus, this guidance does not impose legally binding requirements on EPA, states, or the regulated

community, and may not apply to a particular situation based on the specific circumstances of the

combustion facility. EPA and state regulators base their permitting decisions on the statute and

regulations as applied to the specific combustion facility and retain their discretion to use approaches on a

case-by-case basis that differ from those recommended in this guidance where appropriate. Therefore,

interested parties are free to raise questions and concerns about the substance of this guidance document

and the appropriateness of the application of recommendations to a particular situation. Because this

guidance is not a regulation, EPA and state regulators will consider such questions and concerns when

implementing the recommendations (for example, during the comment period provided on draft

combustion permits). Whether the recommendations in this Handbook are appropriate in a given

situation will depend on facility-specific circumstances.
iii

ACKNOWLEDGMENTS

This document was developed by the U.S. Environmental Protection Agency (EPA) Region 6 and the

Office of Solid Waste. Jeff Yurk from EPA Region 6 was the primary author of this document with

significant technical support and background research being provided by Jeff Ayers of PGM Professional

Services, Jeff Secrest of The Air Group, Tetra Tech EM, Inc, under Contract No. 68-W-99-018, and

Research Triangle Institute, under Contract No. 68-W-03-042. Karen Pollard and Timothy Taylor of the

Office of Solid Waste provided authorship, editorial input, and overall coordination with experts in other

EPA Regions, Headquarters, and the Office of Research and Development. Special thanks are extended

to the following individuals for their valuable comments and contributions. 

U.S. EPA REVIEWERS

Office of Solid Waste

Economics, Methods, and Risk Analysis Division

David Cozzie

Virginia Colten-Bradley

Becky Daiss

Stephen Kroner

David Layland

Alec McBride

Permits and State Programs Division

Sasha Gerhardt

Val De LaFuente

Sonya Sasseville

Rosemary Workman

Municipal and Industrial Solid Waste Division

Bill Schoenborn

Hazardous Waste Minimization and Management

Division

Fred Chanania

Office of Solid Waste and Emergency

Response

Office of the Assistant Administrator

Dorothy Canter

Office of Research & Development

National Center for Environmental

Assessment/Cincinnati

Eletha Brady-Roberts

Randy Bruins

David Reisman

Glenn Rice

Sue Schock

Jeff Swartout

Office of Research & Development (contd.)

National Center for Environmental

Assessment/DC

David Cleverly

Jim Cogliano

Matthew Lorber

National Center for Environmental

Assessment/RTP

Judy Strickland

National Exposure Research Laboratory

Robert Ambrose

Larry Johnson

Donna Schwede

National Health and Environmental Effects

Research Laboratory/RTP

John Nichols

National Risk Management Research Laboratory

Paul Lemieux

Jeffrey Ryan

Office of Air Quality Planning and Standards

Air Quality Monitoring Group

Joe Touma

Risk and Exposure Assessment Group

Dave Guinnup

Deirdre Murphy

Office of General Council

Solid Waste and Emergency Response Law Office

Laurel Celeste

Karen Kraus
iv

EPA Region 1

Office of Ecosystem Protection Division

Jui-Yu Hsieh

EPA Region 2

Division of Environmental Planning and

Protection

John Brogard

EPA Region 3

Waste and Chemicals Management Division

Gary Gross

EPA Region 4

Waste Management Division

Beth Antley

Rick Gillam

Ken Mitchell

EPA Region 5

Waste, Pesticide and Toxic Division

Gary Victorine

Mario Mangino

EPA Region 6

Multimedia Planning and Permitting Division

Cynthia Kaleri

Steve Thompson

David Weeks

 Superfund Group

Ghassan Khoury

Jon Rauscher

Susan Roddy

EPA Region 7

Air, RCRA and Toxics Division

Ken Herstowski

John Smith

EPA Region 8

Hazardous Waste Program

Bob Benson

Carl Daly

Tala Henry

EPA Region 9

Waste Management Division

Stacy Braye

EPA Region 10

Office of Environmental Assessment

Rick Poeton

Marcia Bailey

Roseanne Lorenzana

Office of Waste and Chemicals

Catherine Massimino

STATE REVIEWERS

Texas Natural Resource Conservation

Commission

Toxicology and Risk Assessment Section

Larry Champagne

Lucy Frasier

Roberta Grant

Laurie Haws

Loren Lund

Torin McCoy

Robert Opiela

Mark Rudolph

Dom Ruggeri

Andrew Tachovsky

Arkansas Department of Pollution Control

and Ecology

Phillip Murphy

Tammi Hynum

Colorado Department of Health

Hazardous Materials and Waste Management

Division

Joe Schieffelin

R. David Waltz

Utah Department of Environmental Quality

Christopher Bittner

Alabama Department of Environmental

Management

Air Division

John Rogers

Nathan Hartman

Division of Epidemiology

Brian Hughes
v

In addition, during the public review period of the guidance document, EPA received a number of

insightful and valuable comments from the members of the general public and industry. 

SCIENTIFIC PEER REVIEWERS

On May 25 and 26, 2000, an external peer review workshop was held. The peer review and workshop

were organized, convened and conducted by Tech Law, an EPA contractor under the EPA contract

number: 68-W-99-017. Panel members and reviewers at this workshop included:

Combustion Engineering

Dr. William Schofield

Focus Environmental

Atmospheric Modeling

Dr. Walter Dabberdt

National Center of Atmospheric Research

Human Health Toxicology

Dr. Thomas A. Gasiewicz

University of Rochester

Dr. Mary Davis

University of West Virginia

Human Health Exposure

Dr. James P. Butler

Argonne National Laboratory/University of Chicago

Dr. Richard L. DeGrandchamp

University of Colorado

Mr. Steven Washburn

Environ Corporation

Chemical Fate and Transport

Dr. George F. Fries

U.S. Department of Agriculture (retired)

Dr. Douglas Smith

ENSR International
CONTENTS

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CONTENTS ............ ............ ............ ............ ............ ............ vi

FIGURES ............ ............ ............ ............ ............ ............ . xii

TABLES ............ ............ ............ ............ ............ ............ . xiii

LIST OF ACRONYMS ............ ............ ............ ............ ............ . . xv

INDEXED LIST OF VARIABLES ............ ............ ............ ............ ..... xx

1 INTRODUCTION ............ ............ ............ ............ ........... 1-1

1.1 OBJECTIVE AND DOCUMENT ORGANIZATION ............ ............ . 1-1

1.2 BACKGROUND ............ ............ ............ ............ ...... 1-3

1.3 USING THIS DOCUMENT ............ ............ ............ ......... 1-6

1.4 PRIMARY REFERENCE DOCUMENTS ............ ............ ......... 1-13

1.5 RISK NOMENCLATURE ............ ............ ............ ......... 1-17

2 CHARACTERIZING FACILITY EMISSIONS ............ ............ ............ . 2-1

2.1 COMPILING BASIC FACILITY INFORMATION ............ ............ ... 2-1

2.2 IDENTIFYING EMISSION SOURCES & ESTIMATING EMISSION RATES ..... 2-2

2.2.1 Estimating Stack Emission Rates for Existing Facilities ............ ..... 2-3

2.2.2 Estimating Emission Rates for Facilities with Multiple Stacks ........... 2-13

2.2.3 Estimating Stack Emission Rates for Facilities Not Yet Operational ...... 2-13

2.2.4 Estimating Stack Emission Rates for Facilities Previously Operated ...... 2-14

2.2.5 Emissions From Process Upsets ............ ............ ........... 2-15

2.2.6 RCRA Fugitive Emissions ............ ............ ............ ... 2-17

2.2.7 RCRA Fugitive Ash Emissions ............ ............ ........... 2-27

2.2.8 Cement Kiln Dust (CKD) Fugitive Emissions ............ ............ 2-28

2.3 IDENTIFYING COMPOUNDS OF POTENTIAL CONCERN ............ ..... 2-31

2.3.1 Criteria Pollutants ............ ............ ............ .......... 2-39

2.3.2 Endocrine Disruptors ............ ............ ............ ....... 2-41

2.3.3 Hexachlorobenzene and Pentachlorophenol ............ ............ . . 2-42

2.3.4 Hydrogen Chloride/Chorine Gas ............ ............ .......... 2-43

2.3.5 Metals ............ ............ ............ ............ ....... 2-44

2.3.6 Nitroaromatics ............ ............ ............ ............ 2-57

2.3.7 Particulate Matter ............ ............ ............ .......... 2-58

2.3.8 Phthalates ............ ............ ............ ............ .... 2-59
CONTENTS (contd.)

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2.3.9 Polychlorinated Biphenyls ............ ............ ............ ... 2-61

2.3.10 Polychlorinated Dibenzo(p)dioxins and Dibenzofurans ............ ..... 2-66

2.3.11 Polynuclear Aromatic Hydrocarbons ............ ............ ....... 2-71

2.3.12 Radionuclides ............ ............ ............ ............ . 2-74

2.3.13 Volatile Organic Compounds ............ ............ ............ . 2-78

2.4 ESTIMATING COPC CONCENTRATIONS FOR NON-DETECTS ............ 2-79

2.4.1 Definitions of Commonly Reported Detection Limits ............ ...... 2-79

2.4.2 Using Non-Detect Data In the Risk Assessment ............ .......... 2-82

2.4.3 Statistical Distribution Techniques ............ ............ ......... 2-85

2.4.4 Our Recommendations on Quantifying Non-Detects ............ ....... 2-85

2.4.5 Estimated Maximum Possible Concentration (EMPC) ............ ..... 2-86

2.5 EVALUATING CONTAMINATION IN BLANKS ............ ............ . . 2-87

3 AIR DISPERSION AND DEPOSITION MODELING ............ ............ ....... 3-1

3.1 DESCRIPTION OF AIR MODELS ............ ............ ............ ... 3-3

3.1.1 Background on Air Dispersion Models for Risk Assessment ............ . 3-3

3.1.2 Preprocessing Programs ............ ............ ............ ...... 3-7

3.2 PARTITIONING OF EMISSIONS ............ ............ ............ .... 3-8

3.2.1 Vapor Phase Modeling ............ ............ ............ ....... 3-8

3.2.2 Particle Phase Modeling (Mass Weighting) .......................... 3-8

3.2.3 Particle-Bound Modeling (Surface Area Weighting) .................. 3-12

3.3 SITE-SPECIFIC INFORMATION NEEDED FOR AIR MODELING ........... 3-14

3.3.1 Surrounding Terrain Information ............ ............ .......... 3-15

3.3.2 Surrounding Land Use Information ............ ............ ........ 3-16

3.3.3 Information on Facility Building Characteristics ............ .......... 3-20

3.4 METEOROLOGICAL DATA PRIMER ............ ............ ........... 3-22

3.4.1 Wind Direction and Wind Speed ............ ............ .......... 3-23

3.4.2 Dry Bulb Temperature ............ ............ ............ ...... 3-24

3.4.3 Opaque Cloud Cover ............ ............ ............ ....... 3-25

3.4.4 Cloud Ceiling Height ............ ............ ............ ....... 3-25

3.4.5 Surface Pressure ............ ............ ............ ........... 3-26

3.4.6 Incoming Short-wave Radiation\Leaf Area Index ............ ......... 3-26

3.4.7 Precipitation Amount and Type ............ ............ ........... 3-26

3.4.8 Upper Air Data (Mixing Height) ............ ............ .......... 3-27

3.4.9 Potential Data Sources ............ ............ ............ ...... 3-27

3.5 METEOROLOGICAL PREPROCESSOR DATA NEEDS ............ ........ 3-31

3.5.1 Monin-Obukhov Length ............ ............ ............ ..... 3-32

3.5.2 Anemometer Height ............ ............ ............ ........ 3-33

3.5.3 Surface Roughness Length at Measurement Site ............ .......... 3-33
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3.5.4 Surface Roughness Length at Application Site ............ ........... 3-33

3.5.5 Noon-Time Albedo ............ ............ ............ ......... 3-34

3.5.6 Bowen Ratio ............ ............ ............ ............ . . 3-35

3.5.7 Anthropogenic Heat Flux ............ ............ ............ .... 3-37

3.5.8 Fraction of Net Radiation Absorbed at the Ground ............ ........ 3-38

3.6 ISCST3 MODEL INPUT FILES ............ ............ ............ ..... 3-39

3.6.1 COntrol Pathway ............ ............ ............ ........... 3-42

3.6.2 SOurce Pathway ............ ............ ............ ........... 3-47

3.6.3 REceptor Pathway ............ ............ ............ .......... 3-52

3.6.4 MEteorological Pathway ............ ............ ............ .... 3-55

3.6.5 Terrain Grid (TG) Pathway ............ ............ ............ . . 3-56

3.6.6 OUtput Pathway ............ ............ ............ ........... 3-57

3.7 ISCST3 MODEL EXECUTION ............ ............ ............ ..... 3-58

3.8 USING MODEL OUTPUT ............ ............ ............ ......... 3-58

3.8.1 Unit Rate Output vs. COPC-Specific Output ............ ............ . 3-60

3.8.2 ISCST3 Model Output ............ ............ ............ ...... 3-61

3.8.3 Using Model Output to Estimate Media Concentrations ............ .... 3-62

3.9 MODELING FUGITIVE EMISSIONS ............ ............ ............ 3-64

3.10 MODELING ACUTE RISK ............................................ 3-67

4 EXPOSURE SCENARIO IDENTIFICATION ............ ............ ............ . 4-1

4.1 CHARACTERIZING THE EXPOSURE SETTING ............ ............ ... 4-3

4.1.1 Current and Reasonable Potential Future Land Use ............ ........ 4-4

4.1.2 Water Bodies and their Associated Watersheds ............ ............ 4-7

4.1.3 Special Population Characteristics ............ ............ ......... 4-10

4.2 RECOMMENDED EXPOSURE SCENARIOS ............ ............ ..... 4-11

4.2.1 Farmer ............ ............ ............ ............ ....... 4-15

4.2.2 Farmer Child ............ ............ ............ ............ . . 4-18

4.2.3 Resident ............ ............ ............ ............ ..... 4-18

4.2.4 Resident Child ............ ............ ............ ............ 4-19

4.2.5 Fisher ............ ............ ............ ............ ....... 4-19

4.2.6 Fisher Child ............ ............ ............ ............ . . 4-20

4.2.7 Acute Receptor Scenario ............ ............ ............ .... 4-21

4.3 SELECTING EXPOSURE SCENARIO LOCATIONS ............ ........... 4-21
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5 ESTIMATING MEDIA CONCENTRATIONS ............ ............ ............ . 5-1

5.1 CALCULATING COPC CONCENTRATIONS IN AIR FOR DIRECT

INHALATION ............ ............ ............ ............ ........ 5-2

5.2 CALCULATING COPC CONCENTRATIONS IN SOIL ............ .......... 5-3

5.2.1 Calculating Cumulative Soil Concentration (Cs) ............ ........... 5-4

5.2.2 Calculating the COPC Soil Loss Constant (ks) ............ ............ 5-7

5.2.3 Calculating the Deposition Term (Ds) ............ ............ ...... 5-19

5.2.4 Site-Specific Parameters for Calculating Cumulative Soil Concentration ... 5-19

5.3 CALCULATING COPC CONCENTRATIONS IN PRODUCE ............ .... 5-22

5.3.1 Aboveground Produce Concentration Due to Direct Deposition (Pd) ...... 5-24

5.3.2 Aboveground Produce Concentration Due to Air-to-Plant Transfer (Pv) ... 5-32

5.3.3 Produce Concentration Due to Root Uptake (Pr) ............ .......... 5-35

5.4 CALCULATING COPC CONCENTRATIONS IN BEEF AND DAIRY 

PRODUCTS ............ ............ ............ ............ ......... 5-37

5.4.1 Forage and Silage Concentrations Due to Direct Deposition (Pd) ......... 5-39

5.4.2 Forage and Silage Concentrations Due to Air-to-Plant Transfer (Pv) ...... 5-42

5.4.3 Forage, Silage, and Grain Concentrations Due to Root Uptake (Pr) ....... 5-43

5.4.4 Beef Concentration Resulting from Plant and Soil Ingestion (Abeef) ....... 5-43

5.4.5 COPC Concentration In Milk Due to Plant and Soil Ingestion (Amilk) ...... 5-49

5.5 CALCULATING COPC CONCENTRATIONS IN PORK ............ ........ 5-53

5.5.1 Fraction of Plant Type i Grown on Contaminated Soil and Eaten 

by the Animal (Swine) (Fi) ............ ............ ............ ... 5-54

5.5.2 Quantity of Plant Type i Eaten by the Animal (Swine) Each Day (Qpi) .... 5-55

5.5.3 Concentration of COPC in Plant Type i Eaten by the Animal (Swine) (Pi) . 5-56

5.5.4 Quantity of Soil Eaten by the Animal (Swine) Each Day (Qs) ........... 5-56

5.5.5 Average Soil Concentration Over Exposure Duration (Cs) ............ . . 5-57

5.5.6 Soil Bioavailability Factor (Bs) ............ ............ ........... 5-57

5.5.7 Metabolism Factor (MF) ............ ............ ............ ..... 5-57

5.6 CALCULATING COPC CONCENTRATIONS IN CHICKEN AND EGGS ...... 5-57

5.6.1 Fraction of Plant Type i Grown on Contaminated Soil and Eaten 

by the Animal (Chicken) (Fi) ............ ............ ............ . 5-59

5.6.2 Quantity of Plant Type i Eaten by the Animal (Chicken) Each Day (Qpi) . . 5-59

5.6.3 Concentration of COPC in Plant Type i Eaten by the Animal (Chicken) (Pi) 5-60

5.6.4 Quantity of Soil Eaten by the Animal (Chicken) Each Day (Qs) .......... 5-60

5.6.5 Average Soil Concentration Over Exposure Duration (Cs) ............ . . 5-61

5.6.6 Soil Bioavailability Factor (Bs) ............ ............ ........... 5-61

5.7 CALCULATING COPC CONCENTRATIONS IN DRINKING WATER

AND FISH ............ ............ ............ ............ .......... 5-61

5.7.1 Total COPC Load to the Water Body (LT) ............ ............ ... 5-64
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5.7.2 Universal Soil Loss Equation - USLE ............ ............ ...... 5-69

5.7.3 Sediment Delivery Ratio (SD) ............ ............ ............ 5-70

5.7.4 Total Water Body COPC Concentration (Cwtot) ............ ........... 5-71

5.7.5 Concentration of COPC in Fish (Cfish) ............ ............ ...... 5-85

5.8 USING SITE-SPECIFIC vs. DEFAULT PARAMETER VALUES ............ . . 5-89

6 QUANTIFYING EXPOSURE ............ ............ ............ ............ . . 6-1

6.1 INHALATION EXPOSURE PATHWAYS ............ ............ ......... 6-2

6.1.1 Soil Inhalation Resulting from Dust Resuspension ............ ......... 6-3

6.2 INGESTION EXPOSURE PATHWAYS ............ ............ ........... 6-4

6.2.1 Body Weight ............ ............ ............ ............ ... 6-5

6.2.2 Food (Ingestion) Exposure Pathways ............ ............ ........ 6-6

6.2.3 Soil (Ingestion) Exposure Pathway ............ ............ ......... 6-13

6.2.4 Water (Ingestion) Exposure Pathways ............ ............ ...... 6-14

6.3 DERMAL EXPOSURE PATHWAYS ............ ............ ............ 6-17

6.3.1 Dermal Exposure to Soil ............ ............ ............ ..... 6-17

6.3.2 Dermal Exposure to Water ............ ............ ............ ... 6-18

6.4 EXPOSURE FREQUENCY ............ ............ ............ ........ 6-19

6.5 EXPOSURE DURATION ............ ............ ............ .......... 6-19

6.6 AVERAGING TIME ............ ............ ............ ............ . . 6-21

7 CHARACTERIZING RISK AND HAZARD ............ ............ ............ ... 7-1

7.1 QUANTITATIVELY ESTIMATING CANCER RISK ............ ............ 7-3

7.2 QUANTITATIVELY ESTIMATING NONCANCER HAZARD ............ .... 7-5

7.3 TARGET LEVELS ............ ............ ............ ............ ... 7-10

7.4 ESTIMATING ACUTE EXPOSURE FROM DIRECT INHALATION .......... 7-10

7.4.1 Existing Hierarchical Approaches for Acute Inhalation Exposure ........ 7-10

7.4.2 Our Recommended Hierarchal Approach ............ ............ .... 7-12

7.4.3 Characterizing Potential Health Effects from Acute Exposure ........... 7-14

8 INTERPRETING UNCERTAINTY FOR HUMAN HEALTH RISK ASSESSMENT ...... 8-1

8.1 UNCERTAINTY AND LIMITATIONS OF THE RISK ASSESSMENT PROCESS . 8-1

8.2 TYPES OF UNCERTAINTY ............ ............ ............ ........ 8-2
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8.3 QUALITATIVE ESTIMATES OF UNCERTAINTY . . . . . . . . . . . . . . . . . . . . . . . . . 8-5

8.4 QUANTITATIVE ESTIMATES OF UNCERTAINTY . . . . . . . . . . . . . . . . . . . . . . . . 8-5

8.5 RISK ASSESSMENT UNCERTAINTY DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . 8-7

9 COMPLETING THE RISK ASSESSMENT REPORT AND FOLLOW-ON ACTIVITIES . . 9-1

9.1 CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-1

9.2 ACTIVITIES FOLLOWING RISK ASSESSMENT COMPLETION . . . . . . . . . . . . . 9-2

REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R-1

APPENDICES

A CHEMICAL-SPECIFIC DATA

A-1 CHEMICALS OF POTENTIAL INTEREST

A-2 CHEMICAL-SPECIFIC PARAMETER VALUES

B ESTIMATING MEDIA CONCENTRATION EQUATIONS AND VARIABLE VALUES

B-1 SOIL INGESTION EQUATIONS

B-2 PRODUCE INGESTION EQUATIONS

B-3 ANIMAL PRODUCTS INGESTION EQUATIONS

B-4 DRINKING WATER AND FISH INGESTION EQUATIONS

B-5 DIRECT INHALATION EQUATION

B-6 ACUTE EQUATION

C RISK CHARACTERIZATION EQUATIONS
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FIGURES

Figure Page

1-1 HUMAN HEALTH RISK ASSESSMENT PROCESS ............ ............ ...... 1-10

2-1 EXAMPLE FACILITY PLOT MAP ............ ............ ............ ........ 2-18

2-2 EXAMPLE EMISSIONS INVENTORY ............ ............ ............ ..... 2-19

2-3 COPC IDENTIFICATION ............ ............ ............ ............ .... 2-32

2-4 PHASE ALLOCATION AND SPECIATION OF MERCURY IN AIR ............ ..... 2-47

3-1 SOURCES OF METEOROLOGICAL DATA ............ ............ ............ . 3-28

3-2 EXAMPLE INPUT FILE FOR “PARTICLE PHASE” ............ ............ ...... 3-40

4-1 ISCST3 GRID NODES AND LAND USE DESIGNATIONS ............ ............ 4-23

5-1 COPC CONCENTRATION IN AIR FOR DIRECT INHALATION ............ ......... 5-2

5-2 COPC CONCENTRATION IN SOIL ............ ............ ............ ........ 5-3

5-3 COPC CONCENTRATION IN PRODUCE ............ ............ ............ ... 5-24

5-4 COPC CONCENTRATION IN BEEF AND DAIRY PRODUCTS ............ ........ 5-38

5-5 COPC CONCENTRATION IN PORK ............ ............ ............ ...... 5-53

5-6 COPC CONCENTRATION IN CHICKEN AND EGGS ............ ............ .... 5-58

5-7 COPC LOADING TO THE WATER BODY ............ ............ ............ . 5-63

5-8 COPC CONCENTRATION IN FISH ............ ............ ............ ........ 5-86
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TABLES

Table Page

2-1 EXAMPLE CALCULATION TOTAL FUGITIVE EMISSION RATES FOR

EQUIPMENT IN WASTE FEED STORAGE AREA ............ ............ ...... 2-22

2-2 EXAMPLE CALCULATION SPECIATED FUGITIVE EMISSIONS FOR

EQUIPMENT IN WASTE FEED STORAGE AREA ............ ............ ....... 2-24

2-3 SOCMI AVERAGE EMISSION FACTORS ............ ............ ............ . . 2-25

2-4 QUALITATIVE EFFECTS OF PHYSICAL & CHEMICAL CONDITIONS ON

METHYLATION ............ ............ ............ ............ ........... 2-54

2-5 TOXICITY EQUIVALENCY FACTORS FOR COPLANAR PCBs ............ ....... 2-64

2-6 SLOPE FACTORS FOR PCBs ............ ............ ............ ............ . 2-65

2-7 PCDD/PCDF TOXICITY EQUIVALENCY FACTOR VALUES ............ ......... 2-69

2-8 RELATIVE POTENCY FACTORS FOR CLASS B2 CARCINOGEN PAHs ............ 2-70

3-1 HYPOTHETICAL PARTICLE SIZE DISTRIBUTION DATA TO SUPPORT

EXAMPLE CALCULATIONS ............ ............ ............ ............ 3-10

3-2 URBAN LAND USE TYPES ............ ............ ............ ............ . . 3-17

3-3 SURFACE ROUGHNESS HEIGHTS ............ ............ ............ ....... 3-19

3-4 L VALUES FOR VARIOUS LAND USES ............ ............ ............ ... 3-32

3-5 ALBEDO OF NATURAL GROUND COVERS FOR LAND USE TYPES AND

SEASONS ............ ............ ............ ............ ............ ..... 3-34

3-6 DAYTIME BOWEN RATIOS BY LAND USE, SEASON, AND PRECIPITATION

CONDITIONS ............ ............ ............ ............ ............ . 3-36

3-7 ANTHROPOGENIC HEAT FLUX (Qf) AND NET RADIATION (Q*)

FOR SEVERAL URBAN AREAS ............ ............ ............ .......... 3-38

3-8 ISCST3 INPUT FILE SECTIONS ............ ............ ............ .......... 3-41

3-9 DRY DEPOSITION VELOCITY ESTIMATES AVAILABLE IN LITERATURE ........ 3-43

3-10 ISCST3 AIR PARAMETER OUTPUT .......................................... 3-59
Human Health Risk Assessment Protocol

Contents September 2005

U.S. EPA Region 6 U.S. EPA

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Center for Combustion Science and Engineering xiv

TABLES (contd.)

4-1 RECOMMENDED EXPOSURE SCENARIOS FOR A HUMAN HEALTH RISK

ASSESSMENT ............ ............ ............ ............ ............ . 4-13

6-1 MEAN CONSUMPTION RATES FOR RECOMMENDED EXPOSURE SCENARIOS .... 6-4

6-2 COOKING-RELATED WEIGHT LOSSES FOR VARIOUS HOME-PRODUCED

FOODS ............ ............ ............ ............ ............ ....... 6-11

6-3 EXPOSURE DURATION VALUES ............ ............ ............ ........ 6-21
Human Health Risk Assessment Protocol

Contents September 2005

LIST OF ACRONYMS

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering xv

:g Microgram

:m Micrometer

ACGIH American Conference of Governmental Industrial Hygienists

ADD Average daily dose

AEFA Average emission factor approach

AEGL Acute inhalation exposure guidelines

AERMOD American Meteorological Society/EPA Regulatory Model

Ah Aryl hydrocarbon

AHH Aryl hydrocarbon hydroxylase

AIEC Acute inhalation exposure criteria

AIHA American Industrial Hygiene Association

APCD Air pollution control device

APCS Air pollution control system

ARE Acute reference exposure

Acute REL Acute reference exposure level

ASTM American Society for Testing and Materials

atm Atmosphere

ATSDR Agency for Toxic Substances and Disease Registry

AWFCO Automatic waste feed cutoff

BaP Benzo(a)pyrene

BAF Bioaccumulation factor

BBS Bulletin board service

BCF Bioconcentration factor

BEHP Bis(2-ethylhexyl) phthalate

BIF Boiler and industrial furnace

BPIP Building profile input program check

BSAF Sediment bioaccumulation factor

Btu British thermal unit

BW Body weight

CAA Clean Air Act

CALPUFF California Puff Model

CARB California Air Resources Board

CAS Chemical Abstracts Service

CFR Code of Federal Regulations

CKD Cement kiln dust

CLP Contract Laboratory Program

cm Centimeters

COPC Compound of potential concern

CRQL Contract required quantitation limit

CSV Unspeciated chromatographical semivolatiles

CWA Clean Water Act
Human Health Risk Assessment Protocol

Contents September 2005

LIST OF ACRONYMS (contd.)

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering xvi

DEHP Diethylhexylphthalate

dL Decaliter

DNA Deoxyribonucleic acid

DNOP Di(n)octyl phthalate

DOE Department of Energy

DRE Destruction and removal efficiency

DW Dry weight of soil or plant/animal tissue 

EPACA U.S. Environmental Protection Agency Correlation Approach

EQL Estimated quantitation limit

ERPG Emergency response planning guidelines

ESP Electrostatic precipitator

FW Fresh weight (or whole/wet weight) of plant or animal tissue

g Grams

GAQM Guideline to Air Quality Models

GC Gas chromatography

GEP Good engineering practice

GRAV Unspeciated gravimetric compounds

H3TD Hierarchy of Human Health Toxicity Data

HEAST Health Effects Assessment Summary Tables

HI Hazard index

HQ Hazard quotient

IARC International Agency for Research on Cancer

IDL Instrument detection limit

IEU/BK Integrated exposure uptake/biokinetic

IPM Insoluble polystyrene microspheres

IUPAC International Union of Pure and Applied Chemistry

IRIS Integrated Risk Information System

ISC-PRIME Industrial Source Complex-Plume Rise Model Enhancements

ISCSTDFT Industrial Source Complex Short Term Draft

ISCST3 Industrial Source Complex Short Term 3

K Kelvin

kg Kilogram

LADD Lifetime average daily dose

L Liter

lb Pound

LCD Local climatological data annual summary with comparative data

m Meters

MACT Maximum achievable control technology
Human Health Risk Assessment Protocol

Contents September 2005

LIST OF ACRONYMS (contd.)

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering xvii

MDL Method detection limit

MEHP Monoethylhexyl phthalate

mg Milligram

Mg Megagram

MIR Maximum individual risk

MJ Megajoule

mL Milliliter

MPRM Meteorological processor for regulatory models

MPTER Air quality model for multiple point source gaussian dispersion algorithm with

terrain adjustments

MRL Minimum risk level

NCDC National Climatic Data Center

NC DEHNR North Carolina Department of Environment, Health, and Natural Resources

NCEA National Center for Environmental Assessment

NCP National Oil and Hazardous Substances Pollution Contingency Plan

NIOSH National Institute of Occupational Safety and Health

NRC Nuclear Regulatory Commission

NRC COT National Research Council Committee on Toxicology

NTP National Toxicology Program

NWS National Weather Service

OAQPS Office of Air Quality Planning and Standards

OEHHA Office of Environmental Health Hazard Assessment

ORD Office of Research and Development

OSHA U.S. Occupational Safety and Health Administration

OSW Office of Solid Waste

OSWER Office of Solid Waste and Emergency Response

PAH Polynuclear aromatic hydrocarbon

PCB Polychlorinated biphenyl

PCDD Polychlorinated dibenzo(p)dioxin

PCDF Polychlorinated dibenzofuran

PCRAMMET Personal computer version of the meteorological preprocessor for the old RAM

program

PDF Probability density function

pg Picogram

PIC Product of incomplete combustion

PM Particulate matter

PMD Portable monitoring device

PM10 Particulate matter less than 10 micrometers in diameter

POHC Principal organic hazardous constituent

ppb Parts per billion

ppm Parts per million

ppmv Parts per million by volume

ppt Parts per trillion
Human Health Risk Assessment Protocol

Contents September 2005

LIST OF ACRONYMS (contd.)

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering xviii

PQL Practical quantitation limit

PU Polyurethane

QA Quality assurance

QAPjP Quality assurance project plan

QC Quality control

RCRA Resource Conservation and Recovery Act

RfC Reference concentration

RfD Reference dose

RME Reasonable maximum exposure

RPF Relative potency factor

RTDM Rough terrain diffusion model

RTDMDEP Rough terrain diffusion model deposition

s Second

SAMSON Solar and Meteorological Surface Observational Network

SCAPA Subcommittee on Consequence Assessment and Protective Actions

SCRAM Support Center for Regulatory Air Models

SF Slope factor

SLERA Screening level ecological risk assessment

SOCMI Synthetic Organic Chemical Manufacturing Industries

SQL Sample quantitation limit

SRA Screening ranges approach

SVOC Semivolatile organic compound

SW-846 U.S. Environmental Protection Agency Test Methods for Evaluating Solid Waste

TCDD Tetrachlorodibenzo(p)dioxin

TDA Toluenediamine

TDI Toluene diisocyanate

TEELs Temporary emergency exposure limits

TEF Toxicity equivalent factor

TEQ Toxicity equivalent quotient

TG Terrain grid

TIC Tentatively identified compound

TLV Threshold limit value

TOC Total organic carbon

TOE Total organic emissions

TSD Treatment, storage, and disposal

TTN Technology transfer network

TWA Time-weighted average

U/BK Uptake/biokinetic

USCA Unit-Specific Correlation Approach

USDA U.S. Department of Agriculture
Human Health Risk Assessment Protocol

Contents September 2005

LIST OF ACRONYMS (contd.)

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering xix

U.S. EPA U.S. Environmental Protection Agency

USGS U.S. Geological Survey

USLE Universal soil loss equation

UTM Universal transverse mercator

VOC Volatile organic compound

WHO World Health Organization
Human Health Risk Assessment Protocol

Contents September 2005

INDEXED LIST OF VARIABLES

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering xx

Variable Units Definition

[Sections]/

Equations

( unitless Empirical constant used to generate Rp

8z

unitless Dimensionless viscous sublayer thickness 5-41B; 5-42B; B-4-

20; B-4-21

:a

g/cm-s Viscosity of air 5-42B; B-4-21

:w

g/cm-s Viscosity of water corresponding to water

temperature

5-41B; B-4-20

Da

g/cm3 or g/m3 Density of air 5-18; 5-41-B; 5-

42B; B-2-8; B-3-8;

B-4-20; B-4-21

Ds

kg/L Bed sediment density used to generate 2bs

Dsoil g/cm3Solids particle density 5-7a; B-1-6; B-2-6;

B-3-6; B-4-6

Dw

g/cm3 Density of water corresponding to water

temperature

5-41B; B-4-20

2 unitless Temperature correction factor 5-40; B-4-19

2bs unitless Bed sediment porosity 5-36B; 5-37; 5-47;

B-4-16; B-4-25

2sw mL water/cm3

soil

Soil volumetric water content [5.2.4.4]; 5-4; 5-5A;

5-7A; 5-7C; 5-32; 5-

33; B-1-3; B-1-4; B1-5; B-1-6; B-2-3;

B-2-4; B-2-5; B-2-6;

B-3-3; B-3-4; B-3-5;

B-3-6; B-4-3; B-4-4;

B-4-5; B-4-6; B-4-

10; B-4-11

2v

cm3

/cm3

Soil void fraction 5-7B; 5-7C

a unitless Empirical intercept coefficient 5-34; B-4-14

Abeef mg COPC/kg FW

tissue

Concentration of COPC in beef [5.4.4]; 5-22; B-3-

10

Achicken mg COPC/kg FW

tissue

Concentration of COPC in chicken meat [5.6.1]; 5-26; B-3-

14

ADD mg COPC/kg

BW-day

Average daily dose 6-1

ADDinfant pg COPC/kg BW

infant/day

Average daily dose for infant exposed to

contaminated breast milk

C-3-2

ADDmat pg COPC/kg BW

mother/day

Average daily dose (mother)

AEF kg/hr-source Applicable average emission factor for the

equipment type

Aegg mg COPC/kg FW

tissue

Concentration of COPC in eggs [5.6.1]; C-1-3

Ah m

2 Area planted used to estimate Yp

Ahi m

2 Area planted to ith crop see Ah

AI m

2

Impervious watershed area receiving COPC

deposition

5-31; 5-32; 5-33; 5-

36C; B-4-9; B-4-10
Human Health Risk Assessment Protocol

Contents September 2005

INDEXED LIST OF VARIABLES (contd.)

Variable Units Definition

[Sections]/

Equations

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering xxi

AL m

2 Total watershed area receiving COPC deposition 5-32; 5-33; 5-34; 5-

36C; 5-43; B-4-10;

B-4-11;B-4-14; B-4-

22

Amilk mg COPC/kg FW

tissue

Concentration of COPC in milk [5.4.5]; 5-24; B-3-

11

Apork mg COPC/kg FW

tissue

Concentration of COPC in pork [5.5.1]; 5-25; B-3-

12

AT days Averaging time [6.5]; 6-1; C-1-7; C1-8; C-3-1

AW m

2 Water body surface area [4.1.2]; 5-29; 5-30;

5-35; 5-36C; 5-43;

B-4-8; B-4-12; B-4-

15; B-4-22

b unitless Empirical slope coefficient 5-34; B-4-14

Babeef day/kg FW tissue Biotransfer factor for beef 5-22; [A2.5.1]; A-2-

16; B-3-10

Bachicken day/kg FW tissue Biotransfer factor for chicken 5-26; [A2.5.3]; B-3-

14

Baegg

day/kg FW tissue Biotransfer factor for eggs 5-26; [A2.5.3]; A-2-

18; B-3-13

BAFfish L/kg FW tissue Bioaccumulation factor for fish 5-49; [A2.5.4]; B-4-

27

Bamilk day/kg FW tissue Biotransfer factor for milk 5-24; [A2.5.1]; A-2-

17; B-3-11

Bapork day/kg FW tissue Biotransfer factor for pork 5-25; [A2.5.2]; B-3-

12

BCFfish unitless

(mg COPC/kg

FW tissue)/(mg

COPC/kg

dissolved water)

Bioconcentration factor for fish 5-48; [A2.5.4]; B-4-

26

BD g soil/cm3 soil Soil bulk density [5.2.4.2]; 5-4; 5-5A;

5-7A; 5-11; 5-32; 5-

33; B-1-1; B-1-3; B1-4; B-1-5; B-1-6;

B-2-1; B-2-3; B-2-4;

B-2-5; B-2-6; B-3-1;

B-3-3; B-3-4; B-3-5;

B-3-6; B-4-1; B-4-3;

B-4-4; B-4-5; B-4-6;

B-4-10; B-4-11

Brag

unitless Plant-soil bioconcentration factor for

aboveground produce

5-20A; [A2.4.3]; A2-14A; B-2-9

Brforage unitless

(:g COPC/g DW

plant)/(:g

COPC/g soil)

Plant-soil bioconcentration factor for forage 5-20A; [A2.4.3]; A2-14B; B-3-9
Human Health Risk Assessment Protocol

Contents September 2005

INDEXED LIST OF VARIABLES (contd.)

Variable Units Definition

[Sections]/

Equations

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering xxii

Brgrain unitless

(:g COPC/g DW

plant)/(:g

COPC/g soil)

Plant-soil bioconcentration factor for COPC in

grain

5-20A; [A2.4.3]; A2-14B; B-3-9

Brrootveg unitless

(:g COPC/g FW

plant)/(:g

COPC/g soil)

Plant-soil bioconcentration factor for COPC in

belowground produce

5-20B; [A2.4.2]; A2-13; B-2-10

Bs unitless Soil bioavailability factor [5.4.4.6]; 5-22; 5-

24; 5-25; 5-26; B-3-

10; B-3-11; B-3-12;

B-3-13; B-3-14

BSAF unitless Biota-to-sediment accumulation factor [5.75]; 5-50;

[A2.5.4.3]; B-4-28

Bvag

unitless

(mg COPC/kg

lipid tissue)/(mg

COPC/kg

sediment)

COPC air-to-plant biotransfer factor for

aboveground produce (:g COPC/g DW

plant)/(:g COPC/g air)—unitless

5-18; [A2.4.4]; A-2-

15A&B; B-2-8

Bvforage/silage unitless

(:g COPC/g DW

plant)/(:g

COPC/g air)

Air-to-plant biotransfer factor for forage and

silage

5-18; [A2.4.4]; A-2-

15A&B; B-3-8

C unitless USLE cover management factor 5-33A; B-4-13

Ca

:g/m3 Total COPC air concentration [6.1]; 7-1; 7-5; B-5-

1; C-2-1; C-2-2; C3-1

Cacute Acute air concentration (μg/m3

) 7-9; B-6-1; C-4-1

Cancer Riski unitless Individual lifetime risk through indirect exposure

to COPC carcinogen i

7-3; C-1-7

Cancer

Riskinh(i)

unitless Individual lifetime cancer risk through direct

inhalation of COPC carcinogen i

C-2-1

CBS g sediment/cm3

water

Bed sediment concentration (or sediment bulk

density)

5-36A; 5-37; 5-43;

5-47; B-4-16; B-4-

22; B-4-25

Cd

unitless Drag coefficient 5-41B; 5-42B; B-4-

20; 

Cdw mg COPC/L

water

Dissolved phase water concentration [5.7.4.9]; 5-46; 5-

48; 5-49; B-4-24; B4-26; B-4-27; C-1-5

Cfish mg COPC/kg FW

tissue

Concentration of COPC in fish [5.7.5]; 5-48; 5-49;

5-50; B-4-28; C-1-4

Chv μg-s/g-m3 Unitized hourly air concentration from vapor

phase

B-6-1

Chp μg-s/g-m3 Unitized hourly air concentration from particle

phase

B-6-1

Chpb μg-s/g-m3 Unitized hourly air concentration from particlebound phase
Human Health Risk Assessment Protocol

Contents September 2005

INDEXED LIST OF VARIABLES (contd.)

Variable Units Definition

[Sections]/

Equations

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering xxiii

Cs mg COPC/kg soil Average soil concentration over exposure

duration

[5.2.1]; 5-1C&D; 5-

20A&B; 5-22; 5-24;

5-25; 5-26; 5-32; 5-

33; B-1-1; B-2-1; B2-9; B-2-10; B-3-1;

B-3-9; B-3-10; B-3-

11; B-3-12; B-3-13;

B-3-14; B-4-1; B-4-

10; B-4-11

Csb mg COPC/kg

sediment

Concentration sorbed to bed sediment [5.7.4.10]; 5-47; 5-

50; B-4-25; B-4-28

CSF (mg/kg-day)-1 Cancer slope factor 7-2; [A2.6.2]; C-1-7

CstD mg COPC/kg soil Soil concentration at time tD [5.2.1]; 5-1E; B-1-1;

B-2-1; B-3-1; B-4-1;

C-3-1

Cwctot mg COPC/L

water column

Total COPC concentration in water column [5.7.4.8]; 5-45; 5-

46; B-4-23; B-4-24

Cwtot g COPC/m3 water

body (or mg/L)

Total water body COPC concentration including

water column and bed sediment

[5.7.4]; 5-35; 5-45;

5-47; B-4-15; B-4-

23; B-4-25

Cyp :g-s/g-m3 Unitized yearly average air concentration from

particle phase

[3.8.3.2]; B-5-1

Cyv :g-s/g-m3 Unitized yearly average air concentration from

vapor phase

[3.8.3.1]; 5-18; B-2-

8; B-3-8; B-5-1

Cywv :g-s/g-m3 Unitized yearly (water body and watershed)

average air concentration from vapor phase

[3.8.3.1]; 5-30; B-4-

12

Da

 cm2

/s Diffusivity of COPC in air 5-7A; 5-42B;

[A2.3.5]; A-2-2A;

B-1-6; B-2-6; B-3-6;

B-4-6; B-4-21

dbs m Depth of upper benthic sediment layer 5-35; 5-36A; 5-43;

5-45; 5-47; B-4-15;

B-4-16; B-4-18; B4-22; B-4-23; B-4-

25

Dmean Mean particle size density for a particular filter

cut size

3-1

Ds mg COPC/kg

soil-yr

Deposition term [5.2.3]; 5-1C, D&E;

5-36C; B-1-1; B-2-

1; B-3-1; B-4-1

dwc m Depth of water column [4.1.2]; 5-35; 5-

36A; 5-45; 5-47; B4-15; B-4-16; B-4-

18; B-4-23; B-4-25

Dw

cm2/s Diffusivity of COPC in water 5-41A&B; [A2.3.5];

A-2-2B; B-4-20
Human Health Risk Assessment Protocol

Contents September 2005

INDEXED LIST OF VARIABLES (contd.)

Variable Units Definition

[Sections]/

Equations

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering xxiv

Dydp s/m2

-yr Unitized yearly average dry deposition from

particle phase

[3.8.3.2]; 5-11; 5-

14; B-1-1; B-2-1; B2-7; B-3-1; B-3-7

Dydv s/m2

-yr Unitized yearly average dry deposition from

vapor phase

[3.8.3.2]; 5-11; 5-

14; B-1-1; B-2-1; B2-7; B-3-1; B-3-7

Dytwp s/m2

-yr Unitized yearly (water body or watershed)

average total (wet and dry) deposition from

particle phase

[3.8.3.2]; 5-29; 5-

31; B-4-1; B-4-8; B4-9

Dywp s/m2

-yr Unitized yearly average wet deposition from

particle phase

[3.8.3.2]; 5-11; 5-

14; B-1-1; B-2-1; B2-7; B-3-1; B-3-7

Dywv s/m2

-yr Unitized yearly average wet deposition from

vapor phase

[3.8.3.2]; 5-11; 5-

14; B-1-1; B-2-1; B2-7; B-3-1; B-3-7

Dytwv s/m2

-yr Unitized yearly (water body or watershed)

average total (wet and dry) deposition from

vapor phase

[3.8.3.2]; 5-29; 5-

31; B-4-1; B-4-8; B4-9

dz m Total water body depth 5-36A; 5-39; 5-41A;

B-4-16; B-4-18; B4-20

ED yr Exposure duration 6-1; C-1-7; C-1-8;

C-3-1; C-3-2

EF days/yr Exposure frequency 6-1; C-1-7; C-1-8;

C-3-1

ER unitless Soil enrichment ratio 5-33; B-1-3; B-2-3; 

B-3-3; B-4-3; B-4-

11

Ev

cm/yr Average annual evapotranspiration 5-5A; B-1-5; B-2-5;

B-3-5; B-4-5

fbs unitless Fraction of total water body COPC concentration

in benthic sediment

[5.7.4.1]; 5-36B; 5-

38; 5-47; B-4-16; B4-17; B-4-25

Fi

unitless Fraction of plant type i grown on contaminated

soil and eaten by the animal

5-22; 5-24; 5-25; 5-

26; B-3-10; B-3-11;

B-3-12; B-3-13B-3-

14

flipid unitless Fish lipid content 5-50; B-4-28

Fw unitless Fraction of COPC wet deposition that adheres to

plant surfaces

5-14; B-2-7; B-3-7

fwc

unitless Fraction of total water body COPC concentration

in the water column

[5.7.4.1]; 5-35; 5-

36A; 5-38; 5-45; B4-15; B-4-16; B-4-

17; B-4-23
Human Health Risk Assessment Protocol

Contents September 2005

INDEXED LIST OF VARIABLES (contd.)

Variable Units Definition

[Sections]/

Equations

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering xxv

Fv unitless Fraction of COPC air concentration in vapor

phase

[3.2]; 5-11; 5-14; 5-

18; 5-29; 5-30; 5-31;

B-1-1; B-2-1; B-2-7;

B-2-8; B-3-1; B-3-7;

B-3-8; B-4-1; B-4-8;

B-4-9; B-4-12; B-5-

1; B-6-1

H atm-m3

/mol Henry’s Law constant 5-7A; 5-30; 5-40;

[A2.3.4]; A-2-1; B1-6; B-2-6; B-3-6;

B-4-6; B-4-12; B-4-

19

HI unitless Hazard index 7-6; 7-7; C-1-11

HIj unitless Hazard index for exposure pathway j C-1-10

HQ unitless Hazard quotient 7-5; C-1-8

HQi unitless Hazard quotient for COPC i 7-6

HQinh(i) unitless Hazard quotient for direct inhalation of COPC C-2-2; C-2-4

I cm/yr Average annual irrigation 5-5A; B-1-5; B-2-5;

B-3-5; B-4-5

Ii mg/day Daily intake of COPC (i) from animal tissue [6.2.2]; C-1-3

k unitless von Karman’s constant 5-41B; 5-42B; B-4-

20; B-4-21

K ton/acre USLE erodibility factor 5-33A; B-4-13

kb yrG1 Benthic burial rate constant [5.7.4.7]; 5-38; 5-

43; 5-44; B-4-17

Kdbs cm3 water/g

bottom sediment

Bed sediment/sediment pore water partition

coefficient

5-36B; 5-47;

[A2.3.8]; A-2-8C;

B-4-16; B-4-25; 

Kdij unitless Partition coefficient for COPC i associated with

sorbing material j

Kds cm3 water/g soil Soil-water partition coefficient 5-4; 5-5A; 5-7A; 5-

20B; 5-32; 5-33;

[A2.3.8]; A-2-8A;

B-1-3; B-1-4; B-1-5;

B-1-6; B-2-3; B-2-4;

B-2-5; B-2-6; B-2-

10; B-3-3; B-3-4; B3-5; B-3-6; B-4-3;

B-4-4; B-4-5; B-4-6;

B-4-10; B-4-11

Kdsw L water/kg

suspended

sediment

Suspended sediments/surface water partition

coefficient

5-36A; 5-39; 5-46;

[A2.3.8]; A-2-8B;

B-4-16; B-4-18; B4-24

KG m/y Gas phase transfer coefficient [5.7.4.6]; 5-40; 5-

42A&B; B-4-19; B4-21
Human Health Risk Assessment Protocol

Contents September 2005

INDEXED LIST OF VARIABLES (contd.)

Variable Units Definition

[Sections]/

Equations

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Center for Combustion Science and Engineering xxvi

KL m/yr Liquid phase transfer coefficient [5.7.4.5]; 5-40; 5-

41A&B; B-4-19; B4-20

Koc mL water/g soil Soil organic carbon-water partition coefficient [A2.3.7]; A-2-4; A2-5; A-2-6; A-2-7; 

Kow

unitless

(mg COPC/L

octanol)/(mg

COPC/L octanol)

Octanol-water partition coefficient [A2.3.6]; A-2-4; A2-5; A-2-6; A-2-7;

A-2-12A&B; A-2-

14A&B; A-2-15A;

A-2-16; A-2-17; A2-19

kp yrG1

Plant surface loss coefficient [5.3.1.2]; 5-14; B-2-

7; B-3-7

ks yrG1 COPC soil loss constant due to all processes [5.2.2]; 5-1C, D&E;

B-1-1; B-1-2; B-2-

1; B-2-2; B-3-1; B3-2; B-4-1; B-4-2; 

kse yrG1 COPC loss constant due to soil erosion [5.2.2.2]; 5-2A; B1-2; B-1-3; B-2-2;

B-2-3; B-3-2; B-3-3;

B-4-2; B-4-3 

ksg yrG1 COPC loss constant due to biotic and abiotic

degradation

[5.2.2.1]; 5-2A;

[A2.3.9]; A-2-9; B1-2; ; B-2-2; B-3-2;

B-4-2

ksl yrG1 COPC loss constant due to leaching [5.2.2.4]; 5-2A; 5-

5A; B-1-2; B-1-5; 

B-2-2; B-2-5; B-3-

2; B-3-5; B-4-2; B4-5

ksr yrG1 COPC loss constant due to surface runoff [5.2.2.3]; 5-2A; 5-4;

B-1-2; B-1-4; B-2-2;

B-2-4; B-3-2; B-3-4;

B-4-2; B-4-4

ksv yrG1 COPC loss constant due to volatilization [5.2.2.5]; 5-2A; 5-

7A; B-1-2; B-1-6;

B-2-2; B-2-6; B-3-2;

B-3-6; B-4-2; B-4-6

kv

yrG1 Water column volatilization rate constant [5.7.4.3]; 5-38; 5-

39; B-4-17; B-4-18

Kv m/yr Overall COPC transfer rate coefficient [5.7.4.4]; 5-30; 5-

39; 5-40; B-4-12; B4-18; B-4-19

kwt yrG1 Overall total water body dissipation rate constant [5.7.4.2]; 5-35; 5-

38; B-4-15;B-4-17

L m Monin-Obukhov Length [3.5.1]

LADD mg COPC/kg

BW-day

Lifetime average daily dose 7-2
Human Health Risk Assessment Protocol

Contents September 2005

INDEXED LIST OF VARIABLES (contd.)

Variable Units Definition

[Sections]/

Equations

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Center for Combustion Science and Engineering xxvii

LDEP g/yr Total (wet and dry) particle phase and vapor

phase COPC direct deposition load to water body

[5.7.1.1]; 5-28; 5-

29; B-4-7; B-4-8

Ldif g/yr Vapor phase COPC diffusion load to water body [5.7.1.2]; 5-28; 5-

30; B-4-7; B-4-12

leak rate kg/hr Emission rate from the individual item of

equipment

[2.2.6.1]

LE

g/yr Soil erosion load [5.7.1.5]; 5-28; 5-

33; B-4-7; B-4-11

LR

g/yr Runoff load from pervious surfaces [5.7.1.4]; 5-28; 5-

32; B-4-7; B-4-10

LRI g/yr Runoff load from impervious surfaces [5.7.1.3]; 5-28; 5-

31; B-4-7; B-4-9

LT

g/yr Total COPC load to the water body including

deposition, runoff, and erosion

[5.7.1]; 5-28; B-4-7;

B-4-15

LS unitless USLE length-slope factor 5-33A; B-4-13

Mskin g Mass of a thin (skin) layer of below ground

vegetable

5-19

Mvegetab le g Mass of the entire vegetable 5-19

MF unitless Metabolism factor [5.4.4.7]; 5-22; 5-

24; 5-25; B-3-10; B3-11; B-3-12

MW g/mole Molecular weight [A2.3.1]; A-2-1

OCsed unitless Fraction of organic carbon in bottom sediment 5-50; B-4-28

p°L

atm Liquid phase vapor pressure of chemical A-2-11

p°S

atm Solid phase vapor pressure of chemical A-2-11

P cm/yr Average annual precipitation 5-5A; B-1-5; B-2-5;

B-3-5; B-4-5

PF unitless USLE supporting practice factor 5-33A; B-4-13

Pd mg COPC/kg

DW

Aboveground exposed produce concentration

due to direct (wet and dry) deposition onto plant

surfaces

[5.3.1]; 5-14; 5-23;

B-2-7; B-3-7; C-1-2

Pi mg/kg DW Total COPC concentration in plant type i

ingested by the animal

[5.4.4.3]; 5-22; 5-

23; 5-24; 5-25; 5-

26; 5-27; B-3-10; B3-11; B-3-12; B-3-

13; B-3-14

Pr mg COPC/kg

DW

Aboveground exposed and protected produce

concentration due to root uptake

[5.3.3]; 5-20A&B;

5-23; 5-27; B-2-9;

B-3-9; C-1-2

Prbg mg COPC/kg

DW

Belowground produce concentration due to root

uptake

B-2-10; C-1-2

Pv mg COPC/kg

DW

Concentration of COPC in plant due to air-toplant transfer

[5.3.2]; 5-18; 5-23;

B-2-8; B-3-8; C-1-2
Human Health Risk Assessment Protocol

Contents September 2005

INDEXED LIST OF VARIABLES (contd.)

Variable Units Definition

[Sections]/

Equations

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Center for Combustion Science and Engineering xxviii

Q g/s COPC emission rate 5-11; 5-14; 5-18; 5-

29; 5-30; 5-31; B-1-

1; B-2-1; B-2-7; B2-8; B-3-1; B-3-7;

B-3-8; B-4-1; B-4-8;

B-4-9; B-4-12; B-5-

1; B-6-1

Qi

g/s Emission rate of COPC (i)

Qi(adj) g/s Adjusted emission rate of COPC (i)

Qcpi(adj) g/s Adjusted emission rate of Table A-1

carcinogenic COPC (i)

Qcpi

g/s Emission rate of Table A-1 carcinogenic COPC

(i)

Qf W/m

2 Anthropogenic heat flux [3.5.7]

Qpi

kg DW/day Quantity of plant type i ingested by the animal

each day

[5.4.4.2]; 5-22; 5-

24; 5-25; 5-26; B-3-

10; B-3-11; B-3-12;

B-3-13; B-3-14

Qs kg/day Quantity of soil ingested by the animal each day

Q* W/m

2 Net radiation absorbed [3.5.8]

r unitless Interception fraction—the fraction of material in

rain intercepted by vegetation and initially

retained

R atm-m3

/mol-K Universal gas constant 5-7A; 5-30; 5-40; A2-11; B-1-6; B-2-6;

B-3-6; B-4-6; B-4-

12; B-4-19

RCF (μg COPC/g DW

plant)/(μg

COPC/mL soil

water)

Root concentration factor 5-20B; [A2.4.1]; A2-12A&B; A-2-13;

B-2-10

RO cm/yr Average annual surface runoff from pervious

surfaces

5-4; 5-5A; 5-32; B1-4; B-1-5; B-2-4;

B-2-5; B-3-4; B-3-5;

B-4-4; B-4-5; B-4-

10

REL California EPA Air Toxics Hot Spots Program

acute reference exposure levels

[7.4.2]

RF yrG1 USLE rainfall (or erosivity) factor 5-33A; B-4-13

RfC Inhalation reference dose 7-5; [A2.6.1]; C-2-2

RfD mg COPC/kg

body weight/day

Oral reference dose 7-5; [A2.6.1]; C-1-8

Rp unitless Interception fraction of the edible portion of

plant

[5.3.11]; 5-14; B-2-

7; B-3-7

S mg COPC/L

water

Solubility of COPC in water [A2.3.3]; A-2-1
Human Health Risk Assessment Protocol

Contents September 2005

INDEXED LIST OF VARIABLES (contd.)

Variable Units Definition

[Sections]/

Equations

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Center for Combustion Science and Engineering xxix

SD unitless Sediment delivery ratio [5.7.3]; 5-33; 5-34;

5-36C; 5-43; B-1-3;

B-2-3; B-3-3; B-4-3

)Sf unitless Entropy of fusion [)Sf /R = 6.79] A-2-11

SF (mg/kg-day)-1 Slope factor

ST cm2

/cm3 air Whitby’s average surface area of particulates

(aerosols)

A-2-11

Ta K Ambient air temperature [3.4.2]; 5-7A; A-2-

11; B-1-6; B-2-6; B3-6; B-4-6

T1 yr Time period at the beginning of combustion 5-1D; B-1-1; B-2-1;

B-3-1; B-4-1

T2 yr Length of exposure duration 5-1C&D; B-1-1; B2-1; B-3-1; B-4-1

tD yr Time period over which deposition occurs (time

period of combustion)

5-1C, D&E; B-1-1;

B-2-1; B-3-1; B-4-1

Tm K Melting point of chemical [A2.3.2]

Tp yr Length of plant exposure to deposition per

harvest of edible portion of plant

[5.3.1.3]; 5-14; 5-

16; 5-21; B-2-7; B3-7

tpi yr Length of plant’s exposure to deposition per

harvest of the edible portion of the i th plant

group

5-13

Total Cancer

Risk

unitless Individual lifetime cancer risk through indirect

exposure to all COPC carcinogens

7-3; 7-4; C-1-9

Total Cancer

Riskinh

unitless) Total individual lifetime cancer risk through

direct inhalation of all COPC carcinogens

C-2-3

TSS mg/L Total suspended solids concentration 5-36A; 5-36C; 5-39;

5-43; 5-46; B-4-16;

B-4-18; B-4-22; B4-24

Twk K Water body temperature 5-30; 5-40; B-4-12;

B-4-19; 

t1/2 days Half-time of COPC 5-15

u m/s Current velocity 5-41A; B-4-20

URF :g/m3 Unit risk factor 7-1; C-2-1

Vfx m3

/yr Average volumetric flow rate through water body 5-35; 5-36C; 5-43;

B-4-15; B-4-22; 

VGag unitless Empirical correction factor for aboveground

produce (forage and silage)

[5.3.2.1; 5.4.2.1]; 5-

18; B-2-8; B-3-8

VGrootveg unitless Empirical correction factor for below ground

produce

5-19; 5-20B; B-2-10

Vp atm Vapor pressure of COPC [A2.3.3]; A-2-1

W m/s Average annual wind speed [3.4.1]; 5-41B; 5-

42B; B-4-20; B-4-

21

Wb m/yr Rate of burial 5-44
Human Health Risk Assessment Protocol

Contents September 2005

INDEXED LIST OF VARIABLES (contd.)

Variable Units Definition

[Sections]/

Equations

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Center for Combustion Science and Engineering xxx

Xe

kg/m2-yr Unit soil loss [5.7.2]; 5-33; 5-

33A; 5-36C; 5-43;

B-1-3; B-2-3; B-3-3;

B-4-3; B-4-11; B-4-

13; B-4-22

Yh kg DW Dry harvest yield

Yhi

kg DW Harvest yield of ith crop

Yp kg DW/m2 Yield or standing crop biomass of edible portion

of plant (productivity)

[5.3.1.4; 5.4.1.4]; 5-

14; B-2-7; B-3-7

Ypi

kg DW/m2 Yield or standing crop biomass of the edible

portion of the plant (productivity) 

5-13

Zs

cm Soil mixing zone depth [5.2.4.1]; 5-4; 5-5A;

5-7A&B; 5-11; B-1-

1; B-1-3; B-1-4; B1-5; B-1-6; B-2-1;

B-2-3; B-2-4; B-2-5;

B-2-6; B-3-1; B-3-3;

B-3-4; B-3-5; B-3-6;

B-4-1; B-4-3; B-4-4;

B-4-5; B-4-6

0.01 kg cm2

/mg-m2 Units conversion factor

10-6 g/:g Units conversion factor

10-6 kg/mg Units conversion factor

0.31536 m-g-s/cm-:g-yr Units conversion factor

365 days/yr Units conversion factor

907.18 kg/ton Units conversion factor

0.1 g-kg/cm2

-m2 Units conversion factor

0.001 g/mg Units conversion factor

100 mg-cm2

/kg-cm2 Units conversion factor

1000 mg/g Units conversion factor

4047 m

2

/acre Units conversion factor

1 × 103 g/kg Units conversion factor

3.1536 × 107s/yr Units conversion factor
U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering 1-1

Chapter 1: INTRODUCTION

What’s Covered in Chapter 1:

1. 1 Objective and Document Organization

1. 2 Background

1. 3 Using this Document 

1. 4 Primary Reference Documents

1. 5 Risk Nomenclature

PLEASE NOTE: for the purposes of this guidance, “we” refers to the U.S. EPA OSW. 

The HHRAP is written for the benefit of a varied audience, including risk assessors,

regulators, risk managers, and community relations personnel. However, the “you” to

which we speak is the performer of a risk assessment: the person (or persons) who will

actually put the recommended methods into practice.

1.1 OBJECTIVE AND DOCUMENT ORGANIZATION

The U.S. Environmental Protection Agency’s (“U.S. EPA” or “the Agency”) Office of Solid Waste

(OSW) has developed an approach for conducting multi-pathway, site-specific human health risk

assessments on Resource Conservation and Recovery Act (RCRA) hazardous waste combustors. The

approach, also known as the Human Health Risk Assessment Protocol (“HHRAP” or “protocol”) can be

used where the permitting authority determines such risk assessments are necessary. The HHRAP

replaces an earlier Peer Review Draft published in July 1998.

Our primary objective in developing the protocol was to offer a user-friendly approach to performing sitespecific combustion risk assessments. We wanted to develop a guidance document that would: 

• be useful to a diverse group of users: risk assessors, permit writers, risk managers, and

community relations personnel;
Human Health Risk Assessment Protocol

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• provide a logical method for doing risk assessments of facilities that burn hazardous waste; 

• completely explain the reason for each recommended procedure and parameter value;

• provide a comprehensive enough collection of default input parameters to conduct a risk

assessment. The collection would also be flexible enough to accommodate regional or

site-specific information; and finally

• make sufficient tools available to produce transparent, defensible, and realistic results. When

coupled with an ecological assessment (U.S. EPA 1999a), these tools would provide critical

information often needed by risk managers when faced with the decision of permitting a

hazardous waste combustion facility. 

The HHRAP brings together information from other risk assessment guidance and method documents

prepared by U.S. EPA and state environmental agencies. It also contains the latest advancements in risk

assessment science, as well as experience EPA has gained through conducting and reviewing combustion

risk assessments. This version of the protocol also addresses the comments put forward by the public and

external scientific peer reviewers regarding earlier drafts of the HHRAP.

The first volume of the HHRAP contains the main body of the document, providing a detailed

explanation of a risk assessment approach that we recommend you consider when conducting a risk

assessment. The second volume contains the appendices, including:

Appendix A: a collection of chemical-specific information which might be of interest -

• A-1 - a compilation (from various EPA sources) of compounds of potential

interest;

• A-2 - Compound-specific parameter value information. Details the sources of, or

equations used to calculate, parameter values used in fate & transport-,

biotransfer-, exposure-, and toxicity-related equations. Parameter values

themselves are found in a companion database to the HHRAP, which is also

available for download.

Appendix B: Equations and recommended default variable values for estimating media

concentrations; and

Appendix C: Equations and recommended default variable values for estimating potential cancer

risk and non-cancer health effects.
Human Health Risk Assessment Protocol

Chapter 1: INTRODUCTION September 2005

1

 This section summarizes the historical context of regulatory authority and associated policy regarding hazardous

waste combustion site-specific risk assessment under the RCRA program. This discussion is not intended to update, revise or

articulate new guidance or policy. Nor is it intended to update, revise or provide any new interpretations of any statutory or

regulatory authority, including those relevant to the RCRA 3005(c)(3) “omnibus authority”. In addition, it is not intended to

reopen for consideration any statutory or regulatory interpretations of other related guidance documents, or the MACT rule (64

FR 52828).

2 When combustion sources demonstrate compliance with the Part 63, Subpart EEE MACT standards, they may

request that certain RCRA permit conditions (e.g., those based on the national performance standards) be removed from their

RCRA permit, because they are no longer applicable, through a class 1 permit modification request with prior agency approval. 

In some cases, RCRA performance standards may be retained in the RCRA permit if they are more stringent than the relevant

MACT standard.

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering 1-3

Please Note: Although these guidelines address many types of situations encountered in

the field, they cannot encompass every potential situation. You should ensure that the

recommendations in this guidance are appropriate for the facility, based on site-specific

information and/or circumstances. 

This protocol is a “snapshot” of current risk assessment science, and we encourage you to evaluate

updates and alternatives to the recommended parameters (e.g., toxicological benchmarks; exposure

factors) when they become available. If you use alternative values, however, keep in mind how changes

in one parameter may affect other parameter values and/or calculations. We may revise the protocol in

the future if any of the following become available:

• new research in risk assessment science and/or the combustion field; 

• new information gathered while conducting site-specific risk assessments; and 

• new initiatives introduced by the Agency. 

These types of changes are inevitable in this evolving and highly technical field. 

1.2 BACKGROUND1

Hazardous waste combustors are required to meet RCRA national performance standards and obtain a

permit under 40 CFR Part 264, Subpart O; Part 266, Subpart H; and Part 270.2

 In addition,

Section 3005(c)(3) of RCRA [codified at 270.32(b)(2)] requires that each permit contain the terms and

conditions that the permitting authority considers necessary to protect human health and the environment. 

This is commonly referred to as the “omnibus authority.” The omnibus authority gives the Agency both
Human Health Risk Assessment Protocol

Chapter 1: INTRODUCTION September 2005

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the authority and the responsibility to set up site-specific RCRA permit conditions as necessary to “be

protective of human health and the environment.” These permit conditions are intended to supplement,

not replace those conditions that are already required under the national performance standards [See

Federal Register 1999 (MACT Rule)]. 

The RCRA national performance standards for incinerators were published in 1981 (40 CFR Part 264,

Subpart O) and for boilers and industrial furnaces in 1991 (40 CFR Part 266, Subpart H). Since then,

however, new information on indirect exposure pathways and non-dioxin products of incomplete

combustion (PICs) suggests that these standards may not fully address all potentially significant risks. 

For example the RCRA national standards were based on estimates of risk only from direct exposure to

(i.e. inhaling) stack emissions. New information suggests risks from indirect exposures (e.g. ingesting

contaminated soil, food, or water) are also important (Federal Register 1999). Bioaccumulation tends to

concentrate some chemicals as they migrate through the environment. These higher concentrations can

lead to exposures and risks of concern. For example, Fradkin et al. (1988) linked elevated levels of

chemical pollutants in soils, lake sediments, and cow’s milk to atmospheric transport and deposition of

pollutants from combustion sources. Also, the 1994 Draft Health Reassessment of Dioxin-Like

Compounds (U.S. EPA 1994a), and the 1997 Mercury Study Report to Congress (U.S. EPA 1997c),

indicate that indirect exposure pathways can lead to significant risks. 

Indirect exposure pathways weren’t directly taken into account by the 1981 and 1991 hazardous waste

combustion standards. The regulations also didn’t take into account the uncertainty surrounding the types

and quantities of non-dioxin products of incomplete combustion (non-dioxin PICs) or any potential risks

posed by these compounds. 

To address these concerns, the Agency issued the Hazardous Waste Minimization and Combustion

Strategy in 1994. This strategy recommended conducting a site-specific risk assessment for each

combustion facility seeking a RCRA permit. Permitting authorities could use the results of an assessment

to determine, on a case-by-case basis, if a combustor operating in accordance with the performance
Human Health Risk Assessment Protocol

Chapter 1: INTRODUCTION September 2005

3

 The standards for Phase 1 sources (incinerators, cement kilns, and lightweight aggregate kilns) are

referred to as Replacement Standards. The Replacement Standards replace the February 13, 2002 Interim Standards

that were developed in response to a court decision to vacate challenged portions of the 1999 Phase 1 MACT final

standards. Thus, the 2005 final rule establishes MACT standards for both Phase 1 and Phase 2 (boilers and

industrial furnaces) sources.

U.S. EPA Region 6 U.S. EPA

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Center for Combustion Science and Engineering 1-5

standards is protective of human health and the environment. If the permitting authority finds that the

combustor operating in accordance with the performance standards is not protective of human health and

the environment, the permitting authority would invoke the “omnibus authority” and either add additional

conditions to the RCRA permit, or deny the RCRA permit. The permitting authority must explain the

reasons for any additional permit conditions in the administrative record of the facility (Federal Register

1999).

In 1999 the Agency updated its earlier site-specific risk assessment recommendation, to account for the

Phase 1 Maximum Achievable Control Technology (MACT) standards for hazardous waste incinerators,

cement kilns, and lightweight aggregate kilns (see 64 FR 52828). While the Phase 1 MACT standards

provide additional protection, we recognize that there may continue to be circumstances for which sitespecific risk assessments are appropriate. For example, a site-specific risk assessment might be

appropriate if there is reason to believe that operating in accordance with Phase 1 MACT standards alone

may not be protective of human health and the environment. So, in the MACT standards rulemaking, we

recommend that the permitting authority evaluate the need for a site-specific risk assessment on a caseby-case basis. For hazardous waste combustors not subject to the Phase 1 MACT standards, such as

boilers and industrial furnaces, we continue to recommend that site-specific risk assessments generally be

conducted as part of the RCRA permitting process (see Federal Register 1999).

As part of the September 2005 rule finalizing MACT standards for hazardous waste-burning incinerators,

cement kilns, lightweight aggregate kilns, boilers, and industrial furnaces, we maintain virtually the same

the site-specific risk assessment policy recommendation as conveyed in the 1999 final rule preamble (see

previous paragraph)3

. That policy, which establishes that the need for an SSRA should be determined on

a case-by-case basis, now applies equally to both Phase 1 and Phase 2 sources. 
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In addition, the 2005 final rule codifies additional regulatory language that provides the authority for

SSRAs. Although a comparative risk analysis conducted for the 2005 final rule concluded that the

MACT standards for both Phase 1 and Phase 2 sources are generally protective, there may be instances

where we cannot be assured that emissions from each source will be protective of human health and the

environment. Because we believe that SSRAs are likely to continue to be necessary at some facilities

(i.e., mainly those that have not previously conducted an SSRA), we have codified language in

§§270.10(l) and 270.32(b)(3) that explicitly provides for the permit authority to require SSRAs on a

case-by-case basis and add conditions to RCRA permits based on SSRA results, respectively. The

language also reminds permit authorities that the determination that the MACT standards may not be

sufficiently protective is to be based only on factors relevant to the potential risk from the hazardous

waste combustion unit at the site. Additionally, guiding factors have been identified for permitting

authorities to consider in determining whether the MACT will be sufficiently protective at an individual

site. In summary, the 2005 final rule only modifies the statutory authority under which we implement the

SSRA policy, while maintaining the same SSRA policy from a substantive standpoint.

1.3 USING THIS DOCUMENT

This document contains our generally recommended approach for conducting multi-pathway, sitespecific human health risk assessments of RCRA hazardous waste combustors. This document does not

provide recommendations on how to:

• Determine if a site-specific risk assessment should be performed;

You can find U.S. EPA’s most recent recommendations for when, or if, a site-specific risk

assessment should be performed, in documentation of the MACT rule, published on September

30, 1999 (Federal Register 1999).

• Conduct stack emissions testing for a site-specific assessment;

A separate guidance document entitled Risk Burn Guidance for Hazardous Waste Combustion

Facilities EPA 530-R-01-001, July 2001 (U.S. EPA 2001c) contains approaches for collecting

emissions data to support site-specific risk assessments. This document is on the U.S. EPA OSW

website at: http://www.epa.gov/epaoswer/hazwaste/combust/pdfs/burn.pdf.
Human Health Risk Assessment Protocol

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• Develop a site-specific ecological risk assessment;

We’d previously published our recommendations for conducting screening level ecological

combustion risk assessments in a separate, companion document to the HHRAP. This companion

document, the Screening Level Ecological Risk Assessment Protocol for Hazardous Waste

Combustion Facilities (SLERAP) Peer Review Draft (U.S. EPA 1999a), is currently undergoing

substantial revision. Until revisions are complete, we can’t recommend using the SLERAP.

• Use risk assessment results in risk management decisions, such as setting RCRA permit

conditions.

Because this protocol is a technical risk assessment tool, it does not discuss risk management

issues, such as how risk managers are to use the provided information (including uncertainty

information), the potential for cumulative risks, or target risk levels. U.S. EPA’s generally

recommended risk and hazard targets can be found in Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities (U.S. EPA 1994f). Additionally, EPA Region 6's

region-specific risk target recommendations, Region 6 Risk Management Addendum (U.S. EPA

1998b), are available on their website at: www.epa.gov/earth1r6/6pd/rcra_c/protocol/r6add.pdf.

Please Note: the ultimate decision for how to incorporate risk assessment estimates in risk

management decisions rests with the permitting authority.

For your convenience, the HHRAP many of the recommendations found in the above-referenced

documents. However, unless we say so explicitly, the HHRAP does not intend to update, revise, or

replace any of the information contained in the above-referenced documents. 

The HHRAP does update and replace the following guidance documents:

• U.S. EPA, Guidance for Performing Screening Level Risk Analyses at Combustion

Facilities Burning Hazardous Wastes, April 15, 1994 Draft and the October 4, 1994

Errata;

• U.S. EPA, Protocol For Screening Level Human Health Risk Assessment at Hazardous

Waste Combustion Facilities - Volumes 1 & 2, Internal Review Draft, EPA-R6-096-002

February 28, 1997;

• U.S. EPA, Human Health Risk Assessment Protocol, Draft Interim Final, April 1998

(CD-Rom version);
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• U.S. EPA, Human Health Risk Assessment Protocol for Hazardous Waste Combustion

Facilities - Volume 1-3, Peer Review Draft, EPA 530-D-98-001A, B & C, July 1998 and

the August 2, 1999, Errata.

We anticipate that risk assessments will be completed for new and interim-status facilities, where

necessary, when they apply for their RCRA permit. The process we recommend evaluates risks to

receptors posed by potential emissions from RCRA-regulated units. We encourage you to use existing

and site-specific information throughout the risk assessment process in order to properly evaluate actual

regulated operations for any particular combustor. We generally recommend conservative default

assumptions only when they will provide confidence that ensuing permit limits will be health protective.

Throughout the HHRAP we offer parameter values for you to consider. These values are based on a

number of elements, such as the best science available and professional judgement. Since this is a

national level guidance, the recommended values typically reflect national average conditions. The

values will be more appropriate for some sites, and less so for others. For example, the type of waterbody

near a facility (i.e. lake, river, wetland) may affect the methylation rate of mercury in the waterbody, or

the type of fish consumed may affect percent lipid content used in the assessment. So, a value that is

reasonable for one facility may be over (or under) protective at a different facility.

In all cases, though, we give the reason for the suggested value. We encourage you to consider our

reasoning, in deciding if a more representative estimate of a site-specific value (or range of values) is

available and appropriate. If you use values other than those we recommend, you should explore how, or

if, those changes may affect other parameter values and calculations used in the assessment. As with

values recommended in this guidance, using values other than those recommended here should always be

clearly identified and discussed in the risk plan and/or risk assessment (as appropriate). This will ensure

clarity and transparency of the final risk assessment results. 

You would need considerable time, effort, and funding to investigate the representativeness of all the

values (or ranges of values) available in the HHRAP. As a result, you might choose to use only readily

available site-specific information in an initial assessment. You could then use the results of that
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assessment to determine where (or if) more site-specific risk information should be collected (see Figure

1-1). This allows you to use resources most efficiently and effectively, by focusing resources on areas

that are considered “risk drivers”, rather than areas that do not appreciably affect the risk outcome. For

example, if the assessment shows that the primary pollutant and exposure pathway is mercury in fish, then

you could target site-specific data gathering efforts on values related to mercury emissions, surface water

concentrations and/or fish consumption. You would not have to spend resources collecting site-specific

information that may not affect the final results of the assessment (for example, Manganese exposure

through ingestion of produce).

You can also use the HHRAP as a screening tool. For example, a facility with a highly variable waste

stream might choose to provide the permitting authority with historical data and assume that all

compounds will be retained in the risk analysis. Or you might choose to use more conservative

assumptions throughout, to make the assessment fit a more classic “screening level” approach. For

example, you could choose not to initially investigate the actual land use surrounding a facility, but

instead locate all the selected receptors at the area of greatest contaminant deposition. If estimates don’t

exceed the selected risk target, additional iterations of the assessment may not be necessary. 

Regardless, every risk assessment is limited by the quantity and quality of:

• Site-specific environmental data; 

• Emission rate information; and

• Other assumptions made during the risk estimation process (e.g., fate and transport

variables, exposure assumptions, and receptor characteristics).

These limitations and uncertainties are described extensively throughout the main document and the

appendices, and are summarized in Chapter 8. You should generally make every effort to reduce

limitations and uncertainties in the risk assessment process, since they can affect the confidence in the

risk assessment results.
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Facility Characterization

- Compiling Basic Facility Information (Section 2.1)

- Identifying Emission Sources & Estimating Emission Rates (Section 2.2)

- Identifying Compounds of Potential Concern (COPC) (Section 2.3)

- Estimating COPC Concentrations for Non-Detects (Section 2.4)

- Evaluating Contamination in Blanks (Section 2.5)

Air Dispersion and Deposition Modeling

- Partitioning Emissions (Section 3.2)

- Site-Specific Characteristics Required for Air Modeling (Section 3.3)

- Meteorological Preprocessor Data Needs (Section 3.5)

- ISCST3 Model Input Files (Sections 3.6)

- ISCST3 Model Execution (Section 3.7)

- Using Model Output (Section 3.8)

- Modeling Fugitive Emissions (Section 3.9)

- Modeling Acute Risk (Section 3.10)

Exposure Scenario Selection

- Exposure Setting Characterization (Section 4.1)

- Recommended Exposure Scenarios (Section 4.2)

- Selecting Exposure Scenario Locations (Section 4.3)

Estimating Media Concentrations

- Calculating Air Concentrations in Air for Direct Inhalation (Section 5.1)

- Calculating Concentrations in Soil (Section 5.2)

- Calculating Concentrations in Produce (Section 5.3)

- Calculating Concentrations in Meats, Milk, and Eggs (Sections 5.4 through 5.6)

- Calculating Concentrations in Drinking Water and Fish (Section 5.7)

Quantifying Exposure

- Inhalation Exposure Pathways (Section 6.1)

- Ingestion Exposure Pathways (Section 6.2)

- Dermal Exposure Pathways (Section 6.3)

- Exposure Frequency (Section 6.4)

- Exposure Duration (Section 6.5)

- Averaging Time (Section 6.6)

Characterizing Risk and Hazard

- Quantitatively Estimating Cancer Risk (Section 7.1)

- Quantitatively Estimating Noncancer Hazard (Section 7.2)

- Target Levels (Section 7.3)

- Estimating Acute Exposure from Direct Inhalation (Section 7.4)

Interpreting Uncertainty

- Understanding Uncertainty and Limitations of the Human Health Risk Assessment Process (Section 8.1)

- Identifying Types of Uncertainty (Section 8.2)

- Determining Qualitative Uncertainty (Section 8.3)

- Determining Quantitative Uncertainty (Section 8.4)

- Discussing Human Health Risk Assessment Uncertainty (Section 8.5)

Deny Permit

Collect Additional

Site-Specific Information

Use Additional

Site-Specific Information

To Reevaluate Risk

Issue Permit

Develop Protective

Operating Permit

Risk

Acceptable?

YES

Risk Assessment

Risk Management

NO NO

FIGURE 1-1

HUMAN HEALTH RISK ASSESSMENT PROCESS
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As stated in the U.S. EPA (2002c) “Risk assessments may be performed iteratively, with the first

iteration employing protective (conservative) assumptions to identify possible risks. Only if potential risks are

identified in a screening level assessment is it necessary to pursue a more refined, data-intensive risk assessment.

The screening level assessments may not result in "central estimates" of risk or upper and lower-bounds of risks.

Nevertheless, such assessments may be useful in making regulatory decisions...”

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The EPA Information Quality Guidelines (U.S. EPA 2002c) recommend ensuring the objectivity of

information found in risk assessments by applying, to the extent practicable and consistent with Agency

statutes and existing legislative regulations, the following adaptation of the quality principles found in the

Safe Drinking Water Act (SDWA) Amendments of 1996: 

(A) The substance of the information is accurate, reliable and unbiased. This involves the use of: 

(i) the best available science and supporting studies conducted in accordance with sound

and objective scientific practices, including, when available, peer reviewed science and

supporting studies; and 

(ii) data collected by accepted methods or best available methods (if the reliability of the

method and the nature of the decision justifies the use of the data). 

(B) The presentation of information on human health, safety, consistent with the purpose of the

information, is comprehensive, informative, and understandable. In a document made available to

the public, EPA specifies: 

(i) each population addressed by any estimate of applicable human health risk; 

(ii) the expected risk for the specific populations affected; 

(iii) each appropriate upper-bound or lower-bound estimate of risk; 

(iv) each significant uncertainty identified in the process of the assessment of risk; and 

(v) peer-reviewed studies known to the Administrator that support, are directly relevant

to, or fail to support any estimate of risk and the methodology used to reconcile

inconsistencies in the scientific data.

How risk results are viewed by the risk manager and other stakeholders is complex and can involve other

factors besides those included in this document (e.g. public concern). Consequently, interpreting risk

assessment results warrants careful consideration. Risk management decisions are beyond the scope of

the HHRAP, and we don’t provide any guidance on interpreting risk results. It should be noted, though,

that identifying potentially unacceptable risks does not necessarily signify the end of the risk assessment

process. You can view risk assessments as an iterative process4

, with a number of available options once

risk estimates are produced. The iterative nature of the risk assessment/risk management interface is

graphically represented in Figure 1-1, and the various available options are briefly described below:
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Example 1: If the initial risk estimates (coupled with any other related factors) indicate that risks are not

expected to pose a concern to human health or the environment, the risk manager and/or permit

writer will likely end the site-specific risk assessment process and the facility will likely receive a

permit.

Example 2: If the initial risk estimates (coupled with any other related factors) indicate that the risks are

at or above a level that may pose a risk to human health or the environment, then additional

information might be added to the risk assessment (e.g. site-specific information that’s more

representative of the actual exposure settings). Additional iterations of the risk assessment could

then be performed. This iterative process enables you to determine if the risks identified in the

earlier assessment accurately represent the situation at a given combustion facility.

Example 3: If the initial risk estimates (coupled with any other related factors) or subsequent iterations

(as detailed in Example 2 above), indicate potentially unacceptable risk, risk managers and/or

permit writers might use the results of the risk assessment to propose revised or additional permit

conditions (such as waste feed limits and/or process operating conditions) to lower the potential

risk to acceptable levels. Another risk assessment could verify that the proposed permit

conditions will enable the combustor to operate in a manner that’s protective of human health and

the environment.

In some situations, target risk levels might be selected and back-calculations conducted to

determine what emission and/or waste feed rate would allow the facility to operate in a protective

manor. In any case, the acceptable waste feed rate and other appropriate conditions could be

incorporated into the RCRA permit.

Example 4: If the initial risk estimates or subsequent iterations (coupled with any other related factors)

indicate potentially unacceptable risk, risk managers and/or permit writers might also choose,

where appropriate, to deny the permit.

The HHRAP may also be useful when a facility or regulatory agency decides to perform a pre-trial burn

risk assessment. A pre-trial burn risk assessment can evaluate pre-existing permit limits (e.g. regulatory

limits such as MACT or BIF) to determine if more extensive or refined risk-based testing is necessary as

part of the trial burn testing program. Also, the pre-trial burn risk assessment can test the parameters used

in the initial trial burn sampling and analysis plan. Testing trial burn parameters minimizes trial burn

contributions to risk assessment uncertainty, and avoids the expense of multiple trial burn iterations. For

example, if the initial detection or quantitation limit for a specific compound (such as a dioxin, furan, or

bioaccumulative metal) is too high during trial burn sampling and analysis, then the final risk estimate

may be artificially inflated, especially for indirect exposure pathways. If trial burn sampling and analysis
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uses a lower detection or quantitation limit, the compound might be found not to add appreciably to the

risk results. The pre-trial burn risk assessment can also determine whether modifications to the sampling

collection (such as increased sample volumes) are needed to achieve lower detection or quantitation

limits. Please see Chapter 2 for more detailed information on how risk assessments relate to trial burns.

1.4 PRIMARY REFERENCE DOCUMENTS

One of the main benefits of the HHRAP is that it assembles in one place more than a decade of research

and experience regarding practices for conducting risk assessments of hazardous waste combustion

facilities. This section describes, in chronological order, the primary guidance documents we used to

prepare the HHRAP. Many other important reference materials were also needed to produce a document

of this magnitude. We have listed all reference materials used in preparing this document in the

Reference chapter.

Some of the documents we used were themselves developed over a period of several years, including

revisions. In some cases, revisions to the original document address only specific issues rather than a

complete revision of the original document. The following discussion lists and briefly describes each

document. Overall, the guidance documents listed below reflect a continual refining and enhancing of the

risk assessment method.

The following was the first U.S. EPA guidance document for conducting risk assessments at combustion

units:

U.S. EPA. 1990e. Methodology for Assessing Health Risks Associated with Indirect Exposure to

Combustor Emissions, Interim Final. Environmental Criteria and Assessment Office. ORD. 

EPA-600-90-003. January.

Referred to as the “IEM” document, EPA (1990e) outlines and explains a set of general procedures for

conducting risk assessments that includes both the direct inhalation pathway and indirect food chain

pathways. The IEM document was subsequently supplemented by the following:
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U.S. EPA. 1993f. Addendum to the Methodology for Assessing Health Risks Associated with

Indirect Exposure to Combustor Emissions, Review Draft. Office of Health and Environmental

Assessment. ORD. EPA-600-AP-93-003. November 10.

Referred to as the “Addendum”, EPA (1993f) outlines recommended revisions and added new exposure

pathways to the previous U.S. EPA guidance (1990e), and has been used by the risk assessment

community since its release.

In 1994, we issued several additional hazardous waste combustion risk assessment documents, including:

U.S. EPA. 1994f. Draft Exposure Assessment Guidance for RCRA Hazardous Waste

Combustion Facilities. OSWER. EPA-530-R-94-021. April.

This document (1994f) is made up of a series of four attachments, all issued around the same time frame

(April/May 1994) as separate documents:

U.S. EPA. 1994g. Draft Guidance for Performing Screening Level Risk Analyses at Combustion

Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. April 15.

U.S. EPA. 1994h. Table 1, “Chemicals Recommended for Identification,” and Table 2,

“Chemicals for Potential Identification.” Attachment A, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. April 15.

U.S. EPA. 1994i. Draft Revision, Implementation Guidance for Conducting Indirect Exposure

Analysis at RCRA Combustion Units. Attachment, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. April 22.

U.S. EPA. 1994j. Draft Guidance on Trial Burns. Attachment B, Draft Exposure Assessment

Guidance for RCRA Hazardous Waste Combustion Facilities. May 2

Combined, these four documents present a generally recommended procedure for sampling the combustor

emissions, identifying the compounds of concern, conducting both a direct and indirect risk assessment,

and implementing the results of the risk assessment for hazardous waste combustion facilities. We used

the methodologies identified in both the ORD “IEM” and “Addendum” documents as the foundation of
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our hazardous waste combustion risk assessment methodology. The “IEM” and the “Addendum” were

broader in scope than our document. We used many, but not all, of the methods, models and exposure

scenarios that are described in the two ORD documents. Because the ORD documents contain much of

the background information necessary to complete a risk assessment, that information was not repeated in

our guidance documents. Shortly after the release of our documents, the trial burn portion and the risk

assessment portion were further revised with the following releases:

U.S. EPA. 1994n. Draft Revision of Guidance on Trial Burns. Attachment B, Draft Exposure

Assessment Guidance for RCRA Hazardous Waste Combustion Facilities. OSWER. June 2.

U.S. EPA. 1994p. Errata, Draft Guidance for Performing Screening Level Risk Analyses at

Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment

Guidance for RCRA Hazardous Waste Combustion Facilities. October 4.

As a follow-up to these documents, we prepared another draft guidance. The following was released for

internal review, but never formally or officially released as a program-supported document:

U.S. EPA. 1994r. Revised Draft Guidance for Performing Screening Level Risk Analyses at

Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment

Guidance for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and

Remedial Response. OSW. December 14.

In 1997, the state of North Carolina’s Department of Environment, Health, and Natural Resources

(DEHNR) developed the following guidance document for conducting risk assessments in their state:

NC DEHNR. 1997. North Carolina Protocol for Performing Indirect Exposure Risk

Assessments for Hazardous Waste Combustion Units. January.

The NC DEHNR document reiterates U.S. EPA procedures (1994r), with the addition of a tiered approach

that can help the regulatory agency or facility to choose approaches that reflect the investment they want

to make in conducting risk assessments. For instance, a small, on-site unit with limited waste stream

variability may find the first tier assessment (worst-case) in the North Carolina protocol appropriate,

whereas a larger facility with a diverse waste feed mixture may decide to complete a Tier 2 or Tier 3

assessment, which are progressively more site-specific.
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In 1998, the ORD revised, updated and combined the “IEM” and the “Addendum” documents into one

document, entitled:

U.S. EPA 1998. Methodology for Assessing Health Risks Associated with Multiple Pathways of

Exposure to Combustor Emissions (U.S. EPA 1998c). 

This document is referred to as the “MPE” document. It includes information which was gained from

cross-Agency review, EPA’s Science Advisory Board (SAB) and the public on the “IEM” and the

“Addendum” documents. It also includes information from the draft dioxin reassessment “Estimating

Exposure to Dioxin-Like Compounds” (U.S. EPA 1994a) and the “Mercury Study Report to Congress”

(December 1997). As with the MPE’s predecessor documents, it is considered the foundation of our

hazardous waste combustion risk assessment methodology and is frequently referenced in the HHRAP. 

In 1999 we released a technical document that detailed the risk assessment conducted to support the

hazardous waste combustion Maximum Achievable Control Technology (MACT) standards: 

RTI 1999. The Background Information Document to the Risk Assessment Support to the

Development of Technical Standards for Emissions from Combustion Units Burning Hazardous

Wastes Final Report. EPA Contract Number 68-W6-0053.

To ensure consistency, we considered EPA(1999) throughout the development of the HHRAP.

Finally, in 2001 we updated and finalized the document entitled:

U.S. EPA 2001c. Risk Burn Guidance for Hazardous Waste Combustion Facilities, July.

Referred to as the “risk burn guidance,” EPA(2001c) was prepared by U.S. EPA Region 4 and U.S. EPA

OSW. It details recommendations regarding stack emissions tests which may be performed at hazardous

waste combustion facilities to support site-specific risk assessments. 

As previously stated, our primary objective in developing the HHRAP was to suggest a user-friendly

approach to performing site-specific combustion risk assessments. The HHRAP achieves this goal by
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offering a comprehensive set of tools. You will no longer need to search through a long list of guidance

documents to find an appropriate method and/or value when conducting a site-specific risk assessment of

a hazardous waste combustor. Instead, you have one self-contained document with the majority of all the

available information needed to complete a risk assessment. With the HHRAP’s extensive reference list,

you also have the original source of a method and/or value. This simplifies the process of deciding if the

reference is appropriate to use for your specific situation. 

1.5 RISK NOMENCLATURE

Unless otherwise stated, the following definitions for risk-related terms are from the National Academy of

Sciences 1983, Risk Assessment in the Federal Government, and used throughout this guidance:

Risk Assessment The scientific evaluation of potential health impacts that may result from

exposure to a particular substance or mixture of substances under

specified conditions.

Hazard An impact to human health by chemicals of potential concern.

Risk An estimation of the probability that an adverse health impact may occur

as a result of exposure to chemicals in the amount and by the pathways

identified.

Dose The amount of a substance available for interaction with metabolic

processes or biologically significant receptors after crossing the

exchange boundary of an organism (U.S. EPA 1998c). 

Exposure The condition of a chemical contacting the exchange boundary of an

organism (U.S. EPA 1998c).

Indirect Exposure Resulting from contact of human and ecological receptors with soil,

plants, or waterbodies on which emitted chemical has been deposited. 

For screening level purposes, indirect exposure includes ingestion of

above ground fruits and vegetables, beef and milk, chicken and eggs,

freshwater fish and soil.

Direct Exposure Exposure via inhalation.
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Chapter 2:

Characterizing Facility Emissions

What’s Covered in Chapter 2:

2.1 Compiling Basic Facility Information

2.2 Identifying Emission Sources & Estimating Emission Rates

2.3 Identifying Compounds of Potential Concern (COPCs)

2.4 Estimating COPC Concentrations for Non-Detects

2.5 Evaluating Contamination In Blanks

PLEASE NOTE: for the purposes of this guidance, “we” refers to the U.S. EPA OSW. 

The HHRAP is written for the benefit of a varied audience, including risk assessors,

regulators, risk managers, and community relations personnel. However, the “you” to

which we speak is the performer of a risk assessment: the person (or persons) who will

actually put the recommended methods into practice.

This chapter provides guidance on characterizing the nature and magnitude of facility emissions. 

Characterizing includes (1) compiling basic facility information, (2) identifying emission sources, (3)

estimating emission rates, (4) identifying COPCs, (5) estimating COPC concentrations for non-detects,

and (6) evaluating contamination in blanks. You can consider the information listed in the highlighted

box at the end of each section the minimum that we recommend to ensure a risk assessment is

scientifically sound. However, you may want to consult up front the more detailed discussions found in

each section. A more complete understanding of the relevant issues will make sure that all appropriate

information is collected simultaneously. This will help minimize the time and effort expended collecting

site-specific information.

2.1 COMPILING BASIC FACILITY INFORMATION

If you are a risk assessor, there is basic facility information you should consider while conducting the risk

assessment, and include in the risk assessment report. Including this basic facility information in the

report will enable reviewers to establish a contextual sense of how the facility relates to other facilities
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C Description of physical setting

C Principal business and primary production processes

C Normal and maximum production rates

C Types of waste storage and treatment facilities

C Type and quantity of wastes stored and treated

C Process flow diagrams showing both mass and energy inputs and outputs

< Relevant information from an existing or proposed permit and/or compliance documents (e.g.,

Waste Analysis Plan or Feedstream Analysis Plan; Startup, Shutdown, and Malfunction Plan;

Certifications of Compliance; etc.)

RECOMMENDED INFORMATION FOR THE RISK ASSESSMENT REPORT

and other hazardous waste combustors. It's also very important to thoroughly understand (and document)

any regulatory limits evaluated in the risk assessment, because the risk assessment report informs the

setting of risk-based permit limits. For example, specific emissions data might not be collected for a

particular unit where waste feeds are controlled in lieu of demonstrating compliance with an emissions

limit under the regulations (e.g., Tier I under the BIF rule for certain metals, MTEC under the HWC

MACT rule). For transparency, we therefore recommend clearly identifying the basis for the assumptions

and/or data to be used in the risk assessment, along with the rationale for how the information will be

used.

2.2 IDENTIFYING EMISSION SOURCES & ESTIMATING EMISSION RATES

Burning hazardous waste typically emits combustion by-products from a stack. In addition to emissions

from a combustion stack, types of emissions associated with the combustion of hazardous waste may

include (1) process upsets emissions, (2) accidental releases, (3) general RCRA fugitive emissions, and if

the facility is a cement kiln (4) cement kiln dust (CKD) fugitive emissions. Each of these emission source

types is defined below with regards to the context and scope of this guidance.

Stack Emissions - Release of compounds or pollutants from a hazardous waste combustor into

the ambient air while the unit is operated as intended and in compliance with a permit and/or

regulation (for interim status).
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Process Upset Emissions - Release of compounds or pollutants from a hazardous waste

combustor into the ambient air while the unit is not being operated as intended, or during periods

of startup or shutdown. Upset emissions usually occur during events and times when the unit is

not operating within the limits specified in a permit or regulation. Conditions within the

combustion system during the process upset result in incomplete destruction of the wastes, or

otherwise promote the formation and/or release of hazardous compounds from combustion stacks. 

Upset emissions are generally expected to be greater than stack emissions.

Accidental Releases - an accidental release is defined in Section 112(r) of the Clean Air Act as an

unanticipated emission of a regulated substance or other extremely hazardous substance into the

ambient air from a stationary source. Accidental releases are typically associated with non-routine

emissions from RCRA facilities, such as the failure of tanks or other material storage and

handling equipment, complete failure of combustion and air pollution control systems (e.g.

resulting from explosions, and fires), or transportation accidents.

RCRA Fugitive Emissions - Release of compounds or pollutants into the ambient air from

RCRA-regulated sources other than hazardous waste combustion stacks. RCRA fugitive

emissions are typically associated with the release of pollutants from leaks in the combustion

chamber (e.g., “puffs”); tanks, valves, flanges, and other material-handling equipment used in the

storage and handling of RCRA hazardous wastes; residues from the combustion process such as

ash or quench water; and other RCRA treatment, storage, or disposal units (e.g., landfills). 

CKD Fugitive Emissions - Release of pollutants into the ambient air caused by the handling,

storage, and disposal of cement kiln dust.

We generally recommend that as applicable, all of these emission source types except accidental releases

be addressed in the risk assessment. Accidental releases aren’t within the scope of this guidance. We

generally recommend evaluating accidental releases per Section 112(r) of the CAA and current Agency

guidance (U.S. EPA 1996f) or the RMP Offsite Consequence Analysis Guidance, dated May 24, 1996. 

Despite this general guidance, it is for the permitting authority to decide on a site-specific basis whether

the risk assessment will consider accidental releases.

The following subsections contain guidance for estimating emissions of the source types to be included in

the risk assessment. Guidance on air dispersion modeling of stack and fugitive emissions is presented in

Chapter 3.

2.2.1 Estimating Stack Emission Rates for Existing Facilities

We generally consider it important to determine stack emission rates (in grams per second) of every

COPC identified using the procedures outlined in Section 2.3. We anticipate that emission rates for

existing facilities (i.e. already built and operational) will be based on direct stack measurements from

regulatory performance tests, because permitting authorities generally require performance tests before
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Test Design: Performance vs. Health Criteria

Performance testing involves demonstrating compliance with

emission standards or performance criteria under any

operational circumstance. Facilities typically wish to

maximize the flexibility of operating conditions allowed by

their permit. This leads to performance tests designed to

demonstrate compliance even while operating under extreme

conditions (i.e., conditions that may only seldom occur or

may only occur for brief durations over the course of a year).

Regulatory performance requirements are generally

national-scale, technology-based instantaneous limits. 

Such performance requirements might not consider various

health impacts to receptors located near a particular

facility. Therefore, data needs to assess potential health

risks are typically more comprehensive than those of a

performance test. For example, a performance test will

provide information to calculate destruction and removal

efficiency (DRE) for a principal organic hazardous

constituent (POHC) and perhaps measure total particulate

matter, but will not typically quantify the various products of

incomplete combustion (PICs) in the stack gases, nor

establish particle size distribution for gases exiting the stack.

 Situations have occurred in which some facilities assume

that the only way to maximize permit flexibility and satisfy

risk assessment data needs is to conduct separate tests. We

encourage another interpretation. As mentioned elsewhere,

we suggest modifying performance-based test protocols to

include risk assessment data requirements as appropriate to

evaluate both acute and chronic exposures posed by

facility-specific operations that may occur under the terms of

the permit.

granting a permit to burn hazardous wastes, or in order to demonstrate compliance with emission

standards. 

As mentioned in the Special Note "How This Document Relates to Trial Burns" and elsewhere, we

suggest incorporating data collection for a risk assessment into the regulatory performance testing

program whenever possible. This will optimize the use of both facility and permitting agency resources,

and minimize expenditures associated with stack

testing and subsequent data review, evaluation, and

permitting. Incorporating risk assessment data

collection into the performance test program can

ensure that proper evaluation across test conditions

is achieved for optimal data usability and

versatility– both engineering considerations relating

to unit operations flexibility, and streamlined data

collection considerations for characterizing

potential emissions. 

Experience has shown us that in order to evaluate

both acute and chronic reasonable maximum

exposure estimates, the potential emissions

evaluated in the risk assessment need to be based on

actual operating scenarios that may occur under the

terms of the permit. We acknowledge that proper

design of a regulatory test program that includes

risk assessment data collection is challenging for

facilities that burn highly variable waste and/or

have multiple operating conditions. At the same

time, inadvertently omitting potential risk drivers

from the risk assessment due to improper or

oversimplified test design is to be avoided. 

Therefore, if feed streams differ between the various test conditions in the regulatory test program, we

generally recommend providing appropriate rationale for this difference in the test plan, and discussing in

the risk assessment report any impacts the differences may have had upon the risk analysis.
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Test Conditions’ Relation to Permit Conditions

The feed and operating conditions demonstrated during the

testing will define an operating envelope that not only

establishes the working assumptions for the risk assessment,

but also the final permit terms. If a facility collects

emissions data for the risk assessment under "normal"

operating conditions, additional permit limitations may be

appropriate to ensure that conditions represented as normal

during the test are, in fact, normal over the long-term

operation of the facility.

In some cases, a facility may elect to focus data collection efforts for a risk assessment into one test

condition in the regulatory testing program that demonstrates "normal operations" using feedstreams

considered "worst-case" from an operational and potential emissions standpoint. 

Please Note: We suggest such a test condition only for facilities that can identify and

substantiate via historical operating records the typical (or day-to-day) operating mode

for the hazardous waste combustion unit and ancillary equipment, regardless of the type

of waste fed. 

If combining multiple and variable feedstreams into a single "worst-case" feed, the mixture needs to

represent those actual waste matrices and constituents that are the most difficult to burn (ensuring that the

combustion unit is fairly challenged). A "worst-case" feed also needs to contain the most toxic

substances managed in the unit, on a mass basis proportional to that fed at any time (ensuring that all

potentially toxic emissions are quantified). Multiple and/or highly variable feedstreams that require

different extremes of a wide operating envelope, or feedstreams that are combined on a disproportional

mass basis to that fed at any time, may not be

representative of actual operations. We're

concerned that they might even result in emission

estimates that are not sufficiently conservative for

the risk assessment. Please see the Risk Burn

Guidance for Hazardous Waste Combustion

Facilities (U.S. EPA 2001c) for further information

on designing a testing program that integrates risk

assessment data collection into the regulatory

testing of hazardous waste combustors.

We generally recommend including the risk assessor in the early planning efforts of the test program

development, so that the test program can be more effectively streamlined while meeting multiple and

complex data collection goals. At least three valid runs at steady state are needed to characterize a test

condition. Since steady state conditions are typically outlined in the test plan for each test condition and

verified by field observations during the test program, resulting emission rates for any particular COPC

are likely to be fairly consistent between runs for each test condition. Test reports document any

abnormalities in steady state operations for a particular run or test condition. If any one run experiences

significant issues that may impact the data quality or comparability with the other runs, the facility and

permitting authority might decide during the test to discontinue the problem run and initiate a new run to
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ensure a valid test condition. Test reports also document this occurrence and identify those valid runs of

the test condition. 

For risk assessments, we generally recommend using the maximum of the three emission rates identified

for each COPC during a particular test condition, adjusted for process upsets. This approach is consistent

with implementing a steady state test designed for collecting risk data where the combustor burns

representative, yet worst-case or challenging feeds, at operating conditions that are allowable and/or

typical under the permit. This approach will also allow consistency in refinements to the final risk

analysis that may involve several risk evaluations for different operating scenarios (i.e., across the various

test conditions) in order to afford operational flexibility while maintaining permit provisions that ensure

protection of human health. 

Please Note: The recommendation to use the highest of the three emission rates is an

update to Section 8.1.2 of U.S. EPA (2001c).

An alternative to a regulatory performance test is the use of data "in lieu of" testing. Permitting

authorities generally consider this type of data on a case-by-case basis. Prior to accepting such data as a

surrogate for use in the risk assessment, we recommend evaluating the data from both an engineering

perspective and a data usability perspective. To evaluate the similarities between combustors, consider

the design and construction of the combustor and associated air pollution control devices, along with the

basic operating conditions of the process equipment as tested (e.g., capacity, flow rates, supplemental

fuels used, etc.) to ensure comparable emissions. Stack test measurements from a similar combustor are

useful if the combustor burns similar waste feed(s) in terms of constituents, type of waste matrix, and

amount of waste fed on a mass basis. In addition, we recommend evaluating the methods used to quantify

COPCs and associated detection limits achieved during the test, as well as verifying that the data quality

documentation is acceptable for risk assessment purposes.
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SPECIAL NOTE: HOW THIS DOCUMENT RELATES TO TRIAL BURNS

We believe that generating defensible emission rates for compounds of potential concern (COPCs) is

one of the most important parts of the risk assessment process. This requires special consideration

when planning a risk assessment. Therefore, we consider emissions testing, risk assessment planning,

and implementation as interdependent aspects of the hazardous waste combustion site-specific risk

assessment process.

As described elsewhere in this chapter, traditional regulatory performance tests (e.g., RCRA trial

burns designed solely to measure DRE) do not sufficiently characterize COPC emissions for

performing site-specific risk assessments. We therefore generally recommend that collecting

emissions data for a site-specific risk assessment include a thorough understanding of the operating

limits to be established in the regulatory permit and the possible emissions that may result under the

permitted operations of the unit. Regardless of whether the emissions data for the risk assessment is

collected in a separate test condition or in multiple test conditions that are part of a regulatory

performance test program, we recommend that to the extent possible, the planning, regulatory agency

review, and collecting of emissions data be conducted simultaneously, to ensure consistency in data

evaluation across test conditions is achieved and actual operations allowable under the permit are

appropriately evaluated. This approach also eliminates redundancy or the need to repeat activities and

minimizes cost expenditures overall.

The guidance documents below relate to the RCRA hazardous waste combustion program. You may

find the listed documents useful for developing and conducting trial burns:

U.S. EPA. 1989f. Handbook: Guidance on Setting Permit Conditions and Reporting Trial

Burn Results. Volume II of the Hazardous Waste Incineration Guidance Series. Office of

Research and Development (ORD). EPA/625/6-89/019. January.

U.S. EPA. 1989g. Handbook: Hazardous Waste Incineration Measurement Guidance

Manual. Volume III of the Hazardous Waste Incineration Guidance Series. Office of Solid

Waste and Emergency Response. EPA/625/6-89/021. June.

U.S. EPA 1990i. Handbook: Quality Assurance/Quality Control (QA/QC) Procedures for

Hazardous Waste Incineration. Office of Research and Development. EPA/625/6-89/023. 

January.

U.S. EPA. 1992c. Technical Implementation Document for EPA’s Boiler and Industrial

Furnace Regulations. Office of Solid Waste and Emergency Response. EPA-530-R-92-011. 

March.

U.S. EPA. 2001c. Risk Burn Guidance for Hazardous Waste Combustion Facilities. U.S.

EPA Region 4 and OSW. EPA 530/R/01/001. July.

Generic Trial Burn Plans and/or Quality Assurance Plans and Procedures (QAPP) developed

by individual EPA regional offices or authorized states.
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2.2.1.1 Additional Emissions Testing Considerations

COPC emission rates demonstrated in a traditional regulatory performance test (such as a RCRA trial

burn) are expected to be greater than normal emission rates because a facility “challenges” its combustor

during a trial burn. These challenges introduce a wide range of conditions for automatic waste feed cutoff

(AWFCO) systems. Regulatory performance tests are usually conducted under two conditions: 

1. a high-temperature test, in which the emission rate of metals is maximized, and 

2. a low-temperature test, in which the ability of the combustor to destroy principal organic

hazardous constituents (POHCs) in the waste feed is challenged. 

The combination of high POHC feed rates and extreme operating conditions tested during a

low-temperature trial burn typically produce higher PIC emission rates. However, this is not true in all

cases. For example, the formation of Polychlorinated dibenzo(p)dioxins (PCDDs) and polychlorinated

dibenzofurans (PCDFs) doesn’t depend on “POHC incinerability” low temperature conditions. PCDDs

and PCDFs can be formed catalytically in the low-temperature regions of the combustion unit or APCS. 

We recommend basing the decision to test under low, high, or both temperature conditions on the

characteristics of the facility as discussed in the preceding section, considering facility-specific unit

operation information for the particular types of wastes burned in the combustion unit as well as the

particular APCS.
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C All stack sampling information (current and historical data relevant to the risk assessment) on

emission rates from the combustor during normal or day-to-day operating conditions and/or 

regulatory performance test conditions.

C A description of the waste feed streams burned during the stack sampling. This includes

chemical composition and physical properties, which demonstrate that the waste feeds are

representative of worst-case wastes relative to producing emissions that may pose a potential

risk concern.

C Description of the operating conditions under which each set of emission rate data being used

was developed.

* * * NOTICE * * *

The permitting authority might not request a risk assessment for every possible metal or PIC

from a combustor. This doesn’t imply, however, that it will only ask for targeted sampling for

COPCs during regulatory performance tests. Based on permitting experience and discussions

with analytical laboratories, we maintain that complete target analyte list analyses conducted

when using U.S. EPA standard sampling methods (e.g., 0010 or 0030) don’t subject facilities to

significant additional costs or burdens during the trial burn process. We recommend that stack

emission samplers strive to collect as much information as possible to characterize the stack

gases generated from the combustion of hazardous waste. Facilities should, then, generally

expect that data collected for the risk assessment may include the following tests: Method

0010, Method 0030 or 0031 (as appropriate), total organic compounds (using the Guidance for

Total Organics, including Method 0040), Method 0023A, Method 26A or 26 (as appropriate),

the multiple metals train, and method for particle size distribution (e.g., CARB 501 or Method

5 Modified with analysis by Scanning Electron Microscopy [SEM]). The permitting authority

might also determine that using other test methods is appropriate for the performance test, to

address detection limit or other site-specific issues. See Table B.1-4 of the Risk Burn Guidance

for Hazardous Waste Combustion Facilities (U.S. EPA 2001c) for a complete list of methods.

RECOMMENDED INFORMATION FOR THE RISK ASSESSMENT REPORT

2.2.1.2 Estimating the Total Organic Emission (TOE) Rate

We recognize that despite all efforts, it might not be possible to identify all the compounds in the

emissions from a facility. This data gap has the potential to underestimate risks and represents a

non-conservative uncertainty. Organic compounds that can’t be identified by laboratory analysis can’t be

defensibly treated as COPC’s in the risk calculations. However, these compounds might still contribute

significantly to the overall risk, and so it’s reasonable to consider them qualitatively in the risk assessment

(DeCicco 1995; U.S. EPA 1994i). 
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U.S. EPA developed the total organic emissions (TOE) test as one approach to account for unidentified

organic compounds because pre-existing methods, such as total hydrocarbon analyzers, don’t fully

determine the total mass of organics present in stack gas emissions (Johnson 1996). We anticipate that

trial/risk burns will generally include the TOE test, in order to provide sufficient information to address

concerns about the unknown fraction of organic emissions. The TOE test is used in conjunction with the

identified organic compounds to calculate a TOE factor. We recommend using the TOE factor to

qualitatively evaluate potential risks from the unidentified fraction of organic compounds in the stack gas. 

The TOE test is the subject of other guidance, such as the Guidance for Total Organics (U.S. EPA 1996d)

with additional clarification provided in Section B.7 of U.S. EPA (2001c). Proper use of TOE data

depends on a good understanding of the test method and how the data is reported. The TOE method

defines total organics as the sum of three fractions:

Fraction 1: Total Volatile Organic Compounds (TOVOC) (referred to as Field GC

Component in the TO Guidance) - The fraction of organic compounds with boiling points less

than 100°C. This VOC fraction is collected using U.S. EPA Method 0040. U.S. EPA Method

0040 allows for quantification of the total mass of organic compounds with boiling points less

than 100°C, determined by summing the gas chromatograph/flame ionization detector results as

described in the TO Guidance.

Fraction 2: Total Chromatographical Semivolatiles (TOSVOC) (referred to as Total

Chromatographical Organics Component in the TO Guidance) - The fraction of organic

compounds with boiling points from 100°C to and including 300°C. This VOC fraction is

collected using modified U.S. EPA Method 0010 procedures as defined by U.S. EPA (1996d). 

The total mass of organic compounds with boiling points 100°C up to and including 300°C is

determined by summing the total gas chromatograph/flame ionization detector results as

described in the TO Guidance.

Fraction 3: Total Gravimetric Compounds (TOGRAV) (referred to as Gravimetric

component in the TO Guidance) - The fraction of organic compounds with boiling points

greater than 300°C. This fraction is determined by using modified U.S. EPA Method 0010

procedures defined by U.S. EPA (1996d), which quantify the mass, above this fractions boiling

point, by measuring the total mass by evaporation and gravimetry (weighing) for nonvolatile total

organics.

Please note that the TO total (TOTOTAL) is the sum of the sums of each fraction. The sum of the TO

fractions is described as follows:
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Equation 2-1

Equation 2-2

where:

TOTOTAL = stack concentration of TO, including identified and unidentified

compounds (mg/m3

)

TOVOC = stack concentration of volatile TO, including identified and

unidentified compounds (mg/m3

)

TOSVOC = stack concentration of SVOC TO, including identified and

unidentified compounds (mg/m3

)

TOGRAV = stack concentration of GRAV TO, including identified and

unidentified compounds (mg/m3

)

Use the TOE data in conjunction with the identified data to compute a TOE factor. Previously-computed

TOE factors range from 2 to 40. The HHRAP defines the TOE factor as the ratio of the TOTOTAL mass to

the mass of identified organic compounds, as calculated by the following equation:

where

FTOE = TOE factor (unitless)

TOTOTAL = total organic emission (mg/m3

)

Ci = stack concentration of the ith identified COPC (mg/m3

)

Identifying the organic compounds in the denominator of Equation 2-2 is one of the most critical

components of the TOE factor. Although the permitting authority may not request that you analyze the

organic compounds with all possible analytical methods, you may wish to consider the effects that gaps in

compound-specific identification may have on the computation of the TOE factor. For example,

hazardous waste-burning cement kilns have expressed concern about the amount of light hydrocarbons

that may evolve from the raw materials processed in the cement kilns, because these light hydrocarbons

have not typically been identified in trial burns. If such concerns are significant, you and the permitting

authority might choose to use additional test methods in the trial burn in order to speciate the maximum

number of organic compounds.

We also generally recommend including tentatively identified compounds (TICs) in the denominator

when computing the TOE factor, so that appropriate credit is given to defensible efforts at identifying the
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maximum number of organic compounds. Finally, we generally recommend that non-detect COPCs be

treated consistently between the risk assessment and TOE evaluation. That is, if a non-detected

constituent is deleted as a COPC (See Section 2.3), then it would not be included in the identified fraction

of the TOE equation. COPCs identified per Section 2.3, but not detected, might be included in the TOE

factor equation at the reliable detection limit (non-isotope dilution methods) or the estimated detection

limit (isotope dilution methods).

It’s important to carefully evaluate the results of the gravimetric fraction when using the TOE factor. 

Both regulated industry and U.S. EPA have expressed some concern that the gravimetric fraction may

over-report the organic fraction. It’s been suggested that the gravimetric fraction may consist of organic

and/or inorganic mass not directly attributable to organic incinerator emissions (U.S. EPA 1997a). The

U.S. EPA Office of Research and Development (ORD) National Risk Management Research Laboratory

(NRMRL) recently conducted a series of experiments to investigate this issue. The results indicate that it

is indeed possible for inorganic mass to become soluble and retained in the TOE train methylene chloride

extract. More importantly, the ORD/NRMRL research identified and demonstrated techniques for

successfully mitigating this problem. Details of the experiments, results, and procedures for mitigating

the GRAV bias will be made available in a forthcoming ORD report. Ultimately, these procedures will be

contained in the forthcoming TOE guidance currently being revised by ORD. Further information on this

topic is also available in U.S. EPA (2001c). 

We recommend using the TOE factor in the uncertainty section of the risk assessment report to evaluate

the risks from the unknown fraction of organics. The permitting authority can then evaluate the TOE

factor and assess to what extent actual risks may be greater than estimated risks. For example, if the risk

from the known portion of the emissions show that risks may be borderline and/or the TOE method shows

that the unknowns are a significant portion of the emission profile, the permitting authority has several

options, including:

1. Describe in a narrative form what is known of the unknown portion of the emissions.

2. As a bounding estimate, attribute a risk to the unknown portion of the emissions. 

An example is presented as a preferred option in U.S. EPA (1994f), which assumes that

the unknown compounds are similar in toxicity and chemical properties to the known

compounds taken as a whole. The referenced equation is as follows:
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Equation 2-2A

where

Q i,adj = adjusted emission rate of compound i (g/s)

Q i , = emission rate of compound i (g/s)

TOTOTAL = total organic emission (mg/m3

)

Ci = stack concentration of the ith identified COPC (mg/m3

)

3. Recommend additional testing to identify a greater fraction of the organic compounds.

4. Specify permit conditions that further control total organic emissions or that further 

control the risks associated with known emissions.

Variations of the TOE factor can be useful to address site-specific concerns. For example, compute three

separate TOE factors based on the apportioning provided by the TOE test (i.e., TOVOC, TOSVOC, and

TOGRAV). Then evaluate the unknowns associated with each fraction of unidentified organic compounds

separately.

2.2.2 Estimating Emission Rates for Facilities with Multiple Stacks

We generally recommend that the risk assessment consider emissions from all combustors burning

hazardous waste at a facility, not just the unit currently undergoing the permitting process. As discussed

further in Chapter 3, air dispersion modeling for each combustor (source) is frequently conducted

separately, to evaluate risk on a stack- or source-specific basis. An example case is a chemical

manufacturing facility which operates both an on-site incinerator and several hazardous waste-burning

boilers. Whether it is the incinerator or the boilers being permitted, the risk assessment considers the

emissions from all the combustors in the estimate of facility risk. In addition to RCRA combustors,

emissions from other RCRA treatment, storage, or disposal units (e.g., open burning/open detonation and

thermal desorption) might also be included in the risk evaluation in some cases.

2.2.3 Estimating Stack Emission Rates for Facilities Not Yet Operational

The permitting process for new hazardous waste combustion facilities includes submitting information of

sufficient detail for the regulatory authority to evaluate compliance with existing regulations, guidance,

and standards of protectiveness. Stack (or other source) locations and dimensions, design flow and
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emission rate estimates, waste feed characteristics, surrounding building dimension data, facility plot

plans, and terrain data are frequently reviewed and used in a pre-operation risk assessment. This assists

decision-making and designing permit requirements. 

We generally recommend reviewing design emission rates, waste feed characteristics, and other design

data, along with supplementary documentation, to make sure they are representative, accurate, and

comprehensive. Good engineering practice dictates a check of, and comparison with, data from similar

existing units. Stack test reports for facilities of similar technology, design, operation, capacity, auxiliary

fuels, waste feed types, and APCSs can be useful in estimating COPC emission rates for new facilities

that have not been constructed. In addition to design data, particle size distribution data from a similar

type unit that is operational may be useful. Estimated emission rates used to complete pretrial burn risk

assessments are frequently compared to the measured emission rates from actual performance tests

completed after the new facility receives a permit, is constructed and operational.

If surrogate data from similar facilities aren’t available, some state environmental agencies enforce

emission rate limits based on state laws. Since these limits cannot be exceeded, you could use them to

develop emission rate estimates for the risk assessment. A trial or risk burn could then demonstrate that

facility emissions are less than those considered in the permit and risk assessment. 

2.2.4 Estimating Stack Emission Rates for Facilities Previously Operated

We generally recommend that the risk assessment also consider emissions from the historical operation of

other combustors burning hazardous waste at the facility, not just the unit currently undergoing the

permitting process. The permitting authority will determine the appropriateness of this on a case-by-case

basis. An example case might be when the emissions from historical operation of a source or sources

have already resulted in potential risk concerns at or near the facility. You could model emissions from

historical operations as a separate source or, if applicable, include them in the fate and transport equations

by adding the previous years of operation to the anticipated time period of combustion for an existing or

newly operating source. In some cases, you might also include historical emissions from other RCRA

treatment, storage, or disposal units at the facility (e.g., open burning/open detonation and thermal

desorption) in the risk assessment, in addition to RCRA combustors.
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C All stack test reports for combustors used to develop emission rate estimates

C If using surrogate data to assess a new facility, descriptions of how the combustion data used

represent similar technology, design, operation, capacity, auxiliary fuels, waste feed types,

APCSs, and particle size distributions

C Demonstration that the data used to develop the emission rate estimates were collected using

appropriate U.S. EPA sampling and analysis procedures

C The range of data obtained, and values used, in completing the risk assessment

RECOMMENDED INFORMATION FOR THE RISK ASSESSMENT REPORT

2.2.5 Emissions From Process Upsets

It is possible for unburned hazardous waste to be emitted through the stack as a result of various process

upsets, such as start-ups, shutdowns, and malfunctions of the combustion unit or APCS. Emissions can

also be caused by operating upsets in other areas of the facility (e.g., an upset in a reactor which vents

gases to a boiler burning hazardous waste could trigger a process upset in the boiler, resulting in increased

emissions). U.S. EPA (1994i) indicates that upsets aren’t generally expected to significantly increase

stack emissions over the lifetime of the facility. 

To account for the increased emissions associated with process upsets, we generally recommend that the

stack emission rates estimated from trial burn data be multiplied by an upset factor. The upset factor is

not applied to non-PIC emission rate estimates where the total mass of a constituent in the waste feed is

assumed to be emitted. When available, site-specific emissions or process data can be useful to estimate

the upset factor. You may also want to consider and evaluate the following types of data to derive the

upset factor:

C Data from continuous emissions monitoring systems that measure stack carbon

monoxide, oxygen, total hydrocarbon (if requested), or opacity (if appropriate)

C Data on combustion chamber, APCS, or stack gas temperature

C Data on hazardous waste residence time

C Frequency and causes of automatic waste feed cutoffs (AWFCO)

C Frequency of start-up and shut-down events

C Ratio of AWFCO frequency and duration to operating time
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C Historical operating data demonstrating the frequency and duration of process upsets

C A discussion of the potential cause(s) of the process upsets

C Estimates of upset magnitude or emissions

C Calculations which describe the derivation of the upset factor.

RECOMMENDED INFORMATION FOR THE RISK ASSESSMENT REPORT

C APCS operating variables like baghouse pressure drop, liquid scrubber flow rate, or

electrostatic precipitator voltage

C Stack test data collected while the combustor was operated under upset conditions

You might use this information to estimate the magnitude of the increase in emissions and the percentage

of time, on an annual basis, that the unit operates at upset conditions. Additional information regarding

upset factors for liquid-burning BIFs is available in the Louisiana Chemical Association (LCA) Letter

Report on Upset Factors, dated October 27, 1999, available on the U.S. EPA Region 6 web site

(www.epa.gov/region06/).

If you don’t have site-specific data, or they are inappropriate for deriving an upset factor, we generally

recommend estimating upset emission rates using a procedure based on work by the California Air

Resources Board (CARB) (1990).

Estimating Emissions from Process Upsets: To represent stack emission rates during process

upsets, multiply the emission rate developed from the trial burn data by 2.8 for organics and 

1.45 for metals. These factors are derived by assuming that emissions during process upsets are

10 times greater than emissions measured during the trial burn. Since the unit doesn’t operate

under upset conditions continually, the factor is adjusted to account for only the period of time,

on an annual basis, that the unit operates under upset conditions. For organic compounds, the

facility is assumed to operate as measured during the trial burn 80 percent of the year and operate

under upset conditions 20 percent of the year [(0.80)(1)+(0.20)(10)=2.8]. For metals, the

combustor is assumed to operate as measured during the trial burn 95 percent of the year and

operate under upset conditions the remaining 5 percent of the year [(0.95)(1)+(0.05)(10)=1.45].

Catastrophic process upsets brought about by complete failure of combustion and air pollution control

systems (e.g. resulting from non-routine events such as explosions, fires, and power failures) are typically 

considered accidental releases and consequently aren’t addressed by this guidance.
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2.2.6 RCRA Fugitive Emissions

RCRA fugitive emission sources frequently evaluated in site-specific risk assessments include waste

storage tanks; process equipment ancillary to the combustor; and the handling and disposal of combustion

system residues such as ash. Fugitive emissions from other RCRA treatment, storage, or disposal units

(e.g., landfills) may also warrant evaluation in some cases. 

This section contains guidance for quantitatively estimating fugitive emissions using procedures outlined

in other U.S. EPA guidance. Guidance regarding air dispersion modeling of fugitive emissions is

presented in Chapter 3.

2.2.6.1 Quantitative Estimation of RCRA Fugitive Emissions from Process Equipment

We generally recommend the following series of steps to quantitatively estimate RCRA fugitive

emissions: (1) identify equipment to evaluate as a fugitive emission source(s); (2) group equipment, as

appropriate, into a combined source; and (3) estimate compound-specific emission rates for each resulting

source. We illustrate an example in Figures 2-1 and 2-2 and Tables 2-1 and 2-2, to help explain the

recommended steps. Figure 2-1 presents the plot plan of a hypothetical facility that includes one RCRA

combustion unit (CU-1), two hazardous waste feed storage tanks (WST-1 and WST-2), and ancillary

equipment identified in a RCRA Part B permit application.

Step 1: Identify Fugitive Emission Sources - Generally, identify RCRA fugitive emission sources such

as waste storage tanks and process equipment that comes in contact with a RCRA hazardous

waste. Such equipment is specified in Title 40, Code of Federal Regulations (40 CFR) Part 265,

Subpart BB. Equipment covered under Subpart BB includes:

C Pumps

C Valves

C Connectors (flanges, unions, tees, etc.)

C Compressors

C Pressure-relief devices

C Open-ended lines

C Product accumulator vessels

C Sampling connecting systems

C Closed vent systems
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C Agitators

Note each fugitive emission source on a facility plot map with a descriptor and the location 

denoted with Universal Transverse Mercator (UTM) coordinates (specify if North American

Datum [NAD] of 27 or NAD83).

Step 2: Group Equipment Into a Combined Source - To significantly reduce the effort required to

complete air dispersion modeling and the subsequent risk assessment, group equipment in close

proximity, and evaluate as a single combined source. The speciated emission rates for the group

are the summation of the emissions from the grouped individuals. Clearly denote on a facility

plot plan or map the area extent of the grouped or combined source, as defined by UTM

coordinates (specify if NAD27 or NAD83). Define the area extent of the combined source using

the actual locations of the equipment being grouped, without exaggeration to cover areas without

fugitive sources. It may also be useful to consider how fugitive emission sources are to be

defined when conducting the air dispersion modeling (see Chapter 3).

Equipment in two areas of the hypothetical facility shown in Figure 2-1 are grouped into combined

sources; these consist of the Waste Feed Storage Area and the RCRA Combustor Area.

Step 3: Estimate Fugitive Emissions from Tanks - Obtain fugitive emission rates for waste storage tanks

from the facility’s emission inventory or Title V air permit application prepared in compliance

with Clean Air Act Amendments of 1990 (see example provided as Figure 2-2). If that

information is not available, fugitive emissions from storage tanks can be calculated using U.S.

EPA’s TANKS Program or by following the procedures outlined in U.S. EPA (1995a),

“Compilation of Air Pollution Emission Factors, January 1995.”

The information needed to accurately estimate fugitive emission rates from storage tanks

includes, but is not limited to:

C Dimensions of the tanks

- Shell height and diameter

C Characteristics of the tank roof

- Color and shade

- Condition (e.g., poor, good)

- Type (e.g., cone, dome)

- Height

- Radius or slope

- Fixed or floating

C Characteristics of the shell

- Color and shade

- Condition (e.g., poor, good)

- Heated

C Settings on breathe vents

- Vacuum setting
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- Pressure setting

C Characteristics of the stored liquids

- Maximum and annual average liquid height

- Working volume

- Turnovers per year

- Net throughput

- Average annual temperature

- Vapor pressures of speciated constituents (at annual average temperature)

Step 4: Estimate Fugitive Emissions from Process Equipment - Estimate fugitive emissions for each

type of equipment listed under 40 CFR Part 265, Subpart BB by using the following four

approaches, listed in order of increasing refinement and data requirements:

C Average Emission Factor Approach (AEFA)

C Screening Ranges Approach (SRA)

C U.S. EPA Correlation Approach (EPACA)

C Unit-Specific Correlation Approach (USCA)

These four approaches would generally be applicable to estimate fugitive emission rates of volatile

organic compounds (VOCs) from equipment on any facility. Except for the AEFA method, all of the

approaches need screening data collected using a portable monitoring device (PMD). Because data on

fugitive emissions at a facility is typically limited, the AEFA method is expected to be used in most cases,

and therefore has been selected for use in the example illustrated in Figure 2-1, and Tables 2-1 and 2-2. 

However, we recommend using more refined approaches such as SRA, EPACA, or USCA, if sufficient

data is available. U.S. EPA (1995k) provides a detailed discussion on these three approaches. Additional

information on estimating fugitive emission rates is available in U.S. EPA (1995k), “Protocol for

Equipment Leak Emission Estimates, EPA-453/R-95-017."
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FIGURE 2-1

EXAMPLE FACILITY PLOT MAP
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FIGURE 2-2

EXAMPLE EMISSIONS INVENTORY
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TABLE 2-1

EXAMPLE CALCULATION

TOTAL FUGITIVE EMISSION RATES FOR EQUIPMENT IN WASTE FEED STORAGE ARE

1 2 3 4 5 6 7 8 

Fugitive

Emission

Source

Waste

Stream

Type of Waste

Stream In

Service

Equipment

Type

Number of Each

Equipment

Type Per Waste

Stream

Equipment Emission

Factors Total VOC

Weight

Fraction

Operational

Time Period of

Equipment

(days)

Em

Eq

(kg/hr) (g/sec) 

Waste

Feed

Storage

Area

Process

A

Wastes

Light Liquid Pumps 3 0.01990 0.00553 0.9 180 

Light Liquid Valves 70 0.00403 0.00112 0.9 180 Light Liquid Connectors 30 0.00183 0.00051 0.9 180 Light Liquid Tank WST-1 1 -- -- 0.9 180 Light Liquid Tank WST-2 1 -- -- 0.9 180 

Process

B

Wastes

Heavy Liquid Pumps 2 0.00862 0.00239 0.6 180 Heavy Liquid Valves 75 0.00023 0.00112 0.6 180 Heavy Liquid Connector 50 0.00183 0.00051 0.6 180 Heavy Liquid Tank WST-1 1 -- -- 0.6 0 Heavy Liquid Tank WST-2 1 -- -- 0.6 0 

Notes:

Column 1 Equipment in the Waste Feed Storage Area was identified and grouped as a combined RCRA fugitive emission source with an are

coordinates (NAD83).

Column 2 The waste streams serviced by equipment in the Waste Feed Storage Area can be determined through review of the facility's RCR

Emission Standards. 

Column 3 The type of waste stream in service, defined as light or heavy for determination of equipment-specific emission factors, can be d

stream vapor pressure.

Column 4 Similar types of equipment can be grouped according to the most applicable equipment-specific emission factor and type of waste 

provided in U.S. EPA (1995k).
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Column 5 The number of equipment type (per waste stream) identified in column 3.Column 6 Emission factors specific to each type of equipment can be obtained from U.S. EPA (1995k), with the exception of storage tanks. Column 7 Weight fraction of total volatile organic compounds was obtained from dividing the concentration of VOCs (mg/L) by the density 

Column 8 Assumed the equipment is operational for 180 days a year.Column 9 Equipment-specific fugitive emission rates were determined by multiplying Columns 5, 6, and 7. Emission rates for tanks were o

application. In the absence of such data, emission rates for tanks can be calculated using U.S. EPA’s TANKS Program or by foll

U.S. EPA (1995a).

Column 10 The total fugitive emission rate for each waste stream is determined by summing emission rates for all the equipment. Table 2-2 

speciated fugitive emissions.
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TABLE 2-2

EXAMPLE CALCULATION

SPECIATED FUGITIVE EMISSIONS

FOR EQUIPMENT IN WASTE FEED STORAGE AREA

1 2 3 456

Fugitive

Emission

Source Waste Stream

Waste Stream

Composition

Weight Fraction

of Each VOC In

Waste Stream

(%)

Total

Fugitive

Emission

Rate

(g/sec)

Speciated

Fugitive

Emissions (g/sec)

Waste Feed

Storage Area

Process A Wastes

Acetaldehyde 0.20 0.14926 0.0030

Acetonitrile 0.25 0.0037

2-Nitropropane 0.25 0.0037

Nitromethane 0.20 0.0030

Process B Wastes

Acetaldehyde 0.20 0.06857 0.0137

Acetonitrile 0.10 0.0069

Methanol 0.20 0.0137

Propionitrile 0.05 0.0034

Notes:

Column 1 Equipment in the Waste Feed Storage Area was identified and grouped as a combined RCRA

fugitive emission source with an aerial extent defined by UTM coordinates (NAD83).

Column 2 The waste streams serviced by equipment in the Waste Feed Storage Area can be determined

through review of the facility’s RCRA Part B Permit Application, Air Emission Standards. 

Column 3 The waste stream composition can be determined from analytical data

Column 4 Weight fraction of compounds in the waste stream can be determined from analytical data or review

of the facility’s Title V Air Permit Application, Emissions Inventory Questionnaire (EIQ) for Air

Pollutants (see example in Figure 2-2). 

Column 5 The total fugitive emission rate for each waste stream was obtained from Column 10, Table 2-1. 

Column 6 Speciated fugitive emissions were obtained by multiplying Column 4 and 5.

An Example Calculation Using the AEFA Method

Information needed to estimate fugitive emission rates using the AEFA method includes: 

C Type of waste stream associated with each equipment type (Columns 2 and 3, Table 2-1)

- light liquids are those in which the sum of the concentration of individual

constituents with a vapor pressure over 0.3 kilopascals (kPa) at 20°C is greater

than or equal to 20 weight percent

- heavy liquids are all others liquids not meeting the definition of light liquids as

specified above
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C Number of each equipment type associated with each waste stream (Columns 4 and 5,

Table 2-1) 

C Total VOC weight fraction of each waste stream (Column 7, Table 2-1) 

C Weight fraction of each VOC in each waste stream (Columns 3 and 4, Table 2-2)

C Operational time period of equipment (Column 8, Table 2-1)

In the AEFA method, equipment is grouped by waste streams of similar characteristics and VOC

composition (Columns 1 and 2, Table 2-1). However, the AEFA method doesn’t account for different

site-specific conditions such as temperature, vapor pressure, or screening values, among process units

within a source category. Site-specific factors can significantly influence fugitive emission rates of leaks

from equipment.

U.S. EPA (1995k) presents the average emission factors (Column 6, Table 2-1) for synthetic organic

chemicals manufacturing industry process units, refineries, and natural gas plants. The following table is

an excerpt from this guidance document. These emission factors are most valid for estimating rates of

emissions from a grouping of equipment over a long time period.

TABLE 2-3

SOCMI AVERAGE EMISSION FACTORS

Equipment type Service

Emission factor

(kg/hr/source)

Valves Gas

Light liquid

Heavy liquid

0.00597

0.00403

0.00023

Pump seals Light liquid

Heavy liquid

0.0199

0.00862

Compressor seals Gas 0.228

Pressure relief valves Gas 0.104

Connectors All 0.00183

Open-ended lines All 0.0017

Sampling connectors All 0.0150

Source: U.S. EPA (1995k)
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C Summary of the step-by-step process conducted to evaluate fugitive emissions

C Facility plot map clearly identifying each fugitive emission source with a descriptor and the

location denoted with UTM coordinates (specify if NAD27 or NAD83).

C Speciated emission rate estimates for each waste stream serviced by each source, with

supporting documentation

C Applicable discussion of monitoring and control measures used to mitigate fugitive emissions

RECOMMENDED INFORMATION FOR THE RISK ASSESSMENT REPORT

To calculate the total VOC emissions rate for a specified equipment type, multiply the equipment

emission factor by the total VOC weight fraction and the number of each equipment type per waste

stream (Column 9, Table 2-1 = Column 6 x Column 7 x Column 5).

Generate the total fugitive emission rate for the waste stream (Column 10, Table 2-1) by summing the

total VOC emission rates for each equipment type. Speciated fugitive emissions are then calculated by

multiplying the weight fraction of each VOC in the waste stream and the total fugitive emission rate for

the waste stream (Column 6, Table 2-2 = Column 4 x Column 5). This speciated emission rate is the

emission rate used in the risk assessment.

2.2.6.2 Fugitive Emissions from Combustor Leaks

We recommend that when appropriate, the risk assessment evaluate fugitive emissions resulting from the

construction, design, or operation of a hazardous waste combustor. Examples of fugitive emissions from

combustor leaks include:

C Combustors operating under negative pressure may experience temporary positive pressures

(“puffing”) that cause fugitive emissions. This condition can occur when a slug of high BTU

waste is combusted, causing a rapid expansion in the volume of combustion gases that exceeds

the volume of the combustion chamber.

C Fugitive emissions resulting from the day-to-day operation of the combustor and APCS. These

emissions will typically include (1) leaks that occur due to a positive pressure in the APCS, and

(2) routine maintenance activities such as replacement of baghouse collection bags.
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C Process design information and drawings (if necessary)

C Past operating data indicating the frequency, duration, and magnitude of combustor leaks

C Information regarding the probable cause of combustor leaks

C Summary of procedures in place to monitor or minimize fugitive emissions resulting from

combustor leaks

RECOMMENDED INFORMATION FOR THE RISK ASSESSMENT REPORT

Currently, we don’t offer any specific guidance on how to quantitatively estimate fugitive emissions from

hazardous waste combustors. However, if no site-specific quantitative methods are available, one option

is to address risks associated with leaks in the uncertainty section of the risk assessment. Under such an

approach, the permitting authority could review facility-specific data to determine whether or not the

design addresses equipment leaks and whether the operational data indicate that equipment leaks may be

a problem. 

2.2.7 RCRA Fugitive Ash Emissions

Burning hazardous waste may produce flyash. Fugitive particle emissions may result from the associated

collection, handling, and disposal of the flyash. Typically, fugitive emissions of flyash collected from an

air pollution control device (APCD) will occur during transfer into covered trucks or other conveyance

mechanisms prior to disposal. Emissions generated during the loading process can be controlled by

APCDs or other types of equipment. However, some of the flyash may still escape into the atmosphere as

fugitive emissions. 

We generally recommend the following steps to quantitatively estimate RCRA fugitive ash emissions: 

(1) determine an empirical emission factor, (2) estimate the flyash generation rate, and (3) account for air

pollution control equipment, if applicable. As demonstrated in the example calculation below, it is then

possible to estimate the fugitive ash emission rate by multiplying the empirical emission factor by the

flyash generation rate and, if applicable, the control deficiency of the air pollution control equipment. 
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Step 1: Determine an Empirical Emission Factor - One approach to estimate particle emissions

associated with flyash loading and unloading is to use an empirical emission factor of 1.07 lb per

ton flyash. This factor is based on a field testing program conducted at a coal fired power plant

equipped with an electrostatic precipitator (ESP) (Muleski and Pendleton 1986). Because

burning coal and hazardous wastes are similar activities, flyash generated from similar control

devices is expected to behave similarly under the same conditions, with respect to fugitive

emissions. In general, particle behavior is dependent more on the physical form of the flyash than

on the feed (or waste) stream being burned. The emission factor determined during the empirical

study (0.107 lb per ton flyash) can be adjusted by a factor (e.g., 10) to account for the fact that the

flyash from burning coal (in the study) was wetted. Depending on the facility, the flyash from the

hazardous waste combustion facility may or may not be wetted.

Step 2: Estimate the Flyash Generation Rate - Obtain the APCD flyash generation rate from the Part B

Permit Application. Obtain the total ash content of the “generic” waste streams created from the

waste profile. Both values should be approximately the same. Since a major portion of ash fed to

the combustor is converted to bottom ash, it is likely that this value can be assumed to be a high

estimate of the actual flyash generation rate.

Step 3: Account for Air Pollution Control Equipment - If an APCD is used for controlling emissions

during flyash handling operations, you can generally apply an efficiency factor (e.g., 99.5

percent) to the emission rate. An efficiency factor of 99.5 percent is based on typical collection

efficiencies of particulate matter control devices, for the particle sizes in the range of 2.5 to 10 um

(U.S. EPA 1995a).

Example Calculation

Multiply the empirical emission factor (Step 1) times the estimated flyash generation rate (Step 2): 

[(1.07 lb per ton) * (5,000 tons per year) = 5,350 lbs per year]. 

To account for the air pollution control equipment, multiply the product of Steps 1 and 2 times one minus

the fabric filter efficiency (Step 3) to calculate the final RCRA fugitive ash emission rate for use in the

risk assessment: 

[(5,350 lbs per year) * (1 - 0.995) = 26.75 lbs per year].

2.2.8 Cement Kiln Dust (CKD) Fugitive Emissions

CKD is the particulate matter (PM) that is removed from combustion gas leaving a cement kiln. This PM

is typically collected by an APCS—such as a cyclone, baghouse, ESP—or a combination of APCSs. 

Many facilities recycle a part of the CKD back into the kiln. Current and applicable guidance on

evaluating CKD includes (1) the Technical Background Document for the Report to Congress (U.S. EPA

1993g), and (2) the regulatory determination of CKD (60 FR 7366, February 7, 1995). 
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Most CKD constituents (for example, metals) aren’t volatile but could be released to air through fugitive

dust emissions as volatile or semivolatile organics. These emissions can be in gaseous form and present

in relatively low concentrations, if at all (U.S. EPA 1993a). Dust particles may be suspended in the air by

either wind erosion or mechanical disturbances. The extent to which dust is blown into the air by wind

erosion depends on several site-specific characteristics, including (1) the texture (particle size

distribution) and moisture content of the CKD on the surface of piles, (2) non-erodible elements, such as

clumps of grass or stones on the pile, (3) presence of a surface crust, and (4) wind speeds. Mechanical

disturbances that can suspend CKD constituents in the air include (1) vehicular traffic on and around

CKD piles, (2) CKD dumping and loading operations, and (3) transportation of CKD around a plant site

in uncovered trucks. Cement plants may use various control measures to limit the release of CKD to the

air. For example, CKD may be pelletized in a pug mill, compacted, wetted, and covered to make the

material less susceptible to wind erosion.

To keep the dust down, many facilities add water to CKD before disposal, to agglomerate individual

particles. In addition, as CKD sits in a pile exposed to the elements, occasional wetting by rainfall may

form a thin surface crust in inactive areas of the pile. This acts to mitigate air entrainment of particles. 

However, based on field observations by U.S. EPA (1993g), neither surface wetting nor natural surface

crusting eliminates the potential for CKD to be blown into the air. Wetting the dust before disposal

provides incomplete and temporary control because water is infrequently applied, and the dust ultimately

dries and returns to a fine particulate that is available for suspension and transport. Similarly, a surface

crust may develop, but (1) the crust breaks when vehicles or people move on the pile, and (2) fresh dust is

regularly added to the pile, providing a continual, exposed reservoir of fine particles. Please note that a

crust doesn’t always form, for a variety of reasons such as weather and CKD chemistry.

CKD constituents that are released to the air are transported and dispersed by the winds, and are

ultimately deposited onto land or water, either by settling in a dry form or by being entrained in

precipitation.

2.2.8.1 Composition and Characteristics of CKD

We evaluated the potential direct and indirect risks resulting from on-site and off-site management of

CKD (U.S. EPA 1993g; 1993h). These studies highlight the limited amount of available information

regarding variation in the chemical constituents of CKD generated by facilities burning hazardous waste
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C Physical data, including particle size distribution and density

C Chemical data, including organic and inorganic analytical tests similar to those used for

sampling combustion gases

C Plant net CKD generation rate (how much CKD per year that is available for disposal)

C Ambient air monitoring data

C CKD management, transportation, storage, and disposal methods

C Containment procedures, including fugitive dust prevention measures and the area of exposed

CKD

C Meteorological data, including wind speed and precipitation

RECOMMENDED INFORMATION FOR THE RISK ASSESSMENT REPORT

as fuel, and by facilities burning only fossil or nonhazardous waste fuels. There may also be differences

in composition between the “as-generated” CKD -- a portion of which is recycled back into the system –

and the “as-managed” CKD that is disposed of on or offsite.

The air exposure pathway is generally of concern for CKD, because the dust is a fine PM that is readily

suspendable, transportable, and respirable in air. In general, particles that are #100 micrometers can be

suspended in the wind and transported. Within this range, particles that are #30 micrometers can be

transported for considerable distances downwind. However, particles that are #10 micrometers are of

primary concern for respiration by humans (U.S. EPA, 1993g). Virtually all of the dust generated at the

15 facilities evaluated by U.S. EPA (1993g) in the Cement Kiln Dust Report to Congress may be

suspended and transported in the wind (that is, the vast majority of particles are #100 micrometers), and

over two-thirds of all CKD particles generated may be transported over long distances. Additionally, a

significant percentage of the total dust generated (from 22 to 95 percent, depending on kiln type)

comprises respirable particles that are #10 micrometers.

2.2.8.2 Estimating CKD Fugitive Emissions

In general, the HHRAP doesn‘t address quantitative estimation of risk from fugitive CKD emissions. 

However, risk assessments of cement manufacturing facilities are still able to evaluate the fugitive CKD

emissions qualitatively. The Technical Background Document for the Report to Congress (U.S. EPA
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1993g), includes methods to estimate the magnitude of fugitive emissions from the handling, storage, and

disposal of CKD. Sampling data of CKD collected during maximum waste metal feed rate conditions

from the trial burn, risk burn and/or certification of compliance tests may also be useful in evaluating

CKD fugitive emissions. You can then evaluate it qualitatively by comparing the risks estimated for the

kiln stack emissions, to the high end national screening level estimated by U.S. EPA for CKD in U.S.

EPA (1993g) and the regulatory determination of CKD (60 FR 7366, February 7, 1995). If the risks are

equivalent, the combined risks appear significant, or the risks attributed to the CKD are greater than the

risks estimated for the kiln stack emissions, it might be appropriate to evaluate the risk from CKD

emissions in a more quantitative fashion. We generally recommend that the permitting authority make

sure that any qualitative evaluation includes a comparison of the conditions at the facility to the

conditions at the model facilities we evaluated in U.S. EPA (1993g; 1993h). In addition, an analysis of a

specific facility’s compliance with other risk-based environmental statutes and regulations is often an

appropriate method to qualitatively evaluate risks associated with the handling, storage, and disposal of

CKD. 

2.3 IDENTIFYING COMPOUNDS OF POTENTIAL CONCERN

Compounds of potential concern (COPCs) are those compounds evaluated throughout the risk

assessment. There is no universal list of COPCs, because a compound that’s a COPC for one combustor

may not be a COPC for another combustor. COPCs in the emissions from hazardous waste combustors

vary widely, depending on the type of

< combustor, 

< fuel and hazardous waste feed being burned, and 

< APCS used. 

COPCs include metals, products of incomplete combustion (PICs), and/or reformation products. PICs are

any organic compounds emitted from a source that are present in the feed stream (even in trace amounts)

and not completely destroyed in the combustion process. Reformation products are organic compounds

that are formed immediately after combustion, due to interaction of specific constituents in the

combustion gasses and specific unit operating conditions relative to a particular combustion process and

associated air pollution control equipment.
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PICs can be formed by trace toxic organic compounds in the waste feed stream. Therefore, we generally

recommend evaluating these trace compounds as PIC precursors, in addition to those compounds more

prevalent in the hazardous waste feed. Don’t confuse PICs with principal organic hazardous

constituents (POHCs). POHCs are compounds in the waste feed stream used during a performance test

burn to measure combustor DRE. Unburned POHCs and partially destroyed or reacted POHCs are PICs,

but PICs are not necessarily POHCs. We’ve typically subdivided COPCs into seven different constituent

categories (U.S. EPA 1994g; 1994i; 1994j; 1994n):

C Polychlorinated dibenzo(p)dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs)

C Polynuclear aromatic hydrocarbons (PAHs)

C Polychlorinated biphenyls (PCBs)

C Nitroaromatics

C Phthalates

C Other organics

C Metals

Table A-1 (Appendix A) presents a comprehensive list of compounds typically found (1) in hazardous

waste, and (2) in hazardous waste combustion stack gas emissions. Table A-1 identifies the Chemical

Abstracts Service (CAS) number for each compound, and states whether the compound has been

identified as a carcinogen. Table A-1 also indicates whether a compound has been identified as a

potential COPC by 

• U.S. EPA and state risk assessment reference documents, 

• emission test results that have identified the compound in the emissions from hazardous

waste combustion facilities, or 

• other literature that suggests that the risks from the compound may be significant. 

We provide Table A-1 to help you make sure that the performance test program considers the full range

of compounds potentially emitted from a combustor, and the appropriate analytical method. A risk

assessment won’t necessarily evaluate every metal, potential PIC, and reformation product listed in

Table A-1. Once the performance tests are completed, we recommend selecting the risk assessment

COPCs from the stack test data and available facility-specific process information, rather than Table 

A-1. 

Identify COPCs from the trial/risk burn data based on their potential to pose increased risk or hazard via

one or more of the direct or indirect exposure pathways. We recommend focusing on compounds that

• are likely to be emitted because they (or their precursors) are present in the waste feed,
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• are likely to be emitted because they are likely reformation products, 

• are potentially toxic to humans, and/or 

• have a tendency to bioaccumulate or bioconcentrate in food chains.

Appendix A discusses carcinogenic and noncarcinogenic toxicity of specific compounds. The toxicity

information provided in the HHRAP Companion Database is for informational purposes, to help you

explain the basis for selecting COPCs. Please keep in mind that toxicity benchmarks and slope factors

might change as additional toxicity research is conducted. We recommend consulting the hierarchy of

human health toxicity data (see Appendix A, Section A.2.6) before completing the risk assessment, to

make sure that you use the most current toxicity data.

We generally recommend the following six-step approach (illustrated in Figure 2-3) for identifying the

COPCs to evaluate in a site-specific risk assessment (U.S. EPA 1994i). 

Step 1: Evaluate analytical data from the stack tests performed during the regulatory test burn program,

and compounds associated with fugitive emissions (see Section 2.2.6). Prepare a list that includes

all the compounds specified in the analytical methods performed in the stack tests, and all

compounds found in the fugitive emissions evaluation. Also include compounds of concern due

to site-specific factors (e.g., community and regulatory concern, high background

concentrations), as well as PCDD/PCDFs, PAHs, and PCBs if not otherwise included. Notate

whether each compound was detected or not detected.

In the recommended approach, a detection in any one of the sampling components (e.g., front half rinse,

XAD resin, condensate, Tenax tube), in any run constitutes a detection for that specific compound. 

Evaluating blank contamination results [included in the quality assurance (QA) data section of the trial

burn report] may be relevant when determining the non-detect status of the compounds (see Section 2.5).

Regardless of the analytical methods performed in the regulatory test burn program, we recommend that

risk assessments consider PCDD/PCDFs, PAHs, and PCBs (the rationale for including these compounds

is discussed in greater detail under Step 3 and in Sections 2.3.1 through 2.3.3).

Steps 2 through 4 are unnecessary for compounds detected in the stack test data analysis or identified in

the fugitive emissions evaluation; they may jump to Step 5. All other compounds continue to Step 2.
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Fugitive

emissions data

Trial/risk burn

analysis

Site-specific

concerns

Trial/risk burn analytes and 

fugitive emissions,

PLUS compounds:

* With related site-specific factors;

* Otherwise recommended 

Is non-detected 

compound present in:

Waste being burned; OR

other materials fed to 

unit?

Was compound detected?

Does non-detect 

have a high potential

To be emitted as a 

PIC /Ref. product?

Is toxicological 

data available?

Yes

Yes

Yes

No

No

List of Tentatively

Identified Compounds

(TICs)

with peaks >= 10%

of full scale

DELETE FROM LIST

List of COPCs

for

QUALITATIVE

assessment, using 

surrogate toxicity data 

from a similar 

compound

List of COPCs

for 

QUANTITATIVE 

human health 

risk assessment

Are there:

Related site-specific factors

AND is it 

possibly emitted?

No

No

Yes

NO

YES

STEP 1

STEP 2

STEP 3

STEP 4

STEP 6

STEP 5

FIGURE 2-3

COPC IDENTIFICATION
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Step 2: Evaluate all wastes that the unit will be permitted to burn. Retain for evaluation any non-detected

compound present in the waste (Section 2.4 discusses estimating concentrations for non-detects).

For example, if a facility is permitted to burn explosives which characteristically include nitroaromatic

compounds, yet the stack test didn’t detect any nitroaromatic compounds, it may be appropriate for

nitroaromatic compounds to still be evaluated in the risk assessment. It is prudent to also consider other

materials fed to the combustor (e.g. raw materials, or coal in a cement kiln). 

Steps 3 and 4 are unnecessary for constituents retained as part of the Step 2 evaluation; they may jump to

Step 5. All other compounds, i.e. non-detected compounds that did not satisfy Step 2, continue to Step 3.

Step 3: Retain for evaluation any non-detect with a high potential to be emitted as a Product of

Incomplete Combustion (PIC).

As defined earlier, PICs are either present in the feed stream and not completely destroyed, or formed

during the combustion process. It’s therefore important to consider combustion chemistry in identifying

COPCs. For example, PCDDs and PCDFs may not themselves be found in any feed stream yet still be

emitted, because they can form when chlorine-containing chemicals react with organic matter in the lowtemperature regions of the combustion unit or APCS. We therefore generally recommend that PCDDs

and PCDFs be assessed. The potential for various PICs to be found in combustor emissions is dealt with

in more detail in Sections 2.3.1 through 2.3.13, as well as EPA (2001c).

Identifying/including some compounds (nitroaromatics, phthalates, hexachlorobenzene, and

pentachlorophenol) as PICs in the risk assessment may be warranted, considering waste feed composition

and their potential to be emitted (e.g., nitrogenated wastes, plastics, or highly chlorinated organic waste

streams) (see Sections 2.3.4 through 2.3.6).

Step 4 is unnecessary for PCDDs/PCDFs, PAH’s, PCB’s, and other compounds with high potential to be

emitted as PICs; they may jump to Step 5. All other compounds, i.e. non-detected compounds that did

not satisfy Steps 2 or 3, continue to Step 4.
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Step 4: Retain for evaluation those compounds that (1) are a concern due to site-specific factors, and

(2) may be emitted by the combustor.

As mentioned in Step 1, site-specific factors may contribute COPCs. For example, if there is

community/regulatory concern about high background concentrations of a substance which would not

have otherwise been assessed (i.e. it was neither a risk/trial burn analyte, nor found in the fugitive

emissions evaluation), and there is reasonable potential for it to be emitted, it may be appropriate to

include the compound. Also, if a compound found in the trial/risk burn analysis or fugitive emissions

evaluation (and therefore included in the COPC list) doesn’t satisfy Steps 2 or 3, yet is of concern for sitespecific factors and has reasonable potential to be emitted, it may be appropriate for it to continue to Step

5.

If a compound doesn’t have a reasonable potential of being present in the stack emissions, we generally

recommend that the risk assessment report justify this assertion. This information will generally provide

the risk manager with sufficient information to conclude that the facility has not overlooked a serious risk.

Compounds of concern due to site-specific factors with reasonable potential to be emitted continue to

Step 5. Delete all other compounds (i.e. non-detected compounds that did not satisfy Steps 2 through 4)

from consideration in the risk assessment.

Step 5: Research the recommended hierarchy of human health toxicity data (see Appendix A2.6) for

available compound-specific health benchmarks. Add compounds with available toxicity data to

the COPC list for quantitative assessment. Retain compounds that have no toxicity data on the

COPC list for qualitative assessment, and use surrogate toxicity data from a toxicologically

similar compound.

As detailed in Appendix A, we recommend a hierarchy of sources for toxicity data appropriate to use in

the risk assessment. The tox hierarchy represents a library of sources for scientifically defensible,

compound-specific human health benchmarks.

We generally recommend that the assessment of COPCs using surrogate toxicity data not be quantitative

but rather qualitative, and be reported in the Uncertainty section of the risk assessment. The definition of

a “toxicologically similar compound” will depend on the original compound, which in turn changes from
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SPECIAL NOTE: 

REGARDING FATE & TRANSPORT DATA

Step 5 in Identifying COPCs focuses on availability of toxicity data

because it tends to be the controlling factor: without toxicity parameter

values, quantitative assessment is not possible. Depending on the

compound, though, availability of fate & transport parameter values

could also be a limiting factor.

If these parameter values are available, then it is scientifically

reasonable, and in the interest of protecting human health and the

environment, to evaluate exposure of receptors to the COPC via various

direct and indirect pathways. However, if the necessary fate & transport

properties for a particular exposure pathway aren’t available, then it

seems reasonable to exclude that COPC from consideration for the

affected pathway (or pathways). For example, if a biotransfer value for

milk (see Chapter 5) is not available for a COPC then it can be assumed

that, based on current information, the COPC won’t be assessed via the

ingestion of milk exposure pathway. This principle holds true for other

variables as well. Please note, though, that the lack of fate and transport

data doesn’t automatically equate to an absence of potential exposure

and risk. We generally recommend that as long as sufficient fate &

transport properties are available, the calculations for each exposure

pathway be completed, and any uncertainties introduced into the risk

assessment described in the uncertainty discussion of the risk assessment

report (see Chapter 8).

Fate & transport parameter data may be quite limited for some

compounds, and acquiring that data can be a labor-intensive and timeconsuming process. In an effort to streamline the risk assessment

process, the fate & transport parameter values needed to follow this

Protocol to assess the 200+ compounds most commonly found in

hazardous waste combustor risk assessments are made available in a

database companion to the HHRAP (available for download from the

HHRAP web site). For those compounds not found in the database, the

Superfund Chemical Data Matrix (SCDM) is a good first source to

acquire the necessary values. When actual values aren’t directly

available, HHRAP Appendix A also lists our recommended methods for

estimating parameter values.

We generally recommend consulting with the permitting authority on the

appropriate level of effort to expend acquiring/estimating fate &

transport parameter values.

assessment to assessment. We recognize

the uncertainties involved in even defining

what constitutes “toxicologically similar.”

We therefore recommend consulting with

the permitting authority when identifying

toxicologically similar compounds. It’s

also within the permitting authority’s

purview to determine that it’s technically

appropriate (on a compound-specific basis)

to use surrogate toxicity data quantitatively.

Previous guidance on how to qualitatively

assess risk is inconsistent. Common

practice is also highly variable. One option

is to generate quantitative estimates for

compounds using surrogate toxicity data. 

These results, however, aren’t typically

reported with the rest of the COPCs, nor do

they contribute to risk totals. Instead, the

surrogate-based risk results are typically

reported in the Uncertainty section of the

risk assessment report, to inform risk

management decision-makers. 

Please Note: The above is

only one option. We

recommend consulting with

the permitting authority

regarding the appropriate

level of effort in acquiring

surrogate toxicity data, and

other methods and

processes to use in

qualitative assessment.

Step 6: Evaluate the tentatively identified compound (TIC) peaks obtained during gas chromatography

(GC) analysis, to determine whether any of the TICs have toxicities similar to the detected
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compounds. If they do, qualitatively assess using surrogate toxicity data, as recommended for

identified compounds in Step 5.

All organic compounds that are identified and quantified are ultimately subtracted from the total organic

emissions mass value. It is therefore beneficial for the laboratory to identify and quantify the maximum

number of compounds, including TICs. Although it’s in your interest to characterize as many TICs as

possible, extensive characterization of TICs involves a significant commitment of time and expertise and

can reach a point of diminishing returns. We therefore generally recommend characterizing TICs when

the peak intensity is 10 percent or more of the full chromatographic scale, and obtaining a quantitative

estimate of the value using the nearest eluting internal standard and a response factor of 1. Unless the

identification of the TIC is confirmed by the analysis of an authentic standard, it may be appropriate to

qualify the quantitative value as "estimated." 

We recognize that for many compounds, only limited information on potential health effects is available. 

Also, for those chemicals with identified health effects, the relationship between dose and response may

be poorly understood. We suggest that the risk assessment use the sum of the available toxicological

information and evaluate the uncertainty associated with these issues. As stated previously, toxicity

benchmarks and slope factors may change as additional toxicity research is conducted. You may wish to

consult with the most current versions of the resources found in the tox hierarchy (see Appendix A,

Section A2.6) before completing the risk assessment, to make sure that the toxicity data used in the risk

assessment is the most current available.

Previous Agency guidance (1989e; 1994j; 1994n; 1998) recommended that the COPC list for indirect

exposure analysis consist of only those constituents considered to present the most significant risks. 

These constituents were selected based on the

1. quantity of the hazardous waste to be burned, 

2. toxicity of the hazardous waste to be burned, and 

3. potential for the hazardous waste to bioaccumulate. 

For direct exposure analysis, however, previous guidance recommended including all constituents for

which stack emission data and inhalation health benchmarks exist. We now recommend that a single

COPC list apply to both indirect and direct exposure analysis. We believe that, through the use of

computer-based calculations, you can efficiently assess all identified COPCs via both direct and indirect

exposure pathways. Savings gained through computer-based calculations will provide for an efficient use
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C Complete evaluation of hazardous wastes to be burned in the combustor

C Complete evaluation of any raw materials or primary fuels burned in the combustor

C Waste analysis procedures used to monitor the composition of hazardous waste feed streams

C Analytical data and calculations used to complete the COPC identification process

RECOMMENDED INFORMATION FOR THE RISK ASSESSMENT REPORT

of facility and regulatory resources. Assessing the entire list of COPCs - rather than a subset as

previously recommended - may help minimize public concern over the exclusion of some COPCs and

reduce confusion for those interested in reviewing the results of the risk assessment.

The following subsections provide specific information and guidance on identifying COPCs for each

facility—with discussions for specific classes of compounds—that we typically recommend including in

risk assessments. Emerging issues surrounding the class of compounds referred to as “endocrine

disruptors” are also discussed.

The following subsections also focus on compounds that past experience has shown can drive risk

assessments. These compounds include PCDDs/PCDFs, PAHs, PCBs, nitroaromatics, phthalates,

hexachlorobenzene and pentachlorophenol, and metals. Volatile organic compounds are also discussed. 

We also discuss specific issues that affect the COPC identification process, and evaluating these

compounds in the risk assessment.

2.3.1 Criteria Pollutants

Under the Clean Air Act, EPA establishes air quality standards to protect public health, including the

health of "sensitive" populations such as people with asthma, children, and older adults. EPA has set

national air quality standards (40 C.F.R. Part 40) for six principal air pollutants (also called the criteria

pollutants): nitrogen dioxide (NO2), ozone (O3), sulfur dioxide (SO2), particulate matter (PM), carbon

monoxide (CO), and lead (Pb). We discuss lead in Section 2.3.5.2, and PM in Section 2.3.7.

Nitrogen dioxide is a reddish brown, highly reactive gas that is formed in the ambient air through the

oxidation of nitric oxide (NO). Nitrogen oxides (NOx), the generic term for a group of highly reactive
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gases that contain nitrogen and oxygen in varying amounts, play a major role in the formation of ozone,

PM, haze, and acid rain. The major sources of man-made NOx emissions are high-temperature

combustion processes such as those that occur in automobiles and power plants. Short-term exposures

(e.g., less than 3 hours) to low levels of NO2 may lead to changes in airway responsiveness and lung

function in individuals with preexisting respiratory illnesses. These exposures may also increase

respiratory illnesses in children. Long-term exposures to NO2 may lead to increased susceptibility to

respiratory infection and may cause irreversible alterations in lung structure. NOx react in the air to form

ground-level ozone and fine particle pollution, which are associated with adverse health effects (U.S.

EPA 2005). 

Ozone occurs naturally in the stratosphere approximately 10 to 30 miles above the earth’s surface and

forms a layer that protects life on earth from the sun’s harmful rays. Ozone is also formed at ground level

by a chemical reaction of various air pollutants combined with sunlight. The pollutants that contribute to

ozone formation are oxides of nitrogen (NOx) and volatile organic compounds (VOCs). “Ground-level”

ozone is an air pollutant that damages human health and the environment. Even at relatively low levels,

ozone may cause inflammation and irritation of the respiratory tract, particularly during physical activity.

The resulting symptoms can include breathing difficulty, coughing, and throat irritation. Breathing ozone

can affect lung function and worsen asthma attacks. Ozone can increase the susceptibility of the lungs to

infections, allergens, and other air pollutants. Medical studies have shown that ozone damages lung tissue

and complete recovery may take several days after exposure has ended (U.S. EPA 2004a).

Sulfur dioxide (SO2) belongs to the family of SOx gases. These gases are formed when fuel containing

sulfur (mainly coal and oil) is burned at power plants and during metal smelting and other industrial

processes. High concentrations of SO2 can result in temporary breathing impairment for asthmatic

children and adults who are active outdoors. Short-term exposures of asthmatic individuals to elevated

SO2 levels during moderate activity may result in breathing difficulties that can be accompanied by

symptoms such as wheezing, chest tightness, or shortness of breath. Other effects that have been

associated with longer-term exposures to high concentrations of SO2, in conjunction with high levels of

PM, include aggravation of existing cardiovascular disease, respiratory illness, and alterations in the

lungs' defenses. The subgroups of the population that may be affected under these conditions include

individuals with heart or lung disease, as well as the elderly and children (U.S. EPA 1986d; 2005).

Carbon monoxide is a colorless and odorless gas, formed when carbon in fuel is not burned completely. It

is a component of motor vehicle exhaust, which contributes about 60 percent of all CO emissions
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nationwide. Other sources of CO emissions include industrial processes, non-transportation fuel

combustion, and natural sources such as wildfires. CO enters the bloodstream through the lungs and

reduces oxygen delivery to the body's organs and tissues. The health threat from levels of CO sometimes

found in the ambient air is most serious for those who suffer from cardiovascular disease such as angina

pectoris. At much higher levels of exposure not commonly found in ambient air, CO can be poisonous,

and even healthy individuals may be affected. Visual impairment, reduced work capacity, reduced manual

dexterity, poor learning ability, and difficulty in performing complex tasks are all associated with

exposure to elevated CO levels (U.S. EPA 2000d).

The permitting authority decides whether to include criteria pollutants in the quantitative risk assessment. 

For example, as noted in the November 14, 1997, decision of the Environmental Appeals Board in

reference to the Ash Grove Cement Company Permit No. KSD031203318 and risks associated with

exposure to cement kiln dust controlled through the state solid waste permit, compliance with other

environmental statutes (e.g., CAA, CWA) may be an appropriate method to consider and control risks

from non-RCRA related pollutants (Environmental Appeals Board 1997).

2.3.2 Endocrine Disruptors

Endocrine disruptors are chemicals are thought to mimic natural hormones, inhibit the action of

hormones, or alter the normal regulatory function of the immune, nervous, and endocrine systems.

Possible human health endpoints affected by these agents include breast cancer and endometriosis in

women, testicular and prostate cancers in men, abnormal sexual development, reduced male fertility,

alteration in pituitary and thyroid gland functions, immune suppression, and neurobehavioral effects (U.S.

EPA 1997g).

Problems were encountered while attempting to classify chemical compounds as endocrine disruptors. 

Only limited empirical data are available to support the designation of specific chemicals as endocrine

disruptors, and some of the data are conflicting. There is a lack of clear structure-activity relationship, as

well as a lack of unifying dose-response relationship, among the diverse groups of chemicals considered

endocrine disruptors. Also, there are multiple modes of action for chemicals currently considered

endocrine disruptors. 

Because the information currently available on endocrine disruptors is inconsistent and limited, U.S. EPA

has not yet developed a methodology for quantitative assessments of human health risk resulting from
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exposure to potential endocrine disruptors (U.S. EPA 1996i). However, the methods for addressing

endocrine disruptors are developing at a rapid pace. We therefore generally recommend contacting the

Economics, Methods and Risk Analysis Division (EMRAD) of the Office of Solid Waste for the latest

guidance on how to address endocrine disruptors in site-specific risk assessments. Additional information

(e.g., U.S. EPA 1997g) is available for review at the web site http://epa.gov/endocrine/pubs.html.

2.3.3 Hexachlorobenzene and Pentachlorophenol

In past guidance (U.S. EPA 1994g; 1994i; 1994j; 1994r) we recommended always including

hexachlorobenzene and pentachlorophenol in risk assessments of hazardous waste combustors. However,

we no longer recommend automatically including them. Rather, we generally recommend carefully

considering the information and issues presented below before deciding whether to include

hexachlorobenzene and pentachlorophenol as COPCs for quantitative assessment.

Hexachlorobenzene is an impurity in pentachlorophenol, while pentachlorophenol is formed from

hexachlorobenzene in the body as well as in some factories (ATSDR 1994a; ATSDR 1994b). 

Hexachlorobenzene and pentachlorophenol, like all chlorinated aromatics, are synthesized by the reaction

of elemental chlorine with a parent aromatic (Deichmann and Keplinger 1981; Grayson 1985). The

addition of the first chlorine atom to the benzene or phenol molecule is rapid, but further chlorination

becomes progressively more difficult, requiring ferric chloride or another Lewis acid catalyst to complete

the reaction (March 1985). Therefore, these chlorinated compounds are difficult to make even under

controlled conditions. Hexachlorobenzene, but not pentachlorophenol, has been reported in emissions

from the combustion of municipal solid waste and from other processes (such as the chlorination of wood

pulp) that also produce PCDDs and PCDFs (ATSDR 1994a; ATSDR 1994b). The combustion properties

of these chlorinated compounds indicate that they aren’t likely to be formed as PICs if they aren’t present

in the waste feed stream. 

We consider it prudent to include hexachlorobenzene and pentachlorophenol as COPCs for combustors

that burn waste feeds containing hexachlorobenzene and pentachlorophenol, wood preservatives,

pesticides, or highly variable waste streams such as municipal solid waste. However, we don’t

recommend precluding these compounds from analytical testing during the trial burn based only on

process knowledge and waste feed characteristics. Because PCDDs and PCDFs can be formed from fly

ash-catalyzed reactions between halogens and undestroyed organic material from the furnace, other
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Agency guidance (U.S. EPA 1994i; 1998c) recommends including potential precursor compounds in the

risk assessment and trial burn (see Section 2.3). These precursor compounds might include chlorinated

phenols (such as pentachlorophenol) and chlorinated aromatics (such as hexachlorobenzene). Also, the

toxicity and uncertainties associated with combustion chemistry suggest that stack gas testing always

confirm the absence of these compounds from stack emissions.

2.3.4 Hydrogen Chloride/Chlorine Gas

Hydrogen chloride (which becomes hydrochloric acid when dissolved in water) and chlorine are major

products of the chemical industry, with uses too numerous to list. When chlorine gas dissolves in water

(whether during drinking water treatment or when someone inhales chlorine), it hydrolyzes to form equal

amounts of hydrochloric acid and hypochlorous acid; the adverse effects of which are similar but not

identical (Stokinger 1981; ACGIH 1991).

Hydrochloric acid has many uses. It is used in the production of chlorides, fertilizers, and dyes, in

electroplating, and in the photographic, textile, and rubber industries. Hydrochloric acid is corrosive to

the eyes, skin, and mucous membranes. Acute (short-term) inhalation exposure may cause eye, nose, and

respiratory tract irritation and inflammation and pulmonary edema in humans. Acute oral exposure may

cause corrosion of the mucous membranes, esophagus, and stomach and dermal contact may produce

severe burns, ulceration, and scarring in humans. Chronic (long-term) occupational exposure to

hydrochloric acid has been reported to cause gastritis, chronic bronchitis, dermatitis, and

photosensitization in workers. Prolonged exposure to low concentrations may also cause dental

discoloration and erosion (U.S. DHHS 1993).

Chlorine is a potent irritant to the eyes, the upper respiratory tract, and lungs. Chronic (long-term)

exposure to chlorine gas in workers has resulted in respiratory effects, including eye and throat irritation

and airflow obstruction (Cal EPA 2000). Depending on the exposure concentration, acute (short-term)

exposure to chlorine elicits reactions ranging from tickling of the nose and throat (Calabrese and Kenyon

1991) to chest pain, vomiting, dyspnea, and cough (U.S. DHHS 1993). Chlorine is also extremely

irritating to the skin and can cause severe burns in humans (U.S. DHHS 1993). 
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C Waste feed, raw material, and secondary fuel stream analytical data

C Metal emission rate sampling data or assumptions based on waste feed data

C Explanations for excluding specific metals from evaluation during the risk assessment

RECOMMENDED INFORMATION FOR THE RISK ASSESSMENT REPORT

2.3.5 Metals

Previous guidance (U.S. EPA 1994g; 1994i; 1998c; NC DEHNR 1997) recommends including the

following inorganic substances in the risk assessment: antimony, arsenic, barium, beryllium, cadmium,

hexavalent chromium, lead, mercury (elemental and divalent), nickel, selenium, silver, thallium, and zinc. 

All of these substances, except nickel, selenium, and zinc, are regulated by 40 CFR Part 266, Subpart H 

(the BIF regulations). We recommend evaluating nickel and selenium, to determine whether additional

terms and conditions may need to be incorporated into the permit, pursuant to 42 USC § 6925(c)(3) and

40 CFR Part 270.32(b)(2)–i.e., U.S. EPA’s “omnibus” authority. In addition, U.S. EPA (2001c)

recommends also characterizing the metals aluminum, copper, manganese, and vanadium. Another

potential option is applying the BIF regulation Tier I or MACT MTEC assumptions, which assume that

all metals in the waste feed pass through the combustion unit and APCS to the emission stream (U.S. EPA

1992c). 

Please Note: It may be appropriate to include metals in the risk assessment even if they

aren’t present in the combustor’s feed streams. Although metals cannot be formed as

PICs, we are aware of combustors with metal emissions resulting from leaching from

stainless steel feed piping.

The following subsections provide additional information on our recommended procedures for evaluating

four metals—chromium, lead, mercury, and nickel. When evaluating stack emissions for the risk

assessment, we highly recommend considering how each of these metals may be affected by the

combustion process, including possible interactions with other constituents.

2.3.5.1 Chromium

The oxidation state of chromium is a crucial issue in evaluating the toxicity of this metal, and the risks

associated with exposure. Hexavalent chromium (Cr+6) is the most toxic valence state of chromium and
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has been shown to be a human carcinogen through inhalation exposure (U.S. EPA 2005i). Trivalent

chromium (Cr+3) is a commonly found, less-oxidized form of chromium. Trivalent chromium has not

been shown to be carcinogenic in either humans or laboratory animals (U.S. EPA 2005i). U.S. EPA

(1990a; 1990b) has indicated that chromium emitted from a combustor is not likely to be in the

hexavalent form. However, there is not sufficient evidence to reliably estimate the partitioning of

chromium emissions into these two valence states. In addition, we recognize that chromium may exist

partially or in some cases entirely as trivalent chromium in various media. For example, Amdur et al.

(1991) states that:

 “Trivalent chromium is the most common form found in nature, and chromium in

biological materials is probably always trivalent. There is no evidence that trivalent

chromium is converted to hexavalent forms in biological systems. However, hexavalent

chromium readily crosses cell membranes and is reduced intracellularly to trivalent

chromium..”

We generally consider it best to use measured, speciated emissions data in the risk assessment. If sitespecific speciated emissions data is unavailable, you may generate a default speciation. We generally

recommend using the following method (developed by us through interpretation of data available in the

MACT database, as documented in Appendix D) to generate a default speciation:

• When the measured amount of total chromium is <10 :g/dscm, we recommend a default

of 5 :g/dscm hexavalent chromium.

• When the measured amount of total chromium is in the range of 10 :g/dscm to 100

:g/dscm, we recommend assuming 45 percent is hexavalent chromium.

• When the measured amount of total chromium is >100 :g/dscm, we recommend

assuming 30 percent is hexavalent chromium.

2.3.5.2 Lead

We generally recommend that risk assessments evaluating lead as a COPC use the IEUBK model when

soil concentrations are calculated to be above the benchmark.

The Integrated Risk Information System (IRIS) doesn’t currently list an RfD or RfC for lead, because a

threshold level for exposure to lead has not been established. While the Agency has characterized lead as

a probable human carcinogen, it has not developed a quantitative estimate of cancer risk due to a number

of uncertainties, some of which may be unique to lead (U.S. EPA 2005b). The Agency has typically

relied on the neurological effects observed in children as the sensitive endpoint for evaluating lead

toxicity. Consequently, the Agency developed the integrated Exposure Uptake Biokinetic (IEUBK)
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Model for Lead in Children. Developed through the efforts of U.S. EPA (1990c) and Kneip, et al. (1983),

this model evaluates potential risks based on predicted blood lead levels associated with exposure to lead

(U.S. EPA 1994e). The IEUBK model integrates several assumptions about the complex exposure

patterns and physiological handling of lead by the body, and it has been validated at several sites at which

lead exposure data and human blood lead levels are available (U.S. EPA 1990c). The U.S. EPA Science

Advisory Board (U.S. EPA 1992b) and the U.S. EPA’s Technical Review Workgroup for Lead have both

reviewed and recommended the IEUBK model.

The Agency has developed a computerized version of the IEUBK model that predicts blood lead levels

and distributions for children 0 to 7 years of age (U.S. EPA 1994e). The IEUBK model is available for

download at http://www.epa.gov/superfund/programs/lead/products.htm. The IEUBK computer model

cannot predict potential blood lead levels in adults. The Agency has developed an Interim Approach to

Assessing Risks Associated with Adult Exposures to Lead in Soil (U.S. EPA 1996r). This interim model is

intended for “assessing adult lead risks associated with nonresidential [industrial] exposure scenarios.” 

However, in general, children are more susceptible to lead exposures than adults because of higher soil

ingestion rates and greater absorption by the gut, in addition to nutritional variables and lower body

weight. In fact, The Agency’s interim approach for assessing adult exposures to lead is based not on

limiting adult toxicity, but rather on limiting fetal toxicity by limiting indirect fetal exposure through

direct maternal exposures to lead (U.S. EPA 1996r).

As stated before, we generally recommend that risk assessments evaluating lead as a COPC use the

IEUBK model when soil concentrations are calculated to be above the benchmark. We don’t generally

recommend evaluating carcinogenic risks or noncarcinogenic hazards of lead. When run with standard

recommended default values (these generally represent national averages, or “typical” values), the

Agency’s IEUBK model predicts that no more than 5 percent of children exposed to a lead concentration

in soil of 400 mg/kg will have lead concentrations in blood exceeding 10 μg/dL (U.S. EPA 1994e and

1994o).

2.3.5.3 Mercury

We generally recommend that the risk assessment evaluate exposure to three mercury species via varied

pathways:

1. Assess elemental mercury only through direct inhalation of the vapor phase;
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2. Assess divalent mercury through both direct inhalation and indirect exposure to vapor

and particle-bound mercuric chloride; and. 

3. Assess methyl mercury only through indirect exposure.

Air emissions of mercury contribute to local, regional, and global deposition. The U.S. Congress

explicitly found this to be the case and required the Agency to prioritize maximum achievable control

technology (MACT) controls for mercury (U.S. Congress 1989).

The Mercury Study Report to Congress (U.S. EPA 1997c) found that anthropogenic mercury releases are

thought to be dominated on the national scale by industrial processes and combustion sources that release

mercury into the atmosphere. A portion of these anthropogenic releases is in the form of elemental

mercury, and a portion in the form of mercuric chloride. Coal combustion is responsible for more than

half of all mercury emissions from U.S. anthropogenic sources. The fraction of coal combustion

emissions in oxidized form (i.e. mercuric chloride) is thought to be less than the fraction in oxidized form

from other combustion emission sources (including waste incineration).

Stack emissions include both vapor and particulate forms of mercury. Most of the total mercury emitted

from the stack is in the vapor phase, although exit streams containing soot or particulates can bind up

some fraction of the mercury. Vapor mercury emissions are thought to include both elemental (Hg0

) and

oxidized (e.g., Hg+2) chemical species. Particulate mercury emissions are thought to be composed

primarily of oxidized compounds, due to the relatively high vapor pressure of elemental mercury (U.S.

EPA 1997c).

The methods for analyzing mercury speciation in emission plumes are being refined, and there is still

controversy in this field. The speciation of mercury emissions is thought to depend on the fuel used, flue

gas cleaning, and operating temperatures. True speciation of mercury emissions from the various source

types is still uncertain and thought to vary not only among source types, but also between individual

plants (U.S. EPA 1997c). Total mercury exiting the stack is assumed to consist entirely of elemental and

divalent species, with no emissions of methyl mercury. The exit stream is thought to range from almost

all elemental mercury to nearly all divalent mercury. Much of the divalent mercury is thought to be

mercuric chloride (HgCl2) (U.S. EPA 1997c), particularly in the combustion of wastes containing

chlorine. The divalent fraction is split between vapor and particle-bound phases (Lindqvist et al. 1991).
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Please note that data on mercury speciation in stack emissions is very limited. Also, the behavior of

mercury emissions close to the point of release has not been extensively studied. It is possible for

chemical reactions to occur in the emission plume. This results in a significant degree of uncertainty

implicit in modeling mercury emissions. Additional examples of uncertainties include the precision of

measurement techniques, estimates of pollution control efficiency, limited data specific to source class

and activity level. U.S. EPA (1997c) discusses uncertainty, and sensitivity analyses of several of the

assumptions used in the modeling of mercury emissions. Additional discussions and examples of

mercury modeling can be found in the proceedings of the IT3 conference (Kaleri 2000).

Site-Specific Mercury Sampling

If site-specific mercury sampling information is available, one option is to estimate the oxidation state and

phase distributions. We recommend basing the estimates on the concentration of mercury in various

components of the Agency’s multiple metals sampling train (i.e., U.S. EPA Method 29 or Method 0060)

using the following guidelines:

• Mercury found in the acidic potassium permanganate impingers would be expected to be

the elemental form of mercury (Hg0

).

• Divalent mercury (HgCl2) is soluble in water and would be expected to be found in the

dilute nitric acid/hydrogen peroxide impinges. This is also referred to as the ionic portion. 

• Mercury found in the probe and filter can be assumed to be vapor-phase mercury

adsorbed onto particulate matter or a solid-phase compound. This fraction is referred to

as Hg(PM).

We understand that these methods can be biased by high SO2 and trace Cl2 in the feed. This bias results

in the over-reporting of ionic vapor (or divalent form) and the under-reporting of elemental vapor

mercury. For risk assessment purposes, we consider this protective.

Default Phase Allocation and Speciation of Mercury Exiting the Stack

As discussed above, stack emissions are thought to be speciated into both divalent and elemental mercury,

and include both vapor and particle-bound forms. Vapor-phase divalent mercury is thought to be more

rapidly and effectively removed by both dry and wet deposition than particle-bound divalent mercury. 

This is a result of the reactivity and water solubility of vapor-phase divalent mercury (Lindberg et al.

1992; Peterson et al. 1995; Shannon and Voldner 1994). Also, divalent mercury emitted either in the
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vapor phase or particle-bound, is thought to be subject to much faster atmospheric removal than elemental

mercury (Lindberg et al. 1992; Peterson et al. 1995; Shannon and Voldner 1994). A small fraction (about

one percent) of vapor-phase elemental mercury may be atmospherically transformed into divalent

mercury by tropospheric ozone and adsorbed to particulate soot in the air and subsequently deposited in

rainfall and snowfall (U.S. EPA 1997c).

Based on review of mercury emissions data presented for combustion sources in U.S. EPA (1997c) and

published literature (Peterson et al. 1995), estimates for the percentage of vapor and particle-bound

mercury emissions range widely from 20 to 80 percent. Therefore, unless site-specific mercury sampling

information is available, we generally recommend a protective approach that assumes phase allocation of

mercury emissions from hazardous waste combustion of 80 percent of total mercury in the vapor phase

and 20 percent of total mercury in the particle-bound phase. As illustrated in Figure 2-4, of the 80 percent

total mercury in the vapor phase, 20 percent of the total is in the elemental form and 60 percent of the

total is in the divalent form (Peterson et al. 1995). Of the 20 percent of the total mercury that is

particle-bound, 99 percent (assumed to be 100 percent in Figure 2-4) is in the divalent form. This

allocation is:

C Consistent with mercury emissions speciation data for hazardous waste combustion

sources reported in literature (Peterson et al. 1995); and

C Believed to be reasonably protective, since it results in the highest percentage of total

mercury being deposited in proximity to the source, and therefore, indicative of the

maximum indirect risk.
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FIGURE 2-4

PHASE ALLOCATION AND SPECIATION OF MERCURY IN AIR

20% is Hg0 vapor 

[2.00g]

60% is Hg2+ vapor 

[6.00g]

20% is Hg2+ particle-bound 

[2.00g]

Fv (Total Mercury) = 0.8

LEGENDHg0 - Elemental Mercury

Hg2+ - Divalent Mercury

[ ] - Example Mass Allocation

1% Deposited as Hg0 vapor

99% Enters Global Cycle as Hg

68% Deposited as Hg2+ vapor

32% Enters Global Cycle as H

36% Deposited as Hg2+ particle-bound

64% Enters Global Cycle as Hg

[0.02g][1.98g][4.08g][1.92g][0.72g][1.28g]

Without Considering Global Cycle:

• 20% of Total Mercury Emitted

is deposited as Hg0 [2g / 10g]

• 80% of Total Mercury Emitted

is deposited as Hg2+ [(6g + 2g) / 10g]

Calculated Fv:

•Fv (Hg0) = [2g / 2g] = 1.0

•Fv (Hg2+) = [6g / (6g+2g)] = 0.75

Considering Global Cycle:

• 0.2% of Total Mercury Emitted

is deposited as Hg0 [0.02g / 10g]

• 48% of Total Mercury Emitted

is deposited as Hg2+ [(4.08g + 0.72g) / 10g]

Calculated Fv:

•Fv (Hg0) = [0.02/(0.02 + 0)] = 1.0

•Fv (Hg2+) = [4.08/(4.08 + 0.72)] = 0.85

Compound-Specific Emission Rate (Q)

•Actual Q (Hg0) = 0.2% * Q (Total Mercury

•Actual Q (Hg2+) = 48% * Q (Total Mercury

Total Mercury Emissions Exiting Stack Into Air 

[10.0g]

80% is in Vapor Phase[8.00g]20% is in Particle-Bound Phase[2.00g]
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The Mercury Global Cycle

According to information in U.S. EPA (1997c), a vast majority of mercury exiting the stack doesn’t

readily deposit, but is vertically diffused to the free atmosphere, transported outside the study area and

into the global cycle. Regardless of the source of phase and speciation distribution values (i.e. either sitespecific sampling data or default values), we generally recommend using the following fractions from

U.S. EPA (1997c):

• A vast majority of the vapor-phase elemental mercury (over 99 percent) doesn’t readily

deposit, but becomes part of the global cycle;

• Of the mercury emitted as vapor-phase divalent mercury, about 68 percent deposits and

about 32 percent diffuses vertically to the global cycle; and

• 36 percent of the particle-bound divalent mercury deposits, and the rest diffuses vertically

to the global cycle.

Deposition and Modeling of Mercury

Based on information in U.S. EPA (1997c) and as shown in Figure 2-4, we generally assume that

deposition to the various environmental media is almost entirely divalent mercury in either the vapor or

particle-bound form. Without considering the global cycle, 80 percent of total mercury would be

deposited as divalent mercury and the remaining 20 percent would be deposited as elemental mercury.

We generally recommend using the percentages provided in U.S. EPA (1997c) to account for the global

cycle. Using these figures, the percentage of total mercury deposited would be reduced to a total of

48.2 percent (40.8 percent as divalent vapor, 7.2 percent as divalent particle-bound, and 0.2 percent as

elemental vapor). As discussed in Appendix A-2, these speciation splits result in fraction in vapor phase

(Fv) values of 0.85 (40.8/48.0) for divalent mercury, and 1.0 (0.2/0.2) for elemental mercury. Also, to

account for the remaining 51.8 percent of the total mercury mass that is not deposited, the deposition and

media concentration equations (presented in Appendix B), multiply the compound-specific emission rate

(Q) for elemental mercury by a default value of 0.002; and divalent mercury by a default value of 0.48. 

Methylation of Mercury

The net mercury methylation rate (the net result of methylation and demethylation) for most soils appears

to be quite low; with much of the measured methyl mercury in soils potentially resulting from wet

deposition (U.S. EPA 1997c). Based on the information in U.S. EPA (1997c), We assume that 98 percent
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of the deposited mercury remains divalent mercury, and two percent speciates to organic mercury (methyl

mercury) in soil. A significant and important exception to mercury methylation rate being low in soils

appears to be wetland soils. Wetlands appear to convert a small but significant fraction of the deposited

mercury into methyl mercury; which can migrate to nearby water bodies and potentially bioaccumulate in

the aquatic food chain (U.S. EPA 1997c). Therefore, we assume the percentage of methyl mercury in

wetland soils is higher than the 2 percent assumed for non-wetland soils. However, wetlands soils aren’t

specifically considered in any of the exposure pathways represented in the recommended human health

exposure scenarios (see Chapter 4).

Both watershed erosion and direct atmospheric deposition can be important sources of mercury to a water

body (U.S. EPA 1997c). There appears to be a great deal of variability in the processing of mercury

among water bodies. As a result, you can generally expect different water body types to have different

ranges of methylation, with wetlands generally expected to have higher percentages of methyl mercury

than lakes, and lakes subsequently more than rivers or streams (Driscoll et al. 1994; Hurley et al. 1995;

Krabbenhoft et al. 1999; Watras et al. 1995). Studies have also shown that rivers or lakes with wetland

components (particularly riparian wetlands) have an increased methyl mercury content (Hurley et al.

1995; Krabbenhoft et al. 1999; St. Louis et al. 1996). The percentage of the water body that constitutes a

riparian wetland also contributes (i.e., the higher percentage - the higher the methyl mercury

concentration). The watershed is also an important factor in determining the methyl mercury

concentration of the water body. Waterbodies that are surrounded by agricultural or forested land tend to

have higher methylation fractions. Waterbodies that are surrounded by mining activities have high

amounts of inorganic mercury in the water, and therefore have a lower methylation efficiency

(Krabbenhoft et al. 1999). As briefly discussed later in this section, this variability in methylated mercury

concentrations is primarily due to the characteristically wide range of chemical and physical properties of

water bodies. Additionally, mercury entering the water body can be methylated predominantly through

biotic processes (U.S. EPA 1997c). 

In the absence of site-specific measurements to support evaluation of water body properties and biotic

conditions relevant to mercury methylation, we generally recommend assuming that 85 percent of total

mercury in surface water is divalent mercury, and the remaining mass is methyl mercury. This percentage

(i.e., 15 percent as methyl mercury) is based on the average of reported values for the fraction of total

mercury that is methyl mercury in surface water (Akagi et al. 1979; Bloom and Effler 1990; Bloom et al.

1991; Gill and Bruland 1990; Kudo et al. 1982; Lee and Hultberg 1990; Parks et al. 1989; Watras and

Bloom 1992). These literature sources were originally presented in the SAB Review Draft of the
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Mercury Study Report to Congress (U.S. EPA 1996s). The final Mercury Study Report to Congress (U.S.

EPA 1997c, Volume III; Appendix D) also presents literature values for the fraction of methyl mercury in

the water column. However, the data are specific to the epilimnion and hypolimnion. For the epilimnion,

reported values range from 4.6 percent to 15 percent, with a point estimate of 7.8 percent. For the

hypolimnion, reported values range from 27 percent to 44 percent, with a point estimate of 36 percent.

We are modifying our previous recommendation for applying the default mercury speciation (85 percent

divalent mercury and 15 percent methyl mercury) to each calculated water body loading. Instead, we

recommend that a dissolved water concentration first be calculated for total mercury using the fate and

transport parameters specified for mercuric chloride. Then, the dissolved total mercury concentration

should be apportioned based on an 85 percent divalent and 15 percent methyl mercury speciation split in

the water body. Appendix B (Table B-4-24) presents the equations we recommend for applying the

speciation assumptions. 

For most environmental systems, the literature suggests that various physical and chemical conditions

may influence the methylation of mercury. In some cases you might need to consider these conditions,

and the magnitude of their potential impact, to assess the potential for over- or under-predicting mercury

methylation in media and subsequent biotransfer up the food chain. There is extreme variation between

modeled environmental systems, and at times disagreement in the literature regarding the quantitative

influence of specific conditions on methylation. Table 2-4 summarizes the qualitative effects that some

physical and chemical conditions, as reported in literature, may have on methylation. We therefore

generally recommend conducting extensive research of literature specific to the conditions prevalent at

the site, before deviating from the protective assumptions recommended above.

More recent advances in scientific understanding of the physical, chemical, and biological processes

controlling mercury speciation and partitioning in water bodies are summarized in U.S. EPA (2005g).
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TABLE 2-4

QUALITATIVE EFFECTS OF 

PHYSICAL & CHEMICAL CONDITIONS ON METHYLATION

Physical or Chemical Condition Qualitative Influence on Methylation Referenced Literature

Low dissolved oxygen Enhanced methylation Rudd et al. 1983; Parks et al. 1989

Decreased pH Enhanced methylation in water column Xun 1987; Gilmour and Henry 1991;

Miskimmin et al. 1992

Decreased pH Decreased methylation in sediment Ramlal et al. 1985; Steffan et al. 1988

Increased dissolved organic carbon

(DOC)

Enhanced methylation in sediment Chois and Bartha 1994

Increased dissolved organic carbon

(DOC)

Decreased methylation in water column Miskimmin et al. 1992

Increased salinity Decreased methylation Blum and Bartha 1980

Increased nutrient concentrations Enhanced methylation Wright and Hamilton 1982;

Jackson 1986; Regnell 1994;

Beckvar et al. 1996

Increased selenium concentrations Decreased methylation Beckvar et al. 1996

Increased temperature Enhanced methylation Wright and Hamilton 1982; Parks et al.

1989

Increased sulfate concentrations Enhanced methylation Gilmour and Henry 1991; Gilmour et

al. 1992

Increased sulfide concentrations Enhanced methylation Beckvar et al. 1996

The deposition and media concentration equations that we generally recommend (presented in Chapter 5

and Appendix B) have been modified specifically to account for the methylation and subsequent

biotransfer of mercury, assuming steady-state conditions. The HHRAP companion database provides the

parameter values specific for methyl mercury, and Appendix A-2 includes additional discussion and

reference on their origin.

As noted above, methylation can be highly variable between environmental systems. This results in a

significant degree of uncertainty implicit in the modeling of mercury methylation. To expand on the

qualitative information presented in Table 2-4, and to better understand conditions that may influence

mercury methylation specific to a site, we recommend reviewing the related information presented in U.S.

EPA (1997c; 2005).
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We generally recommend using the equations and protective assumptions presented in this guidance to

estimate risks associated with mercury. If estimated risks exceed target levels, it may be appropriate to

use more extensive site-specific data (if available) and subsequently a more rigorous modeling effort, to

further evaluate points of potential exposure. For example, if sufficient site-specific data is available, it

could be used in a model that predicts transformation of chemical forms and biotransfer of mercury. One

such model is the SERAFM (Spreadsheet Ecological Risk Assessment for the Fate of Mercury) model

developed by EPA's Office of Research and Development, National Exposure Research Laboratory,

Ecosystems Research Division. SERAFM updates the IEM-2M mercury fate and transport algorithms

described in detail in U.S. EPA (1997c) by incorporating more recent advances in scientific

understanding of the physical, chemical, and biological processes controlling mercury speciation and

partitioning in water bodies. The SERAFM enhancements to IEM-2M are summarized in U.S. EPA

(2005g).

SERAFM is written in an easy-to-implement Microsoft Excel format so that all manipulations, parameters

and equations are readily available to the user. By specifying only a few additional water body

parameters beyond those already utilized in this guidance (i.e., water body pH, dissolved organic carbon

and color), the user is able to model specific water body mercury transformation processes instead of

using the default speciation assumptions (i.e., 85 percent divalent/15 percent methyl). In the SERAFM

model, mercury species are subject to several transformation reactions including photo-oxidation and dark

oxidation of elemental mercury in the water column, photo-reduction and methylation of divalent

mercury in the water column and sediment layers, and photo-degradation and demethylation of methyl

mercury in the water column and sediment layers. For hazardous waste combustion sources, it is

recommended that, watershed soil concentrations and water body loadings due to source deposition be

calculated externally to SERAFM using the equations presented in Chapter 5 (Equations 5-1E and 5-28)

and then linked to the appropriate SERAFM worksheets for calculation of speciated mercury

concentrations in the water body.

The decision to use more complex mercury models in a risk assessment is not precluded just because they

are different from the model we recommend in the HHRAP. It is for the permitting authority to decide

whether the assessment will use more complex mercury models. If you use more complex mercury

models, we recommend ensuring that sufficient and reliable site-specific data is readily available, and

then carefully identifying and evaluating the models' associated limitations, and clearly documenting the

evaluation in the Uncertainty section of the risk assessment report.
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Conclusion

We encourage all facilities to implement a combination of waste minimization and control technology

options to reduce mercury emission rates on an ongoing basis. Realistic expectations for mercury

emission reduction efforts may be established by considering various technology-based mercury emission

limits that apply to waste combustors (for example, standards for European combustors, the MACT

standards for hazardous waste combustors, or the MACT standards for municipal waste combustors). We

acknowledge that site-specific risk assessments as currently conducted may not identify the entire

potential risk from mercury emissions. Mercury that doesn’t deposit locally will ultimately enter the

global mercury cycle for potential deposition elsewhere.

2.3.5.4 Nickel

We generally recommend evaluating nickel as an inhalation carcinogen using the inhalation unit risk

factor for nickel refinery dust. We generally recommend evaluating nickel for other effects using the oral

RfD for nickel soluble salts, the only available nickel-related RfD (see Appendix A-2 and the HHRAP

companion database).

Nickel refinery dust is identified as a potential human inhalation carcinogen (U.S. EPA 2005i). Major

components of nickel refinery dust include nickel subsulfide, nickel oxide and nickel sulfate. IRIS

classifies nickel subsulfide - the primary component (roughly 50%) of nickel refinery dust - a Class A

human carcinogen (U.S. EPA 2005e). However, all components responsible for the carcinogenicity of

nickel refinery dust have not been conclusively established (U.S. EPA 2005c). Because the component

(or components) of nickel refinery dust causing it to be carcinogenic have not been conclusively

established, we consider it appropriate to evaluate nickel emissions as a potential carcinogen via the

inhalation pathway. In addition, nickel oxides can be reduced to nickel sulfates (some of which are

carcinogenic) in the presence of sulfuric acid (Weast 1986). Hazardous waste combustors which burn wet

wastes containing significant amounts of nickel and sulfur may need to be especially concerned with

nickel emissions. 

We generally recommend evaluating nickel as an inhalation carcinogen because some forms of

nickel—including nickel carbonyl, nickel subsulfide, and nickel refinery dust—are considered

carcinogens (U.S. EPA 2005c,d,e). This is contrary to the Agency’s previous analysis of the toxicity of
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nickel emissions from hazardous waste combustors. These forms of nickel were not considered in

developing the BIF regulations, because the BIF regulations assumed that nickel can only be emitted as

nickel oxide, which by itself is not considered to be a carcinogen (U.S. EPA 1991a).

If the permitting authority has information at points of potential inhalation exposure that demonstrate the

absence of nickel refinery dust components, or the presence only of noncarcinogenic nickel species, it

may be appropriate to use this information as the basis for supplemental noncarcinogenic calculations. 

For exposure pathways other than inhalation, nickel has not been shown to be carcinogenic (U.S. EPA

2005i). 

2.3.6 Nitroaromatics

We generally recommend carefully considering the information in the following paragraphs before

deciding the appropriateness of including nitroaromatic organic compounds in the risk assessment. It is

reasonable to include nitroaromatics as COPCs if the combustor feed streams include nitroaromatic

compounds or close relatives (TDA and TDI). 

Please Note: In earlier guidance (U.S. EPA 1994g; 1994i; 1994j; 1994r) we

recommended that risk assessments always include nitroaromatic organic compounds,

including 1,3-dinitrobenzene; 2,4-dinitrotoluene; 2,6-dinitrotoluene; nitrobenzene; and

pentachloronitrobenzene. We no longer recommend automatically including

nitroaromatic organic compounds in risk assessments.

Nitroaromatic organic compounds such as 1,3-dinitrobenzene; 2,4-dinitrotoluene; 2,6-dinitrotoluene;

nitrobenzene; and pentachloronitrobenzene (or close relatives such as toluenediamine [TDA] and toluene

diisocyanate [TDI]—derivatives of dinitrotoluene) are typically associated with explosives and other

highly nitrogenated hazardous wastes. Dinitrotoluene is used to make two products: trinitrotoluene and

TDA. TDA is, in turn, used to make TDI. TDI readily reacts with water, and is therefore very unstable at

ambient conditions. TDI is typically reacted with a polyol to form polyurethane (PU) plastics.

Combustion properties of these nitroaromatic compounds indicate that they won’t be formed as PICs if

they aren’t present in the waste feed stream, mainly because of the thermodynamic and chemical

difficulty of adding a nitro group to an aromatic. The process requires that (1) nitronium ions be

generated, and (2) an aromatic ring react with the nitronium ion, with the nitronium ion attaching to the

ring. This reaction process is not likely to occur in a hazardous waste combustor because (1) the reaction

is typically carried out by using a “nitrating acid” solution consisting of three parts concentrated nitric
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acid to one part sulfuric acid, and (2) nitronium ions aren’t usually formed in a combustor environment (if

they are, a thermodynamically more favorable reaction will occur, thereby eliminating the nitronium ion)

(Hoggett, et al 1971; Schofield 1980; March 1985). 

Combustion conditions most likely to result in nitrogenated PICs are associated with premature

quenching of the primary flame—resulting from low temperature or excess air in the primary combustion

chamber of the unit (U.S. EPA 1994j). Under such conditions, sampling for hydrogen cyanide is also

recommended (U.S. EPA 1994j).

2.3.7 Particulate Matter

We don’t recommend evaluating PM as a separate COPC in the risk assessment. However, PM is

generally quite useful as an indicator variable, because it can be measured in real time and is sensitive to

changes in combustion conditions.

Particle pollution is a mixture of solid particles and liquid droplets found in the air. Some particles are

emitted directly from a source, while others form in complicated chemical reactions in the atmosphere. In

general, particle pollution consists of a mixture of larger materials, called "coarse particles," and smaller

particles, called "fine particles." Coarse particles have diameters ranging from about 2.5 micrometers

(:m) to more than 40 :m, while fine particles, also known as known as PM2.5, include particles with

diameters equal to or smaller than 2.5 :m. EPA also monitors and regulates PM10, which refers to

particles less than or equal to 10 :m in diameter. PM10 includes coarse particles that are "inhalable" -

particles ranging in size from 2.5 to 10 :m that can penetrate the upper regions of the body's respiratory

defense mechanisms (U.S. EPA 2004b). 

Exposure to particles can lead to a variety of serious health effects. Scientific studies show links between

these small particles and numerous adverse health effects. Long-term exposures to PM, such as those

experienced by people living for many years in areas with high particle levels, are associated with

problems such as decreased lung function, development of chronic bronchitis, and premature death.

Short-term exposures to particle pollution (hours or days) are associated with a range of effects, including

decreased lung function, increased respiratory symptoms, cardiac arrythmias (heartbeat irregularities),

heart attacks, hospital admissions or emergency room visits for heart or lung disease, and premature

death. (U.S. EPA 1982c; 2004c).
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Ambient PM is a complex mix of constituents derived from many sources, both natural and

anthropogenic. Hence, the physicochemical composition of PM generally reflects the major contributing

local and regional sources arising locally as well as regionally. It stands to reason that the contribution of

any given component within the mix may not be equivalent in value or potency, but may well be highly

dependent on other physicochemical attributes (e.g., co- constituents, specific bioavailability, or chelates),

as well as the health status of the exposed individual. Evidence collected to date indicates that the

discovery of a uniquely responsible physicochemical attribute of PM is not likely to occur (U.S. EPA

2004c).

2.3.8 Phthalates

We generally recommend carefully considering the information in the following paragraphs before

deciding the appropriateness of including phthalates in combustor risk assessments. At the same time,

due to their toxicity and bioaccumulative potential, don’t automatically discount the evaluation of

phthalates in the risk assessment. If phthalates are included as COPCs in the risk assessment, we

generally recommend using a metabolism factor (MF) of 0.01 for BEHP, and 1.0 for all other COPCs. 

Please Note: In earlier guidance (U.S. EPA 1994g; 1994i; 1994j; 1994r) we

recommended always including BEHP and DNOP in every risk assessment. We no

longer recommend automatically including phthalates in risk assessments.

Phthalates such as bis(2-ethylhexyl)phthalate (BEHP) and di(n)octyl phthalate (DNOP) are synthesized

by reacting alcohol with phthalic anhydride in the presence of an acidic catalyst in a nonaqueous solvent

(ATSDR 1993; ATSDR 1995b). Among all phthalate plasticizers, BEHP—also referred to as

di(2-ethylhexyl)phthalate or dioctyl phthalate—is produced in the largest volume; it is used in the

manufacturing of polyvinyl chloride, the most widely produced plastic. DNOP is a plasticizer that is

produced in large volumes, and is used in the manufacture of plastics and rubber materials. Because

plastics have become so widely used in society, phthalate plasticizers such as BEHP and DNOP have

become widely distributed in food, water, and the atmosphere (Howard 1990). The general public’s

exposure to phthalate-contaminated food averages 0.3 μg/day/individual, with an estimated maximum

exposure of 2 mg/day/individual (ATSDR 1992). Phthalate plasticizers are commonly found in the

environment and are practically impossible to avoid, especially at the trace concentrations that modern

analyses can detect.
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Phthalates and their predecessors are readily burned, as indicated by their flash points of 150 to 225 oC

(NIOSH 1994). There is no apparent mechanism for phthalate PICs to be formed by burning other

chemical compounds. Therefore, phthalates are very unlikely to be emitted from a combustor, although

some degradation products, such as PAHs, are likely to be emitted when phthalates are included in the

waste feed. However, facilities that burn plastics or materials with phthalate plasticizers should carefully

consider the potential for phthalate plasticizers to exist in the stack gas emissions due to incomplete

combustion. Also, the uncertainties associated with combustion chemistry suggest that stack gas testing

confirm the absence of these compounds from stack emissions, rather than relying on process knowledge

or waste feed characterization data.

Based on the findings of long-term animal carcinogenicity studies, the Agency has classified BEHP as a

“probable human carcinogen” (class B2) (NTP 1982). Because of its octanol-water coefficient (Kow)

value, BEHP has been presumed to have a high tendency to bioaccumulate (Mackay, Shiu, and Ma 1992;

Karickoff and Long 1995). Considering its ubiquity, B2 classification, and high tendency to

bioaccumulate, BEHP is on most Agency lists of target chemicals (see Table A-1), including the Contract

Laboratory Program (CLP) semivolatile organics analysis list; the Groundwater Monitoring List (40 CFR

Part 264, Appendix IX); and the Hazardous Substances and Reportable Quantities List (40 CFR Part

302.4). 

Evidence indicates BEHP is more readily metabolized and excreted by mammalian species than other

contaminants (ATSDR 1987). As stated above, we generally recommend using an MF of 0.01 for BEHP,

and 1.0 for all other COPCs. An MF represents the estimated amount of COPC that remains in fat and

muscle. Based on a study by Ikeda et al. (1980), the Agency (EPA 1995h) used a COPC-specific MF to

account for metabolism in animals and humans. Considering the recommended values for this variable,

MF has a quantitative effect on animal and human concentrations only for BEHP. No information could

be found on the metabolism or disposition of DNOP in the peer-reviewed literature. However,

disposition data were found for an isomer of DNOP, diisooctyl phthalate (DIOP), a branched-chain

phthalate (Ikeda et al., 1978). Based upon its similarity in structure, it may be assumed that DNOP would

behave comparatively to DIOP and BEHP, and therefore, may be over estimated by approximately a

factor of 100.

The 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 using this guidance are
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intake driven, only apply a metabolism factor to evaluating indirect human exposure via ingestion of beef,

milk, and pork. In summary, using an MF doesn’t apply for direct exposures to air, soil, or water, or to

ingestion of produce, chicken, or fish. Using an MF is further discussed in Section 5.4.4.7 and

Appendix B, Tables B-3-10, B-3-11, and B-3-12.

2.3.9 Polychlorinated Biphenyls

Because of evidence that PCBs can be emitted from combustion sources regardless of feed characteristics,

and considering the significant toxicity of PCBs, we recommend conducting stack testing for PCBs to

support the risk assessment. We also recommend automatically including PCBs as COPCs for

combustors that burn PCB-contaminated wastes or waste oils, highly variable waste streams such as

municipal and commercial wastes (for which PCB contamination is a reasonable assumption), and highly

chlorinated waste streams. Due to the toxicity and uncertainties associated with combustion chemistries,

we generally recommend that stack gas testing confirm the absence of these compounds from stack

emissions.

The most commercially useful property of PCBs is that they are chemically stable in relatively adverse

conditions, such as temperatures of several hundred degrees in an oxygen-containing atmosphere. The

more chlorinated congeners are more resistant to reaction. PCBs were produced commercially by the

reaction of the aromatic hydrocarbon biphenyl with chlorine gas in the presence of a suitable catalyst,

generally ferric chloride or another Lewis acid (ATSDR 1995d). The degree of chlorination was

controlled by manipulating the reaction conditions, including temperature, pressure, and the ratio of the

reactants (Erickson 1992; Grayson 1985). The uses and distribution of polychlorinated biphenyls (PCBs)

were severely restricted in the United States in the late 1970s—with additional bans and restrictions

taking effect over the next decade (ATSDR 1995d).

Due to their stability in adverse conditions, destruction of PCBs by burning generally requires contact

with high temperatures (at least 1,200 oC) for an extended period of time (more than 2 seconds), under

conditions with adequate oxygen (Erickson 1992). Waste combustors can contribute significantly to total

emission inventories of PCBs (Alcock et al. 1999; U.S. EPA 1997e). An increasing body of information

supports the likelihood that PCBs may be emitted as by-products of burning, regardless of PCB

contamination in the combustor feed.
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It is possible that PCBs can be formed by the same types of reactions that produce dioxins and furans,

including gas-phase formation, heterogeneous formation from organic precursors, and de novo synthesis

from flyash-bound carbon. Lemieux et al. (1999) hypothesized that if PCBs and dioxins and furans are

formed by similar mechanisms, then emissions of PCBs should correlate with emissions of dioxins and

furans. This hypothesis was tested by reviewing data where both PCBs and dioxins and furans were

measured. An apparent trend was indeed found showing increased PCB emissions with increased

emissions of dioxins and furans. In most cases, PCBs were found in the stack even when there were no

PCBs in the combustor feed. Overall, PCB emissions exceeded dioxin and furan emissions by

approximately a factor of 20, and this trend appeared to hold over five orders of magnitude in dioxin and

furan emissions.

In addition, there is some limited data, from both laboratory and field studies, showing that PCBs may be

formed from burning hazardous waste. Stack tests performed in U.S. EPA Region 10 on a boiler and an

incinerator burning waste with 0.07 and 1.4 percent chlorine, respectively, confirmed the presence of

PCBs in the stack gases (Kalama Chemical, Inc. 1996; Idaho National Engineering Laboratory 1997). 

The concentration of detected coplanar PCBs (as defined in Section 2.3.9.1) found in the boiler stack gas

was 0.55 ng/dscm @ 7% O2 at low temperature conditions (1,357° F) and 1.12 ng/dscm @ 7% O2 at high

temperature conditions (1,908° F). The concentration of total PCBs detected in the incinerator stack gas

was 211 ng/dscm @ 7% O2 at low temperature conditions (1,750 °F) and 205 ng/dscm @ 7% O2 at high

temperature conditions (2,075° F). PCBs with more than four chlorines comprised 51 percent of the total

PCBs in the low temperature test and 59 percent of the total PCBs in the high temperature test.

Other laboratory studies suggest the possible formation of PCBs as PICs from burning hazardous waste

with a high chlorine content. Bergman et al. (1984) heated samples of two chlorinated paraffins (CP) in

conditions similar to incinerator conditions. A CP containing 70 percent chlorine did produce PCB (up to

0.3 percent of the amount of CP), as well as chlorinated benzenes (up to 0.5 percent), chlorinated toluenes

(up to 0.6 percent), and chlorinated naphthalenes (up to 0.2 percent). Similar treatment of a CP

containing 59 percent chlorine produced only chlorinated benzenes (up to 0.1 percent of the amount of

CP, based on a detection limit of 0.0005 percent for each individual compound) and almost all of those

(about 90 percent) were monochlorobenzene (Bergman 1984). This study indicates that burning highly

chlorinated wastes (60 percent or greater chlorine) can produce PCBs. Also, in an experiment involving

4 percent charcoal, 7 percent chlorine, and 1 percent copper catalyst heated to 300° C, PCBs were formed
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at levels approaching 300 ppb for the penta homologue, 200 ppb for the hexa homologue, 150 ppb for the

hepta homologue, and less than 50 ppb for the tetra homologue (Stieglitz et al. 1989).

2.3.9.1 PCB Carcinogenic Risks

In earlier guidance (1994g; 1994i; 1994j; 1994r) we recommended that risk assessments treat all 209 PCB

congeners as a mixture having a single carcinogenic potency. This recommendation was based on the

Agency drinking water criteria for PCBs (U.S. EPA 1988a), which used available toxicological

information with the following limitations:

C Aroclor 1260 was the only PCB for which a cancer SF had been developed; there was no

agreed upon procedure for applying this SF for similar mixtures with less chlorine

content.

C Available physical, chemical, fate-and-transport, and toxicological information on

individual congeners was limited (primarily because separation and synthesis of pure

congeners can be technically difficult).

C The number of tests conducted with various PCB mixtures and specific congeners to

demonstrate similar toxicological effects was very limited.

Research on PCBs has continued since the compilation of U.S. EPA (1988a),. The most important

finding of this research is that some of the moderately chlorinated PCB congeners can have dioxin-like

effects (U.S. EPA 1992e; 1994a; 1996q; ATSDR 1995d). This sub-category includes PCB congeners

with four or more chlorine atoms and few substitutions in the ortho positions (positions designated 2, 2',

6, or 6'). They are sometimes referred to as “coplanar” PCBs, because the rings can rotate into the same

plane if not blocked from rotation by ortho-substituted chlorine atoms. In this configuration, the shape of

the PCB molecule is very similar to that of a PCDF molecule. Studies have shown that these dioxin-like

congeners can react with the aryl hydrocarbon receptor; the same reaction believed to initiate the adverse

effects of PCDDs and PCDFs. The World Health Organization (WHO) used various test results to derive

interim toxicity equivalency factors (TEFs) ranging from 0.1 to 0.00001 for the dioxin-like coplanar PCB

congeners (WHO 1998). 
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TABLE 2-5

TOXICITY EQUIVALENCY FACTORS

FOR COPLANAR PCBs

CAS Number Chemical Structure WHO 1998 TEFs

(unitless)

32598-13-3 3,3',4,4'-tetrachlorobiphenyl 0.0001

70362-50-4 3,4,4',5-tetrachlorobiphenyl 0.0001

32598-14-4 2,3,3',4,4'-pentachlorobiphenyl 0.0001

74472-37-0 2,3,4,4',5-pentachlorobiphenyl 0.0005

31508-00-6 2,3',4,4',5-pentachlorobiphenyl 0.0001

65510-44-3 2',3,4,4',5-pentachlorobiphenyl 0.0001

157465-28-8 3,3',4,4',5-pentachlorobiphenyl 0.1

38380-08-4 2,3,3',4,4',5-hexachlorobiphenyl 0.0005

69782-90-7 2,3,3',4,4',5'-hexachlorobiphenyl 0.0005

52663-72-6 2,3',4,4',5,5'-hexachlorobiphenyl 0.00001

32774-16-6 3,3',4,4',5,5'-hexachlorobiphenyl 0.01

39635-31-9 2,3,3',4,4',5,5'-heptachlorobiphenyl 0.0001

Source: World Health Organization (1998)

Additional congeners are suspected of producing similar reactions, but there is not yet enough data to

derive TEF values for them. Since available analytical methods can now quantify most if not all

individual PCB congeners, we generally consider it reasonable for the permitting authority to request that

additional congeners be reported. For instance, 2,2',4,4',5,5'-Hexachlorobiphenyl (CAS No. 35065-27-1)

is the most prevalent PCB congener found in human milk and fat (McFarland and Clark 1989). Work is

currently underway to develop a separate slope factor for this particular compound (not a coplanar

congener). However, until that work is complete, this compound can only be qualitatively assessed in the

risk assessment.

We generally recommend estimating risks from coplanar PCBs by computing a toxicity equivalency

quotient (TEQ) for PCBs, and then applying a slope factor for dioxin. High resolution gas chromatograph

test methods, available at most commercial laboratories with dioxin/furan analytical capabilities, are able

to identify the specific concentration of individual coplanar PCBs in stack gas.
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In addition to the coplanar (dioxin-like) PCB congeners, We also generally recommend evaluating the

remaining PCBs in the risk assessment. After considering the accumulated research on PCBs, especially

a recent carcinogenesis study of Aroclors 1016, 1242, 1254, and 1260 and a number of studies of the

transport and bioaccumulation of various congeners, USEPA (1996q) derived three new SFs to replace

the former single SF for PCBs. These new SFs became effective in IRIS on October 1, 1996. These SFs

are subject to revision as additional information from continuing research becomes available. The SFs

and the criteria for their use are as follows (U.S. EPA 1996q):

TABLE 2-6

ORAL SLOPE FACTORS FOR PCBs

Slope Factor (milligrams

per kilogram-day)-1 Criteria for Use

2 Food chain exposure

Sediment or soil exposure

Early-life (infant and child) exposure by all routes to all PCB mixtures 

Congeners with more than four chlorines comprise more than 0.5 percent of the total PCBs

0.4

(Not Typically Used)

Ingestion of water-soluble (less chlorinated) congeners

Inhalation of evaporated (less chlorinated) congeners 

0.07 Congeners with more than four chlorines comprise less than 0.5 percent of the total PCBs

Source: U.S. EPA 1996q

An SF of 2 (milligrams per kilogram-day)-1 is typically used in most circumstances when conducting a

risk assessment. An SF of 0.07 (milligrams per kilogram-day)-1 is generally scientifically defensible for

adult exposures, when congener-specific analyses of emissions demonstrate that at least 99.5 percent of

the mass of the released PCB mixture has fewer than five chlorine atoms per molecule (U.S. EPA 1996q). 

Acceptable congener-specific analyses include high-resolution gas chromatography/mass spectroscopy

(or similar means) for total PCB concentrations for each mono- through deca-isomer group. We don’t

expect that the 0.4 SF will be widely used in combustion risk assessments, because the PCB mixture will

usually contain 0.5 percent or more PCB congeners with more than 4 chlorines.

2.3.9.2 Potential PCB Non-Cancer Effects

In addition to cancer risk associated with all PCBs, we generally recommend determining noncancer

hazard for those Aroclors having RfDs. IRIS specifies RfDs for Aroclor 1254 and Aroclor 1016 (U.S.

EPA 2005i). The RfD for Aroclor 1254 (2x10-5 milligrams per kilogram-day) will typically be used in
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most circumstances when conducting a risk assessment. We consider this approach reasonable because

approximately 77 percent of Aroclor 1254 is composed of PCB congeners with more than 4 chlorines

(Hutzinger et al. 1974). The RfD for Aroclor 1016 (7x10-5 milligrams per kilogram-day) is scientifically

defensible for each homologue group demonstrating that at least 99.5 percent of the mass of the released

PCB mixture has more than four chlorine atoms per molecule (U.S. EPA 1996q). We generally consider

this approach reasonable because approximately 99 percent of Aroclor 1016 is comprised of PCB

congeners with 4 or fewer chlorines (Hutzinger et al. 1974).

We also recommend evaluating th risks to infants from exposure to coplanar PCBs in human breast milk. 

Please see Section 2.3.10.2 for information on comparing estimated levels of coplanar PCBs (along with

dioxins and furans) to background. More information on the breast milk pathway is in Chapter 4, and

Tables C-3-1 and C-3-2.

2.3.9.3 Fate & Transport of PCBs

When evaluating coplanar PCB congeners, or PCB congener mixtures of which greater than 0.5 percent

contain more than 4 chlorines, we recommend using the fate and transport properties for Aroclor 1254. 

When assessing risks and hazards from PCB congener mixtures of which less than 0.5 percent contain

more than 4 chlorines, we recommend using the fate and transport properties of Aroclor 1016.

2.3.10 Polychlorinated Dibenzo(p)dioxins and Dibenzofurans

As was the case with previous Agency guidance (U.S. EPA 1994i, 1994j, 1994n, 1994r, and 1998c), we

recommend including PCDDs and PCDFs in the risk assessment. Information in U.S. EPA (2000b)

suggests that there is adequate evidence that exposure to PCDDs and PCDFs results in a broad spectrum

of cancer and noncancer effects in animals, some of which may occur in humans. 

PCDDs and PCDFs were first discovered as thermal decomposition products of polychlorinated

compounds, including (1) the herbicide 2,4,5-T, (2) hexachlorophene, (3) PCBs, (4) pentachlorophenol,

and (5) intermediate chemicals used to manufacture these compounds. One mode in which PCDDs and

PCDFs form is in dry APCSs, where fly ash catalyzes reactions between halogens and undestroyed

organic material from the furnace. In recent years, as chemical analytical methods have become more

sensitive, additional sources of PCDDs and PCDFs have been identified, including (1) effluent from
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paper mills that use chlorine bleaches, and (2) combustion sources such as forest fires, municipal waste

and medical incinerators, and hazardous waste combustors. Duarte-Davidson et al. (1997) noted that

burning chlorine-containing materials in municipal solid waste is responsible for about two-thirds of the

total annual emissions of newly formed TCDDs and TCDFs in the United Kingdom. In the United States,

U.S. EPA (1998a) estimated that emissions of dioxin TEQs from municipal solid waste incinerators

accounted for 37 percent of all emissions of dioxins into the environment in 1995. The current Agency

draft dioxin sources inventory suggests that open barrel burning is the largest current single source of

release of these compounds (U.S. EPA 2000).

PCDDs and PCDFs are formed at these combustion sources from the reaction of chlorine-containing

chemicals and organic matter. Predicting the formation of PCDDs and PCDFs in a specific situation is

difficult because dechlorination, which produces PAHs from PCDDs and PCDFs, occurs under similar

conditions. Recent studies (Addink et al. 1996; Environment Canada 1987; Fröese and Hutzinger 1996a,

1996b; Gullett et al.1994; Kilgroe et al. 1991; Luijk et al. 1994; and Shriver 1994) have explored some of

these complexities, including (1) the formation of PCDDs and PCDFs from simple organics (such as

ethane) and complex organics (such as dibenzofuran), and (2) the catalysis of these reactions by various

common metals, such as copper. Wikström et al. (1996) found that the form of chlorine—whether

organic, as with chlorinated solvents, or inorganic, as with bleach and salts—has little effect on the

quantity of PCDDs and PCDFs formed. However, their study found that the total concentration of

chlorine is important. In particular, if the waste being burned exceeds 1 percent chlorine, the PCDD and

PCDF formation rate increases significantly. In contrast, Rigo et al. (1995) analyzed over 1,700 test

results with varying chlorine feed concentrations and found no statistically significant relationship. The

formation rate of PCDDs and PCDFs may also depend on the physical characteristics of the waste feed

stream. Solid waste streams or high-ash-content liquid waste feed streams may increase particulate levels

in the combustion system between the combustion unit and the APCS. The increased particulate levels

provide additional surfaces for catalysis reactions to occur.

A review of currently available dioxin data for combustors reveals that total PCDD/PCDF emission rates

vary by more than 28-fold between different facilities, even though they use similar combustion units and

APCSs (U.S. EPA 1996b). Site-specific emission data are therefore needed to complete a more refined

risk assessment of each combustor.
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In evaluating fate-and-transport, it is important to consider the chemical and physical properties of

dioxins. In soil, sediment, and the water column, PCDDs and PCDFs are primarily associated with

particulate and organic matter because of their high lipophilicity and low water solubility. Ambient air

monitoring studies, in which researchers studied the partitioning of dioxin-like compounds between the

vapor and particle phases, suggest that the higher chlorinated congeners (the hexa through octa

congeners) principally sorb to airborne particulates. The tetra and penta congeners significantly, if not

predominantly, partition to the vapor phase (U.S. EPA 2000b). These findings are consistent with

vapor/particle partitioning as theoretically modeled in Bidleman (1988). Dioxin-like compounds exhibit

little potential for significant leaching or volatilization (U.S. EPA 2000b).

The following subsections clarify the procedures we recommend using (in conjunction with the

procedures described in Chapter 7) to estimate risks associated with PCDDs and PCDFs. Also, we’re

aware of growing concern regarding the risks resulting from exposure to (1) fluorine- and

bromine-substituted dioxins and furans, and (2) sulfur analogs of PCDDs and PCDFs. Research

regarding these compounds is ongoing. Until such time as new information is released, though, you can

consider the following subsections as our guidance on how to evaluate fluorine, bromine, and sulfur

PCDD/PCDF Analogs as potential COPCs in hazardous waste combustor risk assessments.

2.3.10.1 PCDD/PCDF Cancer Risks

We recommend using the TEF method to assess carcinogenic risk on the basis of toxicity relative to

2,3,7,8-TCDD, which is the most toxic dioxin. 

There are 210 individual compounds or “congeners” of PCDDs and PCDFs. Seventeen of these 210

congeners are considered to have "dioxin-like" toxicity. In the TEF method, each of these 17 congeners

is assigned a value, referred to as a toxicity equivalency factor (TEF), which compares its toxicity to that

of 2,3,7,8-TCDD. 2,3,7,8-TCDD then has a TEF of 1.0, and other dioxin-like congeners have TEFs

between 0.0 and 1.0. TEF values for these 17 congeners are listed in the Table 2-7.
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TABLE 2-7

PCDD/PCDF TOXICITY EQUIVALENCY FACTOR VALUES

Dioxin Congener TEF

(unitless)

Furan Congener TEF

(unitless)

2,3,7,8-Tetrachlorodibenzo(p)dioxin 1.0 2,3,7,8-Tetrachlorodibenzofuran 0.1

1,2,3,7,8-Pentachlorodibenzo(p)dioxin 1.0 1,2,3,7,8-Pentachlorodibenzofuran 0.05

1,2,3,4,7,8-Hexachlorodibenzo(p)dioxin 0.1 2,3,4,7,8-Pentachlorodibenzofuran 0.5

1,2,3,6,7,8-Hexachlorodibenzo(p)dioxin 0.1 1,2,3,4,7,8-Hexachlorodibenzofuran 0.1

1,2,3,7,8,9-Hexachlorodibenzo(p)dioxin 0.1 1,2,3,6,7,8-Hexachlorodibenzofuran 0.1

1,2,3,4,6,7,8-Heptachlorodibenzo(p)dioxin 0.01 1,2,3,7,8,9-Hexachlorodibenzofuran 0.1

1,2,3,4,6,7,8,9-Octachlorodibenzo(p)dioxin 0.0001 2,3,4,6,7,8-Hexachlorodibenzofuran 0.1

1,2,3,4,6,7,8-Heptachlorodibenzofuran 0.01

1,2,3,4,7,8,9-Heptachlorodibenzofuran 0.01

1,2,3,4,6,7,8,9-Octachlorodibenzofuran 0.0001

Source: World Health Organization (1998)

Van den Berg et al (1998). 

To estimate the exposure media concentrations for PCDDs and PCDFs, we recommend using the 

congener-specific emission rates from the stack. Then, model the fate and transport of each of these 17

congeners to the exposure site to estimate congener-specific exposure media concentrations. The

HHRAP companion database includes congener-specific fate and transport parameter values, and the

media concentration equations are provided in Appendix B. After estimating congener-specific exposure

media concentrations, we recommend using the TEFs to estimate a "toxic equivalent" (TEQ) exposure

media concentration, and an overall TEQ exposure and cancer risk, as follows:

1. convert the exposure media concentrations of an individual congener to a TEQ

concentration for that congener by multiplying the congener’s media concentrations by

the congener’s TEF;

2. sum the TEQ concentrations of the individual congeners to get an overall exposure media

concentration;

3. estimate the lifetime average daily dose (LADD) for the TEQ concentration; and

4. assess the cancer risk on a TEQ basis using the cancer slope factor for 2,3,7,8-TCDD, in

combination with the TEQ-based LADD.

Please see Chapter 7 for a more complete discussion of the steps included in the TEF method. 
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2.3.10.2 PCDD/PCDF Noncancer Hazards

We generally recommend comparing PCDD and PCDF oral exposure estimates to national average

background exposure levels, using 1 pg TEQ/Kg/day for adults and 60 pg TEQ/kg/day for nursing

infants. The pertinent exposure estimate would be the ADD, or Average Daily Dose, experienced over

the course of the exposure duration, rather than the LADD, which is this ADD averaged over a lifetime.

The Agency typically evaluates noncancer effects of chemicals by comparing exposure levels to healthbased reference doses or reference concentrations. However, for reasons discussed in the Agency’s Draft

Dioxin Reassessment (U.S. EPA 2000b), the Agency has not developed these non-cancer benchmarks for

any of the PCDD or PCDF congeners, or for TEQ concentrations/doses.

One approach the Agency has taken to evaluate whether PCDDs and PCDFs emitted from hazardous

waste combustion facilities are likely to cause significant noncancer health effects is to compare estimated

TEQ exposures to national average background exposure levels (1 pg TEQ/kg/day for adults and 60 pg

TEQ/kg/day for nursing infants). The average background level of PCDD/PCDFs and co-planar, dioxinlike PCBs in breast milk is 25 parts per trillion (ppt) of 2,3,7,8-TCDD TEQ (EPA 2000b). The 25- ppt

2,3,7,8-TCDD TEQ is the sum of the average breast milk concentration of 18-ppt TEQ from

PCDD/PCDFs and 7-ppt TEQ from co-planar, dioxin-like PCBs (EPA 200b). After normalization for

infant body weight, this breast milk concentration of 25 ppt TEQ results in an average, background intake

for the infant, ADIb-inf, of 93 picograms per kilogram per day (pg/kg-day) of 2,3,7,8-TCDD TEQ. If

exposures due to the facility’s emissions during the exposure duration of concern are low compared to

background exposures, then the emissions aren’t expected to cause an increase in noncancer effects.

In the future, the Agency may develop alternative approaches to evaluate noncancer effects from

exposures to PCDDs and PCDFs. In that case, those approaches may be included in future risk

assessments.

2.3.10.3 Fluorine, Bromine, and Sulfur PCDD/PCDF Analogs

We generally recommend deciding on a site-specific basis whether to evaluate these compounds, in

consultation with the permitting authority. Considering that neither the likelihood of the formation, nor
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the toxicity of these compounds is well understood, the permitting authority is not likely to request a

quantitative toxicity assessment of fluorine, bromine, and sulfur analogs. 

The Agency is currently evaluating the potential for the formation of (1) fluorine- and brominesubstituted dioxins and furans, and (2) sulfur analogs of PCDDs and PCDFs (U.S. EPA 1996h; 1996m). 

Available information indicates that fluorinated dioxins and furans aren’t likely to be formed as PICs;

although the presence of free fluorine in the combustion gases may increase the formation of chlorinated

dioxins (U.S. EPA 1996h). We aren’t aware of any studies conducted to evaluate this relationship. 

Available information indicates that there is potential for brominated or chlorobrominated dioxins to form

(U.S. EPA 1996i). The Agency has not assigned TEF values for brominated dioxins or furans (U.S. EPA

1994k). However, the toxicity of bromo- and chlorobromo-substituted dioxin analogs is comparable to

that of chlorinated dioxins in short-term toxicity assays (U.S. EPA 1996m).

Although chlorinated dibenzothiophenes (the sulfur analogs of dibenzofurans) have been reported to

form, no information is available indicating the formation of chlorinated dioxin thioethers (the sulfur

analogs of dibenzo[p]dioxins) (U.S. EPA 1996h). This may be because the carbon-oxygen bond is

stronger than the carbon-sulfur bond, and the compound furan (which is part of the dibenzofuran

structure) is more stable than thiophene (which is part of the dibenzothiophene structure) (U.S. EPA

1996c). Another possible reason that chlorinated dioxin thioethers have not been observed is the potential

instability of these compounds. Chlorinated dioxin thioethers contain two carbon-sulfur bonds in the

central ring of the structure (U.S. EPA 1996h). 

Please Note: There is currently no U.S. EPA-approved method for the sampling or

analysis of these dioxin analogs. 

We generally recommend using the TOE method (see Section 2.2.1.2) to account for the potential

presence of these compounds. The Uncertainty section of the risk assessment report (See Chapter 8)

could then discuss the potential for the formation of these analogs.
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C Description of any combustor-specific operating conditions that may contribute to the

formation of dioxins

C Any facility-specific sampling information regarding PCDD and PCDF concentrations in air,

soil, water, or biota

C Information regarding the concentrations of sulfur, fluorine, and bromine in the combustor

feed materials

RECOMMENDED INFORMATION FOR THE RISK ASSESSMENT REPORT

2.3.11 Polynuclear Aromatic Hydrocarbons (PAHs)

As is the case in previous Agency guidance (U.S. EPA 1994i, 1994j, 1994r, 1998c), we recommend

evaluating PAHs as COPCs. The following are commonly detected PAHs: 

• benzo(a)pyrene (BaP); 

• benzo(a)anthracene; 

• benzo(b)fluoranthene; 

• benzo(k)fluoranthene; 

• chrysene; 

• dibenz(a,h)anthracene; and 

• indeno(1,2,3-cd)pyrene. 

The Agency considers all of these compounds to be carcinogenic. However, an IRIS oral cancer slope

factor is only available for benzo(a)pyrene.

PAHs are readily formed in combustors by either (1) dechlorination of other PAHs (such as dioxins)

present in the waste feed or emissions stream, or (2) the reaction of simple aromatic compounds (benzene

or toluene) present in the waste feed or emissions stream. PAHs are well-known as the principal organic

components of emissions from all combustion sources, including coal fires (soot), wood fires, tobacco

smoke ("tar"), diesel exhaust, and refuse burning (Sandmeyer 1981). They are generally the only

chemicals of concern in particulate matter (Manahan 1991), although the presence of metals and other

inorganics in the waste feed can add other contaminants of concern. Based on the toxicity and

combustion chemistry of PAHs, we generally recommend that stack gas testing confirm the absence of

these compounds from stack emissions. 
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At present, BaP is the most studied PAH and the only one for which a 2-year feeding rodent bioassay has

been conducted (U.S. EPA 1991c). The studies available for the other carcinogenic PAHs were

conducted by injection, dermal or gavage. Multiple animal studies in rodent and nonrodent species

demonstrated BaP to be carcinogenic following administration by oral, intratracheal, inhalation, and

dermal routes. BaP also produced positive results in several in vitro bacterial and mammalian genetic

toxicity assays, in addition to numerous in vivo tests for deoxyribonucleic acid (DNA) damage. BaP

metabolizes to reactive electrophiles that are capable of binding to DNA (U.S. EPA 1990h). Therefore,

U.S. EPA (1993d) used various nonbioassay results to determine relative potency factors (RPFs) for the

class B2 carcinogen PAHs. RPFs for these seven PAHs are listed in Table 2-8.

TABLE 2-8

RELATIVE POTENCY FACTORS 

FOR CLASS B2 CARCINOGEN PAHs

Compound RPF

Benzo(a)pyrene 1.0

Benz(a)anthracene 0.1

Benzo(b)fluoranthene 0.1

Benzo(k)fluoranthene 0.01

Chrysene 0.001

Dibenz(a,h)anthracene 1.0

Indeno(1,2,3-cd)pyrene 0.1

Source: U.S. EPA (1993d)

Obtaining test data for an individual chemical from a standard carcinogenesis bioassay that might be used

to develop a cancer slope factor requires: 

1. at least 1 kilogram of relatively pure chemical (greater than 98 percent purity is the most

common specification), 

2. $500,000 to $1,000,000, and 

3. 5 to 6 years. 

However, an alternative to the full carcinogenesis bioassay is to use in vitro studies to compare various

PAHs. In vitro studies, such as those conducted by Knebel et al. (1994) and many other groups, require a

few milligrams of each chemical, a few weeks, and about $1,000 per chemical. Because of these
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differences, we wouldn’t anticipate that many full carcinogenesis bioassays of PAHs will be carried out in

the near future.

As with previous guidance (U.S. EPA 1994g), we generally recommend evaluating PAHs using an

approach similar to the BaP-RPF method. We generally recommend using the fate-and-transport

properties of specific PAHs (versus those of benzo[a]pyrene) to estimate exposure concentrations. Then

following the BaP-RPF method, you adjust the concentrations of the individual PAHs and sum them to

obtain an equivalent total concentration of BaP. Multiply this summed concentration by the BaP cancer

SF to estimate total risk from all carcinogenic PAHs.

We don’t currently recommend a metabolism factor (MF) for PAHs. A published study (Hofelt et al.

2001), however, highlights the uncertainty in the HHRAP’s approach and presents an alternative

metabolism factor for use. If this alternative metabolism factor is used, you may wish to consider the

following site-specific points: 

1. If the PAHs under consideration are metabolized in the animal (beef, pork, etc) has it

been determined that the degradation products/metabolites aren’t persistent in the

meat/and or milk? (This concern has been raised because it is the degradation products

of PAHs that cause the toxicity.); 

2. Is the extrapolation from the rat to larger animal appropriate?; and 

3. If the metabolism factor is appropriate, should it be used equally for all the PAHs being

evaluated? 

Using an MF is discussed further in Section 5.4.4.7 and Appendix B, Table B-3-10.

In addition to carcinogenic effects, noncarcinogenic health effects are associated with exposure to PAHs. 

However, RPFs for noncarcinogenic effects of PAHs (similar to those developed for carcinogenic effects)

have not been developed. The uncertainties associated with attempting to quantify the potential

noncarcinogenic effects of PAHs without RfDs or RfCs is typically considered greater than the

uncertainty associated with not evaluating these potential effects. However, if site-specific emissions data

indicate that significant amounts of noncarcinogenic PAHs are emitted, we generally recommend that the

potential to underestimate the noncarcinogenic health effects associated with exposure to PAHs be

discussed in the Uncertainty section of the risk assessment report.
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2.3.12 Radionuclides

Radionuclides exist in naturally occurring materials such as coal and other rocks, and as radioactive

by-products of industrial processes. The HHRAP doesn’t consider the naturally occurring concentrations

of radioactive materials such as uranium and thorium (and their decay elements), based on Agency policy

and technical limitations for measuring such low levels. However, radioactive wastes and materials, as

defined by the U.S. Nuclear Regulatory Commission (NRC) and the U.S. Department of Energy (DOE),

are subject to evaluation through interagency agreements on this subject. The U.S. NRC considers

“radioactive waste” as waste that is, or contains, by-product material, source material, or special nuclear

material (as defined in 10 CFR Part 20.1003). The U.S. NRC considers “mixed waste” as waste that

contains both radioactive waste and hazardous waste (as defined by U.S. EPA). Both radioactive and

mixed wastes must be handled in accordance with all relevant regulations, including U.S. EPA and U.S.

NRC (10 CFR Part 20.2007) regulations. In particular, U.S. NRC licensees must comply with 10 CFR

Part 20.2004—“Treatment or Disposal by Incineration”—and applicable U.S. EPA regulations.

We generally recommend evaluating the burning of mixed waste and radioactive material if those

substances are components of the combustor feed. We also generally recommend including a

radionuclide as a COPC if it is in the combustor’s feed, and has an available toxicity value (e.g., slope

factor). Slope factors for over 300 radionuclides are available in HEAST. The slope factor for a

particular radionuclide is multiplied by the intake (pCi) or soil concentration and years of exposure (pCi/g

times years of exposure) to estimate cancer risk.

Radionuclide exposure pathways typically evaluated in human health risk assessments include inhalation,

ingestion of food products (e.g., meat, milk, vegetables), incidental soil ingestion, external exposure from

ground surface deposits, and external exposure from air concentrations (air submersion). The submersion

exposure pathway may be of particular concern for radionuclides that emit high-energy beta particles. 

Environmental transport and subsequent human exposure are commonly evaluated through the use of

radionuclide “dose” codes or computer code/spreadsheet combinations. A dose code combines air

dispersion/deposition modeling with terrestrial transport models, human exposure parameters, and

pre-calculated dose conversion factors [ e.g., from Federal Guidance Report No. 11 (U.S. EPA 1988c)

and Federal Guidance Report No. 12 (U.S. EPA 1993j)] to obtain dose and/or risk. The following are

several available dose codes for evaluating radionuclides from mixed waste combustion facilities:
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C CAP-88 (Clean Air Act Assessment Package - 1988)

C GENII (The Hanford Environmental Radiation Dosimetry Software System)

C MEPAS (Multimedia Environmental Pollutant Assessment System)

C ISCST3 (Industrial Source Complex Dispersion Model)

C CALPUFF (California Puff Model)

To calculate air concentrations and ground deposition rates of radionuclides, we generally recommend the

ISCST3 air dispersion model using the exponential decay option. Intake can then be calculated with

appropriate exposure scenario equations and parameters. ISCST3 is a good choice for facilities with

multiple sources, complex terrain, building downwash, and wet/dry deposition requirements. A second

option is to use the air concentration and ground deposition rate output from another dose code (e.g.,

CAP-88 if the facility has completed its NESHAPs analysis). 

We generally recommend that equations for fate and transport of radionuclides in soil and water be

consistent with those presented for non-radionuclides, while factoring in decay (and ingrowth if

applicable). The recommended food chain biotransfer parameters used to determine food concentrations

are available in the user’s guides for most of the dose codes listed previously. However, a comprehensive

reference for obtaining these values is the Handbook of Parameter Values for the Prediction of

Radionuclide Transfer in Temperate Environments; IAEA Technical Report Series No. 364 (International

Atomic Energy Agency 1994).

Decay and ingrowth of radionuclides is a special consideration for integrating radioactive materials into

risk calculations. Most radioactive materials undergo radioactive decay through a series of

transformations rather than in a single step. Until the last step, these radionuclides emit energy or

particles with each transformation and become other radionuclides. As radioactive decay progresses, the

concentration of the original radionuclides decreases, while the concentration of their decay products

increases and then decreases as the decay products themselves transform. The increasing concentration of

decay products and activity is called ingrowth. We recommend that the assessment consider decay over

both the air transport time and the surface exposure duration. Ingrowth may be important, and we

generally recommend the assessment use radionuclide slope factors that include contributions from decay

elements (“+D” slope factors). Ingrowth that involves change of physical state is another situation
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needing special attention in the fate and transport modeling. For instance, solid radium-226 decays to

gaseous radon-222, which then decays through solid polonium-218 to further decay elements. 

Options for estimating cancer risks from exposure to radionuclides include using the slope factor

methodology presented in the Agency’s Estimating Radiogenic Cancer Risks (U.S. EPA 1994s), or using

estimates of the relationship between radiation dose and cancer risk to convert dose to risk. Federal

Guidance Report No. 13 (U.S. EPA 1999d) contains recent estimates of cancer risk for given radiation

dose, based on low-dose, low-Linear Energy Transfer uniform irradiation of the body. For these

conditions, radiation dose equivalent (rem) and absorbed dose (rad) are approximately equivalent. The

Report provides risk estimates in terms of mortality and morbidity. It is important to use the estimate

appropriate to the site and assessment in question. 

The dose-conversion approach uses a single factor to convert dose to risk. It is limited, then, in that it

doesn’t take into account variations among radionuclides in the relationship between dose and risk. In

general, though, this approach is protective. The slope factor approach generally provides a better

estimate of risk. Limitations of the slope factor conversion methodology, however, include:

C It assumes a single chemical form, which is not necessarily site-specific or most

protective; 

C External radiation slope factors are only provided for soil contaminated to an infinite

thickness, which will over-estimate exposure from radionuclide concentrations near the

surface;

C Slope factors aren’t available for the submersion in water exposure pathway; and 

C Slope factors include decay chains for a limited number (18) of parent radionuclides

(although these are the most significant decay chains)

Some radioactive materials, such as uranium, also present a non-carcinogenic hazard that it is possible to

evaluate. We generally recommend also assessing these non-carcinogenic hazards. We also recommend

that the risk summary table in the risk assessment report present the cancer risk from radiological

contaminants alongside the risks from non-radiological contaminants.

To enhance transparency, we generally recommend that results include a discussion of additivity and the

uncertainties of additivity when combining risks from radiological and non-radiological contaminants. 

There are fundamental differences between the slope factors for chemical and radionuclide carcinogens. 
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Most notably, the slope factors for chemical carcinogens generally represent an upper bound or 95th

percent confidence limit value, while radionuclide slope factors are best estimate (50% confidence)

values. 

Please Note: A prescriptive method for calculating risk from combustion facilities

burning mixed waste is beyond the scope of the HHRAP. The above information is

provided to outline the method we recommend.

2.3.13 Volatile Organic Compounds

U.S. EPA (1990e) reported that volatile organics listed as probable PICs (based on Freeman 1988 and

1989) produced by burning hazardous waste include: 

• benzene; 

• chloroform; 

• tetrachloroethylene; 

• 1,1,1-trichloroethane; 

• toluene; and 

• methylene chloride. 

However, the validity of evaluating volatile organic COPCs through the various indirect exposure

pathways (see Chapter 4) is subject to debate. One argument to exclude these COPCs from evaluation is

that there is no empirical evidence that VOC emissions pose a hazard via indirect pathways. We’re

similarly not aware of any such evidence, but we’re also unaware of any evidence to the contrary.

Another argument to exclude VOCs from evaluation is based on the conclusion that 

1. volatile organic COPCs released into the air are expected to remain in the gas phase unless or

until they are transformed into low-volatility compounds, and 

2. this transformation (or atmospheric chemical reaction), and the subsequent removal of the

reaction products, makes irrelevant the toxicity of the parent volatile organic COPC. 

We disagree with both aspects of this argument. First, we’re not aware of any information or research

documenting the fate-and-transport of volatile organic COPCs from hazardous waste combustors. 

Second, although we agree that the toxicity of the parent COPC is irrelevant following transformation,

this argument ignores the potential toxicity of the reaction products. We’re not aware of any available

quantitation methods that could be used to predict atmospheric chemical reactions of this nature. We

therefore generally believe that evaluating the fate-and-transport (and toxicity) of the parent COPC
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remains the best available method for protectively accounting for the potential reaction products to which

receptors are ultimately exposed.

Finally, another argument to exclude VOCs from evaluation is the assertion that there is no firm technical

basis for assessing the rate of deposition of VOCs to soils or uptake by plants (discussed in detail in

Appendix A-2). Although we agree with the basic premise of this issue, we’re unaware of any other

method for evaluating the potential indirect exposure to volatile organic COPCs or their atmospheric

reaction products (empirical data aren’t available).

To summarize, we agree in principle that the science regarding the fate-and-transport of volatile organic

COPCs in the environment is poorly understood. However, because the potential risks associated with

indirect exposure to these COPCs is also poorly understood, we believe that evaluating volatile organic

COPCs via the indirect exposure pathways—with the proper explanation of the uncertainties associated

with this process—generally provides the most reasonable (based on current science) and protective

estimate of these potential risks. We also believe that the risk equations generally address this issue

because a calculation cannot be completed unless there are sufficient fate and transport properties values

for each COPC. 

Finally, current sampling and analytical methods aren’t always able to positively identify all individual

organic compound in stack emissions. We recommend accounting for the mass of unidentified organic

compounds in stack emissions on the basis of TOE from the hazardous waste combustor. The

methodology for using TOE in a risk assessment is discussed further in Section 2.2.1.2.
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2.4 ESTIMATING COPC CONCENTRATIONS FOR NON-DETECTS

One particularly difficult issue in a risk assessment is how to treat data that are reported as below the

“detection limit” (i.e. “Non-detects”). The following subsections:

1. define commonly reported detection limits; 

2. describe the use of non-detect data in the risk assessment; 

3. describe statistical distribution techniques applied to address this issue; 

4. summarize our recommendations on quantifying non-detects for use in risk assessments;

and 

5. clarify use of data flagged as estimated maximum possible concentration (EMPC) in the

risk assessment.

2.4.1 Definitions of Commonly Reported Detection Limits

Generically, a “detection limit” is the lowest level of an analyte that can be detected using a particular

analytical method. The Agency’s commonly-used definition for the detection limit for non-isotope

dilution methods is the method detection limit (MDL), as promulgated in 40 CFR Part 136, Appendix B

(U.S. EPA 1995i). A level above the MDL is the level at which reliable quantitative measurements can

be made; generically called the “quantitation limit” or “quantitation level.” In practice, numerous terms

have been created to describe detection and quantitation levels. We have summarized below the

significance and applicability of the levels most widely reported by analytical laboratories. These

levels—listed generally from the lowest limit to the highest limit—include the following:

C Instrument Detection Limit (IDL): The smallest signal above background that an instrument can

reliably detect, but not quantify. Also commonly described as a function of the signal-to-noise

(S/N) ratio.

C Method Detection Limit (MDL): The minimum concentration of a substance that can be

measured (via non-isotope dilution methods) and reported with 99 percent confidence that the

analyte concentration is greater than zero. It is determined from analysis of a sample in a specific

matrix type containing the analyte. The MDL is considered the lowest level at which a

compound can be reliably detected. The MDL is based on statistical analyses of laboratory data. 

In practice, MDLs are determined on analytical reagents (e.g., water) and not on the matrix of

concern. However, a laboratory may contract to do a matrix-specific “MDL Study” for a

particular project or a particular facility’s waste matrix when needed. However, routine MDL

determinations (water reagent) are conducted on at least an annual basis or whenever equipment

changes occur. MDLs for a given method are laboratory- and compound-specific.
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Equation 2-3

To determine the MDL as specified in 40 CFR Part 136, Appendix A, for example, at least seven

replicate samples with a concentration of the compound of interest near the estimated MDL are

analyzed. The standard deviation among these analyses is calculated and multiplied by 3.14. The

result of the calculation becomes the MDL. The factor of 3.14 is based on a t-test with six

degrees of freedom and provides a 99 percent confidence that the analyte can be detected at this

concentration (U.S. EPA 1995i). 

Please Note: 40 CFR Part 136 is specific to the Clean Water Act, and it identifies the use of

water as the matrix for the MDL determination. The MDL was promulgated in 1984, and is

incorporated in more than 130 Agency analytical methods for determining several hundred

analytes.

C Reliable Detection Level (RDL): A detection level recommended by the National Environmental

Research Laboratory in Cincinnati. It is defined as 2.623 times the MDL (U.S. EPA 1995i).

C Estimated Detection Limit (EDL): A quantitation level defined in SW-846 that has been applied

to isotope dilution test methods (e.g., SW-846 Method 8290). A variation of the SW-846 defined

EDL is also commonly reported by commercial laboratories, however, with the addition of a

multiplication factor that generally elevates the EDL value by 3.5 to 5 times that of the SW-846

definition. Commercial laboratories sometimes report EDLs for non-isotope dilution methods,

even though an EDL is not defined by the methods.

As defined in SW-846: The EDL is defined in SW-846 (presented in various methods,

e.g., Method 8280A) as the estimate made by the laboratory of the concentration of a given

analyte required to produce a signal with a peak height of at least 2.5 times the background signal

level. The estimate is specific to a particular analysis of the sample and will be affected by

sample size, dilution, etc. The presented equation defining EDL is as follows:

where

EDL = Estimated detection limit (ng/L)

2.5 = Peak height multiplier (unitless)

Qis = Nanograms of the appropriate internal standard added to

the sample prior to extraction (ng)

Hn

1

 and Hn

2 = The peak heights of the noise for both of the quantitation

ions of the isomer of interest

His

1

 and His

2 = The peak heights of both the quantitation ions of the

appropriate internal standards

D = Dilution factor - the total volume of the sample aliquot

in clean solvent divided by the volume of the sample

aliquot that was diluted (unitless)

V = Volume of sample extracted (L)

RFn = Calculated relative response factor from calibration

verification (unitless)
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Equation 2-4

Common commercial laboratory practice: The EDL generally reported by commercial

laboratories is defined as the detection limit reported for a target analyte that is not detected or

presents an analyte response that is less than 2.5 times the background level. The area of the

compound is evaluated against the noise level measured in a region of the chromatogram clear of

genuine GC signals times an empirically derived factor. This empirical factor approximates the

area to height ratio for a GC signal. This factor is variable between laboratories and analyses

performed, and commonly ranges from 3.5 to 5. The equation is as follows:

where

EDL = Estimated detection limit

2.5 = Minimum response required for a GC signal

Q$ = The amount of internal standard added to the sample before

extraction

F = An empirical factor that approximates the area to height ratio for

a GC signal

H = The height of the noise

D = Dilution factor

W = The sample weight or volume

RRFF = The mean analyte relative response factor from the initial

calibration

A$ = The integrated current of the characteristic ions of the

corresponding internal standard

C Practical Quantitation Limit (PQL): A quantitation level that is defined in 50 FR 46908 and

52 FR 25699 as the lowest level that can be reliably achieved with specified limits of precision

and accuracy during routine laboratory operating conditions (U.S. EPA 1992g; 1995i). The PQL

is constructed by multiplying the MDL, as derived above, by a factor (subjective and variable

between laboratories and analyses performed) usually in the range of 5 to 10. However, PQLs

with multipliers as high as 50 have been reported (U.S. EPA 1995i).

The PQL has been criticized because of the ambiguous nature of the multiplier and because the

resulting levels have been perceived as too high for regulatory compliance purposes (U.S.

EPA 1995i).

C Target Detection Limit (TDL): A quantitation level constructed similar to the PQL.

C Reporting Limit (RL): A quantitation level constructed similar to the PQL.

C Estimated Quantitation Limit (EQL): A quantitation level constructed similar to the PQL.

C Sample Quantitation Limit (SQL): A quantitation level that is sample-specific and highly

matrix-dependent because it accounts for sample volume or weight, aliquot size, moisture

content, and dilution. SQLs for the same compound generally vary between samples as moisture
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content, analyte concentration, and concentrations of interfering compounds vary. The SQL is

generally 5 to 10 times the MDL, however, it is often reported at much higher levels due to

matrix interferences.

C Contract Required Quantitation Limit (CRQL)/Contract Required Detection Limit (CRDL): A

quantitation pre-set by contract, which may incorporate SW-846 methods, Office of Water

methods, or other methods deemed necessary to meet study objectives. These limits are typically

administrative limits and may actually be one or two orders of magnitude above the MDL.

2.4.2 Using Non-Detect Data In the Risk Assessment

In collecting waste feed or emissions data for use in risk assessments, or in setting regulatory compliance

levels, a permitting authority is often faced with data quality objectives that require analyses near or

below analytical detection or quantitation levels. In such situations, permittees often argue that the

detection levels should be set with a large factor of certainty in order to be confident that measurements

are reliable. Environmental groups frequently argue that a level of zero, or a level at which a single

researcher can demonstrate that the compound can be detected, should be used as the set level. 

Measurements made below analytical detection and quantitation levels are associated with increased

measurement uncertainty, so it is important to understand the impact they may have when they are

applied.

Because of the quantitative differences between the various types of detection levels, “non-detected”

compounds pose two questions: 

1. Is the compound really present?, and 

2. If so, at what concentration? 

The first question is generally hard to answer, and is dependent mainly on the analytical resources

available. The answer to the second question is “somewhere between true zero and the quantitation level

applied.” In earlier guidance (U.S. EPA 1994i) we recommended applying emission rates of one-half the

“detection limit” for non-detects. However, which detection limit to use was not explicitly defined or

presented in quantitative terms. 

For waste feed data (e.g., used as a surrogate when emissions data is not available), we generally

recommend using the SQL, since waste feeds are typically highly concentrated organic or inorganic

matrices that require special analytical clean-up procedures and dilutions of the sample. This approach is

consistent with that used in other program offices for highly contaminated media requiring quantification
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specifically for risk assessment purposes. However, in dealing with stack emissions data, concentrations

of constituents are typically found only at trace levels (assuming good combustion). Therefore, to

increase consistency and reproducibility in dealing with non-detects for emissions data, we generally

recommend using the MDL-derived RDL to quantify non-detects for COPCs analyzed with non-isotope

dilution methods, and using the method-defined EDL to quantify non-detects for COPCs analyzed with

isotope dilution methods. The procedures are as follows:

For COPCs Analyzed With Non-isotope Dilution Methods: Quantify non-detects by using an

MDL-derived RDL. 

1. Require the laboratory to report the actual MDL as specified in the chosen SW-846

analytical method. The laboratory should report MDLs for every non-detect compound

analyzed, in addition to the commonly used reporting limit, such as an EDL, EQL, or

PQL. 

Commonly used SW-846 non-isotope dilution methods such as Method 8260 (volatiles),

and Method 8270 (semivolatiles) don’t themselves define the MDL. They reference 40

CFR Part 136 instead. Though specified in the Method, some laboratories do not always

report MDLs as defined in 40 CFR Part 136.

This would apply to the analysis of each individual component of multiple-component

samples (e.g., front half rinse, XAD resin, condensate, Tenax tube).

Note: Laboratories typically produce MDLs specific to each non-isotope dilution

method performed by the laboratory on an annual basis. 

2. Calculate an MDL-derived RDL for each COPC non-detect by multiplying the MDL by

2.623 (interim factor) (U.S. EPA 1995i).

Another option is to request that the laboratory derive the RDLs for you (per the

definition above), as part of the analysis. Good quality assurance/quality control

(QA/QC) suggests you check to make sure the RDLs have been generated properly.

3. Adjust the RDL, as appropriate, to account for sample-specific volumetric treatments

(e.g., splits and dilutions) that differ from those used in the Part 136 MDL

determinations.

Again, an option is to have the laboratory perform the adjustments for you. We

recommend you check to make sure the adjustments have been done properly.

For COPCs Analyzed With Isotope Dilution Methods: Quantify non-detects using the EDL as

defined by the analytical method, without the use of empirical factors or other mathematical

manipulations specific to the laboratory. Commonly used isotope dilution methods include

SW-846 Methods 8290, 1624, and 1625, as well as CARB 429.

Methods for Metals Analysis: Quantify non-detects for metal analysis in the risk assessment by

using the IDL as defined by the analytical method, without the use of empirical factors or other

mathematical manipulations specific to the laboratory. 
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Please note this recommendation is an update to the information provided in U.S.

EPA [2001c] Risk Burn Guidance for Hazardous Waste Combustion Facilities.)

The MDL definition used in 40 CFR Part 136 addresses errors of the first type (i.e. false negatives). The

99 percent confidence limit states that the MDL has only a 1 percent chance the detects will be

misidentified as negative, when the compound of concern is actually present. Errors of the second type

(false positives) aren’t addressed. By not addressing false positives, the statistically-defined default value

becomes 50 percent. In other words, where 40 CFR did not address false positives, the system required

that 50 percent of the detects at the MDL would be false positives. This is a very protective approach,

and biased toward not missing any compounds of potential concern that may be present. The

MDL-derived RDL, and to a lesser extent the EDL, somewhat indirectly addresses the false positive

issue. As described in defining the RDL (see Section 2.4.1), by the time the standard deviation has been

multiplied by 8, the possibility of false positives is usually less than 1 percent.

2.4.3 Statistical Distribution Techniques

Many statistical distribution techniques are available for calculating a range of standard deviations to

quantify non-detect concentrations of COPCs. These include random replacement scenarios, such as

(Cohen and Ryan 1989; Rao, Ku, and Rao 1991): 

• the uniform fill-in (UFI) method, in which each LOD value is replaced with a randomly

generated data point by using a uniform distribution; 

• the log fill-in (LFI) method which is the same as UFI, except using a logarithmic

distribution;

• the normal fill-in (NFI) method which is the same as UFI, except using a log-normal

distribution; and

• the maximum likelihood estimation (MLE) technique. 

Also, if the permitting authority determines it to be applicable, a Monte Carlo simulation might be used to

determine a “statistical” value for each non-detect concentration.

2.4.4 Our Recommendations on Quantifying Non-Detects

Using non-detects in a risk assessment depends on the analytical method(s) used to produce the data. In

most cases, the Agency estimates emission rates for undetected COPCs (see Section 2.3) by assuming 

that COPCs are present at a concentration equivalent to the MDL-derived RDL for non-isotope dilution
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methods, or to the method-defined EDL for isotope dilution methods. We consider these methods

reasonable, and believe they represent a scientifically sound approach that supports maximum protection

of human health and the environment while recognizing the uncertainty associated with analytical

measurements at very low concentrations in a real world sample matrix. We also recognize that there are

subjective components and limitations to each of the non-detect methodologies presented in this and

previous guidance, including the recommended methods.

Some risk assessors have expressed the desire to obtain and use non-routine data (e.g., uncensored data)

of defensible quality in risk assessments, as a way to deal with non-detect issues. The HHRAP doesn’t

address what forms or how such data might be used. The decision to use non-routine data in a risk

assessment is not precluded just because it is different. Neither does the HHRAP necessarily endorse

using non-routine data. We generally recommend consulting with the permitting authority on the

appropriateness of using non-routine data. If non-routine data is used, we generally recommend carefully

identifying and evaluating the limitations associated with the data, and clearly document this discussion in

the Uncertainty section of the risk assessment report.

As stated previously, a pretrial burn risk assessment can help to make sure that the trial burn test will

achieve the desired quantitation limit (and, therefore, DREs and COPC stack gas emission rates).

2.4.5 Estimated Maximum Possible Concentration (EMPC)

The EMPC as defined in SW-846 is in most cases only used with the isotope dilution methods. An

EMPC is calculated for dioxin isomers that:

• have a response with a signal to noise ratio of at least 2.5 for both the quantitation ions;

and 

• meet all the relevant identification criteria specified in the analytical method, except the

ion abundance ratio. 

Ion abundance ratios are affected by co-eluting interferences that contribute to the quantitative ion

signals. As a result, one or both of the quantitative ions signals may possess positive biases. 

An EMPC is a worst-case estimate of the concentration. An EMPC is not a detection limit and should not

be treated as a detection limit in the risk assessment. We generally recommend using EMPC values as

detections without any further manipulation (e.g., dividing by 2). However, because EMPCs are worst-
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C Actual MDLs for all non-detect stack emissions data, non-isotope dilution methods

C EDLs for all non-detect stack emissions data, isotope dilution methods

C SQLs for all non-detect waste feed or feedstream data used

C Description of the method applied to quantify the concentration of non-detects 

RECOMMENDED INFORMATION FOR THE RISK ASSESSMENT REPORT

case estimates, you may wish to consult with the permitting authority on techniques to minimize EMPCs

when reporting trial and risk burn results. This is especially true when the EMPC values result in risk

estimates above regulatory levels of concern. Some techniques to minimize EMPCs include performing

additional cleanup procedures (as defined by the analytical method) on the sample or archived extract,

and/or reanalyzing the sample under different chromatographic conditions. 

Please Note: using alternative quantitation ions might be acceptable, if the

signal-to-noise ratio of the ion signal is at least 2.5 and if the tune data indicate that the

mass spectrometer is operating within specifications. 

Such actions to reduce the EMPC are expected to be more cost effective than the additional sample

cleanup and/or reanalysis.

2.5 EVALUATING CONTAMINATION IN BLANKS

Blank samples are intended to provide a measure of any contamination that may have been introduced

into a sample: 

1. in the field while the samples were being collected, 

2. in transport to the laboratory, or 

3. in the laboratory during sample preparation or analysis. 

Blank samples are analyzed the same way as the site samples from the trail burn. To prevent including

non-site related compounds in the risk assessment, we generally recommend comparing the

concentrations of compounds detected in blanks to concentrations detected in site samples collected

during the trial burn. Four types of blanks are defined in the Risk Assessment Guidance for Superfund
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(U.S. EPA 1989e): trip blanks, field blanks, laboratory calibration blanks, and laboratory reagent or

method blanks. Detailed definitions of each are provided below. 

Trip Blank - A trip blank is used to indicate potential contamination due to migration of volatile

organic compounds 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. The blank accompanies the empty

sample bottles to the field as well as with the site samples returning to the laboratory for analysis. 

The blank sample is not opened until it is analyzed in the lab with the site samples, thus making

the laboratory “blind” to the identity of the blanks. 

Field Blank - A field blank is used to determine if field sampling or cleaning procedures

(e.g., insufficient cleaning of sample equipment) result in cross-contamination of site samples. 

Like the trip blank, the field blank is transported to the field with empty sample bottles and is

analyzed in the laboratory along with the site samples. Unlike the trip blank, however, the field

blank sample is opened in the field and recovered in the same manner as the collected samples. 

As with trip blanks, the field blanks’ containers and labels may be the same as for site samples

and blind to the laboratory. 

Instrument Blank - An instrument 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. 

Laboratory Reagent or Method Blank - A laboratory reagent of method 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 processed under control, in some instances method

blank contaminants 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.

Blank data is generally compared to the results with which the blanks are associated. However, if the

association between blanks and data can’t be made, blank data is compared to the results from the entire

sample data set.

U.S. EPA (1989e) makes a distinction between blanks containing common laboratory contaminants and

blanks containing contaminants not commonly used in laboratories. Compounds considered to be

common laboratory contaminants are 
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• acetone, 

• 2-butanone (methyl ethyl ketone), 

• methylene chloride, 

• toluene, and 

• the phthalate esters. 

If compounds considered to be common laboratory contaminants are detected in the blanks, then sample

results are usually not considered to be detected unless the concentrations in the sample are equal to or

exceed ten times the maximum amount detected in the applicable blanks. If the concentration of a

common laboratory contaminant in a sample is less than ten times the blank concentration, then the

compound is usually treated as a non-detect in that particular sample.

In some limited cases, it may be appropriate to consider blanks which contain compounds that aren’t

considered by the Agency to be common laboratory contaminants. In these limited cases, sample results

aren’t considered to be detected unless the concentrations in the sample exceed five times the maximum

amount detected in the applicable blanks. If the concentration in a sample is less than five times the

blank concentration, then the compound would be treated as a non-detect in that particular sample.

Carefully consider the evaluation of blank data in the overall context of the risk assessment and

permitting process. We generally expect issues related to non-laboratory contaminant blanks to be

minimal, because data collection and analysis efforts in support of trial/risk burns are expected to be of

high quality and in strict conformance to QA/QC plans and SOPs. Carefully evaluating the trial/risk burn

data will avoid the potential for contaminated blanks to compromise the integrity of the data. It will also

help prevent the need for retesting to properly address data quality issues.

We highly recommend practicing caution in applying blank results to correct or qualify sample results for

any purpose, as blanks are provided in minimal quantities (e.g., one per test condition or one per test) and

therefore are at best qualitative indicators of the validity of a data set. Blank correction can reduce

accuracy and often represent a non-conservative uncertainty. Consequently a permit authority might

dedice not to allow blank correction as a conservative assumption (consistent with a screening level risk

assessment).

When considering blank contamination in the COPC selection process, we recommend that permitting

authorities ensure that:
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(1) The facility or data gatherer has made every reasonable attempt to ensure good data

quality and has rigorously implemented the QA/QC Plan and good industry sampling and

testing practices.

(2) Trial/risk burn data has not been submitted to the permitting authority as “blank

corrected.” Rather, the permitting authority has the full opportunity to review the data

absent additional manipulation by the data gatherer. 

(3) The effect of the blank correction on the overall risk estimates, if such an effect is

considered, is clearly described in the uncertainty section of the risk assessment report.

(4) The risk assessment report lists emissions rates both as measured, and as blank corrected,

in situations where there is a significant difference between the two values.
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Chapter 3

Air Dispersion and Deposition Modeling

What’s Covered in Chapter 3:

3.1 Background on Air Dispersion Models for Risk Assessment

3.2 Partitioning Emissions

3.3 Site-Specific Characteristics Required for Air Modeling

3.4 Meteorological Data Primer

3.5 Meteorological Preprocessor Data Needs

3.6 ISCST3 Model Input Files

3.7 ISCST3 Model Execution

3.8 Using Model Output

3.9 Modeling Fugitive Emissions

3.10 Modeling Acute Risk

PLEASE NOTE: for the purposes of this guidance, “we” refers to the U.S. EPA OSW. 

The “you” to which we speak in this chapter is the air modeler: the person (or persons)

who will actually put the recommended air modeling methods into practice.

The burning of materials produces residual amounts of pollution that could be released to the

environment. Knowledge of atmospheric pollutant concentrations and deposition rates in the areas

around the combustion facility is an integral part of estimating potential human health risks associated

with these releases. Air concentrations and deposition rates are usually estimated using air dispersion

models. Air dispersion models are mathematical constructs that attempt to describe the effects of

physical processes that occur in the atmosphere on rates of dispersion of emissions from a source (such

as the stack of a combustor). These mathematical constructs are coded into computer programs to

facilitate the computational process.
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This chapter provides guidance on criteria to consider when selecting an air model to use to support a

risk assessment. It also describes the development and use of the U.S. EPA air dispersion model—the

Industrial Source Complex Short-Term Model (ISCST3)—which best addresses the selection criteria for

most risk assessments. Although the air dispersion modeling methods presented in the HHRAP focus on

use of ISCST3, other available models may be more appropriate if they better meet the selection criteria

due to study-specific objectives or assessment area characteristics. Of particular interest is the American

Meteorological Society- Environmental Protection Agency Regulatory Model (AERMOD), which has

been proposed by EPA as a replacement for the ISCST3 model for Clean Air Act regulatory purposes. 

More details about AERMOD and other alternative models are provided in Section 3.1.1.

The Guideline on Air Quality Models (GAQM) (U.S. EPA 1996k; 1999b; Federal Register 2000) is a

primary reference for all US EPA and state agencies on using air models for regulatory purposes. The

GAQM is Appendix W of 40 CFR Part 51. The Office of Air Quality Planning and Support (OAQPS)

provides the GAQM and extensive information on updates to air dispersion models, meteorological data,

data preprocessors, and user’s guides on the Support Center for Regulatory Air Models (SCRAM) web

site at www.epa.gov/scram001/index.htm. We suggest you review this web site periodically to check for

updates and changes to the recommended model. General questions regarding air modeling, or

information on the web site may be addressed to atkinson.dennis@epamail.epa.gov. Specific questions

on the use of this guidance may be addressed to the appropriate permitting authority. Please refer to the

respective models User’s Manual for:

< a more in-depth discussion on the physical assumptions embodied in the ISCST3 or other

air dispersion model that may be considered; as well as

< concepts of atmospheric processes that are embodied in dispersion models in general.

Discussions in Section 3.1 focus on a background of available models, and selection criteria to consider

when deciding which air model to use in a risk assessment. The remainder of the chapter provides

information on ISCST3 input data needs, and output file development. Chapter sections include:

• Partitioning emissions (Section 3.2)

• Site-specific characteristics needed for air modeling (Section 3.3)

- Surrounding terrain (Section 3.3.1)

- Surrounding land use (Section 3.3.2)

- Facility building characteristics (Section 3.3.4)

• Meteorological data (Section 3.5)
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If you aren’t familiar with the types of data used in air concentration and deposition models, Section 3.4

provides a short tutorial on the types of meteorological data needed, and potential data sources. Section

3.5 describes the data needs of the preprocessor computer program we recommend using to prepare,

organize, and format meteorological data for use in the ISCST3 model. Section 3.6 describes the

structure and format of ISCST3 input files. Section 3.7 describes limitations to consider in executing

ISCST3. Section 3.8 describes how model outputs are used in the risk assessment computations. Section

3.9 discusses air modeling of fugitive emissions. Section 3.10 discusses air modeling for acute exposure.

3.1 DESCRIPTION OF AIR MODELS

This section gives a brief background on air dispersion models for risk assessment. This section also

introduces some data preprocessing programs developed to aid in preparing air model input files (these

preprocessing programs are described in more detail in Sections 3.3.3 and 3.5).

3.1.1 Background on Air Dispersion Models for Risk Assessment

Before 1990, the Agency and the regulated community used several air dispersion models. These models

were of limited usefulness in risk assessments because they considered only air concentration, and not

the deposition of contaminants to land. The original Agency guidance on completing risk assessments

(U.S. EPA 1990e) identified two models that were explicitly formulated to account for the effects of

deposition:

• COMPLEX I, from which a new model—COMPDEP—resulted

• Rough Terrain Diffusion Model (RTDM), from which a new

model—RTDMDEP—resulted

An updated version of the ISCST model in use at the time, COMPDEP included building wake effects. 

Subsequent Agency guidance (U.S. EPA 1993f and 1994g) recommended using COMPDEP for air

deposition modeling. U.S. EPA (1993f) specified COMPDEP Version 93252, and U.S. EPA (1994g)

specified COMPDEP Version 93340. When these recommendations were made, a combined

ISC-COMPDEP model (a merger of the ISCST2 and COMPLEX I model) was still under development. 

The merged model became known as ISCSTDFT. U.S. EPA guidance (1994r) recommended using the

ISCSTDFT model. After reviews and adjustments, this model was released as ISCST3. The ISCST3

model contains algorithms for dispersion in simple, intermediate, and complex terrain; dry deposition;

wet deposition; and plume depletion.
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Operating the COMPDEP, RTDMDEP, and ISCST models is described in more detail in the following

User’s Manuals. Please note, though, that all models except the current version of ISCST3 are

considered obsolete:

• Environmental Research and Technology (ERT). 1987. User’s Guide to the Rough

Terrain Diffusion Model Revision 3.20. ERT Document P-D535-585. Concord,

Massachusetts.

• Turner, D.B. 1986. Fortran Computer Code/User’s Guide for COMPLEX I Version

86064: An Air Quality Dispersion Model in Section 4. Additional Models for

Regulatory Use. Source File 31 Contained in UNAMAP (Version 6). National

Technical Information Service (NTIS) PB86-222361/AS.

• U.S. EPA. 1979. Industrial Source Complex Dispersion Model User’s Guide, Volume I. 

Prepared by the H.E. Cramer Company. Salt Lake City, Utah. Prepared for the Office of

Air Quality Planning and Standards. Research Triangle Park, North Carolina. EPA

450/4-79/030. NTIS PB80-133044.

• U.S. EPA. 1980b. User’s Guide for MPTER: A Multiple Point Gaussian Dispersion

Algorithm with Optional Terrain Adjustment. Environmental Sciences Research

Laboratory. Research Triangle Park, North Carolina. EPA 600/8-80/016. NTIS

PB80-197361.

• U.S. EPA. 1982a. MPTER-DS: The MPTER Model Including Deposition and

Sedimentation. Prepared by the Atmospheric Turbulence and Diffusion Laboratory

(NOAA). Oak Ridge, Tennessee. Prepared for the Environmental Sciences Research

Laboratory. Research Triangle Park, North Carolina. EPA 600/8-82/024. NTIS

PB83-114207.

• U.S. EPA. 1987b. On-Site Meteorological Program Guidance for Regulatory Modeling

Applications. Office of Air Quality Planning and Standards. Research Triangle Park,

North Carolina.

• U.S. EPA. 1995f. User’s Guide for the Industrial Source Complex (ISC3) Dispersion

Models, Volumes I and II. Office of Air Quality Planning and Standards. Emissions,

Monitoring, and Analysis Division. Research Triangle Park, North Carolina. EPA

454/B-95/003a. September.

Four air models in current regulatory use, or proposed by OAQPS, include ISCST3, AERMOD,

CALPUFF and ISC-PRIME. However, we generally recommend using the latest version of ISCST3 in

most situations to conduct air dispersion and deposition modeling for use in a risk assessment. 

This recommendation is based on ISCST3's status as the:

• Model most used by regional, state and local agencies; and
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• Model satisfying the most of the following criteria:

< Has broad regulatory acceptance and experience in evaluating the impacts of air

contaminants emitted from various industrial sources (e.g., short and tall stack

heights, fugitive emissions from process and storage areas);

< Can evaluate impacts attributable to a single source, with capability to evaluate

multiple sources;

< Can evaluate compounds emitted as vapor or particulate phase with

consideration of deposition and removal processes based on the physical

characteristics of the compound;

< Accepts placement of grid nodes at any location within the applicable range of

the air model;

< Can conduct stepwise evaluation of hourly meteorological conditions for

multiple years of data producing short-term (acute) and long-term (chronic)

averages as outputs; and

< Can evaluate building downwash effects.

The other three air models are proposed by OAQPS as refined regulatory air models in the revisions to

the Guideline on Air Quality Models (U.S. EPA 1996k; 1999b). Of particular interest is AERMOD.

AERMOD is proposed to replace ISCST3 as the recommended air quality model for most regulatory

applications (Federal Register 2000). AERMOD has been evaluated extensively by the air modeling

community for improvements over the ISCST3 algorithms for vertical contaminant distribution from

sources with tall stacks, terrain effects in areas with terrain elevations above the top of emission source

stacks, and enhanced nighttime dispersion in urban areas. However, AERMOD currently has minimal

regulatory experience. AERMOD would be an important consideration for risk assessments if: 

• it gains broad regulatory acceptance, 

• the assessment area contains significant terrain features (i.e., terrain elevations above

emission source stacks)

OAQPS promulgated the California Puff Model (CALPUFF) model for use on a case-by-case basis, for

long-range transport (greater than 50 kilometers), as well as the special conditions of very light or calm

winds (less than 1 meter per second). CALPUFF may be an important consideration when modeling:

• chemical transformation of highly reactive contaminants; 

• long residence times during extended periods of light winds or calm conditions; 

• transport over long distances;

• recirculation of contaminants due to local wind effects; or 

• hilly terrain and river valleys. 
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Also, the proposed OAQPS revisions to the GAQM recommend using the version of ISCST with the new

downwash algorithm, ISC-PRIME, for applications where aerodynamic building downwash is critical

(Federal Register 2000). The necessary information and inputs to evaluate the effects of building

downwash are further discussed in Section 3.2.4. We generally recommend determining the need for the

improved building downwash calculation on a case-by-base basis. 

Although air dispersion modeling methods presented in this guidance use ISCST3, you may want to

evaluate other models (such as ISC-PRIME, AERMOD, or CALPUFF, if the revised GAQM adopts

them), to see whether they more substantially meet the selection criteria. Specific to its ability to meet

the selection criteria listed above, the ISCST3 model is technically capable of evaluating: 

• Gaussian dispersion rates in vertical and horizontal plume cross-section;

• Urban and rural dispersion coefficients;

• Terrain effects;

• Source characterization as a discrete point, two-dimensional area, or three-dimensional

volume;

• Short-term and long-term averages (1-hour and annual);

• Surface meteorology data includes hourly observations of wind speed (nearest

1/10th mile per second), wind direction (nearest degree), stability class (6 categories),

and temperature (nearest degree);

• Mixing height data interpolated from twice daily upper air soundings corresponding to

each hour of surface data;

• Deposition processes for conservation of mass with particle wet and dry deposition and

removal, and vapor wet deposition and removal (dry vapor deposition implemented

within the air modeling; see Section 3.6.1);

• Hourly precipitation amount and type act on wet deposition and removal; and

• Single first order exponential decay rate.

In addition, emission sources can be defined in ISCST3 with either stack dimensions at a discrete point,

as a two-dimensional area source, or in three dimensions as a volume source. Therefore, ISCST3 offers

the flexibility to model sources based on source type (i.e., stack or fugitive area).
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3.1.2 Preprocessing Programs

ISCST3 needs the help of additional computer programs, referred to as “preprocessing” programs. These

programs format available information regarding surrounding buildings and meteorological data into a

format that ISCST3 can read. Currently, these programs include:

• Building Profile Input Program (BPIP) calculates the maximum crosswind widths of

buildings, which ISCST3 then uses to estimate the effects on air dispersion. These

effects by surrounding buildings are typically referred to as building downwash or wake

effects. The BPIP User’s Guide contains detailed information for preparing the

necessary building dimensions (length, height, and width) and locations for the ISCST3

model (U.S. EPA 1995c).

• Meteorological Processor for Regulatory Models (MPRM) prepares meteorological data

for ISCST3. MPRM merges hourly measurements of surface parameters (e.g.,

precipitation, wind speed, and wind direction) into rows and columns of information that

ISCST3 can read. The MPRM User’s Guide contains instructions for using on-site

meteorological data to prepare the necessary meteorological input file for ISCST3 (U.S.

EPA 1996j; 1999c). The Addendum to the MPRM User’s Guide describes the additional

data needed in the meteorological input file for ISCST3 to model dry deposition of

vapors (U.S. EPA 1999c).

We generally recommend using MPRM to process the meteorological data, because MPRM provides all

the meteorological parameter values that ISCST3 needs to function. The peer review draft of the

HHRAP described the personal computer version of the meteorological preprocessor for the old RAM

program (PCRAMMET). Unfortunately, PCRAMMET doesn’t provide the parameters needed for

evaluating dry vapor deposition in ISCST3. Therefore, we no longer recommend using PCRAMMET. 

When sufficient site-specific data is available on the location, size and shape of structures in the vicinity

of the emissions sources, you can use the BPIP program to prepare the ISCST3 input file to consider the

effects of building downwash on pollutant transport. If sufficient site-specific data is not available to run

BPIP, then you will not be able to address building downwash in air modeling efforts. Prior to

performing the air dispersion modeling, we recommend that you consult with the appropriate parties (e.g.

regulatory authority and facility) on the decision to include or omit nearby structures.
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3.2 PARTITIONING EMISSIONS

COPC emissions to the environment occur in either vapor or particle phase. In general, you can assume:

• most metals and organic COPCs with very low volatility (fraction of COPC in vapor

phase [Fv] less than 0.05, see Appendix A-3) occur only in the particle phase;

• highly volatile organic COPCs occur only in the vapor phase (Fv of 1.0, see Appendix

A-3); and

• the remaining organic COPCs occur with a portion of the vapor condensed onto the

surface of particulates (i.e. particle-bound). 

For modeling COPCs released only as particulates, the mass fractions allocated to each particle size are

different than the mass fractions used for modeling organics released in both the vapor and

particle-bound phases.

Due to model limitations, you need to run ISCST3 multiple times to generate estimates of vapor phase

COPCs, particle phase COPCs, and particle-bound COPCs. An example is the risk assessment for the

WTI incinerator located in East Liverpool, Ohio. The study used three runs; a vapor phase run for

organic COPCs, a particle run with mass weighting of the particle phase metals and organic COPCs with

very low volatility, and a particle run with surface area weighting of the particle-bound organic COPCs.

3.2.1 Vapor Phase Modeling

Vapor phase air modeling runs do not need a particle size distribution in the ISCST3 input file. ISCST3

output for vapor phase runs are vapor phase ambient air concentration, dry vapor deposition, and wet

vapor deposition at receptor grid nodes based on the unit emission rate. 

3.2.2 Particle Phase Modeling (Mass Weighting)

ISCST3 uses algorithms to compute the rate at which dry and wet removal processes deposit particle

phase COPCs onto the Earth’s surface. Particle size is the main determinant of the fate of particles in air

flow, whether dry or wet. The key to dry particle deposition rate is the terminal, or falling, velocity of a

particle. Particle terminal velocity is calculated mainly from the particle size and particle density. Large

particles fall more rapidly than small particles, and are deposited closer to the stack. Small particles have

low terminal velocities. Very small particles remain suspended in the air flow. Wet particle deposition
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also depends on particle size as larger particles are more easily removed, or scavenged, by falling liquid

(rain) or frozen (snow or sleet) precipitation. To estimate particle phase deposition rates, ISCST3 needs

an initial estimate of the particle size distribution, broken out by particle diameter.

The diameters of small particles contained in stack emissions are usually measured in micrometers. The

distribution of particle diameters will differ from one combustion process to another, and is greatly

dependent on the: 

1. Furnace type;

2. Combustion chamber design;

3. Feed fuel composition; 

4. Particulate removal efficiency; 

5. APCS design; 

6. Amount of air, in excess of stoichiometric amounts, that is used to sustain combustion;

and 

7. Combustion temperature. 

The particle size distribution cannot be calculated, but only directly measured or inferred from prior data. 

Unfortunately, few studies have been performed to directly measure particle size distributions from a

variety of stationary combustion sources (U.S. EPA 1986a).

We recommend that existing facilities perform stack tests to identify particle size distribution. We

further recommend that these data represent actual operating conditions for the combustion unit and air

pollution control device (APCD) that remove particulate from the stack gas. A table of particle size

distribution data may be prepared using stack test data in the format similar to the example illustrated in

Table 3-1.
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TABLE 3-1

HYPOTHETICAL PARTICLE SIZE DISTRIBUTION DATA 

TO SUPPORT EXAMPLE CALCULATIONS

1 2 3 4 5 6

Mean Particle

Diameter a

(μm)

Particle

Radius

(μm)

Surface

Area/

Volume

(μm-1)

Fraction of

Total

Massb

Proportion

Available

Surface

Area

Fraction

of Total

Surface

 Area

> 15.0 7.50 0.400 0.128 0.0512 0.0149

12.5 6.25 0.480 0.105 0.0504 0.0146

8.1 4.05 0.741 0.104 0.0771 0.0224

5.5 2.75 1.091 0.073 0.0796 0.0231

3.6 1.80 1.667 0.103 0.1717 0.0499

2.0 1.00 3.000 0.105 0.3150 0.0915

1.1 0.55 5.455 0.082 0.4473 0.1290

0.7 0.40 7.500 0.076 0.5700 0.1656

< 0.7 0.40 7.500 0.224 1.6800 0.4880

a Geometric mean diameter in a distribution from U.S. EPA (1980a), as presented in U.S. EPA (1998c)

b The terms mass and weight are used interchangeably when using stack test data

We expect that actual stack test data will be different from the hypothetical values presented in Table 3-

1. This is because actual stack sampling will use particle “cut size” for the different cascade impactor

filters (or Coulter counter-based distributions). The test method will drive the range of particle sizes that

are presented in the results of the stack test. However, ISCST3 needs mean particle diameter for each

particle size distribution, and the stack test data identifies only the mass (“weight”) of particles in a range

bounded by two specific diameters. To address this, we recommend that stack test data be converted into

a mean particle diameter which approximates the diameter of all the particles within a defined range. We

recommend using the following equation to calculate the mean particle diameter:
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Equation 3-1

where

Dmean = Mean particle diameter for the particle size category (μm)

D1 = Lower bound cut of the particle size category (μm)

D2 = Upper bound cut of the particle size category (μm)

For example, the mean particle diameter of 5.5 μm in Table 3-1 is calculated from a lower bound cut size

(assuming a cascade impactor is used to collect the sample) of 5.0 μm to an upper bound cut size of

6.15 μm. In this example, the mean particle diameter is calculated as:

From Table 3-1, the mean particle diameter is 5.5 μm. The mass of particulate from the 5.0 μm stack test

data is then assigned to the 5.5 μm mean particle diameter for the purpose of computing the “fraction of

total mass.” 

Typically, eight to ten mean particle diameters are available from stack test results. However, as

determined from a sensitivity analysis conducted by The Air Group-Dallas under contract to U.S. EPA

Region 6 (http://www.epa.gov/region06), a minimum of three particle size categories (> 10 microns, 2-10

microns, and < 2 microns) detected during stack testing are generally the most sensitive to air modeling

with ISCST3 (U.S. EPA 1997f). For facilities with stack test results which indicate mass amounts lower

than the detectable limit (or the filter weight is less after sampling than before), a single mean particle

size diameter of 1.0 micron may be used to represent all mass (e.g., particle diameter of 1.0 micron or a

particle mass fraction of 1.0) in the particle and particle-bound model runs. Because rudimentary

methods for stack testing may not detect the very small size or amounts of COPCs in the particle phase,

the use of a 1.0 micron particle size will allow these small particles to be included properly as particles in

the risk assessment exposure pathways while dispersing and depositing in the air model similar in

behavior to a vapor. Consequently, we recommend that a minimum of three particle size categories be

used in the air modeling effort.

After calculating the mean particle diameter (Column 1), you can compute the fraction of total mass per

mean particle size diameter (Column 4) from the stack test results. For each mean particle diameter, the
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stack test data provides an associated particulate mass. Calculate the fraction of total mass for each mean

particle diameter by dividing the associated particulate mass for that diameter by the total particulate

mass in the sample. In many cases, the fractions of total mass will not sum to 1.0 because of rounding

errors. In these instances, we advocate forcing the total mass to 1.0 by adding the remaining mass

fraction into the largest mean particle diameter mass fraction. 

Direct measurements of particle-size distributions may not be available at a proposed new facility. You

will need to supply ISCST3 with an assumed particle distributions. In such instances, you may use a

representative distribution. We recommend that the combustor on which the representative distribution

is based be as similar as practicable to the proposed combustor.

ISCST3 uses the mass-based particle size distribution to apportion the mass of particle phase COPCs

(metals and organics with Fv values less than 0.05) according to particle size. The ISCST3 input file uses

the data in Column 4 of Table 3-1 (as developed from actual stack test data) to perform a particulate run

with the particle phase COPCs apportioned per mass weighting.

3.2.3 Particle-Bound Modeling (Surface Area Weighting)

Use a surface area weighting of particles, instead of mass weighting, in separate particle runs of ISCST3. 

Surface area weighting approximates the situation where a portion of a semivolatile organic contaminant,

volatilized in the high temperature environment of a combustion system, condenses to the surface of

particles entrained in the combustion gas after the gas cools in the stack. Apportioning emissions by

particle diameter becomes a function of the surface area of particles available for chemical adsorption

(U.S. EPA 1998c).

The first step in apportioning COPC emissions by surface area is to calculate the proportion of available

surface area of the particles. If particle density is held constant (such as 1 g/cm3), the proportion of

available surface area of aerodynamically spherical particles is the ratio of surface area (S) to volume (V),

is estimated as follows:

• Assume aerodynamically spherical particles.

• Specific surface area of a spherical particle with a radius, r—S = 4 Br

2

• Volume of a spherical particle with a radius, r—V = 4/3 Br

3
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• Copies of all stack test data used to determine particle size distribution

• Copies of all calculations made to determine particle size distribution, fraction of total mass,

and fraction of total surface area

RECOMMENDED INFORMATION FOR RISK ASSESSMENT REPORT

• Ratio of S to V—S/V = 4 Br

2

/ (4/3 Br

3

) = 3/r

The following example uses the hypothetical particle size distribution in Table 3-1 to apportion the

emission rate of the particle-bound portion of the COPC based on surface area. We generally

recommend following this procedure for apportioning actual emissions to the actual particle size

distribution measured at the stack. 

In Table 3-1, a spherical particle having a diameter of 15 μm (Column 1) has a radius of 7.5 μm

(Column 2). The proportion of available surface area (assuming particle density is constant) is 

S/V = 3/7.5 = 0.4, which is the value in Column 3. Column 4 shows that particles with a mean diameter

of 15 μm constitute 12.8 percent of the total mass. Multiplying Column 3 by Column 4 yields the value

in Column 5 of 0.0512. This value is an approximation of the relative proportion of total surface area,

based on the percent of particles that are 15 μm in diameter. Totaling Column 5 yields the total surface

area of all particles in the particle size distribution. In this example, the sum is 3.4423. Column 6 is the

fraction of total surface area represented by the specific particle diameter in the distribution. Column 6 is

calculated by dividing the relative proportion of surface area (Column 5) for a specific diameter by the

total relative proportion of surface area (3.4423 square micrometers [μm2

]). In the example of the 15

μm-diameter particle, the fraction of total surface area available for adsorption is 0.0149

(0.0512/3.4423). This procedure is then repeated for all particle sizes in the array. 

ISCST3 uses the surface area-based particulate size distribution to apportion mass of particle-bound

COPCs (most organics) according to particle size. The ISCST3 input file uses Column 6 of Table 3-1 (as

developed from actual stack test data) to perform a particulate run for the particle-bound COPCs

apportioned according to surface area weighting.
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1

 UTM is a map coordinate projection of geographic coordinates.

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3.3 SITE-SPECIFIC INFORMATION NEEDED FOR AIR MODELING

We generally recommend that the site-specific information for the facility and surrounding area used in

air dispersion modeling include: 

1. the elevation of the surrounding land surface or terrain;

2. surrounding land uses; and 

3. characteristics of on-site buildings that may affect the dispersion of COPCs into the

surrounding environment. 

You can often obtain some of the site-specific information needed for air dispersion modeling by

reviewing available maps and other graphical data on the area surrounding the facility. The first step in

the air modeling process is reviewing these resources. Using U.S. Geological Survey (USGS) 7.5-minute

topographic maps (1:24,000) extending to 10 kilometers from the facility, and USGS 1:250,000 maps

extending out to 50 kilometers, you can identify much of the following:

• site location, 

• nearby terrain features, 

• waterbodies and watersheds, 

• ecosystems, 

• nearby residences, and 

• land use. 

Aerial photographs are frequently available to supplement the depiction of the area. An accurate facility

plot plan—showing buildings, stacks, property and fence lines—is also needed. Facility information

including stack and fugitive source locations, building corners, plant property, and fence lines, in

Universal Transverse Mercator (UTM1) grid coordinates in meters east and north might be available in

both USGS reference systems. Therefore, knowledge of the horizontal datum of the geographic

coordinates from which the UTM coordinates were projected is required. We generally recommend

consulting with personnel experienced and knowledgeable in the intricacies of these types of coordinate

systems, and the various software programs used to conduct conversions.
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• All site-specific maps, photographs, or figures used in developing the air modeling approach

• Mapped identification of facility information including stack and fugitive source locations,

locations of facility buildings surrounding the emission sources, and property boundaries of

the facility

RECOMMENDED INFORMATION FOR RISK ASSESSMENT REPORT

Most USGS paper 7.5-minute topographic maps are published in the North American Datum system

established in 1927 (NAD 27). However, most digital elevation data (e.g., USGS Digital Elevation

Mapping) is in the 1983 revised system (NAD 83). We recommend taking special care not to mix source

data based on NAD 27 with data based on NAD 83. Also, we recommend obtaining emission source

information in the original units from the facility data, and convert it to metric units for air modeling, if

necessary. You can get digital terrain data from USGS, or another source.

The following subsections describe the specific information we generally recommend collecting. 

Entering this information into the ISCST3 input files is described in Section 3.6.

3.3.1 Surrounding Terrain Information

Terrain is important to air modeling because air concentrations and deposition rates are greatly

influenced by the height of the plume above local ground level. Terrain is characterized by elevation

relative to stack height. For air modeling purposes, terrain is referred to as “complex” if the elevation of

the surrounding land within the assessment area—typically defined as anywhere within 50 kilometers of

the stack—is above the top of the stack evaluated in the air modeling analysis. Terrain at or below stack

top is referred to as “simple.” ISCST3 implements U.S. EPA guidance on the proper application of air

modeling methods in all terrain if you include terrain elevation for each receptor grid node and specify

the appropriate control parameters in the input file.

Even small terrain features may have a large impact on the air dispersion and deposition modeling results

and, ultimately, on the risk estimates. We generally recommend that air modeling include terrain

elevations for every receptor grid node. Some exceptions may be those sites characterized by very flat

terrain where the permitting authority has sufficient experience to comfortably defer the use of terrain

data because the terrain’s historical effect on air modeling results have been minimal.
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• Description of the terrain data used for air dispersion modeling

• Summary of any assumptions made regarding terrain data

• Description of the source of any terrain data used, including any procedures used to

manipulate terrain data for use in air dispersion modeling

RECOMMENDED INFORMATION FOR RISK ASSESSMENT REPORT

We generally recommend including electronic copies of the digital terrain data used to extract receptor

grid node elevations in the risk assessment report. One way to obtain receptor grid node elevations is

using digital terrain data available from the USGS on the Internet at web site

http://edc.usgs.gov/guides/dem.html. For most locations, an acceptable degree of accuracy is provided

by the USGS “One Degree” (e.g., 90 meter data) data available as “DEM 250" 1:250,000 scale for the

entire United States free of charge. For areas requiring more accurate terrain, USGS 30-meter (1:24,000

scale) data might be considered, though it is not universally available. Either 90-meter or 30-meter data

is sufficient for most risk assessments which utilize 100 meter or greater grid spacing. Digital terrain

data is also available for purchase from a variety of commercial vendors, who may require

vendor-provided programs to extract the data. You can also manually extract the elevation of each

receptor grid node from USGS topographic maps.

3.3.2 Surrounding Land Use Information

Land use information is needed in the risk assessment for air dispersion modeling, as well as identifying

and selecting exposure scenario locations (see Chapter 4). Land use analysis for air dispersion modeling

usually occurs out to a radius of 3 kilometers from the centroid of the stacks from which emissions are

being modeled. Certain land uses, as defined by air modeling guidance, affect the selection of air

dispersion modeling variables. These variables are known as dispersion coefficients and surface

roughness. You typically use USGS 7.5-minute topographic maps, aerial photographs, or visual surveys

to define the air dispersion modeling land uses.

Land use information is also important for selecting exposure scenario locations, but at a radius further

(50 kilometers) from the emission source(s), to make sure all receptors that may be impacted are

identified. In most cases, though, air modeling performed out to a radius of 10 kilometers allows
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adequate characterization for evaluating exposure scenario locations. If you are evaluating a facility with

multiple stacks or emission sources, we generally recommend extending the radius from the centroid of a

polygon drawn connecting the various stack coordinates.

3.3.2.1 Land Use for Dispersion Coefficients

You need to specify the appropriate dispersion coefficients for ISCST3 to run properly. Land uses need

to be defined in order to specify dispersion coefficients. We generally recommend using the Auer

method specified in the Guideline on Air Quality Models (40 CFR Part 51, Appendix W) (U.S. EPA

1996k; 1999b) to define land use. Land use categories of “rural” or “urban” are taken from Auer (1978). 

Areas typically defined as rural include residences with grass lawns and trees, large estates, metropolitan

parks and golf courses, agricultural areas, undeveloped land, and water surfaces. Auer typically defines

an area as “urban” if it has less than 35 percent vegetation coverage or the area falls into one of the

following use types:

TABLE 3-2

URBAN LAND USE TYPES

Urban Land Use

Type Use and Structures Vegetation

I1 Heavy industrial Less than 5 percent

I2 Light/moderate industrial Less than 5 percent

C1 Commercial Less than 15 percent

R2 Dense single/multi-family Less than 30 percent

R3 Multi-family, two-story Less than 35 percent

In general, the Auer method is described as follows:

Step 1 Draw a radius of 3 kilometers from the center of the stack(s) on the site map.

Step 2 Inspect the maps, and define in broad terms whether the area within the radius is rural or

urban, according to Auer’s definitions.

Step 3 Classify smaller areas within the radius as either rural or urban, based on Auer’s

definitions. (It may be prudent to overlay a grid [for example, 100 by 100 meters] and

identify each square as primarily rural or urban)

Step 4 Count the number of rural squares; if more than 50 percent of the total squares are rural,

the area is rural; otherwise, the area is urban.
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• Description of the methods used to determine land use surrounding the facility

• Copies of any maps, photographs, or figures used to determine land use

• Description of the source of any computer-based maps used to determine land use

RECOMMENDED INFORMATION FOR RISK ASSESSMENT REPORT

Alternatively, digital land use databases may be used in a computer-aided drafting system to perform this

analysis.

3.3.2.2 Land Use for Surface Roughness Height (Length)

Surface roughness height—also referred to as (aerodynamic) surface roughness length—is the height

above the ground at which the wind speed goes to zero. Surface roughness affects the height above local

ground level that a particle moves from the ambient air flow above the ground (for example in the plume)

into a “captured” deposition region near the ground. That is, ISCST3 assumes the particle is deposited to

the ground at some point above the actual land surface, based on surface roughness height. Surface

roughness height is defined by individual elements on the landscape, such as trees and buildings.

There are several methods for computing surface roughness. One uses measurements of hourly surface

roughness based on wind direction (fetch). Another uses the change in wind speed with height in the

surface layer, as measured on an instrumented tower operated at the site. We recommend deciding which

method to use to characterize surface roughness based on the variability of surface features and seasonal

values for the site. In lieu of any other method, the paragraphs below describe our recommendations for

computing surface roughness.

In order to be consistent with the recommended method for determining land use for dispersion

coefficients (Section 3.3.2.1), the land use within 3 kilometers generally is acceptable for determining

surface roughness. Surface roughness height values for various land use types are as follows:
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TABLE 3-3

SURFACE ROUGHNESS HEIGHTS

Surface Roughness Heights for Land Use Types and Seasons (meters)

Land Use Type Spring Summer Autumn Winter

Water surface 0.0001 0.0001 0.0001 0.0001

Deciduous forest 1.00 1.30 0.80 0.50

Coniferous forest 1.30 1.30 1.30 1.30

Swamp 0.20 0.20 0.20 0.05

Cultivated land 0.03 0.20 0.05 0.01

Grassland 0.05 0.10 0.01 0.001

Urban 1.00 1.00 1.00 1.00

Desert shrubland 0.30 0.30 0.30 0.15

Source: Sheih, et al. (1979)

If a significant number of buildings are located in the area, higher surface roughness heights (such as

those for trees) may be appropriate (U.S. EPA 1995g). Previous guidance documents do not recommend

a specific method for determining average surface roughness height. If you are using National Weather

Service surface meteorological data, we generally recommend setting the surface roughness height for

the measurement site at 0.10 meters (grassland, summer). If you intend to propose a different value for

the measurement site, we recommend using the following procedure to determine the value:

Step 1 Draw a radius of 3 kilometers from the center of the stack(s) on the site map.

Step 2 Inspect the maps, and use professional judgment to classify the area within the radius

according to land use type (for example water, grassland, cultivated land, and forest); a

site visit may be necessary to verify some classifications.

Step 3 Divide the circular area into 12 angular sectors of 30 degrees.

Step 4 Identify a single representative surface roughness height for each sector, based on an

area-weighted average of the land use types within the sector using the categories

identified above.

Step 5 Input the area-weighted surface roughness height value representative of each of the 12

sectors into MPRM for preprocessing the meteorological data file.

Site-specific conditions might be such that you consider methods other than those described above more

appropriate for determining surface roughness height. In such instances, we recommend clearly

identifying and discussing the alternative methods with the appropriate parties (regulatory authority or

facility) prior to use.
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3.3.3 Information on Facility Building Characteristics 

Building wake effects, also referred to as “building downwash,” have a significant impact on the

concentration and deposition of COPCs near the stack. Building wake effects are flow lines that cause

plumes to be forced down to the ground much sooner than they would if the building was not there. The

ISCST3 model contains algorithms for evaluating this phenomenon. We recommend that the downwash

analysis consider all nearby structures with heights at least 40 percent of the height of the shortest stack

to be modeled. The 40 percent value is based on Good Engineering Practice (GEP) stack height of 2.5

times the height of nearby structures or buildings (stack height divided by 2.5 is equal to 0.40 multiplied

by the stack height [40 CFR Part 51 Appendix W]). BPIP uses Building dimensions and locations, and

stack heights and locations, to identify the potential for building downwash. BPIP and the BPIP User’s

Guide are available for download from the SCRAM web site (http://www.epa.gov/scram001/) to address

specific questions. The BPIP output file is in a format that can be copied and pasted into the source (SO)

pathway of the ISCST3 input file. We generally recommend the following procedure to identify

buildings for input to BPIP:

Step 1 Lay out facility plot plan, with buildings and stack locations clearly identified (building

heights identified for each building); for buildings with more than one height or roof

line, identify each height (BPIP refers to each height as a tier).

Step 2 Identify the buildings to be included in the BPIP analysis by comparing building heights

to stack heights. The building height test specifies that only buildings at least 40 percent

of the height of a potentially affected stack be included in the BPIP input file. For

example, if a combustion unit stack is 50 feet high, only buildings at least 20 feet tall

(0.40 multiplied by 50 feet) will affect air flow at stack top. Any buildings shorter than

20 feet need not be included in the BPIP analysis. The building height test is performed

for each stack and each building.

Step 3 Use the building distance test to check each building to be included in BPIP from the

building height test. For the building distance test, only buildings “nearby” the stack will

affect air flow at stack top. “Nearby” is defined as “five times the lesser of building

height or crosswind width” (U.S. EPA 1995c). A simplified distance test may be used by

considering only the building height rather than the crosswind width. While some

buildings with more height than width will be included unnecessarily using this

simplification, BPIP will identify correctly only the building dimensions required for

ISCST3. 

An example, hypothetical plot plan identifies a 25-foot tall building that is 115 feet from

the 50-foot tall combustion unit stack center to the closest building corner. The building

distance test, for this building only, is five times the building height, or 125 feet (five

multiplied by the building height, 25 feet). This building would be included in the BPIP

analysis, because it passes the building height test and building distance test.
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Step 4 Repeat steps 2 and 3 for each building and each stack, identifying all buildings to be

included in the BPIP. If the number of buildings exceeds the BPIP limit of eight

buildings, consider combining buildings, modifying BPIP code for more buildings, or

using third-party commercial software which implements BPIP. If two buildings are

closer than the height of the taller building, the two buildings may be combined. For

example, two buildings are 40 feet apart at their closest points. One building is 25 feet

high, and the other building is 50 feet high. The buildings could be combined into one

building for input to BPIP. For input to BPIP, the corners of the combined building are

the outer corners of the two buildings. For unusually shaped buildings with more than

the eight corners allowed by BPIP, approximate the building by using the eight corners

that best represent the extreme corners of the building. The BPIP User’s Guide contains

additional description and illustrations on combining buildings, and BPIP model

limitations (U.S. EPA 1995c).

Step 5 Mark off the facility plot plan with UTM grid lines. Extract the UTM coordinates of

each building corner and each stack center to be included in BPIP input file. Although

BPIP allows the use of “plant coordinates,” we recommend that all inputs to the air

model be prepared using UTM coordinates (meters) for consistency. UTM coordinates

are rectilinear, oriented to true north, and needed in metric units for ISCST3 modeling. 

Almost all air modeling will need to use USGS topographic data (digital and maps) for

receptor elevations, terrain grid files, locating plant property, and identifying

surrounding site features. Therefore, using an absolute coordinate system will enable

you to check inputs at each step of the analysis. Also, the meteorological data are

oriented to true north. Significant errors will result from ISCST3 if incorrect stack or

building locations are used, plant north is incorrectly rotated to true north, or incorrect

base elevations are used. With computer run times requiring many hours (up to 40 hours

for one deposition run with depletion), verifying locations at each step while preparing

model inputs will prevent the need to remodel.

We recommend observing several precautions and guidelines while preparing input files for BPIP:

• Graphically confirming the correct locations before BPIP is run. One method is to plot

the buildings and stack locations using graphics software. Several commercial programs

incorporating BPIP provide graphic displays of BPIP inputs.

• In addition to using UTM coordinates for stack locations and building corners, also use

meters as the units for height.

• Carefully include the stack base elevation and building base elevations according to

BPIP User’s Guide instructions.

• Note that the BPIP User’s Guide (revised February 8, 1995) has an error on page 3-5,

Table 3-1, under the “TIER(i,j)” description, which incorrectly identifies tier height as

base elevation.

• BPIP mixes the use of “real” and “integer” values in the input file. To prevent possible

errors in the input file, note that integers are used where a count is requested (for

example, the number of buildings, number of tiers, number of corners, or number of

stacks).
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• Make the stack identifiers (up to eight characters) in BPIP identical to those used in the

ISCST3 input file, or ISCST3 will report errors.

For most sites, BPIP executes in less than 1 minute. The array of 36 building heights and 36 building

widths (one for each of 36 10-degree direction sectors) are input into the ISCST3 input file by cutting

and pasting from the BPIP output file. We recommend deleting the five blank spaces preceding “SO” in

the BPIP output file, so that the “SO” begins in the first column of the ISCST3 input file.

One use of BPIP is to design stack heights for new facilities. Another is to determine what stack height

increases are necessary to avoid building influence on air flow, which may cause high concentrations and

deposition near the facility. The output for BPIP provides the GEP heights for stacks. Significant

decreases in concentrations and deposition rates will begin at stack heights at least 1.2 times the building

height, and further decreases occur at 1.5 times building height, with continual decreases of up to 2.5

times building height (GEP stack height) where the building no longer influences stack gas.

3.4 METEOROLOGICAL DATA PRIMER

Air dispersion and deposition modeling is extremely complicated, and uses data potentially unfamiliar if

your expertise lies outside meteorology and air modeling. Section 3.4 is an introduction to the types of

meteorological data used by air dispersion and deposition models, as well as information on potential

data sources. Section 3.5 continues this introduction into the specific data parameters required by

MPRM, the data preprocessor for the ISCST3 air model.

Generally speaking, air concentration and deposition models attempt to characterize the effects of

atmospheric forces on a mass of COPC found in the air. These forces can be divided between:

• those which transport the COPC (the dominant factor is wind);

• those which disturb the straight flow of the COPC away from the source (also known as

mixing, examples include building downwash effects, and atmospheric stability); and

• those actors which remove, or conditions which encourage the removal of, the COPC

from the atmosphere (An example of a removal actor would be rain, whereas an example

“condition” would be the point above the ground at which windspeed slows to zero).

Air concentration and deposition models need a variety of meteorological information, at different levels

of temporal definition. The ISCST3 model requires the following:
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• Identification of all sources of meteorological data

RECOMMENDED INFORMATION FOR RISK ASSESSMENT REPORT

• Hourly values (also know as “surface data, as they describe conditions closer to ground

level)

a. Wind direction (degrees from true north)

b. Wind speed (m/s)

c. Dry bulb (ambient air) temperature (K)

d. Opaque cloud cover (tenths)

e. Cloud ceiling height (m)

f. For dry particle deposition:

i. surface pressure (millibar)

ii. solar radiation (watts/m

2

)

g. For wet particle deposition:

i. Precipitation amount (inches)

ii. Precipitation type (liquid or frozen)

• Daily values (also called “upper air data” as they describe conditions higher in the

atmosphere)

a. Morning mixing height (m)

b. Afternoon mixing height (m)

The following subsections describe important characteristics of the needed data.

3.4.1 Wind Direction and Wind Speed

Wind direction and speed are two of the most critical parameters in air modeling. The wind direction

promotes higher concentration and deposition if it persists from one direction for long periods during a

year. For example, a predominantly south wind, such as on the Gulf Coast of Texas, will contribute to

high concentrations and depositions north of the facility. Wind speed is inversely proportional to

concentration predicted using air modeling: The higher the wind speed, the lower the concentration will

be. If wind speed doubles, the concentration and deposition will be reduced by one-half. Air models

need wind speed and wind direction at the stack top. Most air modeling is performed using government

sources of surface data. Wind data are typically measured by National Weather Service (NWS) stations

at a height of 10 meters. However, since some stations have wind speed recorded at a different height,

we recommend always verifying the anemometer height, and that the correct value is input into the

meteorological data preprocessing program. ISCST3 uses a wind speed profile to calculate wind speed at

stack top. This calculation exponentially increases the measured wind speed from the measured height to
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a calculated wind speed at stack height. ISCST3 assumes that wind direction at stack height is the same

as that measured at the NWS station height (U.S. EPA 1995c). 

3.4.2 Dry Bulb Temperature

Dry bulb temperature, or ambient air temperature, is the same temperature reported on the television and

radio stations across the country each day. Dry bulb (ambient) temperature contributes to describing the

surface conditions that vary from hour to hour in the measured meteorological data needed for air

modeling. It therefore has a direct effect on the modeling results, as described below.

Dry bulb temperature is typically measured at 2 meters above ground level. ISCST3 uses air temperature

in the buoyant plume rise equations developed by Briggs (U.S. EPA 1995f). The model results are not

very sensitive to air temperature, except at extremes. However, buoyant plume rise is very sensitive to

the stack gas temperature. Buoyant plume rise is mainly a result of the difference between stack gas

temperature and ambient air temperature. Conceptually, it is similar to a hot air balloon: The higher the

stack gas temperature, and lower the ambient temperature, the higher will be the plume rise. High plume

heights result in low concentrations and depositions as the COPCs travel further and are diluted in a

larger volume of ambient air before reaching the surface. A large variation in ambient temperature will

affect buoyant plume rise, but not as much as variations in stack gas temperature. The fact that the stack

gas temperature is constant (for most modeling analyses) is the very point for noting that it is the changes

in the dry bulb temperature that creates the temperature differential affecting plume rise in the air model

(see also Section 3.6.2.2 regarding selection of stack gas exit temperature). The temperature is measured

in K, so a stack gas temperature of 450°F is equal to 505 K, an ambient temperature of 90°F = 305 K, and

32°F = 273 K.

When determining values for dry bulb temperature (or ambient air temperature), it is important not to

appear to be ‘data shopping’ by artificially selecting a period of meteorological data that has either

average or above-average ambient temperatures that will reduce plume rise. The skewing of results in

one direction or another may over-estimate concentrations near the source, but under-estimate

concentrations and depositions away from the source where more sensitive receptors may be located (see

Chapter 4 for more on Exposure Scenario location) . Attempts to increase protectiveness by applying

such approaches may not achieve the desired result. 
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If the meteorological data sets you use, and your choice of dry bulb temperature are not consistent with

the HHRAP, we recommend clearly identifying and discussing them in the risk plan and/or cost estimate

(as appropriate) to ensure clarity and transparency of the final risk assessment results.

3.4.3 Opaque Cloud Cover

Observations of opaque cloud cover are used to calculate the stability of the atmosphere. Stability

determines the dispersion, or dilution, rate of COPCs in the atmosphere. Rapid dilution occurs in

unstable air conditions, while stable air results in very little mixing, or dilution, of the emitted COPCs. 

With clear skies during the day, the sun heats the Earth’s surface, which heats the air immediately above

it. The warm air rises and overturns with the cooler air above it. During this “unstable” condition, while

layers of air are moving through one another, the stack plume mixes as the air mixes. 

A cool surface occurs at night because of radiative loss of heat on clear nights. With a cloud cover,

surface heating during the day and heat loss at night are reduced, resulting in moderate mixing rates, or

neutral stability. 

Opaque cloud cover is a measure of the transparency of the clouds. For example, a completely overcast

sky with 10/10ths cloud cover may have only 1/10th opaque cloud cover if the clouds are high,

translucent clouds that do not prevent sunlight from reaching the Earth’s surface.

3.4.4 Cloud Ceiling Height

ISCST3 needs cloud ceiling height to calculate stability. Specifically, the height of the cloud cover

affects the heat balance at the Earth’s surface. 

3.4.5 Surface Pressure

The MPRM preprocessor for ISCST3 requires station (i.e. surface) pressure. MPRM uses station

pressure to compute Monin-Obukhov Length and Friction Velocity, two boundary layer parameters that

ISCST3 needs to perform dry particle deposition. ISCST3 is not very sensitive to surface pressure.
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3.4.6 Incoming Short-wave Radiation\Leaf Area Index

Solar radiation affects the respiratory activity of leaf surfaces, which affects the rate of dry vapor

deposition. We recommend using the method described in Section 3.6.1 to address the effects of dry

vapor deposition. Specify a single value in the ISCST3 input file for dry vapor deposition velocity for all

hours. Even though incoming solar radiation and leaf area index are not used when specifying the dry

vapor deposition velocity, the ISCST3 model will not run properly if values for these two data fields

aren’t included in the meteorological input file.

Though we don’t recommend it, ISCST3 is able to compute the hourly dry vapor deposition velocity by

combining hourly incoming short-wave (solar) radiation with the user-specified, site-specific leaf area

index. The default value specified in the Addendum to the MPRM User’s Guide (U.S. EPA 1999c) may

be used for leaf area index when site-specific data is not available. 

3.4.7 Precipitation Amount and Type

In order to calculate wet deposition of vapor and particles, ISCST3 requires that MPRM process

precipitation amount and type into the ISCST3 meteorological file. Precipitation is measured at 3 feet

(roughly 1 meter) above ground level. The amount of precipitation will directly influence the amount of

wet deposition at a specific location. Particles and vapor are both captured by falling precipitation,

known as precipitation scavenging. 

Scavenging coefficients are needed as inputs to ISCST3 for vapors, with a rate specified each for liquid

and frozen precipitation. The precipitation type in a SAMSON weather report (see Section 3.4.9 for

more information on SAMSON) will identify to ISCST3 which event is occurring for appropriate use of

the scavenging coefficients entered (see Section 3.6.2.6). MPRM can also read supplemental

precipitation files from NCDC, and integrate the data with CD-144 data in the ISCST3 meteorological

file. We discuss the importance of precipitation to ISCST3 results further in Section 3.4.9 ( Potential

Data Sources). 

3.4.8 Upper Air Data (Mixing Height)

Upper air data are needed to run the ISCST3 model. MPRM uses measurements of morning and

afternoon (twice daily) upper air data to calculate an hourly mixing height using interpolation methods
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FIGURE 3-1

SOURCES OF METEOROLOGICAL DATA

Meteorological Data Processing - Government Sources

(U.S. EPA 1996j). We recommend that only years with complete upper air data be used as input for air

modeling. It is important that the years you select for upper air data match the years you select for

surface data. If matching years of data are not available from a single upper air station, we recommend

another upper air station be used for completing the five years. We also recommend discussing your

choice of representative data with the appropriate authorities prior to performing air modeling.

3.4.9 Potential Data Sources

As shown in Figure 3-1, these data are available from several different sources. For most air modeling,

we recommend five years of data from a representative NWS station. However, in some instances where

the closest NWS data is clearly not representative of site-specific meteorological conditions, and there is

insufficient time to collect 5 years of onsite data, you might use 1 year of onsite meteorological data

(consistent with GAQM) to complete the risk assessment. We recommend clearly identifying and

discussing your choice of representative meteorological data with the appropriate parties (e.g. permitting

authority or facility) prior to air modeling.
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MPRM On-Site

Surface

NCDC

Mixing 

Height

NCDC

Precipitation

Data

ISCST3

Meteorological File

 Required if not

 included incommercial

 on-site source data

Surface Data Upper Air Data 

Meteorological Data Processing - Commercial Sources

Hourly data, also know as “surface data” because it tends to characterize meteorology nearer the surface,

can be obtained from the National Climatic Data Center (NCDC) web site at address

(http://lwf.ncdc.noaa.gov/oa/ncdc.html). We recommend data in the SAMSON format (available on

CD-ROM). SAMSON data are available for 239 airports across the U.S. for the period of 1961 through

1990. SAMSON data contain all of the needed input parameters used by ISCST3 to compute

concentration, dry and wet particle deposition, and dry and wet vapor deposition. 

You could also get hourly surface data from NCDC in TD-3280 format, then reformat it to CD-144

format for input to MPRM. Precipitation data in TD-3240 format is also available from NCDC. TD3240 formatted data is processed by MPRM to supplement the hourly surface data.

National Climatic Data Center

Federal Building

37 Battery Park Avenue

Asheville, NC 28801-2733

Customer Service: (704) 271-4871

File type: File name:

Hourly precipitation amounts NCDC TC-3240

Hourly surface observations with precipitation type NCDC TD-3280

Hourly surface observations with precipitation type NCDC SAMSON CD-ROM (Vol. I , II, and/or III)

Twice daily mixing heights from nearest station NCDC TD-9689

(also available on SCRAM web site for 1984 through 1991)
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Currently, MPRM is the most appropriate Agency meteorological preprocessor program for preparing the

surface and upper air data into an ISCST3 meteorological input file. Most air modeling analyses will use

MPRM to process the National Weather Service data. 

We recommend using the most recent 5 years of complete meteorological data available on SAMSON (or

more recent sources) for the air modeling. It’s desirable, but not mandatory, that the 5 years be

consecutive. 

Each year of the 5 years of data should be complete before being processed by MPRM. If data gaps

exist, we recommend filling in all missing data. The procedures we recommend for filling missing

surface and upper air data are documented on the SCRAM web site under the meteorological data

section. If the missing data are not addressed by the Agency objective procedures, then with the approval

of the permitting authority, you can develop a subjective method for filling in missing data. If conditions

occur such that:

1. missing values are not able to be replaced; and

2. the permitting authority approves the use of the meteorological data in that condition

then specify the MSGPRO keyword in the COntrol pathway of the ISCST3 input file. Note that the

DEFAULT keyword can't be used with MSGPRO.

If you wish to use less than 5 years of meteorological data, we recommend clearly identifying and

discussing this with all appropriate parties (e.g. permitting authority, or facility). 

To prevent the need to repeat air modeling activities, we recommend that your choices of representative

upper air and surface data be clearly identified and discussed with the appropriate parties (e.g. regulatory

authority, facility) before you begin preprocessing and air modeling. Also, we recommend completely

documenting all processing of meteorological data, including sources of data, selection criteria,

consideration for precipitation amounts, preprocessor options selected, and filled missing data. If your

choices of meteorological data (e.g. selection of upper air data, or determination of dry bulb temperature)

are inconsistent with this guidance, we further recommend clearly identifying and discussing these

choices in the risk plan and/or cost estimate (as appropriate) to ensure clarity and transparency of the

final risk assessment results.
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• Electronic copy of the ISCST3 input code used to enter meteorological information

• Description of the selection criteria and process used to identify representative years used for

meteorological data

• Identification of the 5 years of meteorological selected

• Summary of the procedures used to compensate for any missing data

RECOMMENDED INFORMATION FOR RISK ASSESSMENT REPORT

3.5 METEOROLOGICAL PREPROCESSOR DATA NEEDS

After selecting the appropriate surface and upper air data using the procedures outlined in Section 3.4,

you still need to put the data into a form that ISCST3 can use. As stated above, we recommend using the

meteorological preprocessor MPRM to do this. The following Section describes the data MPRM itself

requires in order to perform the preprocessing. Agency approval is recommended in the selection of

MPRM parameter values.

We recommend preparing an ISCST3 meteorological file that can be used to calculate either

concentration or deposition (what MPRM terms an “ISCGASW” file). All necessary parameters will

then be available to ISCST3 for any subsequent concentration or deposition modeling. For example, if

only the concentration option is selected in ISCST3 for a specific run, ISCST3 will ignore the

precipitation values in the meteorological file. For subsequent air deposition modeling, ISCST3 will

access the precipitation data from the same preprocessed meteorological file. 

MPRM includes extensive QA/QC to check for values that are out of range. MPRM also checks for

missing data and summarizes values that require editing to fill missing data. After a complete surface file

passes the quality checks, it is processed with NCDC upper air data.

MPRM needs the following input parameters representative of the meteorological measurement site

(typically the nearest representative National Weather Station):
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• Minimum Monin-Obukhov length

• Anemometer height

• Surface roughness length (at measurement site)

• Noon-time albedo

• Bowen ratio

• Anthropogenic heat flux

• Fraction of net radiation absorbed at surface

MPRM also needs the following input parameter representative of the application site (e.g., source

location):

• Surface roughness length (at application site)

The MPRM User’s Guide contains detailed information for preparing the ISCST3 meteorological input

file (U.S. EPA 1996j). The parameters listed are briefly described in the following subsections. These

data are not included in the surface or mixing height data files obtained from the U.S. EPA or NCDC. 

We recommend taking special care, while using the tables in the MPRM User’s Guide or reference

literature, to select values representative of the meteorological measurement site and the site to be

modeled. We recommend clearly identifying and discussing the selected values with the appropriate

parties (e.g. permitting authority, or facility) before processing the meteorological data.

3.5.1 Monin-Obukhov Length

The Monin-Obukhov length (L) is a measure of atmospheric stability. It is negative during the day, when

surface heating causes unstable air. It is positive at night, when the surface is cooled and the atmosphere

more stable. In urban areas during stable conditions, the estimated value of L may not adequately reflect

the less stable atmosphere associated with the mechanical mixing generated by buildings or structures. 

However, MPRM needs an input for minimum urban Monin-Obukhov length, even if the area to be

analyzed by ISCST3 is rural. A nonzero value for L must be entered to run MPRM. We recommend

using a value of 2.0 meters for L when the land use surrounding the site is rural (see Section 3.3.2.1). For

urban areas, Hanna and Chang (1991) suggest that a minimum value of L be set for stable hours to
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simulate building-induced instability. The following are general examples of L values for various land

use classifications:

TABLE 3-4

L VALUES FOR VARIOUS LAND USES

Land Use Classification Minimum L

Agricultural (open) 2 meters

Residential 25 meters

Compact residential/industrial 50 meters

Commercial (19 to 40-story buildings) 100 meters

Commercial (>40-story buildings) 150 meters

MPRM will use the minimum L value in calculating urban stability parameters. These urban values will

be ignored by ISCST3 during the air modeling analyses for rural sites.

3.5.2 Anemometer Height

ISCST3 model results are very sensitive to small variations in wind speed. The height of the wind speed

measurements is needed by ISCST3 to calculate wind speed at stack top. The wind sensor (anemometer)

height for every National Weather Service station is identified in the station history section of the Local

Climatological Data Summary available from NCDC. Since 1980, most National Weather Service

stations measure wind speed at the height of 10 meters. However, some stations operate at other heights

or have data at more than one height. We generally recommend verifying the correct measurement height

for each year of data prior to processing with MPRM and running the ISCST3 model.

3.5.3 Surface Roughness Length at Measurement Site

Surface roughness length (or height) is a measure of the height of obstacles to wind flow. It is important

in ISCST3 because it determines how close a particle must be to the ground before it is “captured” for

deposition on the ground. Slight variations in surface roughness can lead to dramatic differences in

ISCST3 results. For surface meteorological data from a National Weather Station, we typically

recommend using a value of 0.10 meters for the “measurement site.” Surface roughness is proportional,

but not equal, to the physical height of the obstacles. Table 3-3 (in Section 3.3.2.2) lists available

roughness height values. These values are based on the general land use in the vicinity of the
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measurement site. We recommend considering these values in discussions with the appropriate parties

prior to air modeling.

3.5.4 Surface Roughness Length at Application Site

MPRM also needs the surface roughness length at the facility (application site) in order to prepare the

ISCST3 meteorological file. ISCST3 model results are very sensitive to the value used in MPRM for this

parameter. Table 3-3 in Section 3.3.2.2 is also applicable to the application site. Compute a single

surface roughness value representative of the site by using the method described in Section 3.3.2.2. We

recommend clearly identifying and discussing the computed surface roughness length for the application

site, along with maps or photographs illustrating land use, with the appropriate parties (e.g. permitting

authority or facility) prior to use.

3.5.5 Noon-Time Albedo

“Noon-time albedo” is the fraction of the incoming solar radiation that is reflected from the ground when

the sun is directly overhead. Albedo is used in calculating the hourly net heat balance at the surface. Net

heat balance at the surface is then used in calculating hourly values of Monin-Obukhov length. MPRM

automatically adjusts for the variation in albedo with solar elevation angle. Experience suggests that

ISCST3 modeling results are not sensitive to the value selected for this parameter. Table 3-5 presents

typical albedo values. Albedo values vary from 0.10 to 0.20 on water surfaces from summer to winter. 

Cultivated farmland values vary the most, from 0.14 during spring when land is tilled to expose dark

earth, to 0.60 in winter when areas are snow-covered.
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TABLE 3-5

ALBEDO OF NATURAL GROUND COVERS FOR LAND USE TYPES AND SEASONS

Land Use Type

Seasona

Spring Summer Autumn Winter

Water surface 0.12 0.10 0.14 0.20

Deciduous forest 0.12 0.12 0.12 0.50

Coniferous forest 0.12 0.12 0.12 0.35

Swamp 0.12 0.14 0.16 0.30

Cultivated land 0.14 0.20 0.18 0.60

Grassland 0.18 0.18 0.20 0.60

Urban 0.14 0.16 0.18 0.35

Desert shrubland 0.30 0.28 0.28 0.45

Source—Iqbal (1983)

a

 The various seasons are defined by Iqbal (1983) as follows:

 Spring: Periods when vegetation is emerging or partially green; this is a transitional situation that applies for 1 to

2 months after the last killing frost in spring.

 Summer: Periods when vegetation is lush and healthy; this is typical of mid-summer, but also of other seasons in

which frost is less common.

 Autumn: Periods when freezing conditions are common, deciduous trees are leafless, crops are not yet planted or

are already harvested (bare soil exposed), grass surfaces are brown, and no snow is present.

 Winter: Periods when surfaces are covered by snow and temperatures are below freezing. Winter albedo depends

on whether a snow cover is present continuously, intermittently, or seldom. Albedo ranges from about

0.30 for bare snow cover to about 0.65 for continuous cover.

Based on the information in Table 3-5, rural area albedo estimates vary from 0.14 to 0.20 for cultivated

land, and from 0.18 to 0.20 for grassland. For urban areas without snow, values vary from 0.14 to 0.18. 

For practical purposes, it is desirable to process a complete year of meteorological data with a single

value for noon-time albedo. For example, the single value of 0.18 may be appropriate to process all

meteorological data for an urban site. For rural sites, a single albedo value of 0.18 for grassland and

cultivated land may be appropriate for areas without significant snow cover during winter months. For

desert shrubland, a single value of 0.28 may be appropriate. A single value of 0.12 could be

representative of forested areas. We recommend discussing the proposed values with the permitting

authority prior to air modeling.
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3.5.6 Bowen Ratio

The Bowen ratio is the ratio of the sensible heat flux to the evaporative or latent heat flux at the ground

surface. The presence of moisture affects the heat balance through evaporative cooling, which, in turn,

affects the hourly Monin-Obukhov length calculated by MPRM. Surface moisture is highly variable. 

Daytime Bowen ratios are presented in Table 3-6.

Bowen ratio values vary throughout the country. For example, in urban areas where annual rainfall is

less than 20 inches, a single Bowen ratio value of 4.0 may be representative. For rural areas, a Bowen

ratio value of 2.0 may be appropriate for grassland and cultivated land. For areas where annual rainfall is

greater than 20 inches, we recommend a single Bowen ratio value of 2.0 for urban areas; and 0.7 for rural

forests, grasslands, and cultivated lands. You can refine the Bowen ratio estimates provided in Table 3-6

by using site-specific precipitation and wind speed data. We recommend clearly identifying and

discussing the proposed values with the appropriate parties (e.g. permitting authority or facility) prior to

use.

TABLE 3-6

DAYTIME BOWEN RATIOS BY LAND USE, SEASON,

AND PRECIPITATION CONDITIONS

Land Use

Seasona

Spring Summer Autumn Winter

Dry Conditions

Water (fresh and salt) 0.1 0.1 0.1 2.0

Deciduous forest 1.5 0.6 2.0 2.0

Coniferous forest 1.5 0.6 1.5 2.0

Swamp 0.2 0.2 0.2 2.0

Cultivated land 1.0 1.5 2.0 2.0

Grassland 1.0 2.0 2.0 2.0

Urban 2.0 4.0 4.0 2.0

Desert shrubland 5.0 6.0 10.0 2.0

Average Conditions

Water (fresh and salt) 0.1 0.1 0.1 1.5

Deciduous forest 0.7 0.3 1.0 1.5

Coniferous forest 0.7 0.3 0.8 1.5

Swamp 0.1 0.1 0.1 1.5

Cultivated land 0.3 0.5 0.7 1.5
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TABLE 3-6

(contd.)

Land Use

Seasona

Spring Summer Autumn Winter

Grassland 0.4 0.8 1.0 1.5

Urban 1.0 2.0 2.0 1.5

Desert shrubland 3.0 4.0 6.0 6.0

Wet Conditions

Water (fresh and salt) 0.1 0.1 0.1 0.3

Deciduous forest 0.3 0.2 0.4 0.5

Coniferous forest 0.3 0.2 0.3 0.3

Swamp 0.1 0.1 0.1 0.5

Cultivated land 0.2 0.3 0.4 0.5

Grassland 0.3 0.4 0.5 0.5

Urban 0.5 1.0 1.0 0.5

Desert shrubland 1.0 5.0 2.0 2.0

Source—Paine (1987)

a

 The various seasons are defined by Iqbal (1983) as follows:

 Spring: Periods when vegetation is emerging or partially green; this is a transitional situation that applies for 1 to

2 months after the last killing frost in spring.

 Summer: Periods when vegetation is lush and healthy; this is typical of mid-summer, but also of other seasons in

which frost is less common.

 Autumn: Periods when freezing conditions are common, deciduous trees are leafless, crops are not yet planted or

are already harvested (bare soil exposed), grass surfaces are brown, and no snow is present.

 Winter: Periods when surfaces are covered by snow and temperatures are below freezing. Winter albedo depends

on whether a snow cover is present continuously, intermittently, or seldom. Albedo ranges from about

0.30 for bare snow cover to about 0.65 for continuous cover.

3.5.7 Anthropogenic Heat Flux

Anthropogenic heat is the surface heating caused by human activity, including automobiles and heating

systems. It is used to calculate hourly L values (Monin-Obukhov lengths). Table 3-7 presents

anthropogenic heat flux (Qf) values for several urban areas around the world (U.S. EPA 1995g). In rural

areas, we recommend using a value 0.0 Watts/m2 for the Qf. A value of 20.0 Watts/m2 is appropriate for

large urban areas, based on the annual value for Los Angeles.
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TABLE 3-7

ANTHROPOGENIC HEAT FLUX (Qf) AND NET RADIATION (Q*)

FOR SEVERAL URBAN AREAS

Urban Area

(Latitude)

Population

(Millions)

Population

Density

(Persons/km2)

Per Capita

Energy Use

(MJ x 103/year)

Qf (Watts/m2)

(Season)

Q*

(Watts/m2

)

Manhattan

(40° North)

1.7 28,810 128 117 (Annual)

40 (Summer)

198 (Winter)

93 (Annual)

Montreal

(45° North)

1.1 14,102 221 99 (Annual)

57 (Summer)

153 (Winter)

52 (Annual)

92 (Summer)

13 (Winter)

Budapest

(47° North)

1.3 11,500 118 43 (Annual)

32 (Summer)

51 (Winter)

46 (Annual)

100 (Summer)

-8 (Winter)

Sheffield

(53° North)

0.5 10,420 58 19 (Annual) 56 (Annual)

West Berlin

(52° North)

2.3 9,830 67 21 (Annual) 57 (Annual)

Vancouver

(49° North)

0.6 5,360 112 19 (Annual)

15 (Summer)

23 (Winter)

57 (Annual)

107 (Summer)

6 (Winter)

Hong Kong (22°

North)

3.9 3,730 34 4 (Annual) 110 (Annual)

Singapore

(1° North)

2.1 3,700 25 3 (Annual) 110 (Annual)

Los Angeles (34°

North)

7.0 2,000 331 21 (Annual) 108 (Annual)

Fairbanks

(64° North)

0.03 810 740 19 (Annual) 18 (Annual)

Source—Oke (1978)

3.5.8 Fraction of Net Radiation Absorbed at the Ground

Also used for calculating hourly values of Monin-Obukhov length, fraction of net radiation absorbed at

the ground is the last component of radiative heat balance. Based on: 
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• the net radiation (Q*) values presented in Table 3-7, and 

• recommendations presented in the MPRM User’s Manual, themselves based on Oke

(1982), 

we recommend values of 0.15 for rural areas and 0.27 for urban areas (U.S. EPA 1995g).

3.6 ISCST3 MODEL INPUT FILES

The ISC3 User’s Guide, Volume I (U.S. EPA 1995f) offers a thorough instruction on how to prepare the

ISCST3 input files. The User’s Guide is available for downloading from the SCRAM at

http://www.epa.gov/scram001. We provide an example ISCST3 input file in Figure 3-2. 

This example illustrates a single year run (1984), for particle phase COPC emissions from a single stack. 

The run is used to compute acute (1-hour average) and chronic (annual average) values. It provides

single year results in a one hour and annual average plot file for post-processing. Specifying a terrain grid

file in the TG pathway is optional. You generally only consider it for modeling dry vapor deposition in

highly variable terrain. Each air modeling analysis has unique issues and concerns that we recommend

you address in the risk assessment report. We recommend using an air modeling methodology

consistently throughout, from data collection and model set-up, to model output. This will assist both

you and the permitting authority in interpreting and communicating model results. A transparent and

scientifically defensible risk assessment report will identify consistent methods while documenting each

section of the ISCST3 input file.
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FIGURE 3-2

EXAMPLE INPUT FILE FOR “PARTICLE PHASE”

CO STARTING

CO TITLEONE Example input file, particle phase run

CO TITLETWO 1984 met data, Baton Rouge Surface, Boothville Upper Air

CO MODELOPT DFAULT CONC DDEP WDEP DEPOS DRYDPLT WETDPLT RURAL

CO AVERTIME 1 ANNUAL

CO POLLUTID UNITY

CO TERRHGTS ELEV

CO RUNORNOT RUN

CO SAVEFILE 84SAVE1 5 84SAVE2

** Restart incomplete runs with INITFILE, changing '**' to 'CO'

** INITFILE 84SAVE1

CO FINISHED

SO STARTING

SO LOCATION STACK1 POINT 637524. 567789. 347.

SO SRCPARAM STACK1 1.0 23.0 447.0 14.7 1.9

SO BUILDHGT STACK1 18.29 18.29 18.29 18.29 18.29 18.29 18.29 18.29

SO BUILDHGT STACK1 18.29 18.29 18.29 18.29 18.29 18.29 18.29 18.29

SO BUILDHGT STACK1 18.29 18.29 18.29 18.29 18.29 18.29 18.29 18.29

SO BUILDHGT STACK1 18.29 18.29 18.29 18.29 18.29 18.29 18.29 18.29

SO BUILDHGT STACK1 18.29 18.29 18.29 18.29

SO BUILDWID STACK1 14.02 15.51 16.53 17.05 17.05 16.53 15.51 14.03

SO BUILDWID STACK1 12.10 14.02 15.51 16.53 17.05 17.05 16.53 15.51

SO BUILDWID STACK1 14.02 12.10 14.02 15.51 16.53 17.05 17.05 16.53

SO BUILDWID STACK1 15.51 14.02 12.10 14.02 15.51 16.53 17.05 17.05

SO BUILDWID STACK1 16.53 15.51 14.02 12.10

SO PARTDIAM STACK1 0.35 0.70 1.10 2.00 3.60 5.50 8.10 12.5 15.0

SO MASSFRAX STACK1 0.22 0.08 0.08 0.11 0.10 0.07 0.10 0.11 0.13

SO PARTDENS STACK1 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 

SO PARTSLIQ STACK1 7E-5 5E-5 6E-5 1.3E-4 2.6E-4 3.9E-4 5.2E-4 6.7E-4 6.7E-4 

SO PARTSICE STACK1 2E-5 2E-5 2E-5 4E-5 9E-5 1.3E-4 1.7E-4 2.2E-4 2.2E-4 

SO SRCGROUP ALL

SO FINISHED

RE STARTING

RE ELEVUNIT METERS

RE DISCCART 630000. 565000. 352.

RE DISCCART 630500. 565000. 365.

RE DISCCART 631000. 565000. 402.

 ...

 (ARRAY OF DISCRETE RECEPTORS)

 ...

RE DISCCART 635000. 570000. 387.

RE FINISHED

ME STARTING

ME INPUTFIL 84BTR.WET

ME ANEMHGHT 10.0

ME SURFDATA 13970 1984 BATON_ROUGE

ME UAIRDATA 12884 1984 BOOTHVILLE

ME FINISHED

TG STARTING

TG INPUTFIL TERRAIN.TER

TG LOCATION 0.0 0.0

TG ELEVUNIT METERS

TG FINISHED

OU STARTING

OU RECTABLE ALLAVE FIRST

OU PLOTFILE 1 ALL FIRST BTR841.PLT

OU PLOTFILE ANNUAL ALL BTR84A.PLT

OU FINISHED
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• Electronic and hard copies of ISCST3 input file for all air modeling runs

RECOMMENDED INFORMATION FOR THE RISK ASSESSMENT REPORT

As discussed in Section 3.2, ISCST3 requires separate runs to model vapor phase COPCs, particle phase

COPCs, and particle-bound phase COPCs, for a total of three runs per COPC source (stack or fugitive). 

The ISCST3 “Control Secondary Keywords” used for these three runs are:

Vapor Phase: CONC DDEP WDEP DEPOS

Particle Phase: CONC DDEP WDEP DEPOS

Particle-Bound Phase: CONC DDEP WDEP DEPOS

ISCST3 needs site-specific inputs for source parameters, receptor locations, meteorological data, and

terrain features. Prepare the model for execution by creating an input file. The input file is

structured in five (or six, if a terrain grid file is used) sections, or pathways, designated by two-letter

abbreviations:

TABLE 3-8

ISCST3 INPUT FILE SECTIONS

Section Abbreviation

Control CO

Source SO

Receptor RE

Meteorology ME

Terrain Grid (Optional) TG

Output OU

The following subsections describe how to specify the parameters for each pathway in the ISCST3 input

file.
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3.6.1 COntrol Pathway

Your choice of model options (MODELOPT) in the COntrol pathway will direct ISCST3 in the types of

computations to perform. We generally recommend specifying the DFAULT parameter for particle and

particle-bound phase runs, so that ISCST3 will implement the following regulatory default options:

• Use stack-tip downwash (except for Schulman-Scire downwash).

• Use buoyancy-induced dispersion (except for Schulman-Scire downwash).

• Do not use final plume rise (except for building downwash).

• Use the calms processing routines.

• Use upper-bound concentration estimates for sources influenced by building downwash

from super-squat buildings.

• Use default wind speed profile exponents.

• Use default vertical potential temperature gradients.

The CONC parameter specifies calculation of air concentrations. The DDEP and WDEP parameters

specify dry and wet deposition. The DEPOS specifies computation of total (wet and dry) deposition flux. 

DRYDPLT and WETDPLT are used for plume depletion resulting from dry and wet removal. We

recommend the following command lines for the vapor and two particle runs (these are for rural areas;

substitute URBAN for urban areas):

Vapor: CO MODELOPT TOXICS CONC DDEP WDEP DEPOS DRYDPLT

WETDPLT RURAL

CO GASDEPVD 0.01

Particle Phase: CO MODELOPT DFAULT CONC DDEP WDEP DEPOS DRYDPLT

WETDPLT RURAL

Particle-Bound: CO MODELOPT DFAULT CONC DDEP WDEP DEPOS DRYDPLT

WETDPLT RURAL

Note that for vapor phase model runs, the DFAULT option is replaced by the TOXICS option. This

directs ISCST3 to execute the dry vapor deposition algorithm in addition to the regulatory default

parameters. You need to add an additional COntrol command line for the vapor phase run, to provide the
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single value of the dry vapor deposition velocity. In order to set a single dry vapor deposition velocity in

ISCST3, use the following options:

• Remove the DEFAULT keyword from the CO MODELOPT card. (This option is

incompatible with the TOXICS option.)

• Add the TOXICS keyword on the CO MODELOPT card. (This option is needed when

using dry vapor deposition.)

• Add the keyword CO GASDEPVD<Uservd>, where Uservd in the dry vapor deposition

velocity (meters/second).

We recommend a dry vapor deposition velocity of 0.5 centimeter per second (cm/s) for organic

contaminants, chlorine, and HCl. We recommend a dry vapor deposition velocity of 2.9 cm/s for divalent

mercury. The recommended dry vapor deposition velocity value of 0.5 cm/s for organic contaminants is

consistent with the range specified for pesticides (0.01 - 1.1 cm/s) and dioxins and furans (0.27 - 0.78

cm/s) (U.S. EPA 2000b). A recent review of dry deposition (Wesely and Hicks 2000) demonstrates

considerable uncertainty about dry deposition even for well-measured species such as ozone and sulfur

dioxide. Uncertainty is greater for organic compounds, with very few measurements available to support

defensible values (see following table). 

TABLE 3-9

DRY DEPOSITION VELOCITY ESTIMATES AVAILABLE IN LITERATURE

Chemical Dry Deposition Velocity (cm/s) Reference

Acetic acid 0.64 - 1.0 Hartmann et al. (1991)1

0.7 Sanheuza et al. (1992)1

Formic acid 1.1 Sanheuza et al. (1992)1

Chlordane 0.01 - 0.04 Bidleman (1988)

Arochlor 1242 0.02 - 0.1

Arochlor 1254 0.08 - 0.2

p,p’-DDT 0.1 - 0.7

TCDD 0.5 Trapp and Matthies (1995)

0.5 McLachlan et al. (1995)

0.27 - 0.78 Smith and Heinhold (1995)

PCDD/Fs 0.19 (0.06-0.60) Koester and Hites (1992)

1

 As cited in Wesely and Hicks (2000)
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The modeling reported in the Mercury Study Report to Congress (U.S. EPA 1997c) used a value of

0.3 cm/s for nighttime dry deposition of divalent mercury, but used daytime values ranging from 0.20 to

4.83 cm/s depending upon atmospheric stability and land-use category. The daytime values were based

on data developed from nitric acid data, not from measurements of divalent mercury. U.S. EPA (1997c)

used an average ISC model-calculated dry deposition velocity of 2.9 cm/s for divalent mercury vapor and

0.06 cm/s for elemental mercury. Higher values were expected for chemicals with greater reactivity than

acetic acid or formic acid, but no measured values were identified for any organic compounds higher

than 1.1 cm/s. As a result, we recommend the default of 2.9 for divalent mercury. 

U.S. EPA (1997c) also calculates site- or contaminant-specific dry vapor deposition velocities based on

various parameters including molecular diffusivity, a solubility enhancement factor, pollutant reactivity,

mesophyll resistance, and Henry’s law constant. If you are assessing a facility surrounded by land uses

other than pine forest (for instance urban, agricultural lands, or wetlands), you may wish to consider how

a site-specific value for this parameter could be calculated. Two important parameters are the stability

class (from the air modeling) and the land use surrounding the facility. The following information can be

found in Section 5.1.2.3 (Dry Deposition of Vapors), page 5-12, in the technical background document of

the MACT rule: "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 (F-1999-RC2F-S0014)", which explains that:

To calculate the weighted dry deposition velocity, it is recommended that land use be obtained

from 1:250,000 scale quadrangles of land use and GIRAS spatial data obtained from EPA

website and placed in an ARC-INFO format (U.S. EPA, 1994b). Table B-6 of Appendix B of the

MACT rule background document shows the land use data for the sites that were detailed in the

MACT rule. In the MACT rule, the fraction of time in each stability class was based on 5-year

hourly meteorological files used in the ISCST3 modeling. Table B-8 of Appendix B in the

MACT rule background document shows the weighted dry deposition velocity for divalent

mercury vapor at the modeled facilities. Dry deposition of elemental mercury was not included

in the MACT analysis, which is consistent with the 1997 Mercury Report to Congress.

Site-specific dry deposition velocity for divalent mercury vapor can be calculated by weighting

land use and stability class. Values for dry deposition velocity for each land use category and

stability class can be found in the "Mercury Study Report to Congress Volume III: Fate and

Transport of Mercury in the Environment, December 1997, EPA-452/R-97-003" in Table 4-3 and

Table 4-4, respectively. It is recommended that these values be averaged to annualized values. 

Generally, night time dry deposition velocities can be treated as constant across all stability. 
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As more research to measure deposition velocities of more organic compounds under a variety of

conditions becomes available, it may be appropriate to develop site- and chemical- specific default dry

deposition of vapor velocities. It is important to note that although we recommend inputting the dry

vapor deposition velocity directly into ISCST3, you might instead elect to execute the dry gas deposition

algorithms within ISCST3 to calculate a deposition velocity. However, we caution you to read

Section 3.1.2 (Preprocessing Programs) and Section 3.4.6 (Solar Radiation), which note additional data

needs and potential limitations to ISCST3 calculating deposition velocities. Having ISCST3 calculate a

deposition velocity may also require that you conduct compound-specific air modeling runs, deviating

from the unit emission rate approach as outlined in this guidance. This may significantly increase the

number of air modeling runs needed.

Note that for each of the three runs for each emission source, 5 complete years of off-site (e.g., National

Weather Service from SAMSON) meteorological data are used. For sites with meteorological data

collected on-site, we recommend that the permitting authority be notified of the data period needed for a

risk assessment. Specify ‘ANNUAL’ for the averaging times (AVERTIME) to compute chronic (annual

average) health risk, and/or ‘1’ to compute acute health risks based on the maximum 1-hour average

concentrations over the 5-year period (see Section 3.10). We generally recommend repeating each phase

run five times (one for each year, or a total of 15 ISCST3 runs) to complete a set of 15 runs for the full

five years of meteorological data.

Alternatively, you can combine the 5 years of meteorological data into a single meteorological data file

and complete only 3 runs for each emission source (one run for each phase). Section 3.5.1.1 of the ISC3

User’s Guide (U.S. EPA 1995f), includes a complete discussion of combining multiple years of

meteorological data into a single file prior to running ISCST3. You may select the ‘ANNUAL’ averaging

time for all risk assessment runs, regardless of the number of years in the meteorological data file. The

incorrect selection of ‘PERIOD’ will not compute the correct deposition rates needed by the risk

assessment equations (refer to Section 3.2.3 of the ISC3 User Guide, Volume I). No additional ISCST3

model execution time is needed to obtain 1-year or 5-year air modeling values.

ISCST3 also allows you to specify COPC half-life and decay coefficients. Unless clearly identified and

discussed with the appropriate parties (regulatory authority or facility), we don’t recommend using these
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keywords when conducting air modeling for risk assessments. You typically use the TERRHGTS

keyword with the ELEV parameter to model terrain elevations at receptor grid nodes. The FLAGPOLE

keyword specifies receptor grid nodes above local ground level and is not typically used for most air

modeling to perform impacts at ground level. 

We also recommend using SAVEFIL to restart ISCST3 in the event of a computer or power failure

during long runs. SAVEFIL is best used by specifying two save files, each with a different name. We

recommend that the save interval not be longer than 5 days for large runs. If two save files are used, and

a failure occurs during writing to the save file, no more than 10 days will be lost. Use the INITFILE

command to restart the runs after the failure, as shown in the following example:

CO SAVEFILE SAVE1 5 SAVE2

** INITFILE SAVE1

ISCST3 will save the results alternately to SAVE1 and SAVE2 every 5 days. If the run fails after

successfully writing to SAVE1, you can restart the ISCST3 run by replacing the two asterisks (*) in the

INITFILE line with CO and running ISCST3 again. The run will begin after the last day in SAVE1. 

Note that you don’t use the MULTYEAR keyword for computing long-term averages, and it should not be

specified.

The following is an example of the COntrol pathway computer code for a single-year ISCST3 particle

run:

CO STARTING

CO TITLEONE Example input file, particle phase run, 1 year

CO TITLETWO 1984 met data, Baton Rouge Surface, Boothville Upper Air

CO MODELOPT DFAULT CONC DDEP WDEP DEPOS DRYDPLT WETDPLT RURAL

CO AVERTIME 1 ANNUAL

CO POLLUTID UNITY

CO TERRHGTS ELEV

CO RUNORRUN RUN

CO SAVEFILE 84SAVE1 5 84SAVE2

** Restart incomplete runs with INITFILE, changing ‘**’ to ‘CO’

** INITFILE SAVE1

CO FINISHED

The corresponding COntrol pathway computer code for a single-year ISCST3 vapor run is:
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• Input values with supporting documentation for each parameter identified in Section 3.7.2

RECOMMENDED INFORMATION FOR RISK ASSESSMENT REPORT

CO STARTING

CO TITLEONE Example input file, vapor phase run, 1 year

CO TITLETWO 1984 met data, Baton Rouge Surface, Boothville Upper Air

CO MODELOPT TOXICS CONC DDEP WDEP DEPOS DRYDPLT WETDPLT RURAL

CO GASDEPVD 0.01

CO AVERTIME 1 ANNUAL

CO POLLUTID UNITY

CO TERRHGTS ELEV

CO RUNORRUN RUN

CO SAVEFILE 84SAVE1 5 84SAVE2

** Restart incomplete runs with INITFILE, changing ‘**’ to ‘CO’

** INITFILE SAVE1

CO FINISHED

Additional runs for the other 4 years are set up with the same COntrol pathway, except for the title

description and SAVEFILE filenames.

3.6.2 SOurce Pathway

As discussed in Section 3.8, ISCST3 normally uses a unit emission rate of 1.0 g/s. Additional source

characteristics the model needs (typically found in the Part B permit application and trial burn report)

include the following:

• Source type (point source for stack emissions; area or volume for fugitive emissions)

• Source location (UTM coordinates, m)

• Source base elevation

• Emission rate (1.0 g/s)

• Stack height (m)

• Stack gas temperature (K)

• Stack gas exit velocity (m/s)

• Stack inside diameter (m)

• Building heights and widths (m)

• Particle size distribution (percent)

• Particle density (g/cm3)

• Particle and gas scavenging coefficients (unitless)
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3.6.2.1 Source Location

The location keyword of the SOurce pathway (SO LOCATION) identifies the:

• source type, 

• location, and 

• base elevation. 

The source type for any stack is referred to as a “point” source in ISCST3. Fugitive source emissions are

discussed in section 3.9. The source location must be entered into ISCST3. We recommend entering

source locations in UTM coordinates. The easterly and northerly coordinates are entered to the nearest

meter; for example, 637524 meters UTM-E, or 4567789 meters UTM-N (no commas are used). Enter the

base elevation of each stack in meters. Sources for base elevations include USGS topographic maps,

facility plot plans or USGS digital data bases. 

An example input for the location keyword on the SOurce pathway includes source type, location, and

base elevation in the following format:

SO LOCATION STACK1 POINT 637524. 4567789. 347.

3.6.2.2 Source Parameters

The source parameters keyword of the SOurce pathway (SO SRCPARAM) identifies the:

• emission rate, 

• stack height, 

• stack temperature, 

• stack velocity, and 

• stack diameter. 

Enter the unit emission rate as 1.0 g/s. Stack height is the height above plant base elevation on the SO

LOCATION keyword. Stack gas exit temperature is the most critical stack parameter for influencing

concentration and deposition. High stack gas temperatures result in high buoyant plume rise, which, in

turn, lowers concentration and deposition rates. We recommend basing stack gas temperatures on stack
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sampling tests for existing stacks. For new or undefined stacks, you might use manufacturer’s data for

similar equipment. Calculate stack gas exit velocity from actual stack gas flow rates and stack diameter. 

Actual stack gas flow rates can be measured during existing stacks during stack sampling. You can get

representative values for new or undefined sources from manufacturer’s data on similar equipment. 

Stack diameter is the inside diameter of the stack at exit.

We highly recommend using a site- or unit-specific stack temperature (low, average, high). Similar to the

Chapter 2 discussion on emissions testing, we recommend choosing the stack gas temperature based on

the objectives of the risk assessment. For example, if permitting is the objective, ‘typical’ operating

temperatures with all control devices operating might be a possible testing condition to select. On the

other hand, you might select low or high operating temperatures because of the potential for emitting

certain COPCs, or the production of specific PICs, regardless of plume rise considerations. We

recommend avoiding the practice of always choosing the lowest stack temperature, in order to decrease

buoyancy and thereby increase concentration and deposition near the source. This is a gross oversimplification of conditions. Increases in concentration and deposition near the source may

underestimate concentrations and deposition rates away from the source where more critical receptors

may be located (see Chapter 4).

Following is an example of the source parameter input in the SOurce pathway for emission rate (grams

per second), stack height (meters), stack temperature (K), stack velocity (meters per second), and stack

diameter (meters):

SO SRCPARAM STACK1 1.0 23.0 447.0 14.7 1.9

3.6.2.3 Building Parameters

The building height and width keywords of the SOurce pathway (SO BUILDHGT; SO BUILDWID)

identify the building dimensions that most influence the air flow for each of the 36 10-degree directions

surrounding a stack. Calculate the dimensions using BPIP software, as described in Section 3.2.4.
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The BPIP output file is transferred into the ISCST3 SOurce pathway as follows:

SO BUILDHGT STACK1 18.29 18.29 18.29 18.29 18.29 18.29 18.29 18.29

SO BUILDHGT STACK1 18.29 18.29 18.29 18.29 18.29 18.29 18.29 18.29

SO BUILDHGT STACK1 18.29 18.29 18.29 18.29 18.29 18.29 18.29 18.29

SO BUILDHGT STACK1 18.29 18.29 18.29 18.29 18.29 18.29 18.29 18.29

SO BUILDHGT STACK1 18.29 18.29 18.29 18.29

SO BUILDWID STACK1 14.02 15.51 16.53 17.05 17.05 16.53 15.51 14.03

SO BUILDWID STACK1 12.10 14.02 15.51 16.53 17.05 17.05 16.53 15.51

SO BUILDWID STACK1 14.02 12.10 14.02 15.51 16.53 17.05 17.05 16.53

SO BUILDWID STACK1 15.51 14.02 12.10 14.02 15.51 16.53 17.05 17.05

SO BUILDWID STACK1 16.53 15.51 14.02 12.10

3.6.2.4 Particle Size Distribution

ISCST3 needs a particle size distribution for determining deposition velocities. We recommend using

site-specific stack test data for existing sources. 

The following example is an ISCST3 input for a particle phase run. From Table 3-1, the distribution for

9 mean diameter sizes includes the data needed for the keywords of the SOurce pathway

(SO PARTDIAM; SO MASSFRAX). The PARTDIAM is taken from Column 1 (Mean Particle Diameter).

The MASSFRAX is taken from Column 4 (Fraction of Total Mass).

SO PARTDIAM STACK1 0.35 0.70 1.10 2.00 3.60 5.50 8.10 12.5 15.0

SO MASSFRAX STACK1 0.22 0.08 0.08 0.11 0.10 0.07 0.10 0.11 0.13

The example for the ISCST3 input for the particle-bound run is described below. From Table 3-1, the

PARTDIAM is the same. The MASSFRAX is taken from Column 6 (Fraction of Total Surface Area).

SO PARTDIAM STACK1 0.35 0.70 1.10 2.00 3.60 5.50 8.10 12.5 15.0

SO MASSFRAX STACK1 0.49 0.17 0.13 0.09 0.05 0.02 0.02 0.01 0.02

3.6.2.5 Particle Density

ISCST3 also needs particle density in order to model the air concentration and deposition rates of

particles. We recommend determining site-specific measured data on particle density for all modeled

sources when possible. For new or undefined sources requiring air modeling, we recommend using a

default particle density of 1.0 g/cm3

. Particles from combustion sources, however, may have densities

that are less than 1.0 g/cm3

 (U.S. EPA 1994d), which would reduce the modeled deposition flux.
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Following is an example of the particle density portion of the SOurce pathway (SO PARTDENS) for the

9 mean particle size diameters of the previous example:

SO PARTDENS STACK1 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0

3.6.2.6 Scavenging Coefficients

ISCST3 calculates wet deposition flux by multiplying a scavenging ratio times the vertically integrated

concentration. The scavenging ratio is the product of a scavenging coefficient and a precipitation rate. 

Studies show that best fit values for the scavenging coefficients vary with particle size. For vapors, wet

scavenging depends on the properties of the COPCs involved. However, not enough data are now

available to adequately develop COPC-specific scavenging coefficients. Therefore, assume that vapors

are scavenged at the rate of the smallest particles, with behavior in the atmosphere that is influenced

more by the molecular processes that affect vapors than by the physical processes that may dominate the

behavior of larger particles (U.S. EPA 1995f).

Wet deposition only occurs during precipitation. To use the wet deposition option in ISCST3, input

scavenging coefficients for each particle size and a file that has hourly precipitation data. For wet

deposition of vapors, we suggest using a scavenging coefficient for a 0.1-μm particle, to simulate wet

scavenging of very small (molecular) particles. ISCST3 will also accept site-specific measured washout

data, or a value calculated based on Henry’s Law constant. If you choose an option other than the

coefficient for a 0.1-μm particle, we recommend clearly identifying and discussing it with the appropriate

parties (e.g. permitting authority, or facility) prior to analysis. You can establish scavenging coefficients

for each particle size from the best fit of the curves presented in the ISC3 User’s Guide (U.S. EPA

1995f). The curves are based on the work of Jindal and Heinhold (1991). The curves are limited to a

maximum particle size of 10-μm. Assume that all scavenging coefficients for particle sizes greater than

or equal to 10-μm are equal. This assumption follows research on wet scavenging of particles (Jindal

and Heinhold 1991).

The ISCST3 model differentiates between frozen and liquid scavenging coefficients. Research on sulfate

and nitrate data shows that frozen precipitation scavenging coefficients are about one-third of the values

of liquid precipitation (Scire et al. 1990; Witby 1978). It is protective to assume that the frozen

scavenging coefficients are equal to the liquid scavenging coefficients (Pei and Cramer 1986). If desired,

you may input separate scavenging coefficients for frozen precipitation. 
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The following is an example of the particle liquid (rain) and frozen (sleet or snow) scavenging

coefficients input in the SOurce pathway for 9 mean particle size diameters, assuming particles are

scavenged by frozen precipitation at 1/3 the rate of liquid precipitation:

SO PARTSLIQ STACK1 7E-5 5E-5 6E-5 1.3E-4 2.6E-4 3.9E-4 5.2E-4 6.7E-4 6.7E-4 

SO PARTSICE STACK1 2E-5 2E-5 2E-5 4E-5 9E-5 1.3E-4 1.7E-4 2.2E-4 2.2E-4 

The complete SOurce pathway for the example particle phase input file is as follows:

SO STARTING

SO LOCATION STACK1 POINT 637524. 4567789. 347.

SO SRCPARAM STACK1 1.0 23.0 447.0 14.7 1.9

SO BUILDHGT STACK1 18.29 18.29 18.29 18.29 18.29 18.29 18.29 18.29

SO BUILDHGT STACK1 18.29 18.29 18.29 18.29 18.29 18.29 18.29 18.29

SO BUILDHGT STACK1 18.29 18.29 18.29 18.29 18.29 18.29 18.29 18.29

SO BUILDHGT STACK1 18.29 18.29 18.29 18.29 18.29 18.29 18.29 18.29

SO BUILDHGT STACK1 18.29 18.29 18.29 18.29

SO BUILDWID STACK1 14.02 15.51 16.53 17.05 17.05 16.53 15.51 14.03

SO BUILDWID STACK1 12.10 14.02 15.51 16.53 17.05 17.05 16.53 15.51

SO BUILDWID STACK1 14.02 12.10 14.02 15.51 16.53 17.05 17.05 16.53

SO BUILDWID STACK1 15.51 14.02 12.10 14.02 15.51 16.53 17.05 17.05

SO BUILDWID STACK1 16.53 15.51 14.02 12.10

SO PARTDIAM STACK1 0.35 0.70 1.10 2.00 3.60 5.50 8.10 12.5 15.0

SO MASSFRAX STACK1 0.22 0.08 0.08 0.11 0.10 0.07 0.10 0.11 0.13

SO PARTDENS STACK1 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 

SO PARTSLIQ STACK1 7E-5 5E-5 6E-5 1.3E-4 2.6E-4 3.9E-4 5.2E-4 6.7E-4 6.7E-4 

SO PARTSICE STACK1 2E-5 2E-5 2E-5 4E-5 9E-5 1.3E-4 1.7E-4 2.2E-4 2.2E-4 

SO SRCGROUP ALL

SO FINISHED

When modeling air vapors using ISCST3, the following is an example of the SOurce pathway input for

wet vapor scavenging coefficients that replaces the PARTDIAM, MASSFRAX, PARTDENS,

PARTSLIQ and PARTSICE lines in the above example:

SO GAS-SCAV STACK1 LIQ 1.7E-4

SO GAS-SCAV STACK1 ICE 0.6E-4

3.6.3 REceptor Pathway

The REceptor pathway identifies sets or arrays of receptor grid nodes (identified by UTM coordinates)

for which ISCST3 generates estimates of air parameters including: 

• air concentration, 

• dry and wet deposition, and 

• total deposition. 
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Previous U.S. EPA guidance (1994l) recommended using a polar receptor grid to identify maximum

values. Polar grids provide coverage over large areas with fewer receptor grid nodes than other grid

types, thereby reducing computer run times. However, U.S. EPA Region 6 experience indicates that,

although polar grids may reduce computer run times, air modelers typically choose a different option. 

The benefit of reduced run time is offset by difficulties in identifying polar grid locations in absolute

UTM coordinates for (1) extracting terrain values from digital terrain files, and (2) selecting exposure

scenario locations (see Chapter 4). Using a Cartesian grid is an alternative to a polar grid.

One method of obtaining a Cartesian grid with terrain elevations is to open both the grid array and the

USGS DEM file in a graphics program (e.g., SURFER®). The software samples the DEM file at the

user-specified locations (i.e. the grid nodes), each defined as the intersection of east (x) and north (y)

values. The software extracts terrain elevation (z) from the DEM file associated with the desired

location. These x, y, and z values are saved as a text file with one receptor grid node per line. Use a text

editor to prefix each line with “RE DISCCART,” to specify a discrete receptor grid node in ISCST3

format. Commercial software is available that generates the recommended receptor grid node array and

extracts terrain elevations from the USGS DEM downloaded files, or any terrain file in x-y-z format.

The following is an example of the REceptor pathway for discrete receptor grid nodes at 500-meter

spacing that includes terrain elevations (in meters):

RE STARTING

RE ELEVUNIT METERS

RE DISCCART 630000. 3565000. 352.

RE DISCCART 630500. 3565000. 365.

RE DISCCART 631000. 3565000. 402.

9

RE DISCCART 635000. 3570000. 387.

RE FINISHED

We recommend that air modeling for each risk assessment include, at a minimum, an array of receptor

grid nodes covering the area within 10 kilometers of the facility. Locate the origin of the grid at the

centroid of a polygon formed by the locations of the stack emission sources. This receptor grid node

array may consist of a Cartesian grid with grid nodes spaced 100 meters apart extending from the

centroid out to 3 kilometers. For the distances from 3 kilometers out to 10 kilometers, the receptor grid

node spacing can be increased to 500 meters. The single grid node array contains both grid node
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• Summary of all information regarding the coordinates and placement of the receptor grid node

array used in air modeling

• Copies of any maps, figures, or aerial photographs used to develop the receptor grid node

array

• Map presenting UTM locations of receptor grid nodes, along with other facility information. 

RECOMMENDED INFORMATION FOR RISK ASSESSMENT REPORT

spacings. Include the same receptor grid node array in the REceptor pathway for all ISCST3 runs for all

years of meteorological data and for all emission sources. 

We recommend specifying individual terrain elevations for all receptor grid nodes. Several methods are

available for assigning terrain elevations to grid nodes using digital terrain data. The 1:250,000 scale

DEM digital data are available for download at the USGS Internet site

(http://edc.usgs.gov/guides/dem.html). This data has horizontal spacing between digital terrain values of

approximately 90 meters, which provides sufficient accuracy for air modeling.

During the risk assessment, select air parameter (concentration and deposition) values for a single

receptor grid node to evaluate a specific exposure scenario location. You can also compute an area

average of air parameter values across multiple receptor grid nodes, to represent the average

concentration or deposition over a watershed or water body (see Chapter 4). However, depending on

site-specific considerations, a different receptor grid node array may be more appropriate.

In addition to the receptor grid node array evaluated out to 10 kilometers, you might consider additional

grid node arrays for evaluating water bodies and their watersheds located beyond 10 kilometers. We

recommend a grid node spacing of 500 meters between nodes for arrays that are more than 10 kilometers

from the emission source. An equally spaced grid node array facilitates subsequent computation of area

averages for deposition rates onto waterbodies and their associated watersheds.
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3.6.4 MEteorological Pathway

The file containing meteorological data is specified in the MEteorological pathway. MPRM creates

individual files for each of the 5 years as ASCII files. ISCST3 uses them to compute hourly

concentrations and deposition rates. You can either specify a single year of meteorological data in each

ISCST3 run, or combine the total period of meteorological data into a single meteorological file, which

ISCST3 will process in a single 5-year run. When combining meteorological files, we caution you to

consider the following:

• Preprocess each year separately using MPRM into an ASCII format

• Combine the years into a single file (using a text editor or DOS COPY command)

• ISCST3 compares the first line (header) of the combined file to the Surface and Upper

Air Station ID numbers specified in the input file ME pathway

• ISCST3 reads the headers of subsequent years unless they’re deleted in the combined

file. If subsequent year headers are included in the combined file, ISCST3 will compare

the station IDs to the input file station ID. 

Your analysis might use meteorological data from more than one surface station or upper

air station (e.g., the upper air station is moved after the third year of the period and

assigned a new station ID by the National Weather Service). If this is the case, delete the

headers for subsequent years in the combined file.

• For sites where the anemometer height is changed during the 5 year period (e.g., during

the period 1984-1988, the anemometer was relocated on December 15, 1985, changing

the height from 20 feet to 10 meters), we recommend running each year separately. Use

the anemometer height in the ISCST3 input file ME pathway which corresponds to that

year’s meteorological data.

We recommend completing each year in the file with a full year of data (365 days, or 366 days for leap

years). Verify the anemometer height for the surface station from Local Climate Data Summary records,

or other sources, such as the state climatologist office. We recommend identifying the correct

anemometer height ANEMHGHT for the wind speed measurements at the surface station before air

modeling. Details of specifying the meteorological data file are in the ISC3 User’s Guide, Section

3.5.1.1. 
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The following is an example input section for the MEteorological pathway, using the 1984 Baton Rouge

file, with an anemometer height of 10 meters and station identification numbers:

ME STARTING

ME INPUTFIL 84BR.WET

ME ANEMHGHT 10.0

ME SURFDATA 13970 1984 BATON_ROUGE

ME UAIRDATA 12884 1984 BOOTHVILLE

ME FINISHED

3.6.5 Terrain Grid (TG) Pathway

Computing dry plume depletion is sensitive to terrain elevation. In the absence of a terrain grid file,

ISCST3 automatically assumes that the terrain slope between the stack base and the receptor grid node

elevation is linear. In concept, this assumption may underestimate plume deposition. However, based on

experience, the magnitude of the differences in computed concentrations and deposition rates is nominal.

Since including a terrain grid file in the TG pathway significantly increases model execution time, we

suggest that a terrain grid file may not be necessary for all sites. If a terrain grid file is desired for a

specific site based on highly variable terrain over short distances, the format of the TG file is available in

the ISC3 User's Guide. 

The location keyword of the TG pathway (TG LOCATION) identifies the x and y values to be added to the

source and receptor grid to align with the terrain file coordinates. If the source and receptor grid nodes

are in relative units such that the source is at location 0,0, the location keywords in the TG pathway

would be the UTM coordinates of the source. We recommend specifying all emission sources and

receptor grid nodes in UTM coordinates (note NAD27 or NAD83 format), and that the TG file, if used,

be in UTM coordinates. Therefore, the location of the origin of the TG file relative to the source location

will be 0,0. Also, we recommend presenting the terrain elevations in the TG file in meters. Following is

an example of the TG pathway:

TG STARTING

TG INPUTFIL TERRAIN.TER

TG LOCATION 0.0 0.0

TG ELEVUNIT METERS

TG FINISHED
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3.6.6 OUtput Pathway

ISCST3 output comes in two basic file types: the mandatory “output summary file” type (mandatory

because ISCST3 automatically creates the file), and numerous optional file formats. As part of its input

file structure, ISCST3 requires the name of the output summary file (See Section 3.8.2). Using text and

tables, this file summarizes the ISCST3 run results, including repeating back all input data (e.g., sources

with parameters, control pathways, grid node list, model options selected), and results summaries for

each annual and 1-hour averaging period. It also states if the run finished successfully. The summary

file also alerts you to special meteorological conditions that were found during runtime (e.g. number of

calm hours, and relationships between source base elevation and grid node elevations). It provides

impacts for the highest grid node values, not the results at every grid node required to perform the

methods found in the remainder of the HHRAP. We recommend using the output summary file for

quality checking, to make sure the run executed successfully and correctly. 

ISCST3 provides numerous optional output file formats in addition to the results in the output summary

file, as specified in receptor tables (RECTABLE). The “plot files” format is the most useful option for

facilitating post-processing of the air parameter values in the model output. For this reason, though “plot

files” are optional in executing ISCST3, they are necessary for HHRAP methods. There are two plot

files for each ISCST3 run on a single source – the ‘annual’ and ‘1-hour’ plot files. The 'annual' plot file

contains all air modeling results at each grid node, for the annual average of five years of met data. The

'1-hour' plot file contains the air modeling results at each grid node for the 'highest 1-hour' impact for all

five years. The file presents data in tabular form, with impacts at every grid node.

The plot file lists the x and y coordinates, and the concentration or deposition rate values for each

averaging period. Data are listed in a format that can easily be pulled into a post-processing program

(e.g. spreadsheet). Note that the ISCST3-generated plot file is not the same format as the ISCST3-

generated post file. We recommend using the plot file, not the post file.

Following is an example OUtput file specification for single-year run of 1-hour and annual average plot

files:

OU STARTING

OU RECTABLE ALLAVE FIRST

OU PLOTFILE 1 ALL FIRST BTR841.PLT

OU PLOTFILE ANNUAL ALL BTR84A.PLT

OU FINISHED
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The second line directs ISCST3 to create a table of values for each receptor grid node for all averaging

periods in the model run (1-hour and annual). The third line directs ISCST3 to create a separate plot file

(named BTTR841.PLT) of the 1-hour average results for all emission sources in the run using the first

highest (e.g., maximum) value for all hours of results during the year for each receptor grid node. The

fourth line directs ISCST3 to create another separate plot file (named BTR84A.PLT) of the annual

average results for all sources in the run for each receptor grid node.

3.7 ISCST3 MODEL EXECUTION

Consider model execution time needs for each analysis. A complete air modeling run—including air

concentration, wet and dry deposition, and plume depletion—may require 10 times the run time for the

same source and receptor grid nodes for air concentration only. You can avoid wasted modeling effort

and analysis time by verifying input parameters and conducting test runs prior to executing ISCST3.

Long run times result mainly from two algorithms—plume depletion and terrain grid file. ISCST3 run

times increase as much as tenfold for runs applying plume depletion. We believe that constituent mass is

conserved between suspended concentration and deposition rate by allowing for depletion of deposited

mass from the plume concentration in ISCST3. The overestimate of plume concentration, and the

subsequent overestimate of deposition which results when plume depletion is not allowed, is too

protective. At the same time, we don’t believe the nominal benefits of including a terrain grid file justify

the added run times. Therefore, we recommend that plume depletion always be included. We don’t

recommend terrain grid files.

3.8 USING MODEL OUTPUT

ISCST3 output (air concentrations and deposition rates) are usually provided on a unit emission rate

(1.0 g/s) basis from the combustor or emission source, and aren’t COPC-specific. This is to preclude

having to run the model for each individual COPC. Use the COPC-specific emission rates from the trial

burn (see Chapter 2) to adjust the unitized concentration and deposition output from ISCST3. The 

resulting COPC-specific air concentrations and deposition rates will be used in the estimating media

concentration equations (see Chapter 5). Concentration and deposition are directly proportional to the

unit emission rate used in the ISCST3 modeling. However, there might be some instances where the risk
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assessor will need to convert modeled output to COPC-specific output for the risk assessment. For

example, the risk assessor may want to compare modeled COPC concentrations in ambient media to

concentrations actually measured in the field.

For facilities with multiple stacks or other emission sources, we recommend that each source be modeled

separately. This is because modeling multiple sources at one time results in an inability to estimate

source-specific risks. This limits the ability of a permitting agency to evaluate which source is

responsible for the resulting risks. Such ambiguity makes it impossible for the agency to specify

protective, combustion unit-specific permit limits. If a facility has two or more sources with identical

characteristics (emissions, stack parameters, and nearby locations), it may be appropriate to model them

with a single set of runs. We recommend getting the approval of the permitting authority prior to such

multi-source modeling.

TABLE 3-10

ISCST3 AIR PARAMETER OUTPUT

Air Parameter Description Units

(Used for most soil-based exposure pathways)

Cyv Unitized yearly average air concentration from vapor phase μg-s/g-m3

Cyp Unitized yearly average air concentration from particle phase μg-s/g-m3

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

(Used for fish and drinking water ingestion exposure pathways)

Cywv Unitized yearly (water body or watershed) average air concentration

from vapor phase

μg-s/g-m3

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

(Used for evaluation of acute risk via direct inhalation exposure pathway)

Chv Unitized hourly air concentration from vapor phase μg-s/g-m3

Chp Unitized hourly air concentration from particle phase μg-s/g-m3

Chpb Unitized hourly air concentration from particle-bound phase μg-s/g-m3
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Equation 3-2

Equation 3-3

3.8.1 Unit Rate Output vs. COPC-Specific Output

The relationship between the unit emission rate and the unit air parameter values (air concentrations and

deposition rates) is linear. Similarly, the relationship between the COPC-specific emission rate (Q) and

the COPC-specific air parameter values (air concentrations and deposition rates) is also linear if the

COPC-specific emission rate is used in the air model. 

In this Section we discuss using the unit emission rate. We also advance the rationale that you should

use a unit emission rate instead of the COPC-specific emission rate. Using a unit emission rate

precludes having to run ISCST3 separately for each individual COPC. We advocate using a unit

emission rate in the air modeling because you can develop a common ratio relationship between the unit

emission rate and the COPC-specific emission rate. The ratio is based on the fact that both individual

relationships are linear in the air model. This ratio relationship is expressed by the following equation:

To use this equation, you must know three of the variables. ISCST3 provides the modeled output air

concentration (or deposition rate). The unit emission is 1.0 g/s. You can get the COPC-specific emission

rate directly from stack or source test data.

3.8.1.1 Determining the COPC-Specific Emission Rate (Q)

The COPC-specific emission rate from the stack, prior to any applicable adjustments (e.g., upset

emissions scaling, revisions based on hours of operation, feed rate adjustments, etc.) is a function of the

stack gas flow rate and the stack gas concentration of each COPC. It can be calculated from the

following equation:

where

Q = COPC-specific emission rate (g/s)

SGF = Stack gas flow rate at dry standard conditions (dscm/s)
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Equation 3-4

SGC = COPC stack gas concentration at 7 percent O2 as measured in the trial burn

(:g/dscm)

CFO2 = Correction factor for conversion to actual stack gas concentration O2

 (unitless)

1 x 106 = Unit conversion factor (:g/g)

Guidance for adjusting COPC-specific emission rates, as well as determining emission rates for fugitive

emission sources, is available in Chapter 2. Also, it is sometimes necessary to derive the COPC-specific

emission rate from surrogate data, such as for a new facility that has not yet been constructed and trial

burned (see Chapter 2).

3.8.1.2 Converting Unit Output to COPC-Specific Output

Once three of the four variables in Equation 3-1 are known, you can derive the COPC-specific air

concentrations and deposition rates by multiplying as follows:

For example, if COPC A is emitted at a rate of 0.25 g/s, and the ISCST3 modeled concentration at a

specific receptor grid node is 0.2 μg/m3 per the 1.0 g/s unit emission rate, the concentration of COPC A

at that receptor grid node is 0.05 μg/m3 (0.25 multiplied by 0.2). Calculating deposition is similarly

proportional to the emission rate of each COPC. You are reminded once again that the process of

converting modeled unitized output into COPC-specific output is taken directly into account in the

estimating media concentration equations in Chapter 5 and Appendix E. 

3.8.2 ISCST3 Model Output

It is important that the risk assessor understand how to read the ISCST3 output structure, in order to

ensure accurate use of modeled output in the risk assessment. The output from each ISCST3 model run

is written to two separate file formats. The ‘output summary file’ is specified by name at run time in the

execution command. Typical command line nomenclature is:

ISCST3 inputfile.INP outputfile.OUT
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where

ISCST3: specifies executing the ISCST3 model

inputfile.INP: is the input file name you (the modeler) select

outputfile.OUT: is the output summary file name you select, typically the same as the

input file name (but with a different suffix)

For example, the following ISCST3 input line would run the input file (PART84R.INP) created by the

modeler for particulate emissions using 1984 meteorological data on the receptor grid. ISCST3 will

automatically write the output summary file (PART84R.OUT) during execution.

ISCST3 PART84R.INP PART84R.OUT

You specify the second file format, the output ‘plot file,’ in the ISCST3 input file OUtput pathway. 

ISCST3 creates it during the run (see Section 3.6.6). The “plot file” is typically then imported into a

post-processing program (e.g. a spreadsheet) before entry into the risk assessment computations.

Vapor phase and Particle-bound phase runs produce similar plot files. The plot files for the vapor phase

runs will include average concentrations and wet deposition rates. The plot files for the particle and

particle-bound phase runs will include average concentrations, dry depositions, wet depositions and total

depositions. You can average the 1-year values at each receptor grid node for a 5-year value at each

node, unless a single five-year ISCST3 run using a combined meteorological file is used. If you use the

5-year combined file, the risk assessor can use the results from the ISCST3 plot file directly in the risk

assessment without averaging over the five years. All values are used in the estimating media

concentration equations (see Chapter 5).

3.8.3 Using Model Output to Estimate Media Concentrations

Section 3.2 discussed how partitioning of the COPCs affects the development of ISCST3 modeling runs.

The choices of which modeled air parameter values (air concentrations and deposition rates) to use in the

estimating media concentration equations is based on this same partitioning theory.

3.8.3.1 Vapor Phase COPCs

ISCST3 generates the following output for vapor phase air modeling runs:
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2

These two PAHs have vapor phase fractions, Fv, less than five percent. 

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• vapor phase air concentrations (unitized Cyv and unitized Cywv), 

• dry vapor deposition (unitized Dydv), and 

• wet vapor depositions (unitized Dywv and unitized Dywwv) 

for organic COPCs at receptor grid nodes based on the unit emission rate. These values are used in the

estimating media concentration equations for all COPC organics except the polycyclic aromatic

hydrocarbons (PAHs) dibenzo(a,h)anthracene and indeno(1,2,3-cd)pyrene2. The air concentration

(unitized Cyv), dry vapor deposition (unitized Dydv), and wet vapor deposition (unitized Dywv) from the

vapor phase run is also used in the estimating media concentration equations for mercury. You select

values for these COPCs from the vapor phase run because the mass of the COPC emitted by the

combustor is assumed to have either all or a portion of its mass in the vapor phase (see Appendix A-3).

3.8.3.2 Particle Phase COPCs

ISCST3 generates the following output for particle phase air modeling runs:

• air concentration (unitized Cyp), 

• dry deposition (unitized Dydp), 

• wet deposition (unitized Dywp), and 

• combined deposition (unitized Dytwp) 

for inorganics and relatively non-volatile organic COPCs at receptor grid nodes based on the unit

emission rate. These values are used in the estimating media concentration equations for all COPC

inorganics (except mercury, see Chapter 2 and Appendix A-3) and polycyclic aromatic hydrocarbons

with fraction of vapor phase, Fv , less than 0.05 (e.g., dibenzo(a,h)anthracene and

indeno(1,2,3-cd)pyrene). You choose values for inorganic and relatively non-volatile COPCs from the

particle phase run because the all the mass of the COPC is assumed to be in the particulate phase (see

Appendix A-3). The mass is apportioned across the particle size distribution based on mass weighting.
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3.8.3.3 Particle-Bound COPCs

ISCST3 particle-bound runs generate the following output:

• air concentration (unitized Cyp), 

• dry deposition (unitized Dydp), 

• wet deposition (unitized Dywp), and 

• combined deposition (unitized Dytwp) 

for organic COPCs and mercury (see Chapter 2 and Appendix A-3) at each receptor grid node. Use these

values in the “estimating media concentration” equations to account for the portion of the vapor

condensed onto particulate surfaces. Select values for these COPCs from the particle-bound run because

the mass of the COPC emitted by the combustor is assumed to have a portion of its mass condensed on

particulates (see Appendix A-3). ISCST3 uses surface area weighting to apportion the particle-bound

mass across the particle size distribution.

3.9 MODELING FUGITIVE EMISSIONS

The procedures presented in this chapter for modeling stack source emissions are also effective for

modeling fugitive source emissions, as defined in Chapter 2. However, you can represent fugitive

emissions in the ISCST3 input file SOurce pathway as either “area” or “volume” source types. Model

fugitive emissions of volatile organics only in the vapor phase. Model fugitive emissions of ash only in

the particle and particle-bound phases, not vapor phase.

As discussed in Chapter 2, fugitive emissions of volatile organic vapors are associated with combustors

that include storage vessels, pipes, valves, seals and flanges. Enter the horizontal area of the fugitive

source into the ISCST3 input file according to the instructions found in the ISC3 User’s Guide, Volume I

(U.S. EPA 1995f). You can get the horizontal area from the facility plot plan. The height of the fugitive

source is defined as the top of the vertical extent of the equipment. If the vertical extent isn’t known, you

can use a default height of ground level (release height of zero). This provides a protective estimate of

potential impacts. The ISCST3 model run time is faster for volume source types than for area source

types. We generally recommend considering the volume source type for most applications. We
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B1

F1 B2

F2

Plot Plan ISC3 Volume F1A F1B F1C

F1D

recommend following the methods in the ISCST3 User’s Guide to define the input parameters

representing the fugitive source. 

The following example is for organic fugitive emissions only (modeling only vapor phase emissions)

modeled as a volume source type. The example includes a facility with two stack emission sources (B1,

B2) and two fugitive emission sources (areas F1, F2). A total of four runs for each year (or 5-year

combined file) of meteorological data is needed. 

Perform one run for each of the two stacks as point sources. Perform one run for each of the two fugitive

areas as volume sources (Note: or you could model as area sources). Since the emissions are fugitive

volatile organics, model only the vapor phase. The vertical extent of the pipes, valves, tanks and flanges

associated with each fugitive emission area is 15 feet (about 5 meters) above plant elevation. To define

the sources for input to ISCST3, specify the release height as 2.5 meters (1⁄2 of vertical extent of fugitive

emissions). Specify the initial vertical dimension as 1.16 meters (vertical extent of 5 meters divided by

4.3, as described in the ISC3 User’s Guide). 

The initial horizontal dimension is the side length of the square fugitive area (footprint) divided by 4.3. If

fugitive area F2 has a measured side of 30 meters, the initial horizontal dimension is 6.98 (30 meters

divided by 4.3). For fugitive area F1, subdivide the area on the plot plan (ISC3 Volume) to create square

areas for input to ISCST3. The four areas depicted represent subdivision into square areas. Fugitive

source F1 is input into a single ISCST3 run as four separate volume sources (F1A, F1B, F1C, F1D). The

initial horizontal dimension for each volume source is the side of the square divided by 4.3.

It is very important to allocate the unit emission rate (1.0 gram per second) proportionately among the

subdivided areas. For example, if the areas of the subdivided squares in the ISC3 Volume figure results

in F1A equal to F1B each with 1/8th the total area, the proportion of the unit emissions allocated to each 
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of these volume sources is 0.125 grams per second. The remaining two areas are each 3/8ths of the total

area of fugitive F1, so that 0.375 grams per second is specified for the emission rate from each source. 

The total emissions for the four volume sources sum to the unit emission rate for the F1 fugitive source

(0.125 + 0.125 + 0.375 + 0.375 = 1.0 g/s). 

If you tell ISCST3 to include all sources in the model results (SO SRCGROUP ALL), the model will

appropriately combine all four volume source subdivisions into combined impact results for fugitive

source F1. You can use the resulting air parameter values in the plot files directly in the risk assessment

equations, the same as if the emissions were modeled as a single point source. The initial vertical

dimension is defined the same as F2, using the vertical extent of 5 meters divided by 4.3 and a release

height of 2.5 meters (1⁄2 vertical extent). For volume sources, the location is specified by the x and y

coordinates of the center of each square area.

The COntrol parameters can follow the recommendations for setting up a vapor phase computation.

CO CONC WDEP

Fugitive emissions of ash particles are from the storage piles associated with combustion units. Enter the

horizontal area of the storage pile into the ISCST3 input file according to the ISCST3 User’s Guide,

Volume I (U.S. EPA 1995f). The height of emissions is the top of the pile. If you don’t know the

vertical extent, you could use ground level (or zero height). You’ll typically model fugitive ash as area

source type. However, the permitting authority might consider volume source type prior to air modeling. 

We generally recommend following the methods in the ISCST3 User’s Guide when defining the input

parameters to represent the ash release as an area source. 

We recommend the COntrol parameters follow the recommendations for setting up a particulate phase

computation.

CO CONC DDEP WDEP DEPOS

We recommend documenting the emissions characterization and source type.
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3.10 MODELING ACUTE RISK

It might be important for you to evaluate the acute, or short-term, effects due to the direct inhalation of

vapor phase, particle phase and particle-bound phase COPCs in the risk assessment. We recommend

considering site- or unit-specific factors such as unit operating conditions during emissions testing,

emission rates to be used in the acute screen, exposure scenario locations, etc. (see Sections 2.2.1, 4.2,

4.3, and 7.5) prior to conducting air modeling for an acute evaluation.

Since only ambient air concentrations are included in the direct inhalation pathway, You can compute the

air parameters needed for a screening acute assessment in the same ISCST3 runs (i.e., same input values

for meteorological data, stack gas exit temperature and velocity, etc.) that compute the air parameters for

the long-term chronic effects. However, as with chronic modeling, a non-steady state dispersion model

(e.g., CALPUFF) might provide a more representative estimate of concentration and deposition. This is

because of differences in methodology for modeling time-varying emissions and time- and space-varying

meteorological fields. 

Methods outlined in this section focus on supporting a screening type acute assessment using the existing

air modeling runs executed for the chronic risk assessment. However, it is important to note that while

this approach provides some obvious efficiencies with regard to air modeling, you might need to execute

separate air modeling runs. For example, you might consider site- or unit-specific characteristics

(i.e., conditions of most concern for a short term or acute release scenario) in order to provide the most

protective or appropriate acute assessment. As discussed in Section 3.1, site-specific conditions and

assessment objectives might result in your choosing a different air model for the acute portion than for

the chronic assessment.

In air modeling for an acute type assessment, the goal is typically to compute the highest 1-hour average

air concentration for each phase (particle-bound, etc) for each source, for the entire period of analysis. In

most cases, this period is the five years of meteorological data. For ISCST3 to identify the highest

one-hour average concentration at each grid node, we recommend making two specifications in the

ISCST3 input files.
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First, you must specify the 1-hour average as one of the averaging times in the COntrol pathway. The

example of this specification is included in Section 3.6.1. The ISCST3 input file includes:

CO AVERTIME 1 ANNUAL

where “1" specifies the 1-hour averaging time ISCST3 computes for each hour of meteorological data. 

Remember that the ‘ANNUAL’ is specified for the chronic effects.

Second, we recommend that the OUtput pathway include the specification of a 1-hour average plot file

which contains the highest 1-hour concentration at each receptor grid node for all the hours evaluated in

the ISCST3 run. For a single year run, the 1-hour concentration reported in the plot file is the highest

value computed at each x, y grid node location for the total hours in the year (8760, or 8784 for leap

years). The acute risk assessment needs the highest 1-hour concentration for the 5-year period. We

recommend reviewing each of the five single year values to identify the highest for all five years at each

receptor grid node. However, if you run a combined 5-year meteorological input file, the resulting plot

file will already identify the highest value for the 5-year period at each grid node with no additional

processing needed. The OUtput pathway instructions to create the plot file for one-hour average

concentrations are:

OU PLOTFILE 1 ALL FIRST BTR841.PLT

where 

1: specifies the 1-hour averaging period, 

ALL: instructs ISCST3 to include all sources in the run, 

FIRST: instructs the model to include only the first highest value at each

receptor grid node, and 

BTR841.PLT: is the name for the plot file. 

The plot file name is unique for the run and the one-hour averaging period results.

The highest air concentration for the 1-hour averaging period is input as the air parameters, Chv, Chp,

and Chpb in the acute risk assessment equations (see Section 7.5 and Appendix B, Table B-6-1).
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Chapter 4

Exposure Scenario Identification

What’s Covered in Chapter 4:

4.1 Characterizing the Exposure Setting

4.2 Recommended Exposure Scenarios

- Farmer

- Farmer Child

- Resident

- Resident Child

- Fisher

- Fisher Child

- Acute Receptor

4.3 Selecting Exposure Scenario Locations

PLEASE NOTE: for the purposes of this guidance, “we” refers to the U.S. EPA OSW. 

The HHRAP is written for the benefit of a varied audience, including risk assessors,

regulators, risk managers, and community relations personnel. However, the “you” to

which we speak in this chapter is the performer of a risk assessment: the person (or

persons) who will actually put the recommended methods into practice.

The purpose of this chapter is to provide guidance on identifying “exposure scenarios” to evaluate in the

risk assessment. Evaluating exposure scenarios will estimate the type and magnitude of human exposure

to COPC emissions from hazardous waste combustors (including fugitive emissions). In this document,

identifying exposure scenarios consists of :

• characterizing the exposure setting, 

• identifying recommended exposure scenarios, and 

• selecting exposure scenario locations.

Characterizing the exposure setting includes defining the dimensions of the assessment area (or “study

area”). It also includes identifying the current and potential human activities and land uses within those

boundaries. Within the context of the exposure setting, an exposure scenario is a combination of

“exposure pathways” to which a “receptor” may be subjected. 
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For this guidance, we define a receptor as a human being potentially exposed to COPCs emitted to the

atmosphere from a hazardous waste combustion facility. An exposure “route” is the particular means of

entry into the body. For the purposes of the HHRAP, receptors come into contact with COPCs via two

primary exposure routes: either directly—via inhalation; or indirectly—via COPC deposition and

subsequent ingestion of water, soil, vegetation, and animals that have been contaminated by COPCs

through the food chain.

An exposure “pathway” is the course a chemical takes from its source to the person being exposed. An

exposure pathway consists of four fundamental components:

1. a source and mechanism of COPC release (see Chapter 2); 

2. a retention medium, or a transport mechanism and subsequent retention medium in cases

involving media transfer of COPCs (see Chapter 3 for air transport of COPCs, and

Chapter 5 for bioaccumulation of COPCs in the food chain); 

3. a point of potential human contact with the contaminated medium; and 

4. an exposure route. 

Exposure to COPCs can occur via numerous exposure pathways, such as ingestion of diary products and

home grown produce (see Section 4.2).

The HHRAP identifies a number of generic exposure scenarios (Farmer, Farmer Child; Fisher, Fisher

Child; Resident, and Resident Child). Used as presented, these standardized scenarios should be

reproducible across most sites and land use areas. We intend these scenarios to be appropriate for a

broad range of situations, rather than to represent actual scenarios. We believe that the recommended

exposure scenarios and associated assumptions are reasonable. They represent a scientifically sound

approach that is protective of human health and the environment, while recognizing the uncertainties

associated with evaluating real world exposures. For example, the scenarios are designed with a level of

protectiveness intended to address potential receptors not directly evaluated, such as populations with

somewhat higher exposures than the general public. At the same time, you can easily alter these

scenarios to more closely reflect site-specific conditions. To be transparent, we recommend welldocumenting, supporting and discussing any changes (i.e. deletions, additions, or modifications) to a

recommended exposure scenario or scenario location with the appropriate parties (regulatory agency,

facility, interested community members).
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Selecting exposure scenario locations involves identifying the physical positions of the exposure

scenarios within the study area. For example, you can position scenarios based on current or future

human activities or land use. Alternatively, you can position scenarios artificially, as part of a screening

assessment. You could, for example, locate all selected receptors at the area of greatest contaminant

deposition, to maximize potential exposure. The HHRAP focuses on placement based on actual or

potential activities and land use.

The following sections describe how we recommend 

1. characterizing the exposure setting, 

2. identifying which of the recommended exposure scenarios are appropriate for the risk

assessment, and 

3. selecting the exposure scenario locations.

4.1 CHARACTERIZING THE EXPOSURE SETTING

The purpose of characterizing the exposure setting is to identify the human receptors, their land uses and

activities, which might be impacted by exposure to emissions from the facility being assessed. The

exposure setting might include multiple sources (e.g., multiple stacks, fugitive emissions), as well as

terrain both inside and outside the facility boundary (or “fenceline”). We believe both current and

reasonable potential human activities or land uses are relevant, when determining which recommended

exposure scenarios are appropriate for the risk assessment (see Section 4.2).

Experience has shown us that most significant deposition occurs within a 10 km radius, as measured 

from the centroid of a polygon centered on the stacks of the facility being assessed. Consequently,

resources for characterizing the exposure setting might initially be focused within this area. Also, most

recommended exposure scenarios appropriate for the assessment will likely be located within this area.

It may be prudent, however, to also characterize the exposure setting beyond the 10 km radius, to

determine if conditions exist which warrant additional exposure scenarios. Such conditions might

include (but are not limited to) recommended exposure scenarios or special populations (see Section

4.1.3) not found within the 10 km area, or topographic features - such as hills - that tend to increase

potential deposition. A 50 km radius is the recognized limit of the ISCST3 air dispersion model, and can

be used as the outer boundary for characterizing additional exposure settings (See Chapter 3 for
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information on air modeling beyond a 50 km radius). All affected parties (i.e. regulators, facilities,

interested community members) can then discuss if additional scenarios need to be assessed, and if so,

their locations.

The study area might include land use and water bodies both inside and outside the facility fenceline. 

It’s important to understand that some of the recommended scenarios might most appropriately be placed

within facility boundaries. For example, some facilities located on substantial property rent portions of

the property to the public for farming, ranching, or recreational purposes (e.g., fishing). 

When characterizing the exposure setting, we highly recommend considering

• current and reasonable potential future land use, 

• waterbodies and their associated watersheds, and 

• special populations. 

The following subsections provide information on these aspects. 

4.1.1 Current and Reasonable Potential Future Land Use

Land use is an important factor in characterizing the exposure setting. When land use is overlaid with

the air dispersion modeling results, the combination will demonstrate which recommended exposure

scenarios (and their locations) are most relevant for the risk assessment. We recommend considering

both current and reasonable potential future land use (i.e. “future land use”), because risk assessments

typically evaluate the potential risks from facilities over long periods of time (greater than 30 years).

One can typically identify current land use, and indications of future land use, by reviewing hard copy

and/or electronic versions of Land Use/Land Cover (LULC) maps, topographic maps, and aerial

photographs. We list some sources below, and general information associated with several potential data

and map resources. Also, as noted in Chapter 3, we recommend verifying that all mapping information

you use is in the same Universal Transverse Mercator (UTM) coordinate system format (NAD27 or

NAD83), to ensure consistency and prevent erroneous geo-referencing of locations and areas.

Land Use/Land Cover (LULC) Maps - you can download LULC maps directly from the United

States Geological Survey (USGS) web site (http://mapping.usgs.gov/index.html), at a scale of

1:250,000, in the GIRAS file format. LULC maps are also available from the EPA web site
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(ftp://ftp.epa.gov/pub), at a scale of 1:250,000, in an Arc/Info export format. Within your study

area, we recommend verifying the exact boundaries of polygons defining land use areas using

available topographic maps and aerial photographs.

Topographic Maps - Topographic maps are readily available in both hard copy and electronic

format directly from the USGS or numerous other vendors. These maps are commonly at a scale

of 1:24,000, and in TIFF file format with a TIFF World File included for georeferencing.

Aerial Photographs - You can purchase hard copy aerial photographs directly from the USGS in

a variety of scales and coverages. Electronic format aerial photographs or Digital Ortho Quarter

Quads (DOQQs) are also available for purchase directly from the USGS, or from an increasing

number of commercial sources. 

Properly georeferenced DOQQs covering a 3-km or more radius of the assessment area, combined with

overlays of the LULC map coverage and the ISCST3 modeled receptor grid node array, provide an

excellent reference for identifying land use areas and justifying your choices of exposure scenario

locations. The information above does not represent the universe of data available on human activities

or land use. They are, however, readily available for little or no cost from a number of government

sources, often via the Internet.

If feasible, we recommend verifying the accuracy of land use information with a site visit. Also,

organizations exist that routinely collect and evaluate land use data (agricultural extension agencies,

U.S. Department of Agriculture, natural resource and park agencies, and local governments). You may

find discussions with these organizations helpful in updating current land use information or providing

information regarding future land use. Local planning and zoning authorities are also potential sources

of information on reasonable potential future land use. These authorities have information on the level of

development allowed under current regulations, and what development may be expected in the future.

The general public is another excellent source of information about land use in the area. Conducting a

public workshop early in the data gathering process for the risk assessment can provide valuable

information on land use, crops, special populations, etc. as well as starting a positive dialogue with the

community. For example, by communicating with local tribes you might find that certain locations hold

special significance for cultural or religious activities.

You can also use site-specific data on physiographic features (e.g., plant types, soil characteristics, land

use, etc.) to verify the land uses identified using the resources listed above. You can readily determine

the presence, type, and extent of physiographic features from the following sources: 

• USGS topographic maps, 
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• Soil Conservation Service reports, 

• county and local land use maps, and 

• information from state departments of natural resources or similar agencies.

A study area might include multiple land uses, with differing current or potential human activity/land use

characteristics. Your activity/land use analysis could identify multiple population centers (e.g.,

communities, residential developments, or rural residences), farms and ranches, or other land use types in

the study area that would support recommended exposure scenarios. For example, if a study area

includes a farm and a small residential community, you could consider both areas as possible exposure

scenario locations (see Sections 4.2 and 4.3).

Once you’ve identified current land uses, we generally recommend also identifying areas with different

reasonable potential future land use characteristics. For example, if a study area includes undeveloped

property which could be converted to a residential community in the future, you might consider both of

these land use types (i.e. undeveloped property, and residential community) in the risk assessment (see

Sections 4.2 and 4.3). We recommend considering only potential future land uses which might

reasonably be expected to occur. For example:

1. A rural area currently characterized as undeveloped open fields, could reasonably be

expected to become farmland if it is able to support agricultural activities; 

2. A rural area currently characterized by open fields and intermittent housing, could

reasonably be expected to become a residential subdivision; and 

3. An area currently characterized as a tidal swamp would not reasonably be expected to

become farm land. 

For transparency and clarity, we recommend describing any current or reasonably expected future land

use in the risk assessment report. Of all the land use areas you identify, we generally recommend

focusing on those areas that could be impacted by the COPC emissions you’re evaluating in the risk

assessment.
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C Identification and/or mapping of current land uses in the area, a description of the use, the

area of the land described by the use, and the source of the information. You might choose to

focus initially on those land use areas impacted by emissions of COPCs.

C Identification and/or mapping of the reasonable potential future land use areas, a description

of the use, the source or rationale on which the description is based. You might choose to

focus initially on those land use areas impacted by emissions of COPCs.

RECOMMENDED INFORMATION FOR RISK ASSESSMENT REPORT

4.1.2 Water Bodies and Their Associated Watersheds

Surface water bodies and their associated watersheds are important factors in evaluating some of the

recommended exposure scenarios. Specifically, water bodies can be important sources of fish for the

fish ingestion pathway, or sources of water for the drinking water pathway (see Section 4.2). Your

careful consideration is warranted when identifying which water bodies in the study area to assess. For

the Fisher scenario, an appropriate water body (and/or its associated watershed) would receive deposition

from the emission source, and be able to sustain a fish population harvested by humans. For the drinking

water ingestion pathway, an appropriate waterbody (and/or its associated watershed) would receive

deposition from the emission source, and be used as a direct drinking water source (i.e. not processed by

a drinking water treatment facility). We recommend considering both current and potential human uses

of water bodies found within the study area. In addition to identifying the human uses of water bodies,

we recommend defining the surface areas and exact locations of the water bodies, and their associated

watersheds. See Section 4.3 for a further discussion of selecting exposure scenario locations and their

associated water bodies. 

You can typically identify the use, area, and location of water bodies and their associated watersheds by

reviewing the same hard copy and /or electronic versions of LULC maps, topographic maps, and aerial

photographs used to identify land uses. We present sources and general information associated with each

of these data types or maps in Section 4.1.1. 

You might also get information on water body use from local authorities (e.g., state environmental

agencies, fish and wildlife agencies, or local water control districts). This might include information

about viability to support fish populations and drinking water sources. Surface water bodies that are used
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As drinking water sources in the assessment area are generally evaluated in the risk assessment. While

water bodies closest to the facility will generally have higher deposition rates, risk estimates are also

affected by other physical parameters (e.g. the size of the water body and the associated watershed) and

by the properties of the COPCs being emitted.

Once you’ve selected a water body, we recommend identifying the area extent (defined by UTM

coordinates) of its watershed. Watershed runoff can be a significant contributor to overall water body

COPC loadings. Media concentration equations use the extent of pervious and impervious areas in the

watershed, as well as COPC concentrations in watershed soil, to calculate the water body COPC

concentrations (see Chapter 5 and Appendix B). We therefore recommend clearly identifying and

discussing the area extent of the watershed with the interested parties (both permitting authority and

facility). 

You generally define the area extent of a watershed by identifying topographic highs that result in

downslope drainage into the water body. We recommend ensuring that the watershed and it’s

contribution to the water body are defined relative to the exposure scenario location associated with the

water body (e.g. location on the water body of the drinking water intake, fishing pier, etc.), and

subsequent risk estimates. Please keep in mind that the total watershed area can be very extensive

relative to the area that is impacted from facility emissions. 

For example, if facility emissions principally impact an area of land which drains into a specific tributary

of a large river system and immediately upstream of a private drinking water intake point, you may wish

to consider evaluating an “effective” watershed area rather than the entire watershed area of the large

river system. For such a large river system, the watershed area can be on the order of thousands of

square kilometers and can include numerous tributaries draining into the river at points that would have

no net impact on the drinking water intake or on the water body COPC concentration at the exposure

point of interest.

To use the HHRAP as recommended, you will need the following water body and watershed parameters

(on an average annual basis):

• Water body surface area

• Watershed surface area

• Impervious watershed area
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• Identification and/or mapping of water bodies and associated watersheds potentially impacted

by facility emissions of COPCs, including surface area of the water body and area extent of

the contributing watershed, defined by UTM coordinates

• Rationale for selecting or excluding water bodies within the assessment area from evaluation

• Information on water body use that may justify including or excluding the water body from

evaluation

• Documentation of water body area, watershed area, impervious area, volumetric flow rate,

current velocity, depth of water column, total suspended solids (TSS), and the USLE

rainfall/erosivity factor

• Description of assumptions made to limit the watershed area to an “effective” area

• Copies of all maps, photographs, or figures used to define water body and watershed

characteristics

RECOMMENDED INFORMATION FOR THE RISK ASSESSMENT REPORT

• Average water body volumetric flow rate

• Water body current velocity

• Depth of water column

• Total suspended solids (TSS)

• Universal Soil Loss Equation (USLE) rainfall/erosivity factor

The impervious watershed area is generally a function of urbanization within the watershed, and is

typically presented as a percentage of the total watershed area. Volumetric flow rate and water body

current velocity are typically annual average values. State or local geologic surveys often keep records

on flow rate and current velocity of larger water bodies. You can calculate the volumetric flow rates for

smaller streams or lakes by multiplying the watershed area by one-half of the local average annual

surface runoff. Lacking site-specific data, you can calculate current velocities by dividing the volumetric

flow rate by the cross-sectional area (NOTE: current velocities are not used in the equations for lakes). 

State or local sources sometimes have information on the depths of water bodies available. Discussions

on determining the USLE rainfall/erosivity factor are included in Chapter 5 and Appendix B.
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4.1.3 Special Population Characteristics

Special populations are human receptors or segments of the population that may be at higher risk due to

increased sensitivity and/or increased exposure to COPCs. Fetuses, infants and children, and the elderly

are examples of human life stages (i.e. populations) which might be more sensitive to COPC exposure. 

You might consider some tribal groups a special population because their ingestion of fish at rates higher

than the general public increases their exposure to chemicals that bioaccumulate. Subsistence residents

are also likely to have higher exposures from ingestion of meat (locally harvested game), produce (wild

berries and onions, for example), and soil. There may be special locations where cultural activities are

conducted, or that are sacred to the tribes, and we encourage evaluating exposures at these locations.

We’ve developed the assumptions specified in this guidance – such as the protective nature of the

recommended exposure scenarios (see Section 4.2), and the use of RfDs which have been developed to

account for toxicity to sensitive receptors – to also protect the health of special populations. However,

you may also need to specifically address 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 hospital may be located in an area that is directly impacted by the facility stack

emissions. Receptors at these locations may be especially sensitive to the adverse effects and/or the

exposure setting is particularly conducive to exposure. Consequently, due to site-specific exposure

characteristics, exposure to children at the day care center, or to the sick in the hospital, might need to be

specifically evaluated. Section 4.2 provides additional discussion on evaluating potential exposure of

special populations, as part of evaluating recommended exposure scenarios. Additionally, the Agency

has a stated policy focused on consistently and explicitly evaluating environmental health risks to infants

and children in all risk assessments (U.S. EPA 1995j).

Concerns about special populations can arise at any time in the permitting process. We therefore

recommend identifying special populations as part of characterizing the exposure setting. You can

identify special populations in the assessment area based on the location of schools, hospitals, nursing

homes, day care centers, parks, community activity centers, etc. If available information indicates that

there are children exhibiting pica behavior (defined for risk assessment purposes as “an abnormally high

soil ingestion rate”) in the assessment area, these children could also represent a special population (see

Section 6.2.3.1).
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C Identification and/or mapping of the locations of special populations at potentially higher risk

from exposure to facility sources (anticipated to be located in areas impacted by facility

emissions); focusing on the characteristics of the exposure setting to ensure that selected

exposure scenario locations are protective of the special populations.

RECOMMENDED INFORMATION FOR THE RISK ASSESSMENT REPORT

4.2 RECOMMENDED EXPOSURE SCENARIOS

We recommend evaluating the following exposure scenarios when they are consistent with site-specific

exposure settings (also see Table 4-1):

C Farmer

C Farmer Child

C Resident

C Resident Child

C Fisher

C Fisher Child

C Acute Receptor

C Nursing Infant (Covered as exposure pathway under adult exposure scenarios)

These are the same exposure scenarios recommended by earlier OSW guidance, with the exception of the

Farmer Child, Fisher Child, and acute receptor. The Farmer Child scenario was introduced into the

indirect screening process in the risk assessment completed to support the proposed Hazardous Waste

Combustion Rule and by NC DEHNR (1997). We include the Fisher Child scenario in order to be

consistent with the adult/child pairings we recommend for the Resident and Farmer scenarios. We

include the acute receptor scenario to ensure that the assessment evaluates all receptors that may be

significantly exposed to emissions from facility sources. 

In addition to the recommended exposure scenarios listed above, we recommend evaluating, where

appropriate, special populations (as defined in Section 4.1.3) and communities of concern. Do this by

identifying their locations, and determining whether they are located in areas with exposure setting

characteristics that are particularly conducive to COPC impacts from facility emissions. Examples of

additional exposure scenarios include hunters, trespassers, workers (see below), recreational fishers, etc. 
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You could evaluate some populations using a combination of a recommended exposure scenario expected

to overestimate exposure compared to the populations, and maximum modeled air parameter values

specific to the location (see Section 4.3). If this initial evaluation suggests that the receptors are

protected, then no additional assessment is necessary. If, on the other hand, this evaluation estimates

levels of risk which are of concern, a refined evaluation may be needed. The refined exposure scenario

would evaluate the specific exposure pathways appropriate to the special population.

Take, for example, a children’s school or day care center located in an area receiving deposition of

facility emissions. You could evaluate potential exposure of children at this location using the Resident

Child scenario at the location of the school or day care center. In most cases, evaluating this scenario at

the school location will over-estimate exposure. This is because the Resident Child scenario includes an

exposure pathway (ingestion of homegrown produce) which is most likely not occurring at that location. 

Also, the residential scenario assumes that a child breaths the air 24 hours/day, ingests 100 mg of

soil/day; and is exposed for 6 years - when the child is probably only at day care 5 days/week and up to

10 hours/day. If this generates risk estimates of concern, you could conduct a more refined evaluation

that adjusts the exposure assumptions to be more representative of the site. 

We don't routinely recommend assessing workers at a facility that burns hazardous waste in the risk

assessment, because we assume that those workers are protected by regulation and guidance of the U.S.

Occupational Safety and Health Administration (OSHA). There are, however, some instances where

workers impacted by exposure to facility emissions are not covered by the appropriate OSHA

regulations. For example, workers located at a nearby but separate facility or commercial area, whose

duties are independent of combustor operations, are not necessarily covered by the appropriate OSHA

regulations. Also, on a site with multiple on-site activities (e.g., manufacturing, hazardous waste

combustion, and military operations) the OSHA regulations would address the worker at the

manufacturing operations with respect to those operations and not the emissions from the separate

hazardous waste combustion operations. Considering such instances in the risk assessment may be

appropriate.

We no longer refer to our recommended farmer and fisher exposure scenarios as “subsistence” scenarios. 

The associated daily consumption amounts (see Table 4-2, as well as Appendix C) are more comparable

to reasonable (versus subsistence) amounts. 
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As mentioned above, an exposure scenario is defined as a combination of exposure pathways to which a

receptor is subjected at a particular location. Table 4-1 presents the exposure pathways we recommend

evaluating for each of the exposure scenarios. Food-related ingestion pathways could represent

significant potential exposure to COPCs released from combustion sources (U.S. EPA 1994l; 1994g;

1998c; NC DEHNR 1997), due primarily to the potential for COPCs to bioaccumulate up the food chain. 

TABLE 4-1

RECOMMENDED EXPOSURE SCENARIOS FOR A 

HUMAN HEALTH RISK ASSESSMENT

Exposure Pathways

Recommended Exposure Scenariosa

FarmerFarmer ChildResidentResident ChildFisherFisher ChildAcute Receptorb

Inhalation of Vapors and Particulates • • • • • • •

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 • • d d d d --

Ingestion of Eggs from Homegrown Chickens • • d d d d --

Ingestion of Homegrown Pork • • -- -- -- -- --

Ingestion of Fish d d d d • • --

Ingestion of Breast Milk c -- c -- c -- --

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 location.

b The acute receptor scenario evaluates short-term 1-hour maximum COPC air concentrations (see Chapter 3) at any

land use area that would support the other recommended exposure scenarios, as well as commercial and industrial

land use areas (excluding workers at the facility being directly evaluated in the risk assessment).

c Infant exposure to PCDDs, PCDFs, and dioxin-like PCBs via the ingestion of their mother’s breast milk is evaluated

as an additional exposure pathway, separately from the recommended exposure scenarios identified in this table (see

Chapter 2).

d Site-specific exposure setting characteristics (e.g., presence of ponds on farms, or presence of ponds or small

livestock within semi-rural residential areas) may warrant the permitting authority consider adding this exposure

pathway to the scenario (see Section 4.2).
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As indicated in Table 4-1, some exposure setting characteristics may warrant you consider including

additional exposure pathways when evaluating a particular exposure scenario. For example, the

recommended Farmer exposure scenario doesn’t typically include the fish ingestion exposure pathway. 

However, in some areas of the country it’s common for farms to have stock ponds that are fished on a

regular basis for the farm family’s consumption. Since the ingestion rates we recommend for those food

pathways already considered in the evaluation are not significant enough to preclude the Farmer also

ingesting the fish caught from the local pond, the fish ingestion exposure pathway may also be relevant in

such locations. You could use the same rationale for residential scenarios where residents are located in

semi-rural areas which allow small livestock (e.g., free range poultry for eggs), and/or residents located

by small ponds suitable for fishing, or wetlands that support crawfish harvest.

We also recommend evaluating infant exposure to PCDDs and PCDFs via the ingestion of their mother’s

breast milk as an additional exposure pathway at all recommended adult exposure scenario locations. 

Chapter 2 and Appendix C further describe the ingestion of breast milk exposure pathway.

In addition, although some risk assessments conducted by U.S. EPA (1996b) have discounted the direct

inhalation risks to all receptors except the adult Resident (nonfarmer) and Resident Child (nonfarmer),

we generally recommend evaluating the direct inhalation exposure pathway for all receptors.

We don’t typically recommend evaluating the following exposure pathways as part of an exposure

scenario: 

Ingestion of Ground Water - U.S. EPA (1998c) found that ground water is an insignificant

exposure pathway for combustion emissions; in addition, U.S. EPA (1994k) noted that uptake

from ground water into food crops and livestock is minimal because of the hydrophobic nature of

dioxin-like compounds. We anticipate potential exposure to COPCs through ingestion of

drinking water from surface water bodies to be much more significant. Ingestion of ground water

is further discussed in Section 6.2.4.2.

Inhalation of Resuspended Dust - U.S. EPA (1990e) found that risk estimates from inhalation of

resuspended dust was insignificant. We anticipate exposure through direct inhalation of vapor

and particle phase COPCs and incidental ingestion of soil to be much more significant. 

Inhalation of resuspended dust is further discussed in Section 6.2.3.3.

Dermal Exposure to Surface Water, Soil, or Air - Available data indicate that the contribution

of dermal exposure to soils to overall risk is typically small (U.S. EPA 1996g; 1995h). For

example, the risk assessment conducted for the Waste Technologies Industries, Inc., hazardous

waste incinerator in East Liverpool, Ohio, indicated that—for an adult farmer in a subarea with

high exposures—the risk resulting from soil ingestion and dermal contact was 50-fold less than
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the risk from any other exposure pathway and 300-fold less than the total estimated risk (U.S.

EPA 1996g; 1995h). Also, there are significant uncertainties associated with estimating potential

COPC exposure via the dermal exposure pathway. The most significant of these uncertainties

are associated with determining the impact of soil characteristics and the extent of exposure (e.g.,

the amount of soil on the skin and the length of exposure) on estimating compound-specific

absorption fractions (ABS). 

We don’t generally recommend evaluating the dermal exposure to soil pathway as part of the

recommended exposure scenarios. However, if either a facility or a permitting authority feel

that site-specific conditions indicate dermal exposure to soil may contribute significantly to total

soil-related exposures, we recommend following the relevant methods described in U.S. EPA

NCEA document, Methodology for Assessing Health Risks Associated with Multiple Pathways of

Exposure to Combustor Emissions (U.S. EPA 1998c). Dermal exposure is further discussed in

Section 6.2.3.2 of this guidance.

Inhalation of COPCs and Ingestion of Water by Animals - We don’t recommend these animal

exposure pathways in calculating animal tissue concentration because we expect their

contributions to total risk to be negligible compared to the contributions of the recommended

animal exposure pathways. However, you might need to evaluate these exposure pathways on a

case-by-case basis considering site-specific exposure setting characteristics.

Our recommended exposure scenarios are further discussed in the following subsections.

4.2.1 Farmer

The Farmer exposure scenario is made up of the exposure pathways through which an adult member of a 

farming or ranching family could be exposed. We recommend including this scenario when farming or

ranching takes place, or may reasonably take place some time in the future, in the study area. As

indicated in Table 4-1, we recommend assuming the Farmer is exposed to COPCs emitted from the

facility 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 (i.e. fruits and vegetables)

• 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 breast milk (evaluated separately, for an infant of the Farmer; see Chapter 2)
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While on the farm property, the Farmer inhales air containing COPC-impacted vapors and suspended

particles. Through daily activities, the Farmer ingests incidental amounts of soil. If site characterization

suggests that impacted surface waterbodies are used as direct drinking water sources (see Section 4.1.2),

the farm family receives its water from a surface waterbody. The farm family raises and consumes beef

and milk cattle, pigs, and free-range chickens (including eggs). Cattle ingest soil while foraging on a

grazing field, as well as being fed silage and grain grown on the farm. Pigs are contained within a yard

or small field, where they are assumed not to forage, but ingest soil while being fed a combination of

silage and grain grown on the farm. Free-range chickens are contained within a yard or field, where they

ingest soil while being fed grain grown on the farm. The Farmer grows enough fruits and vegetables to

supply the family with produce. 

The scenario assumes that a portion of the Farmer’s diet comes from each homegrown food type listed

above (see Table 6-1 and Appendix C for consumption rates). All of these portions are impacted by

emissions from the facility being assessed. The recommended consumption rates don’t represent the

Farmer’s entire intake of each food type, but rather only the homegrown portion of the Farmer’s diet. It

is therefore reasonable to assume that 100% of this subset of each food type (i.e. the homegrown portion)

is contaminated. Also, because the portions represent only the homegrown portion of the Farmer diet,

assuming ingestion of all meat groups by the Farmer does not grossly overestimate the total amount of

meat a farmer or rancher could reasonably consume. Breaking out consumption by food type is an

important step in estimating the relative contributions to COPC-specific risk from ingestion of each food

type.

Previous Agency guidance (for example, U.S. EPA 1993f and U.S. EPA 1994f) didn’t include the

ingestion of chicken and eggs exposure pathways. NC DEHNR (1997) considers chicken and egg

ingestion pathways only for exposure to dioxins and furans, because biotransfer factors were only

available for dioxins and furans when that guidance was published. U.S. EPA (1998c) includes ingestion

of both poultry and eggs. Currently, biotransfer factors can be derived from literature data for other

organic compounds and metals. Therefore, we generally recommend including the chicken and egg

ingestion exposure pathways for all COPCs with available biotransfer factors. Further discussion of

these exposure pathways, including numeric equations, parameters values, and COPC-specific inputs, can

be found in Chapter 5 and Appendices A, B, and C. 
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When evaluating the ingestion of drinking water from surface water for the Farmer scenario, we

generally recommend also considering the potential for ingestion of cistern water at farm or ranch

locations, in addition to surface water sources. If site-specific information (e.g. interviews with local

health departments) suggests that cistern water is likely used, or could be used for a drinking water

source, you could evaluate ingestion of cistern water in a manner similar to that used to evaluate

ingestion of water from a surface water body (see Chapter 5 and Appendix B). Site-specific information

(e.g. do cisterns in the study area tend to be covered or uncovered?) can educate decision makers as to

appropriate equations and parameter values to use in assessing the ingestion of drinking water from

cisterns.

We don’t usually recommend the ingestion of fish exposure pathway for the Farmer exposure scenario. 

However, as indicated in the notes to Table 4-1, we do recommend that you consider evaluating the fish

ingestion pathway if regional or site-specific exposure setting characteristics (e.g., presence of ponds on

farms or ranches that support fish for human consumption) are identified that warrant consideration. You

can use the applicable estimating media concentration equations for ingestion of fish as presented in

Chapter 5 and Appendix B. Also, evaluating the Fisher and Fisher Child exposure scenarios (see

Sections 4.2.5 and 4.2.6) at farm or ranch locations may be appropriate where on-site ponds are used as

sources of fish for human consumption.

We recommend evaluating the exposure of an infant to PCDDs, PCDFs, and dioxin-like PCBs via the

ingestion of breast milk as an additional exposure pathway, separately from this exposure scenario (see

Chapter 2).

If site-specific information is available indicating that farmers in the study area don’t raise a type of 

livestock, nor is raising that type of livestock likely to occur in the future, then you could reasonably

consider eliminating the related exposure pathway (or pathways, in the case of chicken and egg

ingestion). However, if one meat source is not used, its place in the diet is often taken by one or more of

the remaining exposure pathways. Take care, therefore, to consider the intake rates of the remaining

exposure pathways, to ensure that the total amount consumed (summed fraction from each food group) is

representative. See Chapter 6 (Quantifying Exposure) for further discussion of the implications of

modifying our recommended exposure pathways.
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4.2.2 Farmer Child

The Farmer Child exposure scenario is made up of the exposure pathways through which a child member

of a farming or ranching family may reasonably be expected to be exposed. Agency policy recommends

consistently and explicitly evaluating environmental health risks to infants and children in all risk

assessments (U.S. EPA 1995j). As indicated in Table 4-1, the scenario assumes the Farmer Child is

exposed to COPCs emitted from the facility through the same exposure pathways as the Farmer. The

primary differences between the Farmer and Farmer Child are in exposure duration (6 years for the child

vs . 40 years for the adult), and consumption rates (e.g. 1.4 homegrown produce servings per week for

child vs. 2.8 homegrown produce servings per week for adult, see Table 6-1).

4.2.3 Resident

The Resident exposure scenario is made up of the exposure pathways through which an adult receptor

may be exposed in an urban or nonfarm rural setting. We recommend including the adult Resident

scenario, because potential exposure to COPCs through ingesting homegrown produce has been shown to

be potentially significant. This exposure scenario equates with the “Home Gardener” scenario

recommended by U.S. EPA (1994g) and NC DEHNR (1997). As indicated in Table 4-1, the scenario

assumes the adult Resident is exposed to COPCs from the emission source 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 breast milk (evaluated separately, for an infant of the Resident; see Chapter

2)

While on their property, the Resident inhales air containing COPC-impacted vapors and suspended

particles. Through daily activities, the Resident ingests incidental amounts of soil. If site

characterization suggests that impacted surface waterbodies are used as direct drinking water sources

(see Section 4.1.2), the resident family receives its water from a surface waterbody. The Resident grows

fruits and vegetables for home consumption (NC DEHNR 1997). Breaking out consumption by exposure

pathway is an important step in estimating the relative contributions to COPC-specific risk from
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ingestion of each food type. Further discussion of these exposure pathways, including equations,

parameter values, and COPC-specific inputs, can be found in Chapter 5 and Appendices A, B, and C. 

We don’t usually recommend evaluating the ingestion of fish exposure pathway for the Resident

exposure scenario. However, as indicated in the notes to Table 4-1, we do recommend that you consider

evaluating the fish ingestion pathway if exposure setting characteristics (e.g., presence of ponds within

semi-rural residential areas that support fish for human consumption) are identified that warrant

consideration. It may be appropriate to evaluate the Fisher and Fisher Child exposure scenarios (see

Sections 4.2.5 and 4.2.6) at residential locations where ponds or surface water bodies are used as a

potential source of fish for human consumption.

We recommend evaluating exposure of an infant to PCDDs, PCDFs, and dioxin-like PCBs via the

ingestion of breast milk as an additional exposure pathway, separately from this exposure scenario (see

Chapter 2).

4.2.4 Resident Child

The Resident Child exposure scenario is made up of the exposure pathways through which a child

receptor may be exposed in an urban or nonfarm rural setting. This exposure scenario equates with the

“Child of the Home Gardener” scenario recommended by U.S. EPA (1994g) and NC DEHNR (1997). 

Agency policy recommends consistently and explicitly evaluating environmental health risks to infants

and children in all risk assessments (U.S. EPA 1995j). As indicated in Table 4-1, the scenario assumes

the Resident Child is exposed to COPCs emitted from the facility through the same exposure pathways as

the Resident adult. The primary differences between the Resident and Resident Child are in exposure

duration (6 years for the child vs . 30 years for the adult), and consumption rates (e.g. 1.2 homegrown

produce servings per week for the child vs. 2.3 homegrown produce servings per week for the adult, see

Table 6-1).

4.2.5 Fisher

The Fisher exposure scenario is made up of the exposure pathways through which an adult receptor may

be exposed in an urban or nonfarm rural setting where fish is the main source of protein in the receptor

diet. We recommend including the Fisher scenario, because food-related ingestion routes may represent
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significant potential exposure to COPCs released from combustion sources (U.S. EPA 1994l; 1994g;

1998c; NC DEHNR 1997). The potential exposure is due primarily to the potential for COPCs to

bioaccumulate up the food chain. Breaking out consumption by exposure pathway is an important step in

estimating the relative contributions to COPC-specific risk from ingestion of each food type. As

indicated in Table 4-1, the scenario assumes the Fisher is exposed to COPCs emitted from the facility

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

• Ingestion of breast milk (evaluated separately, for an infant of the Fisher; see Chapter 2)

While on their property (i.e. where they reside), the Fisher inhales air containing COPC-impacted vapors

and suspended particles. Through daily activities, the Fisher ingests incidental amounts of soil. If site

characterization suggests that impacted surface waterbodies are used as direct drinking water sources

(see Section 4.1.2), the fisher family receives its water from a surface waterbody. The Fisher grows

fruits and vegetables for home consumption (NC DEHNR 1997). The Fisher harvests enough fish from

waterbodies in the study area impacted by facility emissions to supply the family with a significant

portion of their protein. Further discussion of these exposure pathways, including numeric equations,

parameters values, and COPC specific inputs, can be found in Chapter 5 and Appendices A, B, and C.

We recommend evaluating the exposure of an infant to PCDDs, PCDFs, and dioxin-like PCBs via the

ingestion of breast milk as an additional exposure pathway, separately from this exposure scenario (see

Chapter 2).

4.2.6 Fisher Child

The Fisher Child exposure scenario is made up of the exposure pathways through which a child receptor

may be exposed in an urban or nonfarm rural setting where fish is the main source of protein in the

receptor diet. Evaluating this exposure scenario is the same as the adult/child pairings recommended for

the Farmer and Resident scenarios. In addition, Agency policy recommends consistently and explicitly
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evaluating environmental health risks to infants and children in all risk assessments (U.S. EPA 1995j). 

As indicated in Table 4-1, the scenario assumes the Fisher Child is exposed to COPCs emitted from the

facility through the same exposure pathways as the Fisher. The primary differences between the Fisher

and Fisher Child are in exposure duration (6 years for child vs. 30 years for the adult), and consumption

rates (e.g. 1.2 homegrown produce servings per week for the child vs. 2.3 homegrown produce servings

per week for the adult, see Table 6-1).

4.2.7 Acute Receptor Scenario

In addition to long-term chronic effects evaluated in the other recommended exposure scenarios, we

generally recommend evaluating the acute exposure scenario. The acute receptor scenario accounts for

short-term effects of exposure to maximum 1-hour concentrations of COPCs in emissions from the

facility (see Chapter 3) through direct inhalation of vapors and particles (see Table 4-1 and Chapter 7). 

A receptor could be exposed in an urban or rural setting where human activity or land use supports any of

the recommended exposure scenarios. The receptor could also be exposed in commercial and industrial

land use areas (excluding workers from the facility) not typically covered by the other recommended

exposure scenarios. As mentioned in Section 4.2 above, we assume that workers from the facility being

assessed in the risk assessment are protected by OSHA programs, and therefore aren’t generally included

in hazardous waste combustion risk assessments.

We discuss further this recommended exposure scenario and associated exposure pathway, including

numeric equations, parameters values, and COPC-specific inputs, in Chapter 7 and Appendices A, B, and

C. 

4.3 SELECTING EXPOSURE SCENARIO LOCATIONS

Exposure scenario locations are the physical places within the study area selected for evaluating one or

more of the recommended exposure scenarios. We generally recommend choosing exposure scenario

locations based on COPC air concentrations and deposition rates from ISCST3 (see Chapter 3) specific

to land use areas defined during exposure setting characterization (see Section 4.1). Location-specific air

concentrations and deposition rates are then used as inputs to the equations which estimate media

concentrations. 
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We would like to emphasize that the method and resulting selection of exposure scenario locations is one

of the most critical steps of the risk assessment process, with huge impacts on standardization across all

facilities evaluated, and reproducibility of results. This is, at least partly, because ISCST3-modeled air

parameter values (and the resulting media concentration estimates) can vary significantly, even within

individual land use areas. 

To ensure consistent and reproducible risk assessments, we recommend using the following procedures

to select your exposure scenario locations. These procedures also reduce the chances that the location(s)

you select to evaluate a land use area overlook locations within that same land use area that would result

in higher risk estimates. This can be important given the complexity of multiple modeled air parameters

and phases per location, possibly multiple facility emission sources, each with multiple source-specific

COPCs. This approach also provides a more complete risk evaluation of areas surrounding the facility. 

This information often becomes relevant later in the permitting process and in risk communication to the

surrounding public.

As detailed in Chapter 3, ISCST3 estimates COPC concentrations in the air above, and deposition rates

onto, specific locations (i.e. receptor grid nodes) around a central point (e.g. combustor facility stack). If

all the locations modeled by ISCST3 are viewed as a group, they form a grid of horizontal and vertical

lines on a map, with each location a node, or intersection between vertical and horizontal lines; hence the

name “grid nodes” for modeled locations. Also, Section 4.1 of this chapter explained the steps and issues

involved in characterizing the various uses of the land in the study area. Figure 4-1 is a graphic

representation of these two sets of information, and demonstrates some of the relationship between them. 

For example, a single land use area can have multiple grid nodes associated with it, each node with its

own air concentration and deposition levels. Choosing exposure scenario location(s) for a land use area

is a matter of choosing which grid node(s) will provide the data used to generate media concentrations

used in the exposure scenario. We recommend the following steps:
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FIGURE 4-1

ISCST3 GRID NODES AND LAND USE DESIGNATIONS

Step 1: Define Land Use Areas To Evaluate - To avoid confusion and misidentification, land

use areas, water bodies, and watersheds identified during the exposure setting characterization

step, are best defined and mapped using UTM coordinates in a format consistent with that used

to define locations of facility emission sources and the ISCST3 receptor grid nodes. Formats

include NAD27 or NAD83 UTM. 

Step 2: Identify Receptor Grid Node(s) Within Each Defined Land Use Area - For each defined

land use area, identify the receptor grid nodes within or on the boundary of that area (defined in

Step 1) that represent the location of highest yearly average concentration for each ISCST3 air

parameter output (i.e., air concentration, dry deposition, wet deposition) for each phase

(i.e., vapor, particle, particle-bound). We recommend choosing concentrations specific to each

facility emission source (e.g., stacks, fugitives), as well as all emission sources at the facility

combined. This results in selecting one or more receptor grid nodes (and therefore the exposure

scenario locations for that land use area), with the following attributes:

C Highest vapor phase air concentration

C Highest vapor phase dry deposition rate
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C Highest vapor phase wet deposition rate

C Highest particle phase air concentration

C Highest particle phase wet deposition rate

C Highest particle phase dry deposition rate

C Highest particle-bound phase air concentration

C Highest particle-bound phase wet deposition rate

C Highest particle-bound phase dry deposition rate

With the exception of water bodies and watersheds (discussed in Step 4 below), we recommend

using only air parameters for a single receptor grid node as inputs into the media equations for

each exposure scenario location. We also recommend using actual parameter values, without

averaging or other statistical manipulation. However, based generally on the number and

location of facility emission sources, you might select multiple exposure scenario locations for a

specific land use area.

U.S. EPA Region 6 applied these criteria to actual sites, using actual modeled air parameters, and

found that only 1 to 3 receptor grid nodes were typically selected per land use area. This was

because, in most cases, the highest air concentration and deposition rate occurred at the same

receptor grid node. 

Please note: while these criteria tend to minimize the chances of overlooking maximum

risk within a land use area, they do not preclude you from selecting additional exposure

scenario locations within that same land use area based on site-specific risk

considerations (see Step 3 below).

Step 3: Identify Receptor Grid Nodes For Acute Risk and Site-Specific Risk Considerations - 

In addition to the receptor grid nodes selected in Steps 1 and 2 above, you might consider

additional receptor grid nodes to evaluate acute risk or site-specific risk considerations (e.g.,

special populations). 

To evaluate a land use area (including commercial and industrial land use areas) for acute risk,

choose location(s) from receptor grid nodes with the highest modeled hourly vapor phase air

concentration and highest hourly particle phase air concentration (see Chapter 3) specific to each

emission source, as well as all emission sources combined. For site-specific risk considerations,

we recommend considering the receptor grid node closest to the exposure point being evaluated

(e.g. school, hospital). However, in some cases, a more protective approach might select the

closest receptor grid node or nodes with the highest modeled air parameter values.

Step 4: Identify Receptor Grid Nodes For Water Bodies and Watersheds - For recommended

exposure scenarios that include evaluating water bodies and their associated watersheds, we

recommend considering the receptor grid nodes within their area extent or "effective" areas

(defined and mapped in Step 1). For water bodies, you could select the receptor grid node with

the highest modeled air parameter values. You could also average the air parameter values for all

receptor grid nodes within the area of the water body. For watersheds, you could average the

modeled air parameter values of all receptor grid nodes within the drainage basin (excluding the

area of the water body). Media concentration equations for water bodies and watersheds need

the same air parameter values as found in Step 2 above; yearly averages for each ISCST3
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modeled air parameter (e.g., air concentration, dry deposition, wet deposition) for each phase

(e.g., vapor, particle, particle-bound); specific to each emission source (e.g., stacks, fugitives) as

well as all emission sources at the facility combined.

For evaluating potential exposure routes other than ingestion of fish, we consider it reasonable to assume

that the Fisher and Fisher Child reside at the same exposure scenario locations as the Resident scenario. 

You can similarly assume that the Fisher and Fisher Child exposure scenarios are exposed through

ingestion of fish from the water body with the highest modeled combined deposition, that can or does

support fish populations. As a result of some site specific conditions, it may be appropriate to evaluate

the Fisher and Fisher Child assuming exposure through ingestion of fish calculated using COPC water

concentrations from one water body, and exposure from ingestion of drinking water calculated using

COPC water concentrations from a different water body.

To reiterate, we recommend initially evaluating current and reasonable potential future land use areas

defined during the exposure setting characterization, using the most representative recommended

exposure scenario(s), at actual receptor grid nodes selected using the four-step process explained above.
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5.1 Calculating COPC Concentrations in Air for Direct Inhalation

5.2 Calculating COPC Concentrations in Soil

5.3 Calculating COPC Concentrations in Produce

5.4 Calculating COPC Concentrations in Beef and Dairy Products

5.5 Calculating COPC Concentrations in Pork

5.6 Calculating COPC Concentrations in Chicken and Eggs

5.7 Calculating COPC Concentrations in Drinking Water and Fish

5.8 Using Site-Specific vs. Default Parameter Values

Chapter 5

Estimating Media Concentrations

What’s Covered in Chapter 5:

PLEASE NOTE: for the purposes of this guidance, “we” refers to the U.S. EPA OSW. 

The HHRAP is written for the benefit of a varied audience, including risk assessors,

regulators, risk managers, and community relations personnel. However, the “you” to

which we speak in this chapter is the performer of a risk assessment: the person (or

persons) who will actually put the recommended methods into practice.

The purpose of this chapter is to describe the equations (and associated parameters) for estimating media

concentration that we recommend using to evaluate the exposure scenarios presented in Chapter 4. In

most cases, we include the origin and development of each of these equations, and describe the associated

parameters. We also present the equations in Appendix B in a more condensed form (i.e. without

derivation), and organize them according to exposure pathway. Discussions of ISCST3-modeled unitized

air parameters are presented in Chapter 3. Appendix B also includes equations for modeling phase

allocation and speciation of mercury concentrations. Appendix A-2 lists compound-specific parameters

the equations need to estimate media concentrations, as well as our recommended hierarchies of sources. 

The HHRAP companion database provides recommended values for compound-specific parameters.

Section 5.1 describes the equations that estimate air concentrations for evaluating direct inhalation of

COPCs. Section 5.2 describes equations for estimating COPC concentrations in soils. Section 5.3
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Figure 5-1 - COPC Concentration in Air for Direct 

Inhalation 

describes equations for estimating COPC concentrations in produce. Sections 5.4 through 5.6 describe

equations for estimating COPC concentrations in animal products (such as milk, beef, pork, poultry, and

eggs) resulting from animals ingesting contaminated feed and soil. Section 5.7 describes equations for

estimating COPC concentrations in fish through bioaccumulation (or, for some compounds,

bioconcentration) from the water column, dissolved water concentration, or bed sediment—depending on

the COPC.

Please Note: references made throughout Chapter 5 to particle phase are generic and made

without distinction between particle and particle-bound. 

5.1 CALCULATING COPC CONCENTRATIONS IN AIR FOR DIRECT INHALATION

We recommend calculating COPC concentrations in air by summing the vapor phase and particle

phase air concentrations of COPCs. To evaluate long-term or chronic exposure via direct

inhalation, we generally recommend using unitized yearly air parameter values to calculate air

concentrations, as specified in Appendix B, Table B-5-1. To evaluate short-term or acute exposure via

direct inhalation, we recommend using unitized hourly air parameter values to calculate air

concentrations, as specified in Appendix B, Table B-6-1.
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COPC

Emissions

Vapor Phase

Air Concentration

Vapor Phase

Deposition

to Soil

Leaching,

Erosion,

and Runoff

COPC

Soil Losses

Degradation

(Biotic + Abiotic)

and Volatilization

COPC Concentration

in Soil

Particle Phase

Air Concentration

Particle Phase

Deposition

to Soil

FIGURE 5-2 -

COPC CONCENTRATION IN SOIL

5.2 CALCULATING COPC CONCENTRATIONS IN SOIL

We recommend estimating COPC concentrations in soil by summing the vapor phase and

particle phase deposition of COPCs to the soil. We generally recommend considering wet and

dry deposition of particles and vapors. Calculate dry deposition of vapors from the vapor air

concentration and the dry deposition velocity. We consider it appropriate for soil concentration

calculations to account for loss of COPCs 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. We present our recommended equations for calculating

soil concentration and soil losses of COPCs in Appendix B, Tables B-1 for land use areas, and Tables B-4

for watersheds (see Section 5.7).

Soil concentrations might require many years to reach steady state. As a result, the equations we suggest

to calculate the average soil concentration over the period of deposition were derived by integrating the
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Equation 5-1

instantaneous soil concentration equation over the period of deposition. For carcinogenic COPCs, we

recommend using two variations of the equation (average soil concentration over exposure duration): 

1. one variation if the exposure duration (T2) is greater than or equal to the operating 

lifetime of the emission source or time period of combustion, and 

2. the other form if the exposure duration is less than the operating lifetime of the emission

source or time period of combustion.

For noncarcinogenic COPCs, we recommend using the second form of the carcinogenic equation. This

equation calculates the highest annual average COPC soil concentration occurring during the exposure

duration. We describe these equations in more detail in Section 5.2.1.

Soil conditions—such as pH, structure, organic matter content, and moisture content—affect the

distribution and mobility of COPCs. Modeling the loss of COPCs from soil uses rates specific to the

physical and chemical characteristics of the soil. We describe these variables and their use in the

following subsections, along with the recommended equations.

5.2.1 Calculating Cumulative Soil Concentration (Cs)

U.S. EPA (1990e) recommended using Equation 5-1—adapted from Travis, et al. (1983)—to calculate

cumulative soil concentration:

where

Cs = Average soil concentration over exposure duration (mg COPC/kg soil)

100 = Units conversion factor (mg-m2

/kg-cm2

)

Dydp = Unitized yearly dry deposition from particle phase (s/m2-yr)

Dywv = Unitized yearly wet deposition from vapor phase (s/m2

-yr)

ks = COPC soil loss constant due to all processes (yrG1

)

tD = Time period over which deposition occurs (time period of combustion)

(yr)

Zs = Soil mixing zone depth (cm)

BD = Soil bulk density (g soil/cm3

 soil)

U.S. EPA (1993f) stated that Equation 5-1 evaluated deposition of particle phase COPCs, but failed to

consider vapor phase deposition or diffusion. To account for vapor phase diffusion, U.S. EPA (1998c)

recommended using the following equation:
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Equation 5-1A

Equation 5-1B

where

Cs = Average soil concentration over exposure duration (mg COPC/kg soil)

100 = Units conversion factor (mg-m2/kg-cm2)

Dydp = Unitized yearly dry deposition from particle phase (s/m2

-yr)

Dywv = Unitized yearly wet deposition from vapor phase (s/m2-yr)

Ldif = Dry vapor phase diffusion load to soil (g/m2-yr)

ks = COPC soil loss constant due to all processes (yrG1)

tD = Time period over which deposition occurs (time period of combustion)

(yr)

Zs = Soil mixing zone depth (cm)

BD = Soil bulk density (g soil/cm3 soil)

Other guidance (U.S. EPA 1994g) recommended the original Equation 5-1, but only for calculating Cs for

2,3,7,8-TCDD. U.S. EPA (1994g) also recommended setting the COPC soil loss constant (ks) equal to 0

for all other COPCs. For COPCs other than 2,3,7,8-TCDD, U.S. EPA (1994g) recommended Equation 5-

1B—which eliminates the COPC soil loss constant:

where

Cs = Average soil concentration over exposure duration (mg COPC/kg soil)

100 = Units conversion factor (mg-m2

/kg-cm2

)

Dyd = Yearly dry deposition rate of pollutant (g/m2-yr)

Dyw = Yearly wet deposition rate of pollutant (g/m2-yr)

tD = Time period over which deposition occurs (time period of combustion)

(yr)

Zs = Soil mixing zone depth (cm)

BD = Soil bulk density (g soil/cm3 soil)

More recent guidance documents—U.S. EPA (1994r) and NC DEHNR (1997)—recommended using two

different equations (Equations 5-1C and 5-1D) with carcinogenic COPCs. Equation 5-1C was

recommended for T2 # tD and Equation 5-1D was recommended for T1 < tD < T2

. For noncarcinogenic

COPCs, Equation 5-1E was recommended.
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Equation 5-1C

Equation 5-1D

Equation 5-1E

We recommend using Equations 5-1C, 5-1D, and 5-1E to calculate Cs. Appendix B, Table B-1-1

discusses further how to use these equations.

Recommended Equations for Calculating:

Cumulative Soil Concentration (Cs)

Carcinogens:

For T2 # tD

For T1 < tD < T2

Noncarcinogens:

where

Cs = Average soil concentration over exposure duration (mg COPC/kg soil)

Ds = Deposition term (mg COPC/kg soil/yr)

ks = COPC soil loss constant due to all processes (yrG1

)

tD = Time period over which deposition occurs (time period of combustion) (yr)

T1 = Time period at the beginning of combustion (yr)

CstD = Soil concentration at time tD (mg/kg)

T2 = Length of exposure duration (yr)

We discuss the deposition term further in this Section, as well as Section 5.2.3. Section 5.2.2 discusses

the COPC-specific soil loss constant (ks). Chapter 2 discusses how the period of time at the beginning of

combustion (T1

) relates to characterizing site conditions immediately preceding the study period. Chapter

2 also addresses the time period during which burning - and therefore deposition - occurs (tD), as it
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relates to setting emission rates. Chapter 3 addresses air dispersion modeling aspects of tD. Chapter 6

further discusses how the duration of exposure (T2

) relates to characterizing exposure.

As in U.S. EPA (1994r) and NC DEHNR (1997), we recommend using Equation 5-1C when you model

an exposure duration that is less than or equal to the operating lifetime of the emission source or

hazardous waste combustor (T2 # tD). We recommend using Equation 5-1D when you model an

exposure duration greater than the operating lifetime of the hazardous waste combustor (T1 < tD < T2

). 

For noncarcinogenic COPCs, we recommend Equation 5-1E.

We generally recommend using the COPC soil concentration averaged over the exposure duration

(represented by Cs) for carcinogenic compounds. Carcinogenic risk is averaged over the lifetime of an

individual. Because the hazard quotient associated with noncarcinogenic COPCs is based on a threshold

dose rather than a lifetime exposure, we recommend using the highest annual average COPC soil

concentration (CstD) occurring during the exposure duration period for noncarcinogenic COPCs. CstD

typically occurs at the end of the operating life of the emission source or the time period of combustion.

As in U.S. EPA (1994r) and NC DEHNR (1997), we recommend using the highest 1-year annual average

soil concentration, determined using Equation 5-1E, to evaluate risk from noncarcinogenic COPCs (see

Chapter 7).

5.2.2 Calculating the COPC Soil Loss Constant (ks)

Organic and inorganic COPCs can be lost from the soil by several processes that may or may not occur

simultaneously. The rate at which a COPC is lost from the soil is known as the soil loss constant (ks). 

We recommend determining ks by using the soil’s physical, chemical, and biological characteristics, to

estimate the COPC-specific loss resulting from:

(1) leaching, 

(2) runoff,

(3) erosion,

(4) biotic and abiotic degradation, and 

(5) volatilization.
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Equation 5-2

Equation 5-2A

U.S. EPA (1990e) recommended Equation 5-2 to calculate ks:

where

ks = COPC soil loss constant due to all processes (yrG1

)

ksl = COPC loss constant due to leaching (yrG1)

ksg = COPC loss constant due to biotic and abiotic degradation (yrG1)

ksv = COPC loss constant due to volatilization (yrG1

)

We recommend using Equation 5-2A to calculate ks. We describe this equation further in Appendix B,

Table B-1-2. Using Equation 5-2A is consistent with U.S. EPA (1994g), U.S. EPA (1994r), U.S. EPA

(1998c) and NC DEHNR (1997).

Recommended Equation for Calculating:

COPC Soil Loss Constant (ks)

where

ks = COPC soil loss constant due to all processes (yrG1)

ksg = COPC loss constant due to biotic and abiotic degradation (yrG1)

kse = COPC loss constant due to soil erosion (yrG1)

ksr = COPC loss constant due to surface runoff (yrG1

)

ksl = COPC loss constant due to leaching (yrG1)

ksv = COPC loss constant due to volatilization (yrG1

)

Section 5.2.2.1 discusses loss due to biotic and abiotic degradation (ksg). Section 5.2.2.2 discusses loss

due to erosion (kse). Section 5.2.2.3 discusses loss due to surface runoff (ksr). Section 5.2.2.4 discusses

Loss due to leaching (ksl). Section 5.2.2.5 discusses loss due to volatilization (ksv).

As highlighted in Section 5.2.1, using Equation 5-2A in Equations 5-1C and 5-1D assumes that you can

define COPC loss using first-order reaction kinetics. First-order reaction rates depend on the

concentration of one reactant (Bohn et al. 1985). The loss of a COPC by a first-order process depends

only on the concentration of the COPC in the soil, and a constant fraction of the COPC 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 (Sparks

1989). The assumption that COPC loss follows first-order reaction kinetics may be an oversimplification
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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 first-order loss

constant may be adequate to describe the loss of the COPC from soil (U.S. EPA 1998c).

COPC loss in soil can also follow zero or second-order reaction kinetics. Zero-order reaction kinetics are

independent of reactant concentrations (Bohn et al. 1985). 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 COPC 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 et al. 1985). The loss constant of a COPC 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 COPC 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 COPC loss can occur

simultaneously, using Equation 5-2A might also overestimate loss rates for each process (Valentine

1986). We recommend, when possible, taking into account the common occurrence of all loss processes. 

It’s possible to derive combined rates of soil loss by these processes experimentally. U.S. EPA (1986c)

presents values for some COPCs.

5.2.2.1 COPC 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 available in the literature (U.S. EPA 1998c). According to Lyman et al. (1982), it’s

reasonable to assume that degradation rates follow first order kinetics in a homogenous media. You’re

therefore able to relate the half-life of a compound 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, you can calculate the degradation rate. However,

literature sources don’t provide sufficient data for all such mechanisms, especially for soil. Earlier

Agency guidance (U.S. EPA 1994g) recommended setting ksg for all COPCs other than 2,3,7,8-TCDD

equal to zero. The HHRAP companion database presents our recommended values for this COPCspecific variable.
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Recommended Values for:

COPC Loss Constant Due to Biotic and Abiotic Degradation (ksg)

COPC-Specific

(See the HHRAP companion database)

The rate of biological degradation in soils depends on the concentration and activity levels of the

microbial populations in the soil, the soil conditions, and the COPC concentration (Jury and Valentine

1986). First-order loss rates often fail to account for the high variability of these features in a single soil

system. However, using simple rate expressions may be appropriate at low chemical concentrations (e.g.,

nanogram per kilogram soil). A first-order dependence on chemical concentration may be reasonable at

low chemical concentrations. The rate of biological degradation is COPC-specific, and depends on the

complexity of the COPC and the usefulness of the COPC to the microorganisms. Some substances, rather

than being used by the organisms as a nutrient or energy source, are simply degraded with other similar

COPCs, which can be further utilized. Environmental- and COPC-specific factors that can limit the

biodegradation of COPCs in the soil environment (Valentine and Schnoor 1986) include:

• availability of the COPC;

• nutrient limitations;

• toxicity of the COPC; and 

• inactivation or nonexistence of enzymes capable of degrading the COPC.

Chemical degradation of organic compounds can be a significant mechanism for removing COPCs from

soil (U.S. EPA 1998c). Hydrolysis and oxidation-reduction reactions are the primary chemical

transformation processes occurring in the upper layers of soils (Valentine 1986). General rate expressions

describing the transformation of some COPCs by all non-biological processes are available. These

expressions are helpful when division into component reactions isn’t 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). In soil systems, sorption of the COPC can increase, decrease, or not affect the rate of

hydrolysis, as numerous studies cited in Valentine (1986) have shown. We recommend predicting the

overall (i.e. total) rate of hydrolysis in soil by adding the rates in the soil and water phases. We

recommend assuming that these rates are first-order reactions at a fixed pH (Valentine 1986). Lyman et

al. (1982) describes methods for estimating these hydrolysis constants.
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Equation 5-3

Organic and inorganic compounds also undergo oxidation-reduction (redox) reactions in the soil

(Valentine 1986). Organic redox reactions involve the reacting molecules exchanging oxygen and

hydrogen atoms. Inorganic redox reactions may involve the reactants exchanging atoms or electrons. In

soil systems where the identities of oxidant and reductant species aren’t known, you can acquire a

first-order rate constant for describing loss by redox reactions (Valentine 1986). Redox reactions

involving metals may promote losses from surface soils by making metals more mobile (e.g., leaching to

subsurface soils).

5.2.2.2 COPC Loss Constant Due to Soil Erosion (kse)

U.S. EPA (1998c) recommended using Equation 5-3 to calculate the constant for soil loss resulting from

erosion (kse). 

where

kse = COPC soil loss constant due to soil erosion

0.1 = Units conversion factor (1,000 g-kg/10,000 cm2

-m2

)

Xe= Unit soil loss (kg/m2

-yr)

SD = Sediment delivery ratio (unitless)

ER = Soil enrichment ratio (unitless)

BD = Soil bulk density (g soil/cm3 soil)

Zs = Soil mixing zone depth (cm)

Kds = Soil/water partition coefficient (ml water/g soil)

2sw = Soil volumetric water content (ml water/cm3 soil) = 0.2 ml/cm3

We recommend using the Universal Soil Loss Equation (USLE) to calculate unit soil loss (Xe

)(See

Section 5.7.2). We describe soil bulk density (BD) in Section 5.2.4.2. We describe Soil mixing depth

(Zs) in Section 5.2.4.1. We describe soil volumetric water content (2sw) in Section 5.2.4.4. We discuss

site-specific variables associated with Equation 5-3 further in Appendix B. 

U.S. EPA (1994g and 1994r) recommended setting all kse values equal to zero. U.S. EPA (1994r)

recommended setting kse equal to zero because contaminated soil erodes both onto and off of the site.

As in U.S. EPA (1994g and 1994r), we recommend setting kse equal to zero. 
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Equation 5-4

Recommended Value for:

COPC Loss Constant Due to Erosion (kse)

0

For additional information on addressing kse, we recommend consulting U.S. EPA (1998c). We also

further describe using kse values in Appendix B, Table B-1-3.

5.2.2.3 COPC Loss Constant Due to Runoff (ksr)

Earlier U.S. EPA guidance (1994g) recommended setting all ksr values equal to zero. 

As in U.S. EPA (1994r; 1998c) and NC DEHNR (1997), we recommend using Equation 5-4 to calculate

ksr. We further discuss using Equation 5-4 in Appendix B, Table B-1-4.

Recommended Equation for Calculating:

COPC Loss Constant Due to Runoff (ksr)

where

ksr = COPC loss constant due to runoff (yrG1)

RO = Average annual surface runoff from pervious areas (cm/yr)

2sw = Soil volumetric water content (ml water/cm3 soil) = 0.2 ml/cm3

Zs = Soil mixing zone depth (cm)

Kds = Soil/water partition coefficient (ml water/g soil)

BD = Soil bulk density (g soil/cm3

 soil) = 1.5 g/cm3

The average annual surface runoff from pervious surfaces (RO) is a site-specific water loss term discussed

in Section 5.2.4.3. Section 5.2.4.4 describes soil volumetric water content (2sw). Section 5.2.4.1 discusses

the depth of soil mixing (Zs). Appendix A-2 explains how we recommend calculating the COPC-specific

soil/water partition coefficient (Kds). Section 5.2.4.2 describes soil bulk density (BD).
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Equation 5-5

5.2.2.4 COPC Loss Constant Due to Leaching (ksl)

Losses of soil COPCs 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.

U.S. EPA (1990e) recommended using Equation 5-5 to calculate ksl.

where

ksl = COPC loss constant due to leaching (yrG1

)

P = Average annual precipitation (cm/yr)

I = Average annual irrigation (cm/yr)

Ev = Average annual evapotranspiration (cm/yr)

2sw = Soil volumetric water content (ml water/cm3

 soil) = 0.2 ml/cm3

Zs = Soil mixing zone depth (cm)

Kds = Soil/water partition coefficient (ml water/g soil)

BD = Soil bulk density (g soil/cm3

 soil)

U.S. EPA (1993f) determined that Equation 5-5 does not properly account for surface runoff. U.S. EPA

(1994g) recommended setting all ksl values to zero.

More recent guidance (U.S. EPA 1994r; 1998c; NC DEHNR 1997) have recommended using Equation 5-

5A to calculate ksl. As with U.S. EPA (1994r), U.S. EPA (1998c), and NC DEHNR (1997), we

recommend using Equation 5-5A to account for runoff while calculating ksl. We further discuss the use

of this equation in Appendix B, Table B-1-5.
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Equation 5-5A

Equation 5-6

Recommended Equation for Calculating:

COPC Loss Constant Due to Leaching (ksl)

where

ksl = COPC loss constant due to leaching (yrG1)

P = Average annual precipitation (cm/yr)

I = Average annual irrigation (cm/yr)

RO = Average annual surface runoff from pervious areas (cm/yr)

Ev = Average annual evapotranspiration (cm/yr)

2sw = Soil volumetric water content (ml water/cm3 soil) = 0.2 ml/cm3

Zs = Soil mixing zone depth (cm)

BD = Soil bulk density (g soil/cm3 soil) = 1.5 g/cm3

Kds = Soil/water partition coefficient (cm3 water/g soil)

Appendix B describes how we suggest acquiring site-specific variables associated with Equation 5-5A. 

The average annual volume of water available to generate leachate is the mass balance of all water inputs

and outputs from the area under consideration (P + I - RO - Ev). These variables are described in

Section 5.2.4.3. Section 5.2.4.4 describes soil volumetric water content (2sw). Section 5.2.4.1 describes

the soil mixing depth (Zs). Section 5.2.4.2 soil bulk density (BD). Appendix A-2 describes how we

recommend calculating the COPC-specific soil/water partition coefficient (Kds

).

5.2.2.5 COPC Loss Constant Due to Volatilization (ksv)

Semi-volatile and volatile COPCs emitted in high concentrations may become adsorbed to soil particles

and exhibit volatilization losses from soil. The loss of a COPC from the soil by volatilization depends on

the rate of movement of the COPC 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).

U.S. EPA (1990e; 1993f; 1998c) recommended using Equation 5-6 to calculate ksv.

where

ksv = COPC loss constant due to volatilization (yrG1)

Ke = Equilibrium coefficient (s/cm-yr)

Kt = Gas phase mass transfer coefficient (cm/s)
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Equation 5-6A

U.S. EPA (1990e; 1993f; 1998c) don’t identify a reference for Equation 5-6. U.S. EPA (1993f) stated

that Equation 5-6 had been independently verified as accurately representing volatilization loss, but that

the equation for Kt (Equation 5-8) appeared to fit to data empirically. U.S. EPA (1993f) also stated that

ksv is modeled as a means of limiting soil concentration. Because this mass flux never experiences rain

out, or washout and subsequent re-deposit, soil COPC concentrations are underestimated for soluble

volatile COPCs. U.S. EPA (1993f) further recommended that additional research be conducted to

determine the magnitude of the uncertainty introduced for volatile COPCs. U.S. EPA (1998c)

recommended not considering the volatilized residues of semi-volatile COPCs (such as dioxin). U.S.

EPA (1994g) recommended setting all ksv values to zero.

U.S. EPA guidance (1994r) and NC DEHNR (1997) recommended using Equation 5-6A to calculate ksv. 

Equation 5-6A appears to incorporate equations that U.S. EPA (1990e) recommended for calculating Ke

(equilibrium coefficient) and Kt (gas phase mass transfer coefficient).

where

ksv = COPC loss constant due to volatilization (yrG1

)

3.1536 × 107

= Units conversion factor (s/yr)

H = Henry’s Law constant (atm-m3

/mol)

Zs = Soil mixing zone depth (cm)

Kds = Soil/water partition coefficient (cm3

 water/g soil)

R = Universal gas constant (atm-m3/mol-K)

Ta = Ambient air temperature (K) = 298.1 K

BD = Soil bulk density (g soil/cm3 soil)

0.482 = Empirical constant (unitless) Units conversion factor 

[(3600 s/hr)0.78(100 cm/m)/(3600 s/hr)] A (empirical constant

0.0292)

W = Average annual wind speed (m/s)

0.78 = Empirical constant (unitless)

:a = Viscosity of air (g/cm-s)

Da = Density of air (g/cm3

)

Da= Diffusivity of COPC in air (cm2/s)

-0.67 = Empirical constant (unitless)

A = Surface area of contaminated area (m2)

-0.11 = Empirical constant (unitless)
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Equation 5-7

Equation 5-8

Equation 5-10

Equation 5-9

U.S. EPA (1990e) recommended using Equation 5-7 to calculate Ke and Equation 5-8 to calculate Kt.

where

Ke = Equilibrium coefficient (s/cm-yr)

3.1536 × 107= Units conversion factor (s/yr)

H = Henry’s Law constant (atm-L/mol)

103

= Units conversion factor (L/m3

)

Zs = Soil mixing zone depth (cm)

Kds = Soil/water partition coefficient (cm3 water/g soil)

R = Universal gas constant (atm-m3/mol-K)

Ta = Ambient air temperature (K) = 298.1 K

BD = Soil bulk density (g soil/cm3

 soil)

Kt = Gas phase mass transfer coefficient (cm/s)

0.482 = Units conversion factor [(3600 s/hr)0.78(100 cm/m)/(3600 s/hr)] A

(empirical constant 0.0292)

W = Average annual wind speed (m/s)

Sca = Schmidt number for gas phase (unitless)

de

= Effective diameter of contaminated media (m)

U.S. EPA (1990e) also recommended using Equation 5-9 to calculate the Schmidt number for gas phase

(Sca), and Equation 5-10 to calculate the effective diameter of contaminated media (de).

where

Sca = Schmidt number for gas phase (unitless)

:a = Viscosity of air (g/cm-s)

Da = Density of air (g/cm3

)

Da= Diffusivity of COPC in air (cm2/s)

de

= Effective diameter of contaminated media (m)

A = Surface area of contaminated area (m2

)
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Equation 5-7A

As in U.S. EPA (1998c), we recommend using Equation 5-7A to calculate ksv, in cases where high

concentrations of volatile organic compounds are expected to be present in the soil. 

Recommended Equation for Calculating:

COPC Loss Constant Due to Volatilization (ksv)

where

ksv = COPC loss constant due to volatilization (yrG1)

3.1536 × 107= Units conversion factor (s/yr)

H = Henry’s Law constant (atm-m3/mol)

Zs = Soil mixing zone depth (cm)

Kds = Soil/water partition coefficient (ml/g)

R = Universal gas constant (atm-m3

/mol-K)

Ta = Ambient air temperature (K) = 298.1 K

BD = Soil bulk density (g soil/cm3

 soil) = 1.5 g/cm3

Da

= Diffusivity of COPC in air (cm2/s)

Dsoil = Solids particle density (g/cm3

) = 2.7 g/cm3

2sw = Soil volumetric water content (ml/cm3

 soil) = 0.2 ml/cm3

Henry’s Law constants are compound-specific, and we supply recommended values in the HHRAP

companion database. We describe the soil mixing depth (Zs

) in. Appendix A-2 describes how we

recommend calculating the COPC-specific soil/water partition coefficient (Kds). The Universal gas

constant (R) and ambient air temperature (Ta) are discussed further in Appendix B, Table B-1-6. Soil

bulk density (BD) is described below, as well as in Section 5.2.4.2. Appendix A-2 discusses the

diffusivity of a COPC in air (Da). Solids particle density (Dsoil) is discussed in this Section, below. Soil

volumetric water content (2sw) is further described below, as well as in Section 5.2.4.4.

Equation 5-7A is based on gas equilibrium coefficients and gas phase mass transfer, and combines

Equations 5-7, 5-7B, and 5-7C. You can derive ksv by adapting the Hwang and Falco (1986) equation for

soil vapor phase diffusion, to obtain Equation 5-6, as previously reported by U.S. EPA (1990e). Based on

general soil properties, you can also write the gas-phase mass transfer coefficient, Kt, as follows (Hillel

1980; Miller and Gardiner 1998):
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Equation 5-7B

Equation 5-7C

where

Kt = Gas phase mass transfer coefficient (cm/s)

Zs = Soil mixing zone depth (cm)

Da = Diffusivity of COPC in air (cm2/s) 

2v = Soil void fraction (cm3

/cm3

)

We describe Soil mixing depth (Zs) in Section 5.2.4.1. The soil void fraction (2v) is the volumetric

fraction of a soil that does not contain solids or water, and can be expressed as:

where

2v = Soil void fraction (cm3

/cm3

)

BD = Soil bulk density (g/cm3) = 1.5 g/cm3

Dsoil = Solids particle density (g/cm3) = 2.7 g/cm3

2sw = Soil volumetric water content (ml water/cm3 soil) = 0.2 ml/cm3

The expression containing bulk density (BD) divided by solids particle density (Dsoil) gives the volume of

soil occupied by pore space or voids (Miller and Gardiner 1998). Soil bulk density is affected by the soil

structure, such as looseness or compactness of the soil, and depends on the water and clay content of the

soil (Hillel 1980). A range for bulk density of 0.83 to 1.84 was originally cited in Hoffman and Baes

(1979). Blake and Hartge (1996) and Hillel (1980) both suggest that the mean density of solid particles is

about 2.7 g/cm3

. We recommend a default soil bulk density of 1.5 g/cm3

, based on a mean value for loam

soil from Carsel et al. (1988).

The soil water content (2sw) depends on both the available water and the soil structure of a particular soil. 

Values for 2sw range from 0.03 to 0.40 ml/cm3

 depending on soil type (Hoffman and Baes 1979). The

lower values are typical of sandy soils, which can’t retain much water; the higher values are typical of

soils such as clay or loam soils which can retain water. If site-specific information isn’t available, we

recommend a mid-point default value of 0.2 ml water/cm3 soil. However, since 2sw is unique for each soil

type, we highly recommend using site-specific information. 

We discuss ksv further in Appendix B, Table B-1-6.
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Equation 5-11

5.2.3 Calculating the Deposition Term (Ds)

We recommend using Equation 5-11 to calculate the deposition term (Ds). This equation is further

described in Appendix B, Table B-1-1. Using Equation 5-11 to calculate Ds is consistent with U.S. EPA

(1994r) and NC DEHNR (1997), which both incorporate Ds into Equation 5-1C.

Recommended Equation for Calculating:

Deposition Term (Ds)

where

Ds = Deposition term (mg COPC/kg soil/yr)

100 = Units conversion factor (mg-m2

/kg-cm2

)

Q = COPC emission rate (g/s)

Zs = Soil mixing zone depth (cm)

BD = Soil bulk density (g soil/cm3 soil) = 1.5 g/cm3

Fv = Fraction of COPC 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)

Chapters 2 and 3 explain how we suggest quantifying the COPC emission rate (Q). Chapter 3 describes

generating modeled air parameters Cyv, Dydv, Dywv, Dydp, and Dywp. We describe the soil mixing

depth (Zs) in Section 5.2.4.1. Soil bulk density (BD) is described in Sections 5.2.2.5 and 5.2.4.2, as well

as Appendix B. Appendix A-2 describes how we suggest determining the COPC-specific parameter Fv.

5.2.4 Site-Specific Parameters for Calculating Cumulative Soil Concentration

Calculating Cs requires the following site-specific parameters:

• Soil mixing zone depth (Zs)

• Soil bulk density (BD)

• Available water (P + I - RO - Ev

)

• Soil volumetric water content (2sw)

We discuss these parameters further in the following subsections, and in Appendix B.
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5.2.4.1 Soil Mixing Zone Depth (Zs

)

When modeling exposures to COPCs in soils, the depth of contaminated soils is important in calculating

the appropriate soil concentration. Tilling might mix deposited COPCs deeper into the soil, whether

manually in a garden or mechanically in a large field. Increasing the volume of soil through which

COPCs are mixed will tend to decrease (i.e. dilute) concentrations. The value of Zs

 you choose 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: 

• ingestion of plants contaminated by root uptake; 

• direct ingestion of soil by humans, cattle, swine, or chickens; and

• surface runoff into water bodies.

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. 

In general, U.S. EPA (1992d, 1998c) estimated that if the area under consideration is likely to be tilled,

soil depth is about 10 to 20 centimeters, depending on local conditions and the equipment used. If soil is

not moved, COPCs were assumed to be retained in the shallower, upper soil layer. In this case, earlier

Agency guidance (U.S. EPA 1990e; U.S. EPA 1998c) typically recommended a value of 1 centimeter.

U.S. EPA (1998c) recommended selecting Zs as follows:

Soil Depth (Zs) Exposure Description

1 cm Direct ingestion of soil Human exposure: in gardens, lawns, landscaped areas, parks, and

recreational areas. 

Animal exposure: in pastures, lawns, and parks (untilled soils).

1 cm Surface water runoff in

nonagricultural areas

These areas are typically assumed to be untilled.

20 cm Plant uptake for agricultural

soils

The root depth is assumed to equal the tilling depth of 20 centimeters. 

In untilled soils, the root zone does not directly reflect tilling depth,

although it is assumed that tilling depth is an adequate substitute for

root zone depth.

20 cm Surface water runoff in

agricultural areas

These areas are typically assumed to be tilled.

We recommend the following values for Zs

:
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Recommended Values for:

Soil Mixing Zone Depth (Zs)

2 cm - untilled

20 cm - tilled

We recommend a default Zs of 2 cm for estimating surface soil concentrations in untilled soils, based on a

study that profiled dioxin measurements within soil (Brzuzy et al. 1995). We recommend a default Zs of

20 cm for estimating surface soil concentrations in tilled soils, as in U.S. EPA (1998c). 

5.2.4.2 Soil Dry Bulk Density (BD)

BD is the ratio of the mass of soil to its total volume. This variable is affected by the soil structure, type,

and moisture content (Hillel 1980). 

U.S. EPA (1994r) recommended deriving wet soil bulk density by weighing a thin-walled, tube soil

sample (e.g., a Shelby tube) of known volume and subtracting the tube weight (ASTM Method D2937). 

Moisture content can then be calculated (ASTM Method 2216) to convert wet soil bulk density to dry soil

bulk density.

As in U.S. EPA (1994g; 1998c) and presented in Hoffman and Baes (1979), we recommend the following

value for BD:

Recommended Value for:

Soil Dry Bulk Density (BD)

1.50 g/cm3

5.2.4.3 Available Water (P + I - RO - Ev)

The average annual volume of water available (P + I - 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 could apply in the various Agency regions.
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The average annual precipitation (P), irrigation (I), runoff (RO), and evapotranspiration (Ev) rates and

other climatological data are available 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)—might also

be found in resources such as Geraghty et al. (1973). You could also estimate surface runoff by using the

Curve Number Equation developed by the U.S. Soil Conservation Service (NC DEHNR 1997). U.S.

EPA (1985b) cited isopleths of mean annual cropland runoff corresponding to various curve numbers

developed by Stewart et al. (1975). Curve numbers were assigned to an area on the basis of soil type,

land use or cover, and the hydrologic conditions of the soil (NC DEHNR 1997).

The wide range of available values, however, demonstrates the uncertainties and limitations in our ability

to estimate these parameters. For example, Geraghty et al. (1973) presented isopleths for annual surface

water contributions that include interflow and ground water recharge. U.S. EPA (1994g) recommended

reducing these values by 50 percent, to represent surface runoff only.

5.2.4.4 Soil Volumetric Water Content (2sw)

The soil volumetric water content (2sw) depends on the available water and the soil structure. A wide

range of values for these variables may apply in the various Agency regions. As in earlier guidance

documents, (U.S. EPA 1993i; U.S. EPA 1994g; NC DEHNR 1997), we recommend using a default value

of 0.2 ml/cm3

 for 2sw.

Recommended Value for:

Soil Volumetric Water Content (2sw)

0.2 ml/cm3

5.3 CALCULATING COPC CONCENTRATIONS IN PRODUCE

Indirect exposure resulting from ingestion of produce depends on the total concentration of

COPCs in the leafy, fruit, and tuber portions of the plant. Because of general differences in
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Deposition

of Particles

(Section 5.3.1)

Vapor

Transfer

(Section 5.3.2)

Root Uptake

from Soil

(Section 5.3.3)

COPC Concentration in

Aboveground Produce

FIGURE 5-3

COPC CONCENTRATION IN PRODUCE

contamination mechanisms, we recommend separating produce into two broad categories—aboveground

produce and belowground produce. In addition, aboveground produce can be further subdivided into

exposed and protected aboveground produce. 

Aboveground Produce

Aboveground exposed produce is typically assumed to be contaminated by three possible mechanisms:

• Direct deposition of particles—wet and dry deposition of particle phase COPCs on the

leaves and fruits of plants (Section 5.3.1).

• Vapor transfer—uptake of vapor phase COPCs by plants through their foliage

(Section 5.3.2).

• Root uptake—root uptake of COPCs available from the soil and their transfer to the

aboveground portions of the plant (Section 5.3.3).

As in U.S.EPA (1998c), we recommend calculating the total COPC concentration in aboveground

exposed produce 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. They are therefore protected from contamination from deposition and vapor transfer. 

Root uptake of COPCs is the primary mechanism through which aboveground protected produce becomes
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Equation 5-13

contaminated (Section 5.3.3). Appendix B further describes the equations and parameters we recommend

to calculate COPC concentrations in exposed and protected aboveground produce.

Belowground Produce

For belowground produce, we recommend assuming contamination occurs only through one

mechanism—root uptake of COPCs available from soil (Section 5.3.3). The HHRAP doesn’t address

contamination of belowground produce via direct deposition of particles and vapor transfer because we

assume that the root or tuber is protected from contact with contaminants in the vapor phase. Appendix B

further describes the equations and parameters we recommend to calculate COPC concentrations in

belowground produce.

Generally, we don’t consider risks associated with exposure to VOCs via food-chain pathways

significant. This is primarily because VOCs are typically low-molecular-weight COPCs that do not

persist in the environment and do not bioaccumulate (U.S. EPA 1994r; U.S. EPA 1996g). However, as

discussed in Chapter 2, we recommend evaluating all COPCs, including VOCs, for each exposure

pathway.

5.3.1 Aboveground Produce Concentration Due to Direct Deposition (Pd)

Some earlier guidance documents (U.S. EPA 1990e; 1998c) recommended using Equation 5-

13 to calculate COPC concentrations in aboveground vegetation resulting from wet and dry

deposition onto plant surfaces of leafy plants and exposed produce (Pd):

where

Pdi = Concentration of pollutant due to direct deposition in the ith plant group

(μg COPC/g plant tissue DW))

1,000 = Units conversion factor (kg/103 g and 106 μg/g pollutant)

Dyd = Yearly dry deposition from particle phase (g/m2-yr)

Fw = Fraction of COPC wet deposition that adheres to plant surfaces (unitless)

Dywv = Yearly wet deposition from vapor phase (g/m2

-yr)

Rpi = Interception fraction of the edible portion of plant tissue for the ith plant

group (unitless)

kp = Plant surface loss coefficient (yrG1)
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Equation 5-14

Tpi = Length of plant’s exposure to deposition per harvest of the edible portion

of the ith plant group (yr)

Ypi = Yield or standing crop biomass of edible portion of the ith plant group

(kg DW/m2 )

U.S. EPA (1994r) modified Equation 5-13 to include stack emissions adjusted to remove the fraction of

air concentration in vapor phase [Q (1 - Fv

)] (Equation 5-14). 

We recommend using Equation 5-14 to calculate Pd. We further discuss the use of this equation in

Appendix B, Table B-2-7.

Recommended Equation for Calculating:

Aboveground Produce Concentration Due to Direct Deposition (Pd)

where

Pd = Plant (aboveground produce) concentration due to direct (wet and dry)

deposition (mg COPC/kg DW)

1,000 = Units conversion factor (mg/g)

Q = COPC emission rate (g/s)

Fv = Fraction of COPC air concentration in vapor phase (unitless)

Dydp = Unitized yearly average dry deposition from particle phase (s/m2-yr)

Fw = 0.2 for anions, 0.6 for cations & most organics (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 (yrG1

)

Tp = Length of plant exposure to deposition per harvest of the edible portion of the

ith plant group (yr)

Yp = Yield or standing crop biomass of the edible portion of the plant (productivity)

(kg DW/m2

)

Chapters 2 and 3 explain how we recommend quantifying the COPC emission rate (Q). Appendix A-2

describes how we recommend determining the COPC-specific parameter Fv. Chapter 3 describes how the

modeled air parameters Dydp and Dywp are generated. Appendix B explains our recommendations for

Fw. Rp, kp, Tp, and Yp are neither site- nor COPC-specific, and are described in Sections 5.3.1.1 through

5.3.1.4.
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5.3.1.1 Interception Fraction of the Edible Portion of Plant (Rp)

U.S. EPA (1998c) stated that NRC models assumed a constant of 0.2 for Rp for dry and wet deposition of

particles (Boone et al. 1981). However, Shor et al. (1982) suggested that diversity of plant growth

necessitated vegetation-specific Rp values.

As summarized in Baes et al. (1984), experimental studies of pasture grasses identified a correlation

between initial Rp values and productivity (standing crop biomass [Yp]) (Chamberlain 1970):

Rp = 1 - e

-(Yp Equation 5-14A

where

Rp = Interception fraction of the edible portion of plant (unitless)

( = Empirical constant (Chamberlain [1970] gives the range as 2.3 to 3.3 for

pasture grasses; Baes et al. [1984] used the midpoint, 2.88, for pasture

grasses.)

Yp = Standing crop biomass (productivity) (kg DW/m2

 for silage; kg WW/m2

for exposed produce)

Baes et al. (1984) also developed methods for estimating Rp values for leafy vegetables, silage, and

exposed produce. However, these vegetation class-specific calculations produced Rp values that were

independent of productivity measurements. This independence led to potentially unreasonable estimates

of surface plant concentrations. Therefore, Baes et al. (1984) proposed using the same empirical

relationship developed by Chamberlain (1970) for other vegetation classes. Baes et al. (1984) developed

class-specific estimates of the empirical constant (() by forcing an exponential regression equation

through several points. Points included average and theoretical maximum estimates of Rp and Yp. The

following class-specific empirical constants (() were developed:

• Exposed produce = 0.0324

• Leafy vegetables = 0.0846

• Silage = 0.769

U.S. EPA (1994r) and U.S. EPA (1995e) proposed a default aboveground produce Rp value of 0.05,

based on a weighted average of class-specific Rp values. Specifically, class-specific Rp values were

calculated using the equation developed by Chamberlain (1970) and the following empirical constants:

• Leafy vegetables were assigned the same empirical constant (0.0846) developed by Baes

et al. (1984).
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• Fruits, fruiting vegetables, and legumes were assigned the empirical constant (0.0324)

originally developed by Baes et al. (1984) for “exposed produce.”

Vegetables and fruits included in each class are as follows:

• Fruits—apple, apricot, berry, cherry, cranberry, grape, peach, pear, plum/prune, and

strawberry

• Fruiting Vegetables—asparagus, cucumber, eggplant, sweet pepper, and tomato

• Legumes—snap beans

• Leafy Vegetables—broccoli, brussel sprouts, cauliflower, celery, lettuce, and spinach

The class-specific Rp values were then weighted by relative ingestion (by humans) of each class, to

determine a weighted average Rp value of 0.05. However, the produce classes and relative ingestion

values used by U.S. EPA (1994r) and U.S. EPA (1995e) to calculate and weight the Rp values are not

current with the U.S. EPA 1997 Exposure Factors Handbook (U.S. EPA 1997b). In addition, the overall

Rp value presented in U.S. EPA (1994r; 1995e) was based on limited information; subsequent revision to

U.S. EPA (1994r; 1995e) resulted in an overall Rp value of 0.2 (RTI 1997). 

For purposes of consistency, we combined the produce classes into two groups—exposed fruit and

exposed vegetables. We used the exposed produce empirical constant (() to calculate Rp. Since the

exposed vegetable category includes leafy and fruiting vegetables, we calculated Rp for leafy and fruiting

vegetables. We then calculated the exposed vegetable Rp by a weighted average based on productivity

(Yp) of leafy and fruiting vegetables, respectively. The relative ingestion rates used to determine an

average weighted Rp value we derived from the intake of homegrown produce discussion presented in the

1997 Exposure Factors Handbook (U.S. EPA 1997b). We recommend using the weighted average Rp

value of 0.39 as a default Rp value, because it represents the most current parameters, including standing

crop biomass and relative ingestion rates.

Recommended Value for:

Interception Fraction of the Edible Portion of Plant (Rp)

0.39
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Equation 5-15

Unweighted Rp and ingestion rates used for the weighting are as follows:

Aboveground Produce Class Rp Ingestion Rate (g DW/kg-day)

Exposed fruits 0.053 0.19

Exposed vegetables 0.982 0.11

One of the primary uncertainties associated with this variable is whether the algorithm developed by

Chamberlain (1970) and the empirical constants developed by Baes et al. (1984) for use in this algorithm

accurately represent aboveground produce. Specifically, Chamberlain (1970) based his algorithm on

studies of pasture grass rather than aboveground produce. Baes et al. (1984) noted that their approach to

developing class-specific Rp values is “at best ad hoc,” but stated that this approach was justified,

because the consequences of using Rp estimates that are independent of productivity are “serious.”

5.3.1.2 Plant Surface Loss Coefficient (kp)

U.S. EPA (1998c) identified several processes—including wind removal, water removal, and growth

dilution—that reduce the amount of contaminant that has deposited on plant surfaces. The term kp is a

measure of the amount of contaminant that is lost to these physical processes over time. U.S. EPA

(1998c) cited Miller and Hoffman (1983) for the following equation:

where

kp = Plant surface loss coefficient (yrG1

)

t

1/2 = Half-life (days)

365 = Units conversion factor (days/yr)

Miller and Hoffman (1983) reported half-life values ranging from 2.8 to 34 days for a variety of

contaminants on herbaceous vegetation. These half-life values converted to kp values of 7.44 to

90.36 (yr-1). U.S. EPA (1994r; 1998c) recommended a kp value of 18, based on a generic 14-day half-life

corresponding to physical processes only. The 14-day half-life is approximately the midpoint of the

range (2.8 to 34 days) estimated by Miller and Hoffman (1983).
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Lacking experimental data supporting chemical- and/or site-specific values, we recommend using a

default kp value of 18. This kp value is the midpoint of Miller and Hoffman’s (1983) range of values. 

Based on this range (7.44 to 90.36), plant concentrations could range from about 1.8 times higher to about

48 times lower than the plant concentrations, based on a kp value of 18. If chemical- or site-specific data

is available, you could also calculate site- and chemical-specific kp values using the equation in Miller

and Hoffman (1983). 

Recommended Value for:

Plant Surface Loss Coefficient (kp)

18 yr-1

The primary uncertainty associated with kp relates to its position as the sole surface loss term in Equation

5-14. As defined by Miller and Hoffman (1983) and U.S. EPA (1998c), kp only represents potential

losses from the physical processes listed above, not all potential losses (e.g. chemical degradation). 

However, information regarding chemical degradation of contaminants on plant surfaces is limited. 

Including chemical degradation processes would decrease half-life values and thereby increase kp values. 

Note that effective plant concentration decreases as kp increases. Therefore, using a kp value that does

not consider chemical degradation processes is protective.

In addition, there are uncertainties associated with the half-life values reported by Miller and Hoffman

(1983) with regard to how accurately these values represent the behavior of risk assessment COPCs on

aboveground produce. However, the relative impact of this second uncertainty is less than the omission

of chemical degradation processes.

5.3.1.3 Length of Plant Exposure to Deposition per Harvest of Edible Portion of Plant (Tp)

U.S. EPA (1990e; 1993f; 1994r; 1998c), and NC DEHNR (1997) recommended treating Tp as a constant,

based on the average period between successive hay harvests. Belcher and Travis (1989) estimated this

period at 60 days (0.164 years), which represents the length of time that aboveground vegetation (in this

case, hay) is exposed to contaminant deposition before being harvested. Calculate Tp as follows:
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Equation 5-16

Equation 5-17

where

Tp = Length of plant exposure to deposition per harvest of the edible portion

of plant (yr)

60 = Average period between successive hay harvests (days)

365 = Units conversion factor (days/yr)

As in previous guidance, we recommend using a Tp value of 0.164 year. 

Recommended Value for:

Length of Plant Exposure to Deposition per Harvest of Edible Portion of Plant (Tp)

0.164 years

The primary uncertainty associated with using 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 could be appropriate

to estimate a site-specific Tp value. The greater the difference between site-specific Tp and our

recommended value, the greater the effect on plant concentration estimates.

5.3.1.4 Standing Crop Biomass (Productivity) (Yp)

U.S. EPA (1998c) recommended that the best estimate of Yp is productivity, which Baes et al. (1984) and

Shor et al. (1982) define as follows:

where

Yhi = Harvest yield of the ith crop (kg DW)

Ahi = area planted to the ith crop (m2)

U.S. EPA (1994r) and NC DEHNR (1997) recommended using this equation and calculated a Yp value of

1.6 for aboveground produce, based on weighted average Yh and Ah values for four aboveground produce
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classes (fruits, fruiting vegetables, legumes, and leafy vegetables). Vegetables and fruits included in each

class were as follows:

• Fruits—apple, apricot, berry, cherry, cranberry, grape, peach, pear, plum/prune, and

strawberry

• Fruiting Vegetables—asparagus, cucumber, eggplant, sweet pepper, and tomato

• Legumes—snap beans

• Leafy Vegetables—broccoli, brussel sprouts, cauliflower, celery, lettuce, and spinach.

Class-specific Yp values were estimated using U.S. average Yh and Ah values for a variety of fruits and

vegetables for 1993 (USDA 1994a; USDA 1994b). Yh values were converted to dry weight using

average class-specific conversion factors (Baes et al. 1984). U.S. EPA (1994r and 1995e) calculated

class-specific Yp values and then used relative ingestion rates of each group to calculate the weighted

average Yp value of 1.6. However, the produce classes and relative ingestion values used by U.S. EPA

(1994r and1995e) to calculate and weight the Yp values are not current with the U.S. EPA 1997 Exposure

Factors Handbook. In addition, overall Yp value presented in U.S. EPA (1994r and U.S. EPA 1995e)

was based on limited information; subsequent revision to U.S. EPA (1994r and 1995e) has resulted in an

overall Yp value of 1.7 (RTI 1997). 

For consistency, we combined the produce classes into two groups—exposed fruit and exposed

vegetables. We derived the exposed vegetable Yp summing Yh values for leafy and fruiting vegetables

and dividing by the sum of Ah values for leafy and fruiting vegetables. We derived the relative ingestion

rates used to calculate an overall average weighted Yp value from the homegrown produce discussions

presented in the 1997 Exposure Factors Handbook (U.S. EPA 1997b). We recommend using the

weighted average Yp value of 2.24 as a default Yp value, because this value represents the most complete

and thorough information available.

Recommended Value for:

Standing Crop Biomass (Productivity) (Yp)

2.24
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Unweighted Yp and ingestion rates used for the weighting are as follows:

Aboveground Produce Class Yp Ingestion Rate (g DW/kg-day)

Exposed fruits 0.25 0.19

Exposed vegetables 5.66 0.11

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, you

can estimate the magnitude of the uncertainty introduced by the default Yp value.

5.3.2 Aboveground Produce Concentration Due to Air-to-Plant Transfer (Pv)

The method we recommend for estimating COPC concentrations in exposed and aboveground

produce due to air-to-plant transfer (Pv) was developed with consideration of items which

might limit the transfer of COPC concentrations from plant surfaces to the inner portions of the

plant. These limitations result from mechanisms responsible for 

• inhibiting the transfer of lipophilic COPCs (e.g., the shape of the produce); and 

• removing COPCs from the edible portion of the produce (e.g., washing, peeling, and

cooking).

We recommend using Equation 5-18 to calculate Pv. We further discuss the use of this equation in

Appendix B, Table B-2-8.
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Equation 5-18

Recommended Equation for Calculating:

Aboveground Produce Concentration Due to Air-to-Plant Transfer (Pv)

where

Pv = Concentration of COPC in the plant resulting from air-to-plant transfer 

(:g COPC/g DW)

Q = COPC emission rate (g/s)

Fv = Fraction of COPC air concentration in vapor phase (unitless)

Cyv = Unitized yearly average air concentration from vapor phase (:g-s/g-m3)

Bvag = COPC air-to-plant biotransfer factor ([mg COPC/g DW plant]/[mg COPC/g

air]) (unitless)

VGag = Empirical correction factor for aboveground produce (unitless)

Da = Density of air (g/m3)

Chapters 2 and 3 explain how we recommend quantifying the COPC emission rate (Q). Appendix A-2

describes how we recommend determining the COPC-specific parameters Fv and Bvag. Chapter 3

describes generating the modeled air parameter Cyv. As discussed below in Section 5.3.2.1, the

parameter VGag depends on the lipophilicity of the COPC. Appendix B further describes how we

recommend using Equation 5-18, including calculating Da

.

5.3.2.1 Empirical Correction Factor for Aboveground Produce (VGag)

The parameter VGag was incorporated into Equation 5-18 to address the potential to overestimate the

transfer of lipophilic COPCs 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 COPCs (log Kow greater than

4) to the center of the produce is not as likely as for non-lipophilic COPCs. As a result, the inner portions

will be less affected.

To address this issue, U.S. EPA (1994m) recommended an empirical correction factor (VGag) of 0.01 for

lipophilic COPCs to reduce estimated vegetable concentrations. The factor of 0.01 is based on a similar

correction factor (VGrootveg) for belowground produce. VGrootveg was estimated for unspecified vegetables

as follows:
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Equation 5-19

where

VGrootveg = Correction factor for belowground produce (g/g)

Mskin = Mass of a thin (skin) layer of belowground vegetable (g)

Mvegetable = Mass of the entire vegetable (g)

Assuming that the density of the skin and the whole vegetable are the same, this equation becomes a ratio

of the volume of the skin to that of the whole vegetable. U.S. EPA (1994m) assumed that the vegetable

skin is 0.03 centimeters, which is the leaf thickness of a broad-leaf tree, as was used in experiments

conducted by Riederer (1990). Using this assumption, U.S. EPA (1994m) calculated VGrootveg values of

0.09 and 0.03 for carrots and potatoes, respectively.

Based on the work by Wipf et al. (1982), U.S. EPA (1994m) identified other processes—such as peeling,

cooking, and cleaning—that further reduce the vegetable concentration. U.S. EPA (1994m)

recommended a VGrootveg value of 0.01 for lipophilic COPCs. These are less than the estimates of 0.09 and

0.03 for the carrots and potatoes mentioned earlier, but greater than the estimate would be if the

correction factor was adjusted for cleaning, washing, and peeling, as described by Wipf et al. (1982). 

Following this line of reasoning, U.S. EPA (1994m) recommended a lipophilic COPC VGag value of 0.01

for all aboveground produce except leafy vegetables. As with VGrootveg, U.S. EPA (1994m) noted that

assignment of this value is based on the consideration that it “should be less than estimated just based on

surface volume to whole fruit volume ratios.”

U.S. EPA (1994m) recommended a lipophilic COPC VGag of 1.0 for pasture grass because of a direct

analogy to exposed azalea and grass leaves (for which data were available). Pasture grass is described as

“leafy vegetation.” However, the leafy vegetable group, as defined in Section 5.3.1.1, is composed of

bulkier produce such as broccoli, brussel sprouts, cauliflower, celery, lettuce, and spinach. In addition,

the outer leaves of most of the produce in this category are removed during preparation. Therefore, the

VGag value of 1.0 for leafy vegetables is inappropriate and may overestimate COPC concentrations. A

default lipophilic COPC VGag value of 0.01 for leafy vegetables is more appropriate for leafy vegetables,

because the leafy vegetable category represents bulkier, more protected plants as compared to single
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leaves of grass blades. U.S. EPA (1994r) and NC DEHNR (1997) recommended a lipophilic COPC VGag

value of 0.01, for all classes of aboveground produce.

For COPCs with a log Kow greater than 4, we recommend using a lipophilic VGag value of 0.01 for all

aboveground exposed produce. For COPCs with a log Kow less than 4, we recommend using a VGag value

of 1.0, because we assume these COPCs pass more easily through the skin of produce.

Recommended Values for:

Empirical Correction Factor for Aboveground Produce (VGag)

0.01 for COPCs with a log Kow greater than 4

1.0 for COPCs with a log Kow less than 4

Uncertainty may be introduced by assuming VGag values for leafy vegetables (such as lettuce) and for

legumes (such as snap beans). Assuming a VGag value of 0.01 for legumes and leafy vegetables may

underestimate concentrations because these species often have a higher ratio of surface area to mass than

other bulkier fruits and fruiting vegetables, such as tomatoes.

5.3.3 Produce Concentration Due to Root Uptake (Pr)

Root uptake of contaminants from soil may contribute to COPC concentrations in

aboveground exposed produce, aboveground protected produce, and belowground produce. 

As in previous guidance (U.S. EPA 1994m; U.S. EPA 1994r; and U.S. EPA 1995e), we

recommend using Equations 5-20A and 5-20B to calculate Pr. We discuss the use of these

equations further in Appendix B.
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Equation 5-20A

Equation 5-20B

Recommended Equation for Calculating:

Produce Concentration Due to Root Uptake (Pr)

Exposed and protected aboveground produce:

Belowground produce:

where

Pr = Concentration of COPC in produce due to root uptake (mg/kg)

Cs = Average soil concentration over exposure duration (mg COPC/kg soil)

Br = Plant-soil bioconcentration factor for produce (unitless)

RCF = Root concentration factor (unitless)

VGrootveg = Empirical correction factor for belowground produce (unitless)

Kds = Soil/water partition coefficient (L/kg)

Appendix B and Section 5.2 explain how we recommend calculating Cs. Appendix A-2 describes how

we recommend calculating the COPC-specific parameters Br, RCF, and Kds. Similar to VGag and as

discussed in Section 5.3.2.1, VGrootveg is based on the lipophilicity of the COPC. 

Equation 5-20A is based on the soil-to-aboveground plant transfer approach developed by Travis and

Arms (1988). This approach is appropriate for evaluating exposed and protected aboveground produce;

however, it might not be appropriate for soil-to-belowground plant transfers. For belowground produce,

U.S. EPA (1994m) and U.S. EPA (1995e) recommended Equation 5-20B, which includes a root

concentration factor (RCF) developed by Briggs et al. (1982). RCF is the ratio of COPC concentration in

the edible root to the COPC concentration in the soil water. Since Briggs et al. (1982) conducted their

experiments in a growth solution, in order to use this equation you must divide the COPC soil

concentration (Cs) by the COPC-specific soil/water partition coefficient (Kds ) (U.S. EPA 1994m). 

As in U.S. EPA (1994m), we recommend using a VGrootveg value of 0.01 for lipophilic COPCs (log Kow

greater than 4) based on root vegetables like carrots and potatoes. A value of 0.01 appears to represent

the most complete and thorough information available. For COPCs with a log Kow less than 4, we

recommend a VGrootveg value of 1.0.
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Recommended Values for:

Empirical Correction Factor for Belowground Produce (VGrootveg)

0.01 for COPCs with a log Kow greater than 4

1.0 for COPCs with a log Kow less than 4

5.4 CALCULATING COPC CONCENTRATIONS IN BEEF AND DAIRY PRODUCTS

We generally recommend that you estimate COPC concentrations in beef tissue and milk

products on the basis of the amount of COPCs that cattle are assumed to consume through

their diet. The HHRAP assumes the cattle's diet consists of:

• forage (primarily pasture grass and hay), 

• silage (forage that has been stored and fermented), and 

• grain.

Additional contamination may occur through the cattle ingesting soil. The HHRAP calculates the total

COPC concentration in the feed items (e.g., forage, silage, and grain) as a sum of contamination occurring

through the following mechanisms:

• Direct deposition of particles—wet and dry deposition of particle phase COPCs onto

forage and silage (Section 5.4.1).

• Vapor transfer—uptake of vapor phase COPCs by forage and silage through foliage

(Section 5.4.2).

• Root uptake—root uptake of COPCs available from the soil and their transfer to the

aboveground portions of forage, silage, and grain (Section 5.4.3).

Feed items consumed by animals can be classified as exposed or protected, depending on whether they

have a protective outer covering. Because the outer covering on protected feed acts as a barrier, we

assume that there is negligible contamination of protected feed through deposition of particles and vapor

transfer. In the HHRAP, grain is classified as protected feed. As a result, we recommend that you

assume grain contamination occurs only through root uptake. We also recommend assuming that

contamination of exposed feed items, including forage and silage, occurs through all three mechanisms.
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Vapor

Transfer

(Section 5.4.2)

Wet and Dry

Deposition

of Particles

(Section 5.4.1)

Root Uptake

from Soil

(Section 5.4.3)

Forage and

Silage

Concentration

Grain

Concentration

COPC Concentration

in Beef & Dairy Products

Soil

Concentration

FIGURE 5-4

COPC CONCENTRATION IN BEEF AND DAIRY PRODUCTS The HHRAP assumes that

the amount of grain,

silage, forage, and soil

consumed varies between

dairy and beef cattle. 

Sections 5.4.4 (beef) and

5.4.5 (dairy) describe the

methods we recommend

to estimate consumption

rates and subsequent

COPC concentrations in

cattle. As in previous

guidance (U.S. EPA

1990e and 1994a; NC

DEHNR 1997), we

recommend assuming that 100 percent of the plant materials eaten by cattle were grown on soil

contaminated by emission sources. Therefore, we recommend assuming that 100 percent of the feed 

items are contaminated.

Appendix B, Tables B-3-1 through B-3-11, describe how we recommend calculating (1) the COPC

concentrations in soil and feed items (forage, silage, and grain) consumed by beef and dairy cattle, and

(2) the resulting COPC concentrations in beef and milk.

5.4.1 Forage and Silage Concentrations Due to Direct Deposition (Pd)

COPC concentrations in forage and silage result from wet and dry deposition onto exposed

plant surfaces; similar to aboveground produce (Section 5.3.1). Therefore, we recommend

also using Equation 5-14 to calculate Pd for forage and silage. We discuss calculating Pd

for Forage and silage further in Appendix B. Appendix A-2 explains how we recommend

calculating COPC-specific Fv values for forage and silage (i.e. exactly as they are calculated for

aboveground produce). Sections 5.4.1.1 through 5.4.1.4 describe how we recommend calculating Rp, kp,

Tp, and Yp for use in calculating forage and silage concentrations.
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5.4.1.1 Interception Fraction of the Edible Portion of Plant (Rp)

As discussed in Section 5.3.1.1, Chamberlain (1970) found a correlation between Rp and productivity, Yp

(standing crop biomass). This correlation is expressed in Equation 5-14A. 

Based on U.S. EPA (1994r and 1995b) and NC DEHNR (1997), we recommend using Equation 5-14 to

calculate Rp values for forage and silage.

Substituting the Baes et al. (1984) empirical constant (() value of 2.88 for pasture grass, and the standing

crop biomass value of 0.24 kg DW/m2 (these variables are discussed in Section 5.3.1.1) into Equation 5-

14, the forage-specific Rp is 0.5. Substituting the Baes et al. (1984) empirical constant (() value of 0.769

for silage, and the standing crop biomass value of 0.8 kg DW/m2

 into Equation 5-14, the silage-specific

Rp value is 0.46.

Recommended Value for:

Interception Fraction of the Edible Portion of Plant (Rp)

Forage = 0.5

Silage = 0.46

Several uncertainties are associated with the Rp variable:

• The empirical relationship developed by Chamberlain (1970) is based on a study of

pasture grass, and therefore may not accurately represent site-specific silage types. 

• The empirical constant for silage developed by Baes et al. (1984) used in Chamberlain’s

empirical relationship may also fail to accurately represent site-specific silage types. 

• The range of empirical constants recommended by Baes et al. (1984) for pasture grass

does not result in a significant range of estimated Rp values for forage (the calculated Rp

range is 0.42 to 0.54). Therefore, using the empirical constant midpoint (2.88 for pasture

grass) does not significantly affect the Rp value and the resulting estimate of plant COPC

concentration.

5.4.1.2 Plant Surface Loss Coefficient (kp)

We recommend using Equation 5-15 (Section 5.3.1.2) to calculate the plant surface loss coefficient kp for

aboveground produce. The kp factor is derived in the same manner for cattle forage and silage. The

uncertainties of kp for cattle forage and silage are similar to the uncertainties for aboveground produce.
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Equation 5-21

5.4.1.3 Length of Plant Exposure to Deposition per Harvest of the Edible Portion of Plant (Tp)

As discussed in Section 5.3.1.3, the HHRAP treats Tp as a constant, based on the average period between

successive hay harvests. This period, which Belcher and Travis (1989) estimated at 60 days, represents

the length of time that aboveground vegetation (in this case, hay) would be exposed to particle deposition

before being harvested. We used Equation 5-16 (Section 5.3.1.3), to calculate a Tp of 0.16 year for cattle

silage.

For cattle forage, we modified Equation 5-16 to consider the average of :

1. the average period between successive hay harvests, and 

2. the average period between successive grazing. 

Based on Belcher and Travis (1989), the we assumed the average period between hay harvests is 60 days,

and the average period between successive grazing is 30 days. We therefore calculated Tp as follows: 

Recommended Value for:

Plant Exposure Length to Deposition per Harvest of the Edible Portion of Plant (Tp)

Forage = 0.12 yr

Silage = 0.16 yr

The primary uncertainties associated with Tp are similar to those for aboveground produce, as discussed

in Section 5.3.1.3.

5.4.1.4 Standing Crop Biomass (Productivity) (Yp)

As discussed in Section 5.3.1.4, U.S. EPA (1998c) stated that the best estimate of Yp is productivity, as

defined in Equation 5-17. Consequently, under this approach, you would consider dry harvest yield (Yh)

and area harvested (Ah).
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We calculated forage Yp as a weighted average of the calculated pasture grass and hay Yp values. We

assumed weightings of 0.75 for forage and 0.25 for hay. The weightings are 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). We assumed an unweighted pasture grass Yp of 0.15 kg DW/m2

 (U.S. EPA

1994r; U.S. EPA 1994m). We then calculated an unweighted hay Yp of 0.5 kg DW/m2 using Equation

5-17 and the following Yh and Ah values:

Yh = 1.22×1011 kg DW, calculated from the 1993 U.S. average wet weight Yh of

1.35×1011 kg (USDA 1994b) and a conversion factor of 0.9 (Fries 1994).

Ah = 2.45×1011 m2

, the 1993 U.S. average for hay (USDA 1994b).

The unweighted pasture grass and hay Yp values were multiplied by their weighting factors (0.75 and

0.25, respectively), and summed to calculate the recommended weighted forage Yp of 0.24 kg DW/m2

.

We recommend assuming a production-weighted U.S. average Yp of 0.8 kg DW/m2

 for silage (Shor, et al.

1982).

Recommended Values for:

Standing Crop Biomass (Productivity) (Yp)

Forage = 0.24 kg DW/m2

Silage = 0.8 kg DW/m2

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, it’s

feasible to estimate the magnitude of the uncertainty introduced by the default Yp value. 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) could be adjusted to reflect site-specific conditions, as appropriate.

5.4.2 Forage and Silage Concentrations Due to Air-to-Plant Transfer (Pv)

We recommend using Equation 5-18 (Section 5.3.2) to calculate the COPC concentration in aboveground

produce resulting from air-to-plant transfer (Pv). Pv is calculated for cattle forage and silage similarly to

the way that it’s calculated for aboveground produce. We provide a detailed discussion of Pv in Section

5.3.2. We present differences in VGag values for forage and silage, as compared to the values for

aboveground produce described in Section 5.3.2.1, in Section 5.4.2.1. We discuss calculating Pv further
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in Appendix B. Appendix A-2 explains how we recommend calculating COPC-specific Bv values for

forage and silage (i.e. the same as they are calculated for aboveground produce).

5.4.2.1 Empirical Correction Factor for Forage and Silage (VGag)

Please Section 5.3.2.1 for a detailed, general introduction to VGag. Using such a factor while estimating

COPC concentrations specifically for forage and silage assumes that there is insignificant translocation of

COPCs deposited on the surface of bulky silage to the inner parts of the vegetation. Applying a silage

VGag would be relevant if the silage can’t be characterized as leafy (e.g., if grain is used as silage). As a

point of clarification, forage and silage are considered vegetative plant parts, and grains are considered

reproductive plant parts.

U.S. EPA (1994m) didn’t recommend a VGag value for silage. NC DEHNR (1997) recommended a VGag

factor of 0.5 for bulky silage but didn’t present a specific rationale for this value. U.S. EPA (1995b)

noted that a volume ratio of outer whole surface area to volume of vegetation could be used to assign a

silage VGag value, if one knew the proportions of each type of vegetation of which silage consisted. In the

absence of specific data concerning the quantities of different silage material (e.g., hay and grain), U.S.

EPA (1995b) recommended assuming a VGag of 0.5 for silage without rigorous justification.

We recommend using 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.

Recommended Values for:

Empirical Correction Factor for Forage and Silage (VGag)

Forage = 1

Silage = 0.5

5.4.3 Forage, Silage, and Grain Concentrations Due to Root Uptake (Pr)

We recommend using Equations 5-20A and 5-20B (Section 5.3.3) to calculate the COPC

concentration in aboveground and belowground produce resulting from root uptake. Pr is

calculated for cattle forage, silage, and grain in the same way that it is calculated for

aboveground produce, except that we recommend using forage/silage- and grain-specific
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Equation 5-22

bioconcentration factors (Brforage and Brgrain respectively). Appendix A-2 explains how we recommend

calculating COPC-specific Br values for forage and silage (i.e. exactly as it’s calculated for aboveground

produce). We provide a detailed discussion on how we recommend calculating Pr in Section 5.3.3. We

further discuss the calculation of Pr in Appendix B.

5.4.4 Beef Concentration Resulting from Plant and Soil Ingestion (Abeef)

As in U.S. EPA (1995h), we recommend using Equation 5-22 to calculate COPC concentration

in beef tissue (Abeef). The equation was modified from an equation presented in U.S. EPA

(1990c), U.S. EPA (1994r), U.S. EPA (1995b), and NC DEHNR (1996) by introducing a metabolism

factor (MF). Equation 5-22 calculates the daily amount of a COPC 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 COPC (mg/day) into an animal COPC tissue

concentration (mg COPC/kg tissue). We further discuss using this equation in Appendix B, Table 3-10. 

Recommended Equation for Calculating:

Concentration of COPC in Beef (Abeef)

where

Abeef = Concentration of COPC in beef (mg COPC/kg FW tissue)

Fi = Fraction of plant type i grown on contaminated soil and ingested by the animal

(cattle) (unitless)

Qpi = Quantity of plant type i eaten by the animal (cattle) per day (kg DW plant/day)

Pi = Concentration of COPC 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 COPC/kg soil)

Bs = Soil bioavailability factor (unitless)

Babeef = COPC biotransfer factor for beef (day/kg FW tissue)

MF = Metabolism factor (unitless)

Sections 5.4.4.1 through 5.4.4.7 describe the parameters Fi

, Qpi

, Pi

, Qs, Cs, Bs, and MF, respectively. 

Appendix A-2 explains how we recommend calculating the COPC-specific parameter Babeef.
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5.4.4.1 Fraction of Plant Type i Grown on Contaminated Soil and Eaten by the Animal (Cattle)(Fi

)

As in U.S. EPA (1990e and 1994r), and NC DEHNR (1997), we recommend assuming that 100 percent

of the plant materials eaten by cattle were grown on soil contaminated by the emission sources being

evaluated. This assumption translates to a default value of 1.0 for Fi.

Recommended Value for:

Fraction of Plant Type i Grown on Contaminated Soil and Eaten by the Animal (Cattle) (Fi

)

1

5.4.4.2 Quantity of Plant Type i Eaten by the Animal (Cattle) Each Day (Qpi)

The daily quantity of plants eaten by cattle can be estimated (kg DW/day) for each category of plant feed. 

U.S. EPA (1994r and 1998c) and NC DEHNR (1997) recommended including forage, silage, and grain

feeds in this estimate. 

NC DEHNR (1997) recommended plant ingestion rates for the cattle of either subsistence beef farmers or

typical beef farmers. Subsistence beef farmers rely on a higher percentage of forage and silage to feed

cattle, whereas typical beef farmers rely on greater amounts of grain to feed cattle. U.S. EPA (1990e) and

U.S. EPA (1994r) identified plant ingestion rates only for subsistence farmers. The following daily

quantities of forage, grain, and silage eaten by cattle were recommended by NC DEHNR (1997), U.S.

EPA (1994r and 1990e), and Boone et al. (1981):
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Source Forage

(kg DW/day)

Grain

(kg DW/day)

Silage

(kg DW/day)

References

NC DEHNR (1997)

Subsistence Farmer Beef

Cattle

8.8 0.47 2.5 Boone et al. (1981)

NAS (1987)

NC DEHNR (1997)

Typical Farmer Beef

Cattle

3.8 3.8 1.0 Rice (1994)

U.S. EPA (1994r)

Subsistence Farmer Beef

Cattle

8.8 Not reported Not reported Boone et al. (1981)

NAS (1987)

U.S. EPA (1990e)

Subsistence Farmer Beef

Cattle

8.8 0.47 2.5 Boone et al. (1981)

McKone and Ryan

(1989)

Boone et al. (1981) 8.87 1.9 2.5 Boone et al. (1981)

With the exception of a higher grain ingestion rate, Boone et al. (1981) rates are consistent with those

recommended by U.S. EPA (1990e and 1994r), and NC DEHNR (1997). For typical farmer beef cattle,

NC DEHNR (1997) cites Rice (1994) as a reference for the Qpi variables and notes that the values include

grain supplemented during the growing phase for beef cattle.

U.S. EPA (1990e) noted that McKone and Ryan (1989) reported an average total ingestion rate of

12 kg DW/day for the three plant feeds, which is consistent with the total recommended by U.S. EPA

(1990e) and NC DEHNR (1997) (forage, grain, and silage total of 11.8 kg DW/day). U.S. EPA (1994r)

and NC DEHNR (1997) also noted that NAS (1987) reported a daily dry matter intake that is 2 percent of

an average beef cattle body weight of 590 kilograms. This results in a daily total intake rate of

11.8 kg DW/day. NAS (1987) reported that a nonlactating cow eats dry matter equivalent to 2 percent of

its body weight.

We recommend using 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.
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Equation 5-23

Recommended Values for:

Quantity of Plant Type i Eaten by the Animal (Cattle) Each Day (Qpi)

Forage = 8.8 kg DW/day

Silage = 2.5 kg DW/day

Grain = 0.47 kg DW/day

The principal uncertainty associated with Qpi

 is the variability between forage, silage, and grain ingestion

rates for cattle. 

5.4.4.3 Concentration of COPC in Plant Type i Eaten by the Animal (Cattle) (Pi)

We generally recommend using Equation 5-23 to calculate the total COPC concentration in forage, silage,

and grain. We recommend deriving values for Pd, Pv, and Pr for each type of feed by using Equations

5-14, 5-18, and 5-20, respectively.

Recommended Equation for Calculating:

Concentration of COPC in Plant Type i Eaten by the Animal (Cattle) (Pi)

where

Pi = Concentration of COPC in each plant type i eaten by the animal (mg

COPC/kg DW)

Pd = Plant concentration due to direct deposition (mg COPC/kg DW)

Pv = Plant concentration due to air-to-plant transfer (mg COPC/kg DW)

Pr = Plant concentration due to root uptake (mg COPC/kg DW)

This equation is further described in Appendix B.

5.4.4.4 Quantity of Soil Eaten by the Animal (Cattle) Per Day (Qs)

Additional cattle contamination occurs through ingestion of soil. 

NC DEHNR (1997) and U.S. EPA (1994r) recommended a soil ingestion rate for subsistence beef cattle

of 0.5 kg/day. This rate is based on Fries (1994). U.S. EPA (1994r) and NC DEHNR (1997) noted that
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Fries (1994) reported soil ingestion to be 4 percent of the total dry matter intake. NAS (1987) was also

referenced. NAS (1987) cited an average beef cattle weight of 590 kg, and a daily dry matter intake rate

(nonlactating cows) of 2 percent of body weight. This results in a daily dry matter intake rate of 11.8 kg

DW/day and a daily soil ingestion rate of about 0.5 kg/day. U.S. EPA (1990e) reported a soil ingestion

rate that is 3 percent of the forage intake rate of 8.8 kg DW/day, resulting in a daily soil ingestion rate of

approximately 0.3 kg/day. Simmonds and Linsley (1981) and Thornton and Abrams (1983) were cited as

the references for this assumption.

We recommend using 0.5 kg/day for the quantity of soil ingested by the animal (cattle).

Recommended Value for:

Quantity of Soil Ingested by the Animal (Cattle) Per Day (Qs)

0.5 kg/day

5.4.4.5 Average Soil Concentration Over Exposure Duration (Cs)

We recommend using Equations 5-1C, 5-1D, and 5-1E to calculate the COPC concentration in soil as

discussed in Section 5.2.1. Also, Appendix B further describes how we recommend calculating the soil

concentration.

Please Note: You might need to generate soil concentration estimates for grain separate

from those for forage and silage. Currently, the HHRAP assumes that forage and silage

are grown on untilled land, and grain is grown on tilled land. We highly recommend that

your Cs calculations include the appropriate Zs (1 for untilled land, 20 for tilled land). 

5.4.4.6 Soil Bioavailability Factor (Bs)

The efficiency of transfer from soil may differ from the efficiency of transfer from plant material for some

COPCs. If the transfer efficiency is lower for soils, then the ratio would be less than 1.0. If it is equal to

or greater than that of vegetation, the Bs value would be equal to or greater than 1.0.

Until more COPC-specific data becomes available for this parameter, we recommend a default value of 1

for Bs. 
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Recommended Values for:

Soil Bioavailability Factor (Bs)

1.0

5.4.4.7 Metabolism Factor (MF)

The metabolism factor (MF) estimates the amount of COPC that remains in fat and muscle. Based on a

study by Ikeda et al. (1980), U.S. EPA (1995h) used a COPC-specific MF to account for metabolism in

animals and humans. Evidence indicates BEHP is more readily metabolized and excreted by mammalian

species than other contaminants (ATSDR 1987). As in U.S. EPA (1995h), we recommend a MF of 0.01

for bis(2-ethylhexyl)phthalate (BEHP). Lacking data to support derivation of other chemical-specific

MFs, we recommend using a MF of 1.0 for all chemicals other than BEHP. Using the recommended

values for this variable, MF has no quantitative effect on Abeef (with the exception of BEHP).

Recommended Values for:

Metabolism Factor (MF)

bis(2-ethylhexyl)phthalate (BEHP) = 0.01

All other COPCs = 1.0

The MF presented above for BEHP 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 guidance are intake driven, using an MF applies only to estimating COPC concentrations

in food sources used in evaluating indirect human exposure, including ingestion of beef, milk, and pork. 

In summary, an MF is not applicable for direct exposures to air, soil, or water, or to ingestion of produce,

chicken, or fish.

5.4.5 COPC Concentration In Milk Due to Plant and Soil Ingestion (Amilk)

We recommend modifying Equation 5-22 (Section 5.4.4) to calculate COPC milk concentrations 

(Amilk), as follows:
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Equation 5-24

Recommended Equation for Calculating:

Concentration of COPC in Milk (Amilk)

where

Amilk = Concentration of COPC in milk (mg COPC/kg milk)

Fi = Fraction of plant type i grown on contaminated soil and ingested by the animal

(dairy cattle) (unitless)

Qpi = Quantity of plant type i eaten by the animal (dairy cattle) each day (kg DW

plant/day)

Pi = Concentration of COPC 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 COPC/kg soil)

Bs = Soil bioavailability factor (unitless)

Bamilk = COPC biotransfer factor for milk (day/kg WW tissue)

MF = Metabolism factor (unitless)

Appendix A-2 explains how we recommend calculating the COPC-specific parameter Bamilk. The

discussion in Section 5.4.4 of the variables Fi, Qpi, Pi, 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.

We recommend using Equation 5-24 to estimate Amilk. Using Equation 5-24 is described further in

Appendix B, Table B-3-11.

5.4.5.1 Fraction of Plant Type i Grown on Contaminated Soil and Eaten by the Animal (Dairy

Cattle) (Fi)

The calculation of Fi for dairy cattle is identical to that for beef cattle (Section 5.4.4.1).

5.4.5.2 Quantity of Plant Type i Eaten by the Animal (Dairy Cattle) Per Day (Qpi)

As discussed in Section 5.4.4.2, 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
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differently than for beef cattle. We generally recommend estimating the daily quantity of feed consumed

by cattle on a dry weight basis for each category of plant feed. 

NC DEHNR (1997) recommended using plant ingestion rates for either subsistence dairy farmer or

typical dairy farmer cattle. In addition, subsistence dairy farmers rely on a higher percentage of forage

and silage to feed cattle, whereas typical dairy farmers rely on greater amounts of grain to feed cattle. 

U.S. EPA (1990e and 1994r) identified plant ingestion rates only for subsistence farmers. 

The following daily quantities of forage, grain, and silage eaten by dairy cattle were recommended by NC

DEHNR (1997), U.S. EPA (1994r), U.S. EPA (1990e), and Boone et al. (1981):

Source Forage

(kg/day DW)

Grain

(kg/day DW)

Silage

(kg/day DW)

References

NC DEHNR (1997)

Subsistence Dairy

Farmer Cattle

13.2 3.0 4.1 Boone et al. (1981)

NAS (1987)

NC DEHNR (1997)

Typical Dairy Farmer

Cattle

6.2 12.2 1.9 Rice (1994)

U.S. EPA (1994r)

Subsistence Dairy

Farmer Cattle

13.2 Not reported Not reported Boone et al. (1981)

NAS (1987)

U.S. EPA (1990e)

Subsistence Dairy

Farmer Cattle

11.0 2.6 3.3 Boone et al. (1981)

McKone and Ryan

(1989)

Boone et al. (1981) 11.0 2.6 3.3 Boone et al. (1981)

U.S. EPA (1990e) noted that McKone and Ryan (1989) reports an average total ingestion rate of

17 kg/day DW for the three plant feeds, which is consistent with the total ingestion rate recommended by

U.S. EPA (1990e). U.S. EPA (1994r) and NC DEHNR (1997) noted that NAS (1987) reports a daily dry

matter intake that is 3.2 percent of an average dairy cattle body weight of 630 kilograms. This results in a

daily total intake rate of approximately 20 kg/day DW, which is consistent with the average total

ingestion rates for the three plant feeds recommended by U.S. EPA (1994r) and NC DEHNR (1997) . 

NAS (1987) reported that dairy cows eat dry matter equivalent to 3.2 percent of their body weight; the
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630-kilogram average dairy cow body weight was not confirmed. U.S. EPA (1995b) also cited a feed

ingestion rate of 20 kg/day DW, citing U.S. EPA (1993c). 

Based on more recent references (NAS 1987; U.S. EPA 1993c) which recommend a feed ingestion rate of

20 kg/day DW, we recommend a default total ingestion rate of 20 kg DW/day for dairy cattle. 

Recommended Values for:

Quantity of Plant Type i Eaten by the Animal (Dairy Cattle) Per Day (Qpi

)

Forage = 13.2 kg DW/day

Silage = 4.1 kg DW/day

Grain = 3.0 kg DW/day

Uncertainties associated with estimating Qpi

 include estimating forage, grain, and silage ingestion rates,

which will vary from site to site. Assuming uniform contamination of plant materials consumed by cattle

also introduces uncertainty.

5.4.5.3 Concentration of COPC in Plant Type i Eaten by the Animal (Dairy Cattle) (Pi

)

The estimation of Pi

 for dairy cattle is identical to that for beef cattle (Section 5.4.4.3).

5.4.5.4 Quantity of Soil Eaten by the Animal (Dairy Cattle) Per Day (Qs)

As discussed in Section 5.4.4.4, contamination of dairy cattle also results from the ingestion of soil. We

generally recommend the following soil ingestion rate for dairy cattle: 

Recommended Values for:

Quantity of Soil Eaten by the Animal (Dairy Cattle) Per Day (Qs)

0.4 kg/day

U.S. EPA (1994r) and NC DEHNR (1997) recommended a soil ingestion rate of 0.4 kg/day for dairy

cattle, based on Fries (1994). U.S. EPA (1994r) and NC DEHNR (1997) noted that Fries (1994) reported

soil ingestion rates as 2 percent of the total dry matter intake. NAS (1987) was also referenced, which
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reported an average dairy cattle weight of 630 kilograms and a daily dry matter intake rate (nonlactating

cows) of 3.2 percent of body weight. This resulted in a daily dry matter intake rate of 20 kg/day DW, and

a daily soil ingestion rate of approximately 0.4 kg/day. NC DEHNR (1997) recommended a soil

ingestion rate of 0.2 kg/day for the cattle of typical dairy farmers, citing Rice (1994). U.S. EPA (1990e)

reported soil ingestion rates as 3 percent of the forage intake rate. U.S. EPA (1990e) assumed that the

more protective forage intake rate of 13.2 kg/day DW results in a daily soil ingestion rate of about

0.4 kg/day. Simmonds and Linsley (1981) and Thornton and Abrams (1983) were cited as the references

for this assumption.

Uncertainties associated with Qs include the lack of current empirical data to support soil ingestion rates

for dairy cattle. Assuming uniform contamination of soil ingested by cattle also adds uncertainty.

5.4.5.5 Average Soil Concentration Over Exposure Duration (Cs)

The calculation of Cs for dairy cattle is the same as for beef cattle (Section 5.4.4.5).

Please Note: You might need to generate soil concentration estimates for grain separate

from those for forage and silage. Currently, the HHRAP assumes that forage and silage

are grown on untilled land, and grain is grown on tilled land. We highly recommend

making sure that your Cs calculations include the appropriate Zs (2 for untilled land, 20

for tilled land). 

5.4.5.6 Soil Bioavailability Factor (Bs)

The calculation of Bs for dairy cattle is the same as for beef cattle (Section 5.4.4.6).

5.4.5.7 Metabolism Factor (MF)

The recommended values for MF are identical to those we recommend for beef cattle (Section 5.4.4.7).

5.5 CALCULATING COPC CONCENTRATIONS IN PORK

Under the approach recommended in this guidance, COPC concentrations in pork tissue are

estimated on the basis of the amount of COPCs that swine consume through a diet consisting

of silage and grain. Additional COPC contamination of pork tissue may occur through their

ingestion of soil.
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FIGURE 5-5

COPC CONCENTRATION IN PORK

Equation 5-25

Equation 5-22 (Section 5.4.4) describes how

we recommend calculating COPC

concentration in beef cattle (Abeef). We suggest

modifying Equation 5-22 to calculate COPC

concentrations in swine (Apork), as follows:

Recommended Equation for Calculating:

Concentration of COPC in Pork (Apork)

where

Apork = Concentration of COPC in pork (mg COPC/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 i eaten by the animal (swine) each day (kg DW

plant/day)

Pi = Concentration of COPC 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 COPC/kg soil)

Bs = Soil bioavailability factor (unitless)

Bapork = COPC biotransfer factor for pork (day/kg FW tissue)

MF = Metabolism factor (unitless)

Appendix A-2 explains how we recommend calculating the COPC-specific parameter Bapork. The

discussions in Section 5.4.5 of the variables Fi, Qpi, Pi, Qs, Cs and MF for beef cattle generally apply to

the corresponding variables for pork. However, some different assumptions are made for pork. These

differences are summarized in the following subsections.
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We generally recommend using Equation 5-25 to calculate COPC pork concentrations (Apork). This

equation is further described in Appendix B, Table B-3-12. 

5.5.1 Fraction of Plant Type i Grown on Contaminated Soil and Eaten by the Animal (Swine) (Fi

)

The calculation of Fi for pork is identical to that for beef cattle (Section 5.4.4.1).

5.5.2 Quantity of Plant Type i Eaten by the Animal (Swine) Each Day (Qpi

)

Section 5.4.4.2 discusses estimating the daily quantity of forage, silage, and grain feed consumed by beef

cattle for each feed category. However, daily ingestion rates for pork are estimated differently than for

beef cattle. U.S. EPA (1994r and 1998c), and NC DEHNR (1997) recommended only including silage

and grain feeds to estimate daily plant quantity eaten by swine. Because swine are not grazing animals,

they are assumed not to eat forage (U.S. EPA 1998c). We therefore generally recommend estimating the

daily quantity of plant feeds (kilograms of DW) consumed by swine for each category of plant feed. 

U.S. EPA (1990e) and NC DEHNR (1997) recommended grain and silage ingestion rates for swine of 3.0

and 1.3 kg DW/day, respectively. NC DEHNR (1997) references U.S. EPA (1990e) as the source of

these ingestion rates. U.S. EPA (1990e) reported total dry matter ingestion rates for hogs and lactating

sows as 3.4 and 5.2 kg DW/day, respectively. U.S. EPA (1990e) cites Boone et al. (1981) as the source

of the ingestion rate for hogs, and NAS (1987) as the source of the ingestion rate for a lactating sow. 

Boone et al. (1981) reported a grain ingestion rate of 3.4 kg DW/day for a hog. NAS (1987) reported an

average ingestion rate of 5.2 kg DW/day for a lactating sow. U.S. EPA (1990e) recommended using the

average of these two rates (4.3 kg DW/day). 

U.S. EPA (1990e) 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. U.S. EPA (1990e)

cited U.S. EPA (1982b) as the source of the grain and silage dietary fractions. U.S. EPA (1995b)

recommended an ingestion rate of 4.7 kg DW/day for a swine, referencing NAS (1987). NAS (1987)

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. 
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Recommended Values for:

Quantity of Plant Type i Eaten by the Animal (Swine) Each Day (Qpi

)

Grain = 3.3 kg DW/day 

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. You could use site-specific data to mitigate this uncertainty. In addition, assuming

uniform contamination of the plant materials consumed by swine produces some uncertainty.

5.5.3 Concentration of COPC in Plant Type i Eaten by the Animal (Swine) (Pi

)

The suggested calculation of Pi

 for pork is identical to that for beef cattle (Section 5.4.4.3).

5.5.4 Quantity of Soil Eaten by the Animal (Swine) Each Day (Qs)

As discussed in Section 5.4.4.4, additional contamination of swine results from ingestion of soil. The

following Qs values were recommended by earlier guidance:

Guidance Quantity of Soil Eaten by Swine Each Day (Qs)

U.S. EPA (1990e) Stated that sufficient data are not available to estimate swine soil

ingestion rates.

NC DEHNR (1997) 0.37 kg/day 

Estimated by assuming a soil intake that is 8% of the plant

ingestion rate of 4.3 kg DW/day). U.S. EPA (1993f) was cited as

the reference for the soil ingestion rate of 8 percent of dry matter

intake.

U.S. EPA (1998c) Cites a companion “Parameters Guidance Document” for detailed

recommendations on Q. The “Parameters” document has not been

published.

As in NC DEHNR (1997), we recommend the following soil ingestion rate for swine:
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Recommended Value for:

Quantity of Soil Eaten by the Animal (Swine) Each Day (Qs)

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 assuming uniform contamination of the soil ingested by swine.

5.5.5 Average Soil Concentration Over Exposure Duration (Cs)

Our suggested calculation of Cs for pork is the same as for beef cattle (Section 5.4.4.5).

Please Note: You might need to generate soil concentration estimates for grain separate

from those for silage. We recommend assuming that silage is grown on untilled land, and

grain is grown on tilled land. We highly recommend that you make sure that your Cs

calculations include the appropriate Zs (2 for untilled land, 20 for tilled land). 

5.5.6 Soil Bioavailability Factor (Bs)

Our suggested calculation of Bs for pork is the same as for beef cattle (Section 5.4.4.6)

5.5.7 Metabolism Factor (MF)

Our recommended values for MF are identical to those we recommended for beef cattle (Section 5.4.4.7).

5.6 CALCULATING COPC CONCENTRATIONS IN CHICKEN AND EGGS

Under the approach outlined in this guidance document, estimates of the COPC

concentrations in chicken and eggs are based on the amount of COPCs that chickens

consume through ingestion of grain and soil. We recommend assuming that the uptake of

COPCs via inhalation and via ingestion of water are insignificant relative to other pathways. The

HHRAP assumes that chickens are housed in a typical manner that allows contact with soil. Because of

this, chickens are assumed to consume 10 percent of their diet as soil. Assuming 10 percent is consistent

with the study from which the biotransfer factors were obtained (Stephens et al. 1995). We recommend

assuming that the remainder of the diet (90 percent) consists of grain grown at the exposure scenario
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Soil

Concentration

Root Uptake

from Soil

Grain

Concentration

COPC

Concentration

in Chicken and Egg

FIGURE 5-6

COPC CONCENTRATION IN CHICKEN & EGGS

location. Therefore, it’s appropriate to assume 100 percent of the grain consumed is contaminated. The

equations don’t account for the uptake of COPCs via ingestion of contaminated insects and other

organisms (e.g., worms, etc.), which may also contribute to the ingestion of COPCs. This may be a

limitation, depending on the site-specific conditions under which the chickens are raised. 

We generally recommend using the

algorithm for aboveground produce

described in Section 5.3 to estimate the

COPC concentration in grain. Grain is

considered to be protected from direct

deposition of particles, and vapor transfer. 

This approach considers only contamination

due to root uptake of COPCs in calculating

COPC concentrations in grain. Our

recommended equations for calculating

concentrations in chicken and eggs are

presented in Appendix B. The method we

used to derive biotransfer factors, and the

COPC-specific values for chicken and eggs are presented in Appendix A-2.

As in NC DEHNR (1997), we recommend using Equation 5-26 to calculate COPC concentrations in

chicken and eggs (Stephens et al. 1995). We generally recommend calculating COPC concentrations in

chicken and eggs separately. Parameters and variables in Equation 5-26 are further described in

Appendix B, Tables B-3-13 and B-3-14.
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Equation 5-26

Recommended Equation for Calculating:

Concentration of COPC in Chicken and Eggs (Achicken or Aegg)

where

Achicken = Concentration of COPC in chicken (mg COPC/kg FW tissue)

Aegg = Concentration of COPC in eggs (mg COPC/kg FW tissue)

Fi = Fraction of plant type i (grain) grown on contaminated soil and ingested by the

animal (chicken)(unitless)

Qpi = Quantity of plant type i (grain) eaten by the animal (chicken) each day (kg

DW plant/day)

Pi = Concentration of COPC 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 COPC/kg soil)

Bs = Soil bioavailability factor (unitless)

Bachicken = COPC biotransfer factor for chicken (day/kg FW tissue)

Baegg = COPC biotransfer factor for eggs (day/kg FW tissue)

Appendix A-2 explains how we recommend determining the COPC-specific parameters Bachicken and Baegg. 

The remaining parameters are discussed in Appendix B and in the following subsections.

5.6.1 Fraction of Plant Type i Grown on Contaminated Soil and Eaten by the Animal

(Chicken)(Fi

)

The calculation of Fi for chicken is identical to that for beef cattle (Section 5.4.4.1).

5.6.2 Quantity of Plant Type i Eaten by the Animal (Chicken) Each Day (Qpi

)

Section 5.4.4.2 discusses estimating the daily quantity of forage, silage, and grain feed consumed by beef

cattle for each feed category. However, daily ingestion rates for chicken are estimated differently than for

beef cattle. NC DEHNR (1997) recommended that only grain feeds be included in this estimate. Because

chickens are not grazing animals, they are assumed not to eat forage (U.S. EPA 1998c). Chickens are

similarly assumed not to consume any silage. We recommend only estimating the daily quantity of plant

feeds (kilograms of DW) consumed by chicken (Qp) for grain feed.
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Equation 5-27

As in Ensminger (1980), Fries (1982), and NAS (1987), we recommend using the following ingestion

rate:

Recommended Value for:

Quantity of Plant Type i Eaten by the Animal (Chicken) Each Day (Qpi)

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, assuming uniform contamination of plant materials consumed by chicken produces

some uncertainty.

5.6.3 Concentration of COPC in Plant Type i Eaten by the Animal (Chicken) (Pi)

The total COPC concentration is the COPC concentration in grain. We recommend using Equation 5-27

to calculate Pi. This equation is further described in Appendix B.

Recommended Equation for Calculating:

Concentration of COPC in Plant Type i Eaten by the Animal (Chicken) (Pi)

where

Pi = Concentration of COPC in each plant type i eaten by the animal (mg

COPC/kg DW)

Pr = Plant concentration due to root uptake (mg COPC/kg DW)

We generally recommend calculating plant concentration due to root uptake (Pr) using Equation 5-20, as

discussed in Section 5.3.3.

5.6.4 Quantity of Soil Eaten by the Animal (Chicken) Each Day (Qs)

COPC concentration in chickens also results from intake of soil. As discussed earlier, The HHRAP

assumes that chickens consume 10 percent of their total diet as soil, a percentage that is consistent with

the study from Stephens et al. (1995). We recommend the following soil ingestion rate for chicken:
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Recommended Value for:

Quantity of Soil Eaten by the Animal (Chicken) Each Day (Qs)

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 assuming uniform contamination of soil ingested by chicken.

5.6.5 Average Soil Concentration Over Exposure Duration (Cs)

The calculation of Cs for chicken is the same as for beef cattle (Section 5.4.4.5).

Please Note: We recommend assuming that forage and silage are grown on untilled land,

and grain is grown on tilled land. We highly recommend making sure that your Cs

calculations include the appropriate Zs (20 for tilled land). 

5.6.6 Soil Bioavailability Factor (Bs)

The calculation of Bs for chicken is the same as for beef cattle (Section 5.4.4.6)

5.7 CALCULATING COPC CONCENTRATIONS IN DRINKING WATER AND FISH

We generally recommend calculating COPC concentrations in surface water for all

water bodies you selected to evaluate in the risk assessment. Specifically, those

waterbodies selected as potential sources for the drinking water and/or fish ingestion exposure pathways. 

Mechanisms we suggest considering in determining COPC loading of the water column include:

• Direct deposition, 

• Runoff from impervious surfaces within the watershed, 

• Runoff from pervious surfaces within the watershed, 

• Soil erosion over the total watershed, 

• Direct diffusion of vapor phase COPCs into the surface water, and

• Internal transformation of compounds chemically or biologically.
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Volatilization

Vapor

Transfer

Particle

Deposition

Bed

Benthic Sediment

Burial

Water Body Soil Erosion

(Sediments)

Runoff to

Direct

Deposition

(Section 5.7.1.1)

Runoff from

Impervious

Surfaces

(Section 5.7.1.3)

Runoff from

Pervious

Surfaces

(Section 5.7.1.4)

Soil

Erosion

(Section 5.7.1.5)

Vapor

Transfer

(Section 5.7.1.2)

Toal W ater Body

Concentration

Volatilization

(Section 5.7.4.3)

Benthic

Burial

(Section 5.7.4.7)

FIGURE 5-7

COPC LOADING TO THE WATER BODY

Considering other potential mechanisms may be appropriate, due to site-specific conditions (e.g., tidal

influences). Typically, though, we assume that contributions from other potential mechanisms are

negligible compared to those evaluated in the HHRAP.

The total concentration of each COPC partitions between the sediment and the water column. 

Partitioning between water and sediment varies with the COPC. The HHRAP uses the Universal Soil

Loss Equation (USLE) and a sediment delivery ratio to estimate the rate of soil erosion from the

watershed. The equations we recommend for estimating surface water concentrations 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, we typically assume 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 COPC concentration is the sum of the COPC

concentration dissolved in water and the COPC concentration associated with suspended solids. 

Appendix B-4 presents the equations we recommend using to estimate surface water concentrations. 
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To evaluate the COPC loading to a water body from its associated watershed, we generally recommend

calculating watershed soil-specific COPC concentrations. The equation in Section 5.2 for estimating

COPC 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. Appendix B (Tables B-4-1 through B-4-28) provides the equations we recommend for calculating

COPC concentrations in watershed soils and in the water body.

The equations presented in Appendix B for modeling COPC loading to a water body represent a simple

steady-state model to solve for a water column in equilibrium with the upper sediment layer. These

equations (Appendix B) predict the steady-state mass of contaminants in the water column and underlying

sediments, and don’t address 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, evaluating complex water bodies or shorter term loading scenarios might be improved

by using a dynamic modeling framework [e.g., Exposure Analysis Modeling System (EXAMS), or Water

Quality Analysis Simulation Program (WASP), both of which can be downloaded from the EPA Center

for Exposure Assessment Modeling]. Although typically more resource intensive, such analysis may be

able to refine modeling of contaminant loading to a water body. Also, the computations may better

represent the exposure scenario you are evaluating. 

For example, EXAMS allows performing computations 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 evaluating exposure is of greatest interest.

The following are some considerations regarding the selection and use of a dynamic modeling framework

or simulation model to evaluate water bodies:

• Will a complex surface water modeling effort provide enhanced results over the use of

the more simplistic steady-state equations presented in Appendix B?

• Are the resources needed to conduct, as well as review, a more complex modeling effort

justified compared to the more refined results?

• Has the model been used previously for regulatory purposes, and therefore, already has

available documentation to support such uses?
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Equation 5-28

• 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?

As mentioned previously in Chapter 2 (Section 2.3.5.3 - “Mercury”), the SERAFM model offers a

dynamic modeling framework for mercury that enables the user to model specific water body mercury

transformation processes in lieu of applying default speciation assumptions.

5.7.1 Total COPC Load to the Water Body (LT

)

As in U.S. EPA (1994r) and NC DEHNR (1997), we recommend using Equation 5-28 to calculate the

total COPC load to a water body (LT). This equation is described in detail in Appendix B, Table B-4-7.

Recommended Equation for Calculating:

Total COPC Load to the Water Body (LT)

where

LT = Total COPC load to the water body (including deposition, runoff, and erosion)

(g/yr)

LDEP

= Total (wet and dry) particle phase and vapor phase COPC direct deposition

load to water body (g/yr)

Ldif

= Vapor phase COPC 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)

LI = Internal transfer (g/yr)

Due to the limited data and uncertainty associated with the chemical or biological internal transfer, LI, of

compounds into degradation products, we generally recommend a default value for this variable of zero. 

However, if a permitting authority determines that site-specific conditions indicate calculating internal

transfer may need to be considered, we recommend following the methods described in U.S. EPA

(1998c). The remaining variables (LDEP, Ldif, LRI, LR, and LE) are discussed in the following subsections.
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Equation 5-29

5.7.1.1 Total (Wet and Dry) Particle Phase and Vapor Phase COPC Direct Deposition Load to

Water Body (LDEP)

As in U.S. EPA (1994r) and NC DEHNR (1997), with the inclusion of the direct deposition of total

vapor, we recommend using Equation 5-29 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). The equation is

described in detail in Appendix B, Table B-4-8.

Recommended Equation for Calculating:

Total Particle Phase and Vapor Phase Direct Deposition Load to Water Body (LDEP)

where

LDEP = Total (wet and dry) particle phase and vapor phase COPC direct deposition

load to water body (g/yr)

Q = COPC emission rate (g/s)

Fv = Fraction of COPC 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

)

Appendix A-2 describes how we recommend determining the COPC-specific parameter Fv

. Chapter 3

describes generating the modeled air parameters, Dytwv and Dytwp. Methods for determining the water

body surface area, Aw

, are described in Chapter 4 and Appendix B.

5.7.1.2 Vapor Phase COPC Diffusion Load to Water Body (Ldif)

As in U.S. EPA (1994r) and NC DEHNR (1997), we recommend using Equation 5-30 to calculate Ldif.

The equation is described in detail in Appendix B, Table B-4-12.
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Equation 5-30

Recommended Equation for Calculating:

Vapor Phase COPC Diffusion Load to Water Body (LDif)

where

Ldif

= Vapor phase COPC diffusion load to water body (g/yr)

Kv = Overall COPC transfer rate coefficient (m/yr)

Q = COPC emission rate (g/s)

Fv = Fraction of COPC air concentration in vapor phase (unitless)

Cywv = Unitized yearly (water body or watershed) average air concentration from

vapor phase (μg-s/g-m3)

AW = Water body surface area (m2)

10-6

= Units conversion factor (g/μg)

H = Henry’s Law constant (atm-m3/mol)

R = Universal gas constant (atm-m3/mol-K)

Twk = Water body temperature (K)

Calculating the overall COPC transfer rate coefficient (Kv) is described in Section 5.7.4.4, as well as in

Appendix B, Table B-4-19. Chapters 2 and 3 explain how we recommend quantifying the COPC

emission rate (Q). Appendix A-2 describes how we recommend determining the COPC-specific

parameters Fv

, H, and R. Chapter 3 describes generating the modeled air parameter, Cywv. Methods for

determining the water body surface area, Aw, are described in Chapter 4 and Appendix B. Consistent with

U.S. EPA (1994r) and U.S. EPA (1998c), we recommend a default water body temperature (Twk) of 298 K

(or 25°C).

5.7.1.3 Runoff Load from Impervious Surfaces (LRI)

In some watershed soils, a portion 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. As in U.S.

EPA (1994r) and NC DEHNR (1997), with the inclusion of total (wet and dry) vapor phase deposition,

we recommend using Equation 5-31 to calculate impervious runoff load to a water body (LRI). The

equation is also presented in Appendix B, Table B-4-9.
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Equation 5-31

Recommended Equation for Calculating:

Runoff Load from Impervious Surfaces (LRI)

where

LRI = Runoff load from impervious surfaces (g/yr)

Q = COPC emission rate (g/s)

Fv = Fraction of COPC 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)

AI = Impervious watershed area receiving COPC deposition (m2)

Chapters 2 and 3 explain how we recommend quantifying the COPC emission rate (Q). Appendix A-2

describes how we recommend determining the COPC-specific parameter Fv. Chapter 3 describes a

method for generating the modeled air parameters, Dytwv and Dytwp. Impervious watershed area

receiving COPC deposition (AI) 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. Our

recommended method for determining AI

 is described in Chapter 4 and Appendix B.

5.7.1.4 Runoff Load from Pervious Surfaces (LR

)

As in U.S. EPA (1994r) and NC DEHNR (1997), we recommend using Equation 5-32 to calculate the

runoff dissolved COPC load to the water body from pervious soil surfaces in the watershed (LR). The

equation is also presented in Appendix B, Table B-4-10.
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Equation 5-32

Recommended Equation for Calculating:

Runoff Load from Pervious Surfaces (LR

)

where

LR = Runoff load from pervious surfaces (g/yr)

RO = Average annual surface runoff from pervious areas (cm/yr)

AL = Total watershed area receiving COPC deposition (m2

)

AI = Impervious watershed area receiving COPC deposition (m2)

Cs = Average soil concentration over exposure duration (in watershed soils) (mg

COPC/kg soil)

BD = Soil bulk density (g soil/cm3 soil) = 1.5 g/cm3

2sw

= Soil volumetric water content (ml water/cm3

 soil) = 0.2 ml/cm3

Kds = Soil-water partition coefficient (cm3 water/g soil)

0.01 = Units conversion factor (kg-cm2/mg-m2)

Appendix B describes how we recommend determining the site-specific parameters RO, AL, AI, BD, and

2sw. We also address soil bulk density (BD) in Section 5.2.4.2. We also address soil water content (2sw) in

Section 5.2.4.4. Our recommended method for calculating the COPC concentration in watershed soils

(Cs) is discussed in Section 5.2.1 and Appendix B, Table B-4-1. Appendix A-2 describes how we

recommend calculating the COPC-specific soil/water partition coefficient (Kds

).

5.7.1.5 Soil Erosion Load (LE)

As in U.S. EPA (1994r) and NC DEHNR (1997), we recommend using Equation 5-33 to calculate soil

erosion load (LE

). The equation is also presented in Appendix B, Table B-4-11.
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Equation 5-33

Recommended Equation for Calculating:

Soil Erosion Load (LE)

where

LE = Soil erosion load (g/yr)

Xe = Unit soil loss (kg/m2

-yr)

AL = Total watershed area (evaluated) receiving COPC deposition (m2

)

AI = Impervious watershed area receiving COPC deposition (m2

)

SD = Sediment delivery ratio (watershed) (unitless)

ER = Soil enrichment ratio (unitless)

Cs = Average soil concentration over exposure duration (in watershed soils) (mg

COPC/kg soil)

BD = Soil bulk density (g soil/cm3

 soil) = 1.5 g/cm3

2sw = Soil volumetric water content (ml water/cm3 soil) = 0.2 ml/cm3

Kds = Soil-water partition coefficient (ml water/g soil)

0.001 = Units conversion factor (k-cm2

/mg-m2)

Section 5.7.2 describes unit soil loss (Xe). Chapter 4 and Appendix B describe how we recommend

determining the site-specific parameters AL and AI

. We generally recommend calculating the watershed

sediment delivery ratio (SD) as described in Section 5.7.3 and in Appendix B, Table B-4-14. COPC

concentration in soils (Cs) is described in Section 5.2.1, and Appendix B, Table B-4-1. Soil bulk density

(BD) is described in Section 5.2.4.2. Soil water content (2sw) is described in Section 5.2.4.4. Appendix B,

Table B-4-11 describes how we recommend determining the COPC-specific soil enrichment ration (ER). 

5.7.2 Universal Soil Loss Equation - USLE

As in U.S. EPA (1994g and 1994r), we generally recommend using the universal soil loss equation

(USLE), Equation 5-33A, to calculate the unit soil loss (Xe) specific to each watershed. This equation is

further described in Appendix B, Table B-4-13. Appendix B also describes how we suggest determining

the site- and watershed-specific values for each of the variables associated with Equation 5-33A. 
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Equation 5-33A

Equation 5-34

Recommended Equation for Calculating:

Unit Soil Loss (Xe)

where

Xe = Unit soil loss (kg/m2-yr)

RF = USLE rainfall (or erosivity) factor (yrG1

)

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)

The USLE 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). 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) and U.S. EPA guidance (U.S. EPA 1985b). 

Refer to Appendix B, Table B-4-13 for additional discussion of the USLE.

5.7.3 Sediment Delivery Ratio (SD)

We recommend using Equation 5-34 to calculate the sediment delivery ratio (SD). The use of this

equation is further described in Appendix B, Table B-4-14.

Recommended Equation for Calculating:

Sediment Delivery Ratio (SD)

where

SD = Sediment delivery ratio (watershed) (unitless)

a = Empirical intercept coefficient (unitless)

b = Empirical slope coefficient (unitless)

AL = Total watershed area (evaluated) receiving COPC deposition (m2)
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The sediment delivery ratio (SD) for a large land area (i.e. a watershed or part of a watershed) can be

calculated, on the basis of the area of the watershed, by using an approach proposed by Vanoni (1975). 

Accordingly, U.S. EPA (1998c) recommended using Equation 5-34 to calculate the SD.

According to Vanoni (1975), sediment delivery ratios vary approximately with the -0.125 power of the

drainage area. Therefore, the empirical slope coefficient is assumed to be equal to 0.125. An inspection

of the data presented by Vanoni (1975) indicates that the empirical intercept coefficient varies with the

size of the watershed, as illustrated in Appendix B, Table B-4-14. 

AL

 is the total watershed surface area evaluated that is affected by deposition and drains to the body of

water (see Chapter 4). In assigning values to the watershed surface area affected by deposition, we

generally consider the following relevant:

• the distance from the emission source, 

• the location of the area affected by deposition fallout with respect to the point at which

drinking water is extracted or fishing occurs

• the watershed hydrology. 

5.7.4 Total Water Body COPC Concentration (Cwtot)

We recommend using Equation 5-35 to calculate the total water body COPC concentration (Cwtot). Cwtot

includes both the water column and the bed sediment. The equation is also presented in Appendix B,

Table B-4-15.
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Equation 5-35

Recommended Equation for Calculating:

Total Water Body COPC Concentration (Cwtot)

where

Cwtot = Total water body COPC concentration (including water column and bed

sediment) (g COPC/m3

 water body)

LT = Total COPC load to the water body (including deposition, runoff, and erosion)

(g/yr)

Vfx = Average volumetric flow rate through water body (m3/yr)

fwc = Fraction of total water body COPC concentration in the water column

(unitless)

kwt = Overall total water body COPC dissipation rate constant (yrG1

)

AW = Water body surface area (m2)

dwc = Depth of water column (m)

dbs = Depth of upper benthic sediment layer (m)

The total COPC load to the water body (LT

)—including deposition, runoff, and erosion—is described in

Section 5.7.1 and Appendix B, Table B-4-7. Average volumetric flow rate through the water body (Vfx)

and water body surface area (Aw) are discussed in Appendix B. Section 5.7.4.1 discusses the fraction of

total COPC concentration in the water column (fwc). Section 5.7.4.2 discusses the COPC dissipation rate

constant (kwt). Chapter 4 discusses the water body-specific dwc. We discuss the depth of the upper benthic

sediment layer (dbs) below.

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, U.S. EPA (1998c) recommended values

ranging from 0.01 to 0.05. As in U.S. EPA (1994r), we recommend a default value of 0.03, which

represents the midpoint of the specified range. Issues related to the remaining parameters are summarized

in the following subsections.

Recommended Default Value for:

Depth of Upper Benthic Sediment Layer (dbs)

0.03 m
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Equation 5-36B

Equation 5-36A

5.7.4.1 Fraction of Total Water Body COPC Concentration in the Water Column (fwc) and Benthic

Sediment (fbs)

We generally recommend using Equation 5-36A to calculate the fraction of total water body COPC

concentration in the water column (fwc), and Equation 5-36B to calculate the total water body contaminant

concentration in benthic sediment (f

bs). The equations are also presented in Appendix B, Table B-4-16.

Recommended Equation for Calculating:

Fraction of Total Water Body COPC Concentration in 

the Water Column (fwc) and Benthic Sediment (fbs)

where

fwc = Fraction of total water body COPC concentration in the water column

(unitless)

f

bs = Fraction of total water body COPC concentration in benthic sediment

(unitless)

Kdsw = 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)

dz = Total water body depth (m)

2bs = Bed sediment porosity (L water/Lsediment)

Kdbs = Bed sediment/sediment pore water partition coefficient (L water/kg bottom

sediment)

CBS = Bed sediment concentration (g/cm3

 [equivalent to kg/L])

dwc = Depth of water column (m)

dbs = Depth of upper benthic sediment layer (m)

The COPC-specific partition coefficient (Kdsw) describes the partitioning of a contaminant between

sorbing material, such as soil, surface water, suspended solids, and bed sediments (see Appendix A-2). 

Total suspended solids (TSS), total water body depth (dz), bed sediment porosity (2bs) and bed sediment

concentration (CBS) are addressed below. Bed sediment and sediment pore water partition coefficient
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Equation 5-36C

(Kdbs) is discussed in Appendix A-2. Depth of water column (dwc) and depth of upper benthic layer (dbs)

are discussed in Section 5.7.4.

U.S. EPA (1998c) and NC DEHNR (1997) recommended using Equations 5-36A and 5-36B to calculate

fwc and f

bs. NC DEHNR (1997) also recommended adding the depth of the water column to the depth of

the upper benthic layer (dwc + dbs) to calculate the total water body depth (dz

).

NC DEHNR (1997) recommended a default total suspended solids (TSS) concentration of 10 mg/L, which

was adapted from U.S. EPA (1993e). However, due to variability in water body specific values for this

variable, we recommend using water body-specific measured TSS values representative of long-term

average annual values. Average annual values for TSS are generally expected to be in the range of 2 to

300 mg/L. Additional information on anticipated TSS values is available in U.S. EPA (1998c).

If measured data are not available, or of unacceptable quality, it’s possible to calculate a TSS value for

non-flowing water bodies using Equation 5-36C.

where

TSS = Total suspended solids concentration (mg/L)

Xe = Unit soil loss (kg/m2-yr)

AL = Total watershed area (evaluated) receiving COPC deposition (m2)

AI = Impervious watershed area receiving COPC 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) (m3/yr)

Dss = Suspended solids deposition rate (a default value of 1,825 for quiescent

lakes or ponds) (m/yr)

AW = Water body surface area (m2

)

The default value of 1,825 m/yr provided for Dss is characteristic of Stoke’s settling velocity for an

intermediate (fine to medium) silt.

Also, it’s possible to evaluate the appropriateness of watershed-specific values used in calculating the unit

soil loss (Xe

), as described in Section 5.7.2 and Appendix B, by comparing the water-body specific

measured TSS value to the estimated TSS value obtained using Equation 5-36C. If the measured and
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Equation 5-37

calculated TSS values differ significantly, we recommend re-evaluating the parameter values used to

calculate Xe. You might also re-evaluate TSS and Xe if the calculated TSS value is outside of the normal

range expected for average annual measured values, as discussed above.

One approach to calculating bed sediment porosity (2bs) from the bed sediment concentration is by using

the following equation (U.S. EPA 1998c):

where

2bs = Bed sediment porosity (L water/Lsediment)

Ds = Bed sediment density (kg/L)

CBS = Bed sediment concentration (kg/L)

We recommend the following default value for bed sediment porosity (2bs), adapted from NC DEHNR

(1997):

Recommended Value for:

Bed Sediment Porosity (2bs)

2bs = 0.6 Lwater/Lsediment

assuming

Ds = 2.65 kg/L [bed sediment density] 

and 

CBS = 1.0 kg/L [bed sediment concentration])

U.S. EPA (1994r) and NC DEHNR (1997) recommended a benthic solids concentration (CBS) ranging

from 0.5 to 1.5 kg/L, which was adapted from U.S. EPA (1993e). We recommend the following default

value for bed sediment concentration (CBS):

Recommended Default Value for:

Bed Sediment Concentration (CBS)

1.0 kg/L
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Chapter 5: Estimating Media Concentrations September 2005

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Equation 5-38

5.7.4.2 Overall Total Water Body COPC Dissipation Rate Constant (kwt)

As in U.S. EPA (1994r) and NC DEHNR (1997), we recommend using Equation 5-38 to calculate the

overall dissipation rate of COPCs in surface water, resulting from volatilization and benthic burial. The

equation is also presented in Appendix B, Table B-4-17.

Recommended Equation for Calculating:

Overall Total Water Body COPC Dissipation Rate Constant (kwt)

where

kwt

= Overall total water body dissipation rate constant (yrG1)

fwc = Fraction of total water body COPC concentration in the water column

(unitless)

kv = Water column volatilization rate constant (yrG1)

f

bs = Fraction of total water body COPC concentration in benthic sediment

(unitless)

kb = Benthic burial rate constant (yrG1

)

The variables fwc and f

bs are discussed in Section 5.7.4.1. The water column volatilization rate constant

(kv) is discussed in Section 5.7.4.3. The benthic burial rate constant (kb)is discussed in Section 5.7.4.7. 

5.7.4.3 Water Column Volatilization Rate Constant (kv)

As in U.S. EPA (1994r) and NC DEHNR (1997), we recommend using Equation 5-39 to calculate kv

. 

The equation is also presented in Appendix B, Table B-4-18.
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Chapter 5: Estimating Media Concentrations September 2005

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Equation 5-39

Recommended Equation for Calculating:

Water Column Volatilization Rate Constant (kv)

where

kv

 = Water column volatilization rate constant (yrG1

)

Kv = Overall COPC transfer rate coefficient (m/yr)

dz = Total water body depth (m)

Kdsw = 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)

The overall transfer rate coefficient (Kv

) is discussed in Section 5.7.4.4. Total water body depth (dz

),

suspended sediment and surface water partition coefficient (Kdsw), and total suspended solids

concentration (TSS), are described in Section 5.7.4.1. Kdsw is also discussed in Appendix A-2. 

5.7.4.4 Overall COPC 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.

As in U.S. EPA (1993f; 1993e; 1998c), and NC DEHNR (1997), we recommend using Equation 5-40 to

calculate Kv. The equation is also presented in Appendix B, Table B-4-19.
Human Health Risk Assessment Protocol

Chapter 5: Estimating Media Concentrations September 2005

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Equation 5-40

Recommended Equation for Calculating:

Overall COPC Transfer Rate Coefficient (Kv)

where

Kv = Overall COPC 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-m3/mol)

R = Universal gas constant (atm-m3

/mol-K)

Twk = Water body temperature (K)

2 = Temperature correction factor (unitless)

The liquid and gas phase transfer coefficients, KL

 and KG

, respectively, vary with the type of water body. 

We discuss the liquid phase transfer coefficient (KL) in Section 5.7.4.5, and the gas phase transfer

coefficient (KG) in Section 5.7.4.6.

Henry’s Law constants generally increase with increasing vapor pressure of a COPC and generally

decrease with increasing solubility of a COPC. Henry’s Law constants are COPC-specific and we offer

recommended default values in the HHRAP companion database. The universal ideal gas constant, R, is

8.205 × 10-5 atm-m3/mol-K, at 20°C. The temperature correction factor (2), which is equal to 1.026,

adjusts for the actual water temperature. Equation 5-40 assumes that volatilization occurs much less

readily in lakes and reservoirs than in moving water bodies.

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. 

5.7.4.5 Liquid Phase Transfer Coefficient (KL)

We generally recommend using Equations 5-41A and 5-41B to calculate liquid phase transfer coefficient.

(KL

). The use of these equations is further described in Appendix B, Table B-4-20. 
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Equation 5-41A

Equation 5-41B

Recommended Equation for Calculating:

Liquid Phase Transfer Coefficient (KL)

For flowing streams or rivers:

For quiescent lakes or ponds:

where

KL = Liquid phase transfer coefficient (m/yr)

Dw = Diffusivity of COPC in water (cm2

/s)

u = Current velocity (m/s)

1 × 10-4= Units conversion factor (m2/cm2)

dz = Total water body depth (m)

Cd = Drag coefficient (unitless)

W = Average annual wind speed (m/s)

Da = Density of air (g/cm3)

Dw = Density of water (g/cm3

)

k = von Karman’s constant (unitless)

8z = Dimensionless viscous sublayer thickness (unitless)

:w = Viscosity of water corresponding to water temperature (g/cm-s)

3.1536 x 107

=

Units conversion factor (s/yr)

As in U.S. EPA (1994r) and NC DEHNR (1997), we recommend using the following default values:

• a diffusivity of chemical in water ranging (Dw) from 1.0 × 10G5 to 8.5 × 10-2 cm2/s, 

• a drag coefficient (Cd

) of 0.0011 which was adapted from U.S. EPA (1998c),

• a density of air (Da) of 0.0012 g/cm3 at standard conditions (temperature = 20°C or 293 K,

pressure = 1 atm or 760 millimeters of mercury) (Weast 1986),

• a density of water (Dw

) of 1 g/cm3 (Weast 1986),

• a von Karman’s constant (k) of 0.4,

• a dimensionless viscous sublayer thickness (8z) of 4,

• a viscosity of water (:w) of a 0.0169 g/cm-s corresponding to water temperature

(Weast 1986).
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Equation 5-42A

Equation 5-42B

The values above are further discussed in Appendix A-2. Chapter 4 discusses the current velocity (u). 

Chapter 3 describes methods for determining the average annual wind speed (W). Section 5.7.4.1

discusses the total water body depth (dz

) for liquid phase transfer coefficients. 

For a flowing stream or river, the transfer coefficients are controlled by flow-induced turbulence. For

these systems, we recommend calculating KL using Equation 5-41A, which is the O’Connor and Dobbins

(1958) formula, as presented in U.S. EPA (1998c). 

For a stagnant system (quiescent lake or pond), the transfer coefficient is controlled by wind-induced

turbulence. For quiescent lakes or ponds, we recommend calculating KL

 using Equation 5-41B

(O’Connor 1983; U.S. EPA 1998c).

5.7.4.6 Gas Phase Transfer Coefficient (KG)

We generally recommend using Equations 5-42A and 5-42B to calculate gas phase transfer coefficient

(KG). The equation is also discussed in Appendix B, Table B-4-21.

Recommended Equation for Calculating:

Gas Phase Transfer Coefficient (KG)

For flowing streams or rivers:

For quiescent lakes or ponds:

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)

8z = Dimensionless viscous sublayer thickness (unitless)

:a = Viscosity of air corresponding to air temperature (g/cm-s)

Da = Density of air corresponding to water temperature (g/cm3)

Da = Diffusivity of COPC in air (cm2

/s)

3.1536 x 107

= Units conversion factor (s/yr)
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Chapter 5: Estimating Media Concentrations September 2005

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Equation 5-43

The following parameters, including default values, are discussed in Section 5.7.4.5, and in Appendix A2: Cd

, k, 8z, and Da. Chapter 3 describes methods for determining the average annual wind speed (W). 

As in U.S. EPA (1994r) and NC DEHNR (1997), we recommend using a value of 1.81 x 10-4 g/cm-s for

the viscosity of air corresponding to air temperature (:a

). Appendix A-2 discusses the COPC-specific

parameter Da.

U.S. EPA (1998c) indicated that the rate of transfer of a COPC from the gas phase for a flowing stream or

river is assumed to be constant, in accordance with O’Connor and Dobbins (1958) (Equation 5-42A).

For a stagnant system (quiescent lake or pond), the transfer coefficients are controlled by wind-induced

turbulence. For quiescent lakes or ponds, we recommend calculating the gas phase transfer coefficient

using the equation presented in O’Connor (1983) (Equation 5-42B).

5.7.4.7 Benthic Burial Rate Constant (kb

)

We generally recommend using Equation 5-43 to calculate benthic burial rate (kb). The equation is also

discussed in Appendix B, Table B-4-22. 

Recommended Equation for Calculating:

Benthic Burial Rate Constant (kb)

where

kb

 = Benthic burial rate constant (yrG1)

Xe = Unit soil loss (kg/m2

-yr)

AL = Total watershed area (evaluated) receiving deposition (m2

)

SD = Sediment delivery ratio (watershed) (unitless)

Vfx

 = Average volumetric flow rate through water body (m3/yr)

TSS = Total suspended solids concentration (mg/L)

AW

 = Water body surface area (m2

)

CBS = Bed sediment concentration (g/cm3)

dbs = Depth of upper benthic sediment layer (m)

1 x 10G6

 =

Units conversion factor (kg/mg)

1 x 103 = Units conversion factor (g/kg)
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Equation 5-44

Section 5.7.2 discusses the unit soil loss (Xe

). Section 5.7.3 discusses watershed area evaluated receiving

COPC deposition (AL) and sediment delivery ratio (SD). Average volumetric flow rate through the water

body (Vfx

) and water body surface area (Aw

) are discussed in Appendix B. Aw

 is also discussed in

Appendix A-2. Section 5.7.4.1 discusses total suspended solids concentration (TSS) and bed sediment

concentration (CBS). Section 5.7.4 discusses the depth of the upper benthic sediment layer (dbs).

It’s possible to express the benthic burial rate constant (kb

), which is calculated in Equation 5-43, in terms

of the rate of burial (Wb):

where

Wb = Rate of burial (m/yr)

kb = Benthic burial rate constant (yrG1

)

dbs

= Depth of upper benthic sediment layer (m)

According to U.S. EPA (1994r) and NC DEHNR (1997), COPC loss from the water column resulting

from burial in benthic sediment can be calculated using Equation 5-43.

We expect kb values to range from 0 to 1.0: Low kb values for water bodies with limited or no

sedimentation (rivers and fast flowing streams), and kb values closer to 1.0 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 5-44; with the depth of upper benthic sediment layer held

constant. If you calculate a negative kb value (water bodies with high average annual volumetric flow

rates in comparison to watershed area evaluated), we recommend using a kb value of 0 in calculating the

total water body COPC concentration (Cwtot) in Equation 5-35. If the calculated kb

 value exceeds 1.0, we

recommend re-evaluating the parameter values used in calculating Xe. Our experience has shown that the

value calculated for Xe is the most likely reason for estimating a large and potentially unrealistic benthic

burial rate. Information about determining site-specific values and variables for calculating Xe are in the

references cited in Section 5.7.2. 

5.7.4.8 Total COPC Concentration in Water Column (Cwctot)

As in U.S. EPA (1994r) and NC DEHNR (1997), we generally recommend using Equation 5-45 to

calculate total COPC concentration in water column (Cwctot). The equation is also discussed in Appendix

B, Table B-4-23.
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Chapter 5: Estimating Media Concentrations September 2005

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Equation 5-45

Equation 5-46

Recommended Equation for Calculating:

Total COPC Concentration in Water Column (Cwctot)

where

Cwctot = Total COPC concentration in water column (mg COPC/L water column)

fwc = Fraction of total water body COPC concentration in the water column

(unitless)

Cwtot = Total water body COPC concentration, including water column and bed

sediment (mg COPC/L water body)

dwc = Depth of water column (m)

dbs = Depth of upper benthic sediment layer (m)

We discussed the fraction of total water body COPC concentration in the water column (fwc) in Section

5.7.4.1. We discussed the total COPC Concentration in the water column (Cwctot), as well as depth of the

water column (dwc) and benthic sediment layer (dbs) in Section 5.7.4.

5.7.4.9 Dissolved Phase Water Concentration (Cdw)

We recommend using Equation 5-46 to calculate the concentration of COPC dissolved in the water

column (Cdw). The equation is discussed in detail in Appendix B, Table B-4-24.

Recommended Equation for Calculating:

Dissolved Phase Water Concentration (Cdw)

where

Cdw = Dissolved phase water concentration (mg COPC/L water)

Cwctot = Total COPC concentration in water column (mg COPC/L water column)

Kdsw = 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)
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Chapter 5: Estimating Media Concentrations September 2005

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Equation 5-47

We discussed Cwctot in Section 5.7.4.8. We discussed Kdsw and TSS in Section 5.7.4.1.

Using Equation 5-46 to calculate the concentration of COPC dissolved in the water column is consistent

with recommendations in U.S. EPA (1994r) and NC DEHNR (1997).

5.7.4.10 COPC Concentration Sorbed to Bed Sediment (Csb)

We recommend using Equation 5-47 to calculate COPC concentration sorbed to bed sediment (Csb). The

equation is also presented in Appendix B, Table B-4-25.

Recommended Equation for Calculating:

COPC Concentration Sorbed to Bed Sediment (Csb)

where

Csb = COPC concentration sorbed to bed sediment (mg COPC/kg sediment)

fbs = Fraction of total water body COPC concentration in benthic sediment

(unitless)

Cwtot = Total water body COPC concentration, including water column and

bed sediment (mg COPC/L water body)

Kdbs = Bed sediment/sediment pore water partition coefficient (L COPC/kg

water body)

2bs = Bed sediment porosity (Lpore water/Lsediment)

CBS = Bed sediment concentration (g/cm3

)

dwc = Depth of water column (m)

dbs = Depth of upper benthic sediment layer (m)

We discussed fbs, 2bs, and CBS in Section 5.7.4.1. We discussed Cwtot, dwc, and dbs in Section 5.7.4. We

discuss Kdbs in Appendix A-2.

As in U.S. EPA (1994r) and NC DEHNR (1997), we continue to recommend using Equation 5-47 to

calculate the COPC concentration sorbed to bed sediment.
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Soil

Concentration

Direct

Deposition

Vapor

Transfer

Total Water Body

Concentration

Benthic

Burial

Dissolved-Phase

Water

Concentration

Total Water

Column

Concentration

Bed Sediment

Concentration

Volatilization

FIGURE 5-8

COPC CONCENTRATION IN FISH

5.7.5 Concentration of COPC in Fish (Cfish)

We generally recommend calculating the COPC concentration in fish using either a

COPC-specific bioconcentration factor (BCF), a COPC-specific bioaccumulation factor

(BAF), or a COPC-specific biota-sediment accumulation factor (BSAF). Under this approach you would

use BCFs for COPCs with a log Kow less than 4.0. We assume that COPCs with a log Kow greater than

4.0 (except for extremely hydrophobic compounds such as dioxins, furans, and PCBs), have a high

tendency to bioaccumulate. As a result, BAFs are used. While we assume that extremely hydrophobic

COPCs like dioxins, furans, and PCBs also have a high tendency to bioaccumulate, they are expected to

be sorbed to the bed sediments more than associated with the water phase. Therefore, we recommend

using BSAFs to calculate concentrations of dioxins, furans, and PCBs in fish. Appendix A-2 provides a

detailed discussion on the sources of the COPC-specific BCF, BAF, and BSAF values, and the method we

used to derive them.
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Chapter 5: Estimating Media Concentrations September 2005

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Equation 5-48

BCF and BAF values are generally based on dissolved water concentrations. Therefore, when you use

BCF or BAF values, it’s appropriate to calculate the COPC concentration in fish using dissolved water

concentrations. BSAF values are based on benthic sediment concentrations. Therefore, when using BSAF

values, we recommend calculating COPC concentrations in fish using benthic sediment concentrations. 

We describe our recommended equations for calculating fish concentrations in the subsequent

subsections.

5.7.5.1 Fish Concentration (Cfish) from Bioconcentration Factors Using Dissolved Phase Water

Concentration

As in U.S. EPA (1994r) and NC DEHNR (1997), we recommend using Equation 5-48 to calculate fish

concentration from BCFs using dissolved phase water concentration. Using this equation is further

described in Appendix B, Table B-4-26.

Recommended Equation for Calculating:

Fish Concentration (Cfish) from Bioconcentration Factors (BCFfish)

Using Dissolved Phase Water Concentration 

where

Cfish = Concentration of COPC in fish (mg COPC/kg FW tissue)

Cdw = Dissolved phase water concentration (mg COPC/L)

BCFfish = Bioconcentration factor for COPC in fish (L/kg)

We discussed Cdw in Section 5.7.4.9. COPC-specific BCFfish values are presented in the HHRAP

companion database. 

5.7.5.2 Fish Concentration (Cfish) from Bioaccumulation Factors Using Dissolved Phase Water 

Concentration

We recommend using Equation 5-49 to calculate fish concentration from BAFs using dissolved phase

water concentration. The equation is also presented in Appendix B, Table B-4-27.
Human Health Risk Assessment Protocol

Chapter 5: Estimating Media Concentrations September 2005

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Equation 5-49

Equation 5-50

Recommended Equation for Calculating:

Fish Concentration (Cfish) from Bioaccumulation Factors (BAFfish)

Using Dissolved Phase Water Concentration

where

Cfish = Concentration of COPC in fish (mg COPC/kg FW tissue)

Cdw = Dissolved phase water concentration (mg COPC/L)

BAFfish = Bioaccumulation factor for COPC in fish (L/kg FW tissue)

We discussed Cdw in Section 5.7.4.9. COPC-specific bioaccumulation factor (BAFfish) values are presented

in the HHRAP companion database. 

5.7.5.3 Fish Concentration (Cfish) from Biota-To-Sediment Accumulation Factors Using COPC

Sorbed to Bed Sediment

As in U.S. EPA (1994r) and NC DEHNR (1997), we recommend using Equation 5-50 to calculate fish

concentration from BSAFs using COPC concentrations sorbed to bed sediment. We recommend using

BSAFs for very hydrophobic compounds such as dioxins, furans, and PCBs. The equation is also

presented in Appendix B, Table B-4-28.

Recommended Equation for Calculating:

Fish Concentration (Cfish) from Biota-To-Sediment Accumulation Factors (BSAF)

Using COPC Sorbed to Bed Sediment

where

Cfish = Concentration of COPC in fish (mg COPC/kg FW tissue)

Csb = Concentration of COPC sorbed to bed sediment (mg COPC/kg bed sediment)

f

lipid = Fish lipid content (unitless)

BSAF = Biota-to-sediment accumulation factor (unitless)

OCsed = Fraction of organic carbon in bottom sediment (unitless)
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We discussed Csb in Section 5.7.4.10. We discuss flipid and OCsed below. Our recommended default values

for flipid and OCsed are given in Appendix B, Table B-4-28. We offer biota-to-sediment accumulation

factors (BSAF), which are applied only to dioxins, furans, and PCBs, in the HHRAP companion database. 

Values recommended by U.S. EPA (1998c) range from 0.03 to 0.05 for OCSED. These values are based on

an assumption of a surface soil organic carbon (OC) content of 0.01. U.S. EPA (1998c) 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 (flipid) value is site-specific and dependent on the type of fish consumed. As stated

in Appendix B, Table B-4-28, we recommend a default range of 0.03 to 0.07 specific to warm or cold

water fish species. U.S. EPA (2000c) provides information supporting a value of 0.03 (3 percent lipid

content of the edible portion). U.S. EPA (1993e) recommended a default value of 0.04 for OCSED, which is

the midpoint of the specified range. U.S. EPA (1993f; 1993e) recommended using 0.07, which was

originally cited in Cook et al. (1991).

5.8 USING SITE-SPECIFIC vs. DEFAULT PARAMETER VALUES

As initially discussed in Chapter 1, many of the parameter values we recommend in the HHRAP are not

site-specific. After completing a risk assessment using HHRAP default values, you might choose to

investigate using site-specific parameter values. More site-specific values might provide a more

representative estimate of site-specific risk. If you use parameter values other than those specified in the

HHRAP, we recommend that you clearly described them in the risk assessment report. We also

recommend that you discuss them with the permitting authority prior to using them. We recommend that

requests to change default parameter values include the following information, as appropriate:

1. An explanation of why using a more site-specific parameter value is warranted (e.g., the

default parameter is based on data or studies at sites in the northwestern U.S., but the

facility is located in the southeast);

2. The technical basis of the site-specific parameter value, including readable copies of any

relevant technical literature or studies;
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C Identification of site-specific or alternate default media equations and/or inputs; including

justification and full referencing

C Media concentration calculations

RECOMMENDED INFORMATION FOR RISK ASSESSMENT REPORT

3. A comparison of the weight-of-evidence between the competing studies (e.g., the

site-specific parameter value is based on a study that is more representative of site

conditions, a specific exposure setting being evaluated, or a more scientifically valid

study than the default parameter, the site-specific parameter is based on the analysis of 15

samples as opposed to 5 for the default parameter, or the site-specific study used more

stringent quality control/quality assurance procedures than the study upon which the

default parameter is based);

4. A description of other risk assessments or projects that used the site-specific parameter

value, and how such risk assessments or projects are similar to the current risk

assessment.
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Chapter 6

Quantifying Exposure

What’s Covered in Chapter 6:

6.1 Inhalation Exposure Pathways

6.2 Ingestion Exposure Pathways

6.3 Dermal Exposure Pathways

6.4 Exposure Frequency

6.5 Exposure Duration

6.6 Averaging Time

PLEASE NOTE: for the purposes of this guidance, “we” refers to the U.S. EPA OSW. 

The HHRAP is written for the benefit of a varied audience, including risk assessors,

regulators, risk managers, and community relations personnel. However, the “you” to

which we speak is the performer of a risk assessment: the person (or persons) who will

actually put the recommended methods into practice.

This chapter describes the factors to evaluate in quantifying the exposure received under each of the

recommended exposure scenarios described in Chapter 4. Calculating COPC-specific exposure rates for

each exposure pathway involves some or all of the following, depending upon the medium being

assessed: 

• the estimated COPC media concentrations calculated in Chapter 5, 

• consumption rates of the medium, 

• receptor body weight, and 

• the frequency and duration of exposure. 

We recommend repeating the appropriate calculation for each COPC and for each exposure pathway

included in an exposure scenario, to generate multiple exposure concentration estimates, as recommended

in the EPA information quality guidelines (see Chapter 1, page 1-11). We present recommended

exposure pathway-specific equations in Appendix C. The following sections describe a general exposure

rate calculation and the exposure pathway-specific variables that may affect this calculation. Acute

exposure resulting from direct inhalation is discussed as a separate issue in Chapter 7, Section 7.4.
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6.1 INHALATION EXPOSURE PATHWAYS

We recommend using COPC air concentrations calculated using the equation in Table B-5-1 to represent

air concentrations for estimating exposure via inhalation by all exposure scenarios in the risk assessment

(see Table 4-1).

Direct inhalation of vapors and particulate emissions from combustion sources is a potential pathway of

exposure. Chapter 2 presented various variables and conditions that affect the rate, type, and quantity of

combustor emissions. Chapter 3 presented the air dispersion and deposition modeling techniques we

recommend using to estimate airborne concentrations of vapors and particulates in the assessment area.

As a result of normal respiration, receptors in the assessment area could be exposed to COPCs in vapor,

particle, and particle-bound phases. Examples of factors that affect exposure from vapor and particulate

inhalation include vapor and particulate COPC concentrations, particle size, and length of exposure.

Exposure can occur over a period of time. To calculate an average exposure per unit of time (Exposure

Concentration, or EC), we recommend dividing the total exposure by the time period. We generally

recommend using total COPC air concentrations (Ca

, estimated using the equation in Table B-5-1) when

estimating EC values. Estimating ECs doesn’t involve or require adjustment for respiration rates, as

those are inherent to inhalation toxicity factors. Sections 6.4 through 6.6 discuss exposure time-related

parameters, and Appendix C Tables C-2-1 and C-2-2 further discuss estimating EC.

We consider it appropriate to estimate noncarcinogenic hazards and carcinogenic risks associated with

direct inhalation exposure by combining ECs with inhalation toxicity factors (reference concentrations

[RfCs] or unit risk factors [URFs]). These toxicity factors are developed for all human populations,

including sensitive subpopulations (including children) who might be exposed to continuous

concentrations over a lifetime. Inhalation risk parameters and inhalation pharmacokinetics are largely

chemical-specific and a "one size fits all" approach to convert the standard RfC or URF parameters into

scenario-specific toxicity values may not be appropriate. We therefore generally recommend that a

single (lifetime) inhalation risk be predicted for each receptor identified in Chapter 4, Table 4-1. 
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Inhalation exposure concentrations for vapors and particles (arising from outdoor sources) can be

influenced by the relative amount of time that a receptor spends indoors. Although vapors entering

buildings and residences as a result of air exchange are likely to remain airborne and, therefore may be

inhaled, particulates entering these same buildings are more likely to settle out and not be inhaled. 

However, for the purpose of the risk assessment, we recommend assuming that both vapor and

particulates are inhaled throughout the day, both indoors and outdoors.

6.1.1 Soil Inhalation Resulting from Dust Resuspension

We don’t typically recommend evaluating the soil inhalation of resuspended dust exposure pathway. 

However, site-specific exposure setting characteristics might support evaluating it (e.g. arid, windy

climates). This section therefore discusses exposure to soil resulting from dust resuspension.

Inhalation of soil resulting from dust resuspension could be an issue for site-specific exposure scenario

locations at which there is little vegetative cover. Wind erosion could resuspend pollutants in

contaminated soil as particles in the air. As dust is resuspended, receptors could inhale the pollutant

particles (direct inhalation of particulate matter is addressed in Section 6.1). The amount resuspended

depends on the:

• moisture content of the soil, 

• fraction of vegetation cover, 

• wind velocity, 

• soil particle size, 

• pollutant concentration in the soil, and 

• size of the contaminated area. 

Study of estimated exposures to deposited combustor emissions via dust resuspension indicates that dust

resuspension by wind erosion is usually not a significant pathway (U.S. EPA 1998c). Methods have also

been developed to assess the exposure to pollutants resuspended by wind erosion for landfills and

Superfund sites (U.S. EPA 1985a; 1988b; 1994q). We recommend consulting these reference documents
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Equation 6-1

if you’ll be evaluating this exposure pathway. Also, it may be useful to review the methods described in

U.S. EPA (1998c).

6.2 INGESTION EXPOSURE PATHWAYS

Exposure can occur over a period of time. To calculate an average exposure per unit of time, we

recommend dividing the total exposure by the time period. Express an average exposure in terms of body

weight. Ingestion exposures quantified per the HHRAP are

• unitized for time and body weight, 

• presented in units of milligrams per kilogram of body weight per day, and 

• termed “intakes.” 

Equation 6-1 is a generic equation for calculating ingestion chemical intake (U.S. EPA 1989e):

where

I = Intake—the amount of COPC at the exchange boundary (mg/kg/day); for

evaluating exposure to noncarcinogenic COPCs, 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)

Cgen = Generic COPC concentration in medium of concern (e.g., mg/kg for soil

or mg/L for surface water; see Chapter 5)

CR = Consumption rate—the amount of contaminated medium consumed per

unit of time or event (e.g., kg/day for soil or L/day for water)

EF = Exposure frequency (days/year)

ED = Exposure duration (years)

BW = 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 25,550 days, based on a lifetime

exposure of 70 years; for noncarcinogens, averaging time equals ED

(years) multiplied by 365 days per year.
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We recommend variations of Equation 6-1 to calculate pathway- and receptor-specific exposures to

COPCs. We present the equations recommended for each exposure pathway in Appendix C. The

variation of input variables is also described in Appendix C.

The exposures calculated using the HHRAP are intended to represent reasonable maximum exposure

(RME) conditions, as further described in U.S. EPA (1989e). Studies of the compounding of

conservatism in probabilistic risk assessments show that setting as few as two factors at RME levels or

high end (e.g., near the 90th percentile), while setting the remaining variables at less protective typical, or

“central tendency” values (e.g., near the 50th percentile) results in output insignificantly different from

output generated using all input variables at an RME level (e.g., 99th percentile value) (Cullen 1994).

As described in Chapter 2 (Section 2.2.1), the estimated air concentrations and deposition rates are based

on RME emissions from trial or risk burns. We recommend setting the following variables set at RME

levels:

• the highest ISCST3 modeled air concentrations and deposition rates at chosen exposure

scenario locations, 

• the exposure frequency, and 

• the exposure duration. 

We generally recommend setting other exposure parameters (e.g. body weight) at average levels.

6.2.1 Body Weight

The choice of body weight to use in the risk characterization equations presented in Appendix C depends

on the definition of the receptor at risk—which, in turn, depends on exposure and susceptibility to

adverse effects. U.S. EPA (1990e) defines the body weight of the receptor as either adult weight

(70 kilograms) or child weight (1 to 7 years; 17 kilograms) on the basis of data presented in Nelson et al.

(1969). However, as in other Agency guidance (U.S. EPA 1991b; 1994r; 1994g), we recommend using a

weight of 15 kilograms for the child (exposure duration of 6 years) in the risk assessment. 

The daily intake for an exposure pathway is expressed as the dose per body weight. Because children

have lower body weights than adults. Typical ingestion exposures per body weight, such as for soil,
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milk, and fruits & vegetables, can be substantially higher for children. This is the primary reason to

evaluate the child resident scenario (U.S. EPA 1996g). However, using these two body weights may not

account for significant differences between weights of infants and toddlers or weights of teenagers and

adults. Please remember that, for the purposes of the risk assessment, the child scenario is defined by the

average body weight, rather than the chronological age. Obviously, the weight of a child changes

significantly over the first several years. We assume 15 kilograms is a realistic average estimate for an

exposure duration of 6 years. 15 kilograms overestimates the weight of the child for the early years, and

then underestimates it for the later years (U.S. EPA 1996g).

6.2.2 Food (Ingestion) Exposure Pathways

Plants and animals impacted by emission sources may take up emitted COPCs in the air or deposited

COPCs in soil. Humans could then be exposed to COPCs via the food chain when they consume these

plants and animals as food. We generally recommend determining human intake of COPCs based on the:

• types of foods consumed, 

• amount of food consumed per day, 

• concentration of COPCs in the food, and 

• percentage of the diet contaminated by COPCs. 

Chapter 6 describes procedures for determining the concentration of COPCs in food. It also considers

the variations in exposure resulting from food preparation methods and type of food item (e.g.,

aboveground versus belowground - i.e. root - vegetables). Other variables, described below, may also

significantly affect exposure estimates.

6.2.2.1 Types of Foods Consumed

The types of foods consumed will affect exposure, because different plant and animal tissues take up

different COPCs, and take them up at different rates. The COPC concentrations a receptor is exposed to

will then vary with the types of food in the diet. Therefore, it is important to determine COPC
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concentrations in food according to the type of food. The types of food consumed might also vary with

the age of the receptor, geographical region, and socio-cultural factors.

6.2.2.2 Food Consumption Rate

Consumption rate is the amount of contaminated medium (soil, food) consumed per unit of time or event. 

The soil at an exposure location are inherent to the location. Food consumed at an exposure location,

however, may or may not have originated there. The HHRAP assumes that only food produced at the

exposure location is contaminated by emissions from the facility being assessed. Food not produced at

the point of exposure is not assumed to be contaminated, and is irrelevant to the assessment. Therefore,

the consumption rates we recommend in the HHRAP (see Table 6-1 and Appendix C) are for food that is

both produced and consumed at the exposure location (i.e. at home). 

Please Note: these rates do not represent the entire dietary intake of the individual, but only that

portion of the diet produced at home. For example, the beef consumption rate represents only the

amount of beef consumed each day which was raised on the farm property.

TABLE 6-1

MEAN CONSUMPTION RATESa FOR RECOMMENDED EXPOSURE SCENARIOS 

(number of servings per week)

Contaminated food

Exposure Scenario

Farmer b Farmer

Childb

Resident Resident

Child

Fisher Fisher

Child

Produce (8 oz servings) 2.8 1.4 2.3 1.2 2.3 1.2

Beef (1/4 lb servings) 5.3 0.7 N/A N/A N/A N/A

Milk (8 oz servings) 29.5 10.5 N/A N/A N/A N/A

Chicken (1/4 lb servings) 2.8 0.4 N/A N/A N/A N/A

Eggs (numberc) 4.3 0.7 N/A N/A N/A N/A

Pork (1/4 lb servings) 2.4 0.4 N/A N/A N/A N/A

Fish (1/4 lb servings) N/A N/A N/A N/A 5.4 0.8

Notes:

a Values derived from the U.S. EPA Exposure Factors Handbook (1997).

b Values based on consumption rates of a 154 lb adult and a 33 lb child.

c Values based on an assumed egg weight of 3.0 ounces.
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As described in Section 6.2, exposures calculated using HHRAP methods are intended to represent RME

conditions. Accordingly, the HHRAP recommends default values for exposure parameters that will

result in RME estimates. However, there are likely to be differences between recommended default, and

regional and site-specific exposure parameter values. This may be especially true for the consumption

rates (a general term for intake rates and inhalation rates). In addition to estimates using the

recommended default parameter values, you can refine the your risk assessment by including

supplemental calculations using regional- or site-specific parameter values. We recommend doing this

only if you document the regional- or site-specific parameter values in the risk assessment report. We

recommend providing these supplemental calculations in addition to, and not instead of estimates based

on recommended default exposure parameter values. This will help standardize risk assessment methods,

thereby aiding the ability to compare outputs from different risk assessments. The following subsections

describe exposure pathway-specific considerations regarding consumption rate.

This section gives some of the pertinent history of consumption rates. It also describes the series of steps

we followed to derive the recommended consumption rates found in Table 6-1. Site-specific conditions

might exist such that you need to derive an alternative, or additional consumption rate. For example, you

may need a consumption rate for an additional exposure scenario (e.g. consumption of deer meat for a

hunter scenario). If you need to calculate your own consumption rate(s), we recommend using the

process described below. For transparency and clarity, we recommend identifying all consumption rates

used in the risk assessment. We also recommend clearly identifying and discussing alterations to

recommended default rates, and additional consumption rates, with the permitting authority prior to use.

The amount of daily food consumption varies with age, sex, body weight, and geographic region, and it

also varies within these categories. U.S. EPA (1998c) recommended using values from the 1997

Exposure Factors Handbook (EFH) (U.S. EPA 1997b) to complete the risk assessment process. The

EFH used the 1987-1988 USDA Food Consumption Survey to represent consumption rates for urban and

suburban areas. However, if site-specific information indicates that the population is in a more rural or

agricultural area, U.S. EPA (1990e) recommended using the 1966-67 USDA Food Consumption Survey

to represent the consumption rates of a more agrarian population.
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The 1997 Exposure Factors Handbook (EFH) (U.S. EPA 1997b) performed an analysis of the 1987-1988

USDA National Food Consumption Survey (NFCS). The NFCS collects information over a 7-day period

on the socioeconomic and demographic characteristics of households, and the types, values, and sources

of foods consumed. The following information was taken from the survey: 

• whether or not the food product was used in the house that week;

• whether or not the food product used that week was home produced; 

• the quantity (mass, such as pounds or kilograms) of food consumed (home produced or

not) in the house that week;

• the number, age, and body weight of individuals in the household; and 

• the number of weekly meals consumed by each family member. 

All households were surveyed about the same food types, and consumption rates were averaged over the

entire survey population - to calculate what are known in the EFH as the “Per Capita” rates. In addition,

EPA calculated consumption rates for “consumers only:” a rate for only those households which

consumed a particular food stuff during the week the survey was taken. In addition to total consumption

(i.e. for the entire population of consumers), rates were broken out according to various criteria, such as

age of consumer, geographic region, and level of urbanization. Survey participants were also asked if

they operated a farm or ranch, raised animals, or had a home garden, and consumption rates were also

broken out for these sub-groups. We recommend using food consumption rate information (ingestion

rates) from the EFH; specifically, the section regarding home produced food items. 

Chapter 13 of the EFH (Intake Rates for Various Home Produced Food Items) lists consumer only

consumption rates of home produced food. For example, Table 13-65 (Consumer Only Intake of Home

grown Root Vegetables (g/kg-day)) lists a mean consumption rate of 1.16 g/kg-day for all households

that consumed root vegetables they produced themselves. From these households, the EFH also breaks

out consumption rates specific to households who farm (e.g. a mean of 2.63 g/kg-day). These farmspecific rates represent the amount of food that farm families produced themselves that was consumed

during the week the survey was taken. We recommend using these consumption rates to estimate

exposures to the Farmer and Farmer Child scenarios. 
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The recommended farm-specific consumption rates, as listed in the EFH, are averaged across all family

members, regardless of age or body weight. They also do not consider losses during preparation and

cooking of the food. Additional work is needed, therefore, to acquire scenario-appropriate actual

consumption rates:

As mentioned above, the EFH provides consumption rates for the entire population of consumers - the

consumer only rate. Depending on data availability, the consumer only rate is also broken out into

various age-specific demographics, covering 0-1 year, 1-2 years, 3-5 years, 6-11 years, 12-19 years,

20-39 years, and 40-69 years. We suggest combining the consumer only rate, age-appropriate

demographic rates, and the sub-population rate (e.g. for a farm family) to derive a scenario-specific

consumption rate (e.g. for an adult Farmer) using equation 6-2:

Equation 6-2

where:

CRscen = Consumption rate for scenario

CRsubpop = Consumption rate of subpopulation

TWAgen = Time-weighted average of age-appropriate subset of consumer only population

CRgen = Consumption rate for consumer only population

Sufficient age-specific data were not always available. For example, there was insufficient data for the

EFH to provide a consumer only poultry consumption rate for the 12-19 age group. In this event we

suggest again using Equation 6-2, to combine the total consumer only population rate, the age-specific

Per Capita rate, and the total Per Capita rate (for poultry, Per Capita values are found in EFH Table

11-11), to generate an age-specific consumer only rate.

See the example derivation below for a demonstration of how we recommend generating scenariospecific consumption rates. To derive consumption rates for the Farmer and Farmer Child exposure

scenarios, we recommend using the home produced, consumers only consumption rates of households

who farm, for home produced beef, pork, chicken, milk, eggs, vegetables, and fruits.
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TABLE 6-2

COOKING-RELATED WEIGHT LOSSES 

FOR VARIOUS HOME-PRODUCED FOODS

Percent Weight Losses from Preparation of Various Meats

(SOURCE: EFH Table 13-5)

Meat Type Mean Net Cooking

Loss (%)

Mean Net Post Cooking

Loss (%)

Beef 27 24

Pork 28 36

Chicken 32 31

Milk N/A N/A

Eggs N/A N/A

Fish 30 11

Percent Weight Losses from Preparation of Various Produce

(SOURCE: EFH Tables 13-6 and 13-7)

Produce Type Mean Paring or

Preparation Loss

(%)

Moisture Content (%)

Protected Fruits 29 87

Protected

Vegetables

23 82

Exposed Fruit 21 85

Exposed Vegetables 16 90

Consumption rates of households who farm are not necessarily the most appropriate rates for households

who don’t farm. For certain food types, the EFH also breaks out consumption rates of home-produced

foods specific to those households who garden. This combination of subpopulation (i.e. gardeners) and

food source (i.e. home produced) is the closest option available in the EFH to the residential and fishing

scenarios we recommend in the HHRAP. Consumption rates for this subpopulation are available for the

food types included in the produce-related exposure pathways we recommend (i.e. protected produce,

exposed produce, and belowground vegetables). We recommend using these rates to generate producerelated consumption rates for the Resident, Resident Child, Fisher, and Fisher Child exposure scenarios.

The EFH provides information to account for cooking and post-cooking losses for food products which

are home produced. These data are summarized in Table 6-2. See the example derivation below for a

demonstration of how to use cooking loss data in deriving consumption rates.
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Example Consumption Rate Derivation: Homegrown Poultry consumption for the Farmer

The Farmer scenario includes an average consumption rate during a 70-year lifetime, from age 7 to 70. 

Table 13-55 of the EFH lists the following Farmer-related mean consumption rates of home produced

poultry (g/kg-day):

Total population 1.57

broken out by age group:

ages 6-11 ND (5 years)

ages 12-19 ND (8 years)

ages 20-39 1.17 (20 years)

ages 40-69 1.51 (30 years)

households who farm 1.54

Please note that though the EFH demographic subset includes years 6-11, the Farmer

scenario begins at age 7, so only 5 years of that consumption rate are used.

In addition, Table 11-11 (Mean Meat Intakes Per Individual in a Day, by Sex and Age (g/day as

consumed) for 1987-1988) lists the following Per Capita consumption rates of poultry (among others):

All individuals 26

broken out by age group:

ages 6-11 27

ages 12-19 27

Using the 12-19 age group as an example, equation 6-2 is used to calculate age-specific consumer only

rates as follows:

CRages12-19 = 1.57 * 27/26 = 1.63 g/kg-day

A time weighted average for an adult Farmer = 

And, using Equation 6-2:

CRFarmer = 1.54 * 1.43/1.57 = 1.40 g/kg-day

Table 13-5 of the EFH lists cooking and post-cooking losses for poultry of 31% and 32%, respectively. 
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Therefore:

1.40 * (1-0.31)*(1-0.32) = 0.66

Poultry consumption rate for the Farmer = 0.66 g/kg-day

Additional consumption rate information is presented in Appendix C as follows: Table C-1-2 (produce);

Table C-1-3 (beef, milk, pork, chicken, and eggs); and Table C-1-4 (fish).

6.2.2.3 Percentage of Contaminated Food

The percentage of food consumed by an individual which is home-grown will affect exposure, because

the HHRAP assumes that only the portion of an individual’s dietary intake which is home-grown is

impacted by facility emissions. 

We recommend assuming that all food produced at the exposure location - i.e. the farm for the farming

scenarios, and the home garden for the residential and fishing scenarios - is impacted by facility

emissions. Only that portion of the diet produced at home (and therefore exposed to facility emissions) is

of consequence in the risk assessment. As detailed in Section 6.2.2.2, the consumption rates we

recommend represent only the home-produced portion of the diet. Therefore, by using consumption rates

specific to home produced foods, we consider it reasonable to assume that 100% of those home produced

foods are contaminated. 

6.2.3 Soil (Ingestion) Exposure Pathway

Soil ingestion, dermal exposure to soil, and inhalation of resuspended dust are potential soil exposure

pathways. For the purpose of RCRA combustion permitting decisions, we recommend considering soil

ingestion. However, we currently only recommend evaluating dermal exposure to soil (see Section 6.3)

and inhalation of resuspended dust (see Section 6.1.1) if site-specific exposure setting characteristics

support evaluating these exposure pathways. Based on air dispersion modeling and deposition of

COPCs, emission concentrations in soil will vary with distance from the source. It’s possible to

determine potential routes of exposure by evaluating the way in which the soils in the area are used. Soil
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used for farming or recreation will be involved in pathways of human exposure that differ from those of

soil on roadways or in urban areas.

Children and adults are exposed to COPCs in soil when they consume contaminated soil that has adhered

to their hands. Factors that influence exposure by soil ingestion include soil concentration, 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 measured the quantities of non-absorbable

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 activity. Indoor dust and outdoor soil may both

contribute to the total daily ingestion. Exposure levels are also influenced by the amount of time that the

individual spends in the vicinity of soil exposed to deposition of emitted pollutants.

In addition, some young children—referred to as “pica” children—may intentionally eat soil. As

discussed in U.S. EPA (1989f), the typical medical and scientific use of the term “pica” refers to the

ingestion of non-food items, such as soil, chalk, and crayons. Such behavior is considered a temporary

behavior and a normal part of child 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

(U.S. EPA 1989f). Agency risk assessment documents don’t identify a default “pica” soil ingestion rate

(U.S. EPA 1989e; 1989f ; 1991b). Pica behavior is not generally included as part of risk assessments.

If available information indicates that there are children exhibiting pica behavior in the assessment area,

and you determine that these children represent a special subpopulation potentially receiving significant

exposure (see Chapter 4), it may be prudent to include these children in the risk assessment. We

recommend making this evaluation on a case-by-case basis based on site-specific exposure setting

characterization.

6.2.4 Water (Ingestion) Exposure Pathways

Evaluating HHRAP water exposure pathways involves estimating COPC concentrations in drinking

water from surface water bodies or collected precipitation (e.g., cisterns). Contaminants moving through

the water pathways also influence COPC concentrations in fish. Various models are available to estimate
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daily exposures of individuals using these water sources for various purposes, such as fishing and

drinking water.

We recommend using site-specific information to determine which water exposure pathways to evaluate

in the risk assessment. Whether it’s collected precipitation, or from a surface water body such as a lake,

farm pond, or city reservoir, the way in which water is used will suggest possible exposure pathways. 

For example, using a surface water body as a drinking water source will introduce water ingestion as a

possible exposure pathway. Commercial and/or recreational fishing, with subsequent use of fish and

shellfish as a food source, make the food chain an important route of exposure for communities having a

surface water body in the vicinity of a combustor.

U.S. EPA (1998c) recommended varying the water input variables to determine a range of exposures. An

individual that fishes and obtains drinking water from the same water source could represent an average

exposure scenario. A worst-case possibility might involve a person who (1) uses drinking water from a

cistern that collects precipitation, and (2) fishes in a small farm pond.

Because ground-level concentrations of COPCs generally decrease with distance from the source,

important factors in determining the water concentration include:

• the location of the precipitation-collection apparatus, 

• surface water body onto which emitted COPCs are deposited, and 

• the COPC soil concentration (which affects runoff and leachate concentrations). 

In addition, the location and size of the watershed will affect the concentration of COPCs suspended in

runoff.

6.2.4.1 Ingestion of Drinking Water from Surface Water Sources

For evaluating a surface water body as a drinking water source, exposure is affected by the COPC

concentration in the water, the daily amount of water ingested, and the length of time that the receptor

spends in the area serviced by that water supply system. The equations we recommend for estimating the

COPC concentration in a surface water body are discussed in Chapter 5 and Appendix B. These
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equations also consider contributions of COPC loading from the surrounding watershed. We recommend

using the water consumption rates specified in U.S. EPA (1997b) and described in Appendix C.

As in previous Agency guidance (U.S. EPA 1998c), we recommend typically assuming that treatment

processes for drinking water do not alter dissolved COPC concentrations.

6.2.4.2 Ingestion of Drinking Water from Ground Water Sources

For the purpose of RCRA combustion permitting decisions, we don’t typically recommend evaluating

exposure from ground water sources used as drinking water. Study of this pathway for combustor

emissions indicates that this isn’t a significant exposure pathway (U.S. EPA 1998c). However, COPCs

may - because of special site-specific characteristics - infiltrate into ground water, resulting in COPC

exposure via ingestion when ground water is used as drinking water. This could be because of extremely

shallow aquifers being tapped for drinking water, or a karst environment in which the local surface water

significantly affects the quality of ground water used as a drinking water source. The method developed

to calculate risks from the ground water pathway was originally intended for use in evaluating impacts of

the land disposal of various wastes (U.S. EPA 1998c; 1994q; 2003). We recommend consulting these

reference documents if you intend to evaluate this exposure pathway.

6.2.4.3 Ingestion of Fish

You may find the fish ingestion rates specified in U.S. EPA (1997b) and further described in HHRAP

Appendix C useful for evaluating the fish ingestion pathway. Factors that affect human exposure by

ingestion of fish from a surface water body affected by combustion unit emissions include:

• COPC concentrations in the sediment and water column, 

• the types of fish and shellfish consumed, 

• the ingestion rates for the various fish and shellfish groups, and 

• the percent of dietary fish caught in the surface water body affected by the combustor. 
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The types of fish consumed will affect exposure, because different types of fish and shellfish take up

COPCs at different rates. For example, fatty fish tend to accumulate organic COPCs more readily than

lean fish. The amount of fish consumed also affects exposure, because people who eat large amounts of

fish will tend to have higher exposures. Fish consumption rates vary greatly, depending on geographic

region and social or cultural factors. For example, populations such as Indian tribes, American & Pacific

Islanders, and some immigrant groups are known to have high local fish consumption rates. Because 100

percent of a receptor’s dietary fish may not originate from the surface water body near the combustion

facility, the percentage of locally caught fish is also a variable for exposure.

6.3 DERMAL EXPOSURE PATHWAYS

6.3.1 Dermal Exposure to Soil

For the purpose of RCRA combustion permitting decisions, We don’t typically recommend evaluating

dermal exposure to COPCs through contact with soil. However, site-specific exposure setting

characteristics may support evaluating this exposure pathway. Therefore, this section discusses dermal

soil exposure.

Available data indicate that the contribution to overall risk from dermal exposure to soils impacted from

hazardous waste combustion facilities is typically small relative to contributions resulting from exposures

via the food chain (U.S. EPA 1995h; 1996g). For example, the risk assessment conducted for the Waste

Technologies Industries, Inc., hazardous waste incinerator in East Liverpool, Ohio, indicated that—for an

adult subsistence farmer in a subarea with high exposures—the risk resulting from soil ingestion and

dermal contact was 50-fold less than the risk from any other exposure pathway and 300-fold less than the

total estimated risk (U.S. EPA 1995h; 1996g).

Humans can be exposed to COPCs by absorption through the skin when it comes into contact with

contaminated soil. Factors that affect dermal exposure include: 

• exposed skin surface area;

• contact time;
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• contact amount; 

• amount of time spent near the combustion source; and 

• fraction of COPCs absorbed through the skin. 

In general, an increased dose of COPCs can potentially be absorbed through the skin as the surface area

of the skin is increased. Surface area is affected by age and body weight; for example, children have less

total surface area than adults. The amount of surface area available for exposure to soil is also affected

by the amount of clothing worn. An adult working in the garden in long sleeves and pants will have a

smaller exposed surface than an adult working in shorts and a short-sleeved shirt. For dermal exposure

from soil, the exposed surface area affects the amount of soil that can adhere to exposed skin.

Contact time refers to the duration of time each day that skin is in contact with contaminated soil. As

duration increases, so does the amount of COPCs that can be absorbed. Dermal exposure is also affected

by the amount of time each day spent in the vicinity of the combustion source, where the soil may

contain pollutants emitted from the combustion facility. Indoor dust and outdoor soil may both increase

the daily contact. Consider seasonal exposure might also be appropriate, because regional climate will

influence contact time.

The amount of COPCs that can be absorbed through the skin depends on the chemical properties of the

COPC, properties of the soil matrix, and dermal pharmacokinetics. If a COPC can’t be readily absorbed

through the skin, the daily intake of the COPC may be small even if other exposure characteristics (e.g.

contact time) encourage absorption. However, if site-specific conditions suggest that dermal exposure to

soil may contribute significantly to total soil-related exposures, we recommend considering the

assessment methods described in U.S. EPA (2004d).

6.3.2 Dermal Exposure to Water

We don’t typically recommend evaluating the dermal water exposure pathway when assessing risk from

hazardous waste combustor emissions. However, if the surface water body affected by combustor

emissions is used frequently for recreational purposes such as swimming and boating, dermal absorption
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of contaminated water becomes another possible route for human exposure. Dermal exposure is affected

by:

• the surface area of exposed skin, 

• the COPC concentration in the water, 

• the permeability of the skin to the COPC, and 

• the length of time that the individual is in contact with the water.

6.4 EXPOSURE FREQUENCY

The HHRAP assumes that the receptors in each recommended exposure scenario are exposed to all of the

scenario-specific exposure pathways 350 days per year (U.S. EPA 1989e; 1991b; 1991d). This

assumption is based on the protective estimate that all receptors spend a maximum of 2 weeks away from

the exposure scenario location selected in Section 4.3.

6.5 EXPOSURE DURATION

Exposure duration is the length of time that a receptor is exposed via a specific exposure pathway. A

receptor is no longer exposed to COPCs via the direct inhalation exposure pathway after an emission

source ceases operation. However, a receptor could be exposed via the indirect exposure pathways for

as long as they remain in the assessment area. We recommend using default RME values to estimate

exposure duration for specified receptors.

As in U.S. EPA (1998c), we recommend assuming that receptors are exposed to the long-term average

COPC soil or water concentrations (and the subsequent COPC plant or animal concentrations) present in

the environment or media following a period of time during which there were continuous hazardous

waste combustor emissions. For existing facilities, U.S. EPA (1990e) assumed that this period of time

can be represented by default time periods of 30, 60, or 100 years. U.S. EPA (1998c) simplified this to

assume that the period could be $ 30 years. These values are based on the assumptions that the

hazardous waste combustion unit or the emission source: 

1. is already in place, 
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2. will continue to be used for the rest of its useful life (estimated to be 30 years), and 

3. may be replaced when it reaches the end of its useful life (possibly as long as 60 or 100

years), because it is an integral part of the facility operations. 

We consider these assumptions reasonable for a hazardous waste emission source, such as an industrial

boiler burning a continuous stream of facility hazardous waste.

Although a combustor may remain in the same location for 100 years—and a person may have a lifetime

of exposure to emissions from that combustor— data on population mobility (U.S. Bureau of the Census,

1986) indicate that many Americans do not remain in the same area for their 70-year lifetime. An

estimate of the number of years that a person is likely to spend in one area, such as the vicinity of a

combustion facility, can be derived from information about mobility rate and median time in a residence. 

In addition to the number of years at a particular location or residence, the amount of time spent at that

location each day directly affects exposure. For example, children that attend day care or adults that

work in a different location for part of the day may be exposed to higher or lower COPC levels.

The exposure duration values we recommend are presented in Table 6-3.

TABLE 6-3

EXPOSURE DURATION VALUES

Recommended Exposure

Scenario Receptor Value Source

Child Resident 6 years U.S. EPA 1990f; 1994r

Adult Resident 30 years U.S. EPA 1990f; 1994r

Fisher 30 years U.S. EPA 1990f; 1994r

Fisher Child 6 years Assumed to be the same as the Child

Resident

Farmer 40 years U.S. EPA 1994l; 1994r

Farmer Child 6 years Assumed to be the same as the Child

Resident
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6.6 AVERAGING TIME

For noncarcinogenic COPCs, we generally recommend using a value of exposure duration (years-as

specified for each receptor in Section 6.4) x 365 days/year as the averaging time (U.S. EPA 1989e;

1991d). However, for carcinogenic COPCs—the effects of which may have long latency periods—the

age of the receptor (i.e., child, adult, or elderly) influences the COPC exposure pathway, because the

exposure duration and, therefore, the quantity of exposure, will vary. For carcinogenic COPCs, we

recommend using an averaging time of 70 years.

We recommend evaluating carcinogenic exposures for different receptor ages separately, because the

daily activities of these receptors (and body weights, as described in Section 6.6) vary, including: 

• the amounts of food and water consumed; 

• the types of food consumed; and 

• the amount of exposed skin surface. 

Health-based criteria, such as health advisories for drinking water, are also different for children and

adults. As a result, for some exposure pathways, such as soil ingestion, children may have a greater

quantifiable exposure and be at greater risk than adults. Some behaviors, such as mouthing of dirty

objects or direct ingestion of soil, which could also contribute to exposure, are also much more prevalent

in children than adults.

Because quantifying carcinogenic COPC exposure depends on the duration of exposure, the age of the

receptor is important. For risk assessment purposes, the average human lifespan is generally considered

to be 70 years. Childhood represents only about 10 percent of the lifespan (6 years) (U.S. EPA 1998c). 

In actual exposure scenarios, individuals may be exposed only during childhood or adulthood. In other

cases, exposure may overlap these periods, such as a child who grows into adulthood and remains in the

same geographical area. Based on the age of the receptor and information on the duration of exposure,

U.S. EPA (1990e) recommended considering risk to three different receptors: 

1. a child who grows to an adult and is exposed for his or her entire 70-year lifetime, 
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C Identification of site-specific or alternate default media equations and/or inputs; including

justification and full referencing

C Exposure calculations

RECOMMENDED INFORMATION FOR THE RISK ASSESSMENT REPORT

2. a child who grows to an adult and is exposed for only a part of his or her adulthood—a

total of 30 years, and 

3. an adult exposed for 16 years.

Because the effects of certain carcinogenic COPCs may have long latency periods—in some instances

approaching the human lifespan—it may be appropriate to estimate daily intake by using the adult value

for body weight and a longer averaging time. In cases where effects have a shorter latency period,

U.S. EPA (1990e) recommended an averaging time period of less than 10 years. However, where

children are known to be at special risk, it may be more appropriate to use this averaging time with a

body weight value for toddlers, infants, or young children. For COPCs classified as carcinogens, we

recommend using a longer averaging time and the adult body weight to calculate the risk resulting from

air or water exposure.

It is significant that childhood is defined differently in the different references. U.S. EPA (1990e)

defines childhood as being from 1 to 7 years old. As in this and other Agency guidance (U.S. EPA

1991b; 1994r; 1998c), we define childhood as having an exposure duration of 6 years. Please note that

some of the data used for input into the various exposure scenario equations in Appendix C was not

available for children, or was available for more restrictive age groups, such as 2-year-olds or 4- to

6-year-olds. In such cases, and as noted in Appendix C where such values are presented,

1. the available data were evaluated to ensure that the presented default values are

sufficient for conducting a risk assessment, and 

2. in cases in which the available data were not sufficient, reasonable interpolations of the

available data were possible.
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PLEASE NOTE: for the purposes of this guidance, “we” refers to the U.S. EPA OSW. 

The HHRAP is written for the benefit of a varied audience, including risk assessors,

regulators, risk managers, and community relations personnel. However, the “you” to

which we speak in this chapter is the performer of a risk assessment: the person (or

persons) who will actually put the recommended methods into practice.

Chapter 7

Characterizing Risk and Hazard

What’s Covered in Chapter 7:

7.1 Quantitatively Estimating Cancer Risk

7.2 Quantitatively Estimating Noncancer Hazard

7.3 Target Levels 

7.4 Estimating Acute Exposure from Direct Inhalation

It is important that risk characterization exhibit the core values

of transparency, clarity, consistency, and reasonableness

(please see the related EPA Information Quality Guidelines

recommendations as discussed in Chapter 1, page 1-11).

The final step of a risk assessment is risk characterization. This involves combining the exposure

quantities generated in Chapter 6, and the toxicity benchmarks available in the HHRAP companion

database, to calculate the excess lifetime cancer risks (risk) and noncancer hazards (hazard) for each of

the pathways and receptors identified in Chapter 4. Risks (and hazards) are then summed for each

receptor, across all applicable exposure pathways, to obtain an estimate of total individual risk and

hazard. Risk characterization also involves documenting the uncertainties and limitations associated with

the rick assessment, as described in Chapter 8.

Risk from exposure to combustor emissions is the probability that a human receptor will develop cancer,

based on a unique set of exposure, model, and toxicity assumptions. We recommend using the slope or

unit risk factor in risk assessments to estimate the probability of an individual developing cancer as a
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 1 Currently 2,3,7,8-TCDD TEQ and dioxin-like PCBs are the only COPCs with biotransfer factors for the

breastmilk pathway. However, appropriate biotransfer factors for other chemicals may become available and thus

provide the information needed to include them in this pathway evaluation. We suggest consulting Chapter 9

(Breastmilk Pathway) of U.S. EPA (1998c).

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result of exposure to a particular level of a COPC. For example, a risk of 1 x 10-5 is interpreted to mean

that an individual has up to a one in 100,000 chance of developing cancer during their lifetime from the

exposure being evaluated. In contrast, hazard is the potential for developing noncancer health effects as

a result of exposure to COPCs. A hazard is not a probability but, rather, a comparison (calculated as a

ratio) of a receptor’s potential exposure relative to a standard exposure level (RfD or RfC). The standard

exposure level is calculated over a similar exposure period and is estimated to pose no appreciable

likelihood of adverse health effects to potential receptors, including special populations (U.S. EPA

1989e).

Risks and hazards here are typically characterized for single scenarios, and are referred to as individual

risks and hazards (U.S. EPA 1989e; 1994g; NC DEHNR 1997). Individual risk and hazard descriptors

are intended to convey information about the potential risks to individuals potentially impacted by

emissions from a facility burning hazardous waste. A risk assessment developed following the

procedures described in Chapters 2 through 8 and Appendixes B and C will provide 

• quantitative and qualitative estimates of risk and hazard associated with exposure to

COPCs;

• estimates of blood levels associated with exposure to lead;

• evaluation of infant exposure via breast milk to COPCs with appropriate biotransfer

factors1

, and 

• evaluation of acute risk and hazard resulting from direct inhalation.

If a permitting authority feels that you need to consider calculating population risks, we recommend

following the applicable methods described in the U.S. EPA NCEA document, Methodology for

Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions (U.S.

EPA 1998c).

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
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C Indicate the scope of the risk assessment (match the level of effort to the scope)

C Summarize the major risk conclusions.

C Identify key issues (a key issue is critical to properly evaluate the conclusions). For example,

was surrogate or measured emissions data used.

C Describe clearly the methods used to determine risk (provide qualitative narration of the

quantitative results).

C Summarize the overall strengths and major uncertainties.

INFORMATION RECOMMENDED FOR RISK ASSESSMENT REPORT

cancer risk estimates are usually reported as one significant figure. We recommend rounding only the

final reported results, not the intermediate calculations. 

7.1 QUANTITATIVELY ESTIMATING CANCER RISK

As described above, risk estimates represent the incremental probability that an individual will develop

cancer over a lifetime as a result of a specific exposure to a carcinogenic chemical (U.S. EPA 1989e). We

recommend calculating these risks as follows:

Inhalation Cancer Risk

Cancer Risk = EC @ URF Equation 7-1

where

EC = Exposure concentration (:g/m3

) [see Chapter 6]

URF = Unit risk factor (:g/m3

)

-1

Ingestion Cancer Risk

Cancer Risk = LADD @ CSF Equation 7-2

where

LADD = Lifetime average daily dose (mg/kg-day)

CSF = Cancer slope factor (mg/kg-day)-1
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PLEASE NOTE: In the Supplemental Guidance for Assessing Susceptibility from

Early-Life Exposure to Carcinogens (U.S. EPA 2005g), the Agency recommends

estimating inhalation and ingestion cancer risk slightly differently for carcinogens the

Agency determines to cause cancer by a mutagenic Mode of Action (MOA, as defined in

Guidelines for Carcinogen Risk Assessment [U.S. EPA 2005f]). Unfortunately, we haven’t

completed our recommendations for how to implement the guidelines set out in U.S. EPA

(2005f; g). We recommend periodically checking the EPA hazardous waste combustion

web site (http://www.epa.gov/epawaste/hazard/tsd/td/combust/index.htm) for updates on our

recommendations.

It’s possible for receptors to be exposed to multiple COPCs within a individual exposure pathway. We

recommend estimating the total risk associated with exposure to all COPCs through a single exposure

pathway as follows (U.S. EPA 1989e):

 Cancer RiskT = 3i Cancer Riski Equation 7-3

where

Cancer RiskT = Total cancer risk for a specific exposure pathway

Cancer Riski = Cancer risk for COPC i for a specific exposure pathway

Receptors might be exposed through a number of exposure pathways (see Table 4-1). We consider it

appropriate to sum risks from multiple exposure pathways for a given receptor. The cumulative risk

posed to a receptor is the sum of total risks from each individual exposure pathway. Express the

cumulative risk as follows:

Cumulative Cancer Risk = 3 Cancer RiskT Equation 7-4

where

Cumulative Cancer Risk= Cumulative cancer risk from multiple exposure

pathways

Cancer RiskT = Cumulative cancer risk for exposure pathway T

In addition to multiple pathways, a receptor might be exposed to emissions from multiple sources (See

Chapter 2 for additional discussion on emission sources). In addition to emission source-specific

risk/hazard estimates (see Chapter 3 regarding source-specific modeling), we recommend summing the

risks from all modeled sources for each receptor at each exposure scenario location. For example, if a

facility operates an incinerator and a boiler that both burn hazardous waste, sum the risks from both units

for each receptor. For fugitive emissions from storage and handling of hazardous waste, add the risk
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 2 Some chemicals don’t demonstrate a threshold response. Lead and ozone are two examples of chemicals with

noncancer effects that don’t have a threshold below which no adverse effects are observed.

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associated with fugitive emissions to the risks from the combustion unit for each receptor at each

exposure scenario location. 

We present the equations we recommend to estimate dose and risk levels in Appendix C. The HHRAP

companion database presents inhalation URFs and oral CSFs for many potential COPCs. However, for

each risk assessment, we recommend checking the hierarchy of toxicity benchmark and slope factor

resources listed in Appendix A-2, Section A2.6 (Human Health Benchmarks) for updated values. We

suggest using the same hierarchy to acquire toxicity values for COPCs not identified in Appendix A-2.

In the assessment of carcinogenic risk from COPCs, we recommend U.S. EPA-derived or reviewed health

benchmarks (URFs and CSFs). However, for numerous compounds, a complete set of inhalation and oral

EPA-derived health benchmarks are not available. In such cases, we calculated the health benchmarks

presented in the companion database based on available U.S. EPA-derived benchmark values. 

If relevant information is not available from these sources, we recommend contacting the appropriate

permitting authority, which may be able to assist in developing the necessary toxicity values. For

example, Minimum Risk Levels published by the Agency for Toxic Substances and Disease Registry

(ATSDR) might be applicable.

7.2 QUANTITATIVELY ESTIMATING NONCANCER HAZARD

Standard risk assessment models assume that, for most chemicals with noncancer effects, the noncancer

effects exhibit a threshold response2

,. That is, there is a level of exposure below which no adverse effects

will be observed (U.S. EPA 1989e). The default approaches used by USEPA to assess the potential for

health effects associated with a nonlinear or threshold relationship with exposure as set out in U.S. EPA

(2002; 2005f) involve:

1. Comparing an estimate of ingested exposure (see Chapter 6) to an RfD for oral exposures;

and 
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RfC

EC

or HQ RfD

ADD HQ = = Equation 7-5

2. Comparing an estimated chemical-specific air concentration to the RfC for direct

inhalation exposures. 

An RfD is a daily oral intake rate that is estimated to pose no appreciable risk of adverse health effects,

even to sensitive populations, over a 70-year lifetime. Similarly, an RfC is an estimated daily

concentration of a chemical in air, the exposure to which over a specific exposure duration poses no

appreciable risk of adverse health effects, even to sensitive populations (U.S. EPA 2002).

The exposure durations assumed for the exposure pathways identified in Table 4-1 range from subchronic

to chronic in relative length. However, we consider it appropriate to use chronic RfDs and RfCs to

evaluate all recommended exposure pathways. The comparisons of oral and inhalation exposure

estimates to RfD and RfC values, described above, are known as hazard quotients (HQ), which are

calculated as follows:

where

HQ = Hazard quotient (unitless)

ADD = Average daily dose (mg/kg-day)

RfD = Reference dose (mg/kg-day)

EC = Exposure air concentration (mg/m3

)

RfC = Reference concentration (mg/m3

)

Please note that each program office within U.S. EPA determines what HQ level poses a concern to

exposed individuals. For example, Superfund has determined that an HQ of less than or equal to 1 is

considered health-protective (U.S. EPA 1989e). However, because RfDs and RfCs do not have equal

accuracy or precision, and are not based on the same severity of effect, the level of concern does not

increase linearly as an HQ approaches and exceeds 1 (U.S. EPA 1989e). In addition, noncancer estimates

only identify the exposure level below which adverse effects are unlikely; an RfD or RfC does not say

anything about incremental risk for higher exposures (U.S. EPA 1998c). 

Also note that background exposures may be an important consideration in setting HQ levels of concern. 

This is because you generally model noncancer effects as thresholds, and biologic systems (including

human receptors) do not distinguish between exposures from regulated versus non-regulated sources. In
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certain cases, a permitting authority may elect to adjust the assessed facility-specific HQ downward, to

account for any exposure that individuals may have from non-assessed sources.

As with carcinogenic chemicals, a receptor might be exposed to multiple chemicals associated with

noncancer health effects. We recommend calculating the total chronic hazard for each exposure pathway

by following the procedures outlined in U.S. EPA (1986e; 1989e; and 2000e). Specifically, the total

chronic hazard attributable to exposure to all COPCs through a single exposure pathway is known as a

hazard index (HI). The HI is calculated as follows:

HI = 3i HQi Equation 7-6

where

HI = Hazard index for a specific exposure pathway

HQi = Hazard quotient for COPC i

This method assumes that the health effects of the various COPCs are additive. This method is a

simplification of the HI concept because it doesn’t, at this stage, directly consider the portal of entry

associated with each exposure pathway (i.e. inhalation, or ingestion). This method also doesn’t consider

the often unique toxic endpoints and toxicity mechanisms of the various COPCs. 

As discussed in Section 7.1 for carcinogenic risks, a receptor might be exposed to COPCs associated with

noncancer health effects through more than one exposure pathway, and from multiple emissions sources. 

We recommend estimating the noncancer hazards from each modeled source (including fugitive

emissions) separately, as well as all sources summed for each receptor. We consider it reasonable to

estimate a receptor’s total hazard as the sum of the HIs for each of the exposure pathways chosen for the

receptor. Specifically, a receptor’s cumulative hazard is the sum of hazards from each individual

exposure pathway, expressed as follows:

 Cumulative HI = 3 HI Equation 7-4

where

Cumulative HI = Cumulative hazard index from all scenario-specific exposure

pathways

HI = Hazard index for a specific exposure pathway
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Summing all HIs

As stated above, estimating a single HI encompassing

all HIs across all exposure pathways is a simplification

of the HI concept. However, it may save valuable

resources: if the single HI is not above the target

hazard level, then no further segregation would be

necessary. We recommend this as a first step, and

going to the expense of segregating HIs only if the

single HI falls above the target hazard level.

As in U.S. EPA (1989e), we recommend further evaluating a cumulative HI which exceeds the target

hazard level. A cumulative HI can exceed the target hazard level due to either 

• One or more COPCs with an HQ exceeding the target hazard level, or 

• The summation of several COPC-specific HQs that are each less than the target hazard

level.

In the former case, you can interpret the presence of at least one COPC-specific hazard greater than the

target hazard level as indicating the potential for noncancer health effects. In the latter case, you need to

perform a detailed analysis to determine whether the potential for noncancer health effects is accurately

estimated by the total HI. This is because the toxicological effects associated with exposure to multiple

chemicals, often through different exposure pathways, may not be additive. The total HI might therefore

overestimate the potential for noncancer health effects. 

To address this issue, we recommend summing the COPC-specific hazards according to toxicological

similarity (e.g. the same target organs or systems) (U.S.

EPA 2000e). This process is referred to as segregating the

HI. It is especially important to consider any differences

related to exposure route. If any segregated HI exceeds

the target hazard level, noncancer health effects cannot be

ruled out. However, if all segregated HIs are less than the

target hazard level, noncancer health effects are not likely

to result from exposure to the COPCs included in the HI.

Technically, segregating the HI based only on target organs or systems is a simplification of HI. Ideally,

the HI would also be segregated according to the often unique mechanisms of toxicity of the COPCs. 

However, segregating the HI based on mechanisms of toxicity is beyond a screening level or initial risk

evaluation approach (U.S. EPA 2000e).

The HHRAP companion database includes information on target organs and systems that are affected by

each COPC. The database also presents RfDs and RfCs for these same COPCs. If you include COPCs

not identified in Appendix A-2 (and therefore not in the companion database) in the risk assessment, we

recommend obtaining RfDs and RfCs for these compounds using the hierarchy of toxicity benchmark and
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slope factor resources listed in Appendix A-2, Section A2.6 (Human Health Benchmarks). If relevant

information is not available from these sources, we recommend working with the permitting authority to

contact the U.S. EPA National Center for Environmental Assessment (NCEA) office in Cincinnati, Ohio. 

NCEA personnel may be able to assist in developing the necessary toxicity values.

In the assessment of noncancer risk from COPCs, we recommend U.S. EPA-derived or reviewed RfDs

and RfCs. However, for numerous compounds, a complete set of inhalation and oral health benchmarks is

not available. If such was the case for COPCs listed in Appendix A-2, we calculated the health

benchmarks presented based on available U.S. EPA-derived benchmarks values. For instance, if the oral

RfD (mg/kg/day) was available and the RfC (mg/m3

) was not, we calculated the RfC by multiplying the

RfD by an average human inhalation rate of 20 m3

/day and dividing by the average human body weight of

70 kg. This conversion is called a route-to-route extrapolation, which assumes that the toxicity of the

given compound is equivalent over all routes of exposure. 

Route-to-route extrapolation introduces additional uncertainty into the risk assessment, and there isn’t

Agency consensus regarding the appropriateness of its use. This method assumes that the qualitative data

supporting the benchmark value for a certain route also applies to the route in question. For example, if

an RfD is available and you calculate the RfC from that value, you are assuming that the toxicity seen

following oral exposure will be equivalent to toxicity following inhalation exposure. This assumption

could overestimate or underestimate the toxicity of the given compound following inhalation exposure. 

Because of the degree of uncertainty involved in using toxicity benchmark values calculated based on

route-to-route extrapolation, we recommend using route-to-route extrapolations for organic compounds

(but not inorganic), and revisiting the appropriateness of applying this extrapolation for individual

chemicals if they are found to be risk drivers. An example might include using route-to-route

extrapolations as the first step in a screening risk assessment, then expending resources evaluating the

appropriateness of only those extrapolations associated with risk drivers. Including this further evaluation

(a qualitative assessment of the toxicity information available for the compound and exposure route ) in

the Uncertainty section of the risk assessment report will enable the risk manager to make an informed

decision concerning the validity of values calculated based on route-to-route extrapolation.
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7.3 TARGET LEVELS

Target levels are risk management-based and set by the permitting authority. Target values are not a

discrete indicator of observed adverse effect. If a risk estimate falls below target levels, a regulatory

authority may, without further investigation, conclude that a proposed action does not present an

unacceptable risk. A risk estimate that exceeds these targets, however, would not, in and of itself,

necessarily indicate that the proposed action is not safe or that it presents an unacceptable risk. Rather, a

risk estimate that exceeds a target value triggers further careful consideration of the underlying scientific

basis for the calculation.

7.4 ESTIMATING ACUTE EXPOSURE FROM DIRECT INHALATION

In addition to long-term chronic effects, we recommend considering short-term or acute effects from

direct inhalation of vapor phase and particle phase COPCs. Short-term emissions don’t typically have a

significant impact through the indirect exposure pathways (as compared to impacts from long-term

emissions). Therefore, we recommend evaluating acute effects only through the short-term (maximum 1-

hour) inhalation of vapors and particulates exposure pathway of the acute risk scenario. We give our

recommendations for where and when to evaluate the acute risk scenario in Sections 4.2 and 4.3. 

In order to establish acute inhalation exposure criteria (AIEC), we needed to identify and evaluate

1. Existing guidelines for acute inhalation exposure; and 

2. Existing approaches for developing acute inhalation exposure levels. 

Existing approaches are composed of hierarchical guidelines for acute inhalation exposure, ranked in

order of applicability and technical basis, and all being protective of the general public. 

Please Note: hierarchical approaches are needed because criteria values are COPCspecific, and no single organization or method has developed acute criteria values or

benchmarks for all of the potential COPCs.

7.4.1 Existing Hierarchical Approaches for Acute Inhalation Exposure

Existing guidelines or criteria for evaluating acute inhalation exposure have been or are being developed

by several organizations in the United States, including: 
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• Agency for Toxic Substances and Disease Registry (ATSDR 1997); 

• American Conference of Governmental Industrial Hygienists (ACGIH 1996); 

• American Industrial Hygiene Association (AIHA 1997); 

• California Environmental Protection Agency (Cal/EPA) (Cal/EPA 1999); 

• National Advisory committee (NAC 1997); and 

• National Institute of Occupational Safety and Health (NIOSH 1994); 

• National Research Council Committee on Toxicology (NRC COT 1986; U.S. EPA

1987b); 

• Occupational Safety and Health Administration (NIOSH 1994); 

• U.S. Department of Energy, Subcommittee on Consequence Assessment and Protective

Actions (SCAPA) (SCAPA 2001a; 2001b). 

• U.S. EPA (U.S. EPA 1987b); 

Acute inhalation exposure guidelines and criteria are 

• Designed to protect a variety of exposure groups, including occupational workers,

military personnel, and the general public, 

• Based on varying exposure durations up to 24 hours in length, and 

• Intended to protect against a variety of toxicity endpoints ranging from discomfort or

mild adverse health effects to serious, debilitating, and potentially life-threatening effects,

up to and including death. 

Hierarchical approaches for establishing acute inhalation exposure levels protective of the general public

have been developed by a variety of organizations and teams of organizations. These organizations

include:

C U.S. Department of Defense (DoD 1996); 

C U.S. Department of Energy (DoE) (SCAPA 1997a; WSRC 1998).

C U.S. EPA Region 3 (EPA 1996b); 

C U.S. EPA Region 10 (U.S. EPA 1996a); and
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C Federal Emergency Management Agency, Department of Transportation (DoT), and

U.S. EPA (U.S. EPA 1993i).

The acute inhalation exposure guidelines developed by these organizations are generally quite

heterogenous, developed to protect different subpopulations against different effects and apply to various

exposure durations. All the hierarchical approaches listed above except the SCAPA approach needed to

adjust the existing guidelines using safety factors (usually multiples of 10) to account for differences in

exposure group, exposure duration, and toxicity endpoint, to arrive at acute inhalation exposure values

applicable to the general public.

In contrast to the hierarchical approaches developed using safety factors, the DoE’s Emergency

Management Advisory Committee’s SCAPA developed temporary emergency exposure limits (TEELs)

based on tiered, formula-like statistical analyses between existing guidelines for acute inhalation exposure

and AIHA emergency response planning guidelines (ERPG) (Craig et al. 1995; WSRC 1998). The

methodology is described at http://www.orau.gov/emi/scapa/files/Method_for_deriving_TEELs.pdf and

available on-line at http://www.atlintl.com/DOE/teels/teel/teel_pdf.html. Like ERPGs, TEELs are

multiple-tiered, representing concentrations associated with no effects (TEEL-0), mild, transient effects

(TEEL-1), irreversible or serious effects (TEEL-2), and potentially life-threatening (TEEL-3). DOE

developed TEELs for situations where no other value is available. TEELs do not undergo peer review. 

For compounds for which TEEL values could not be developed using this approach, SCAPA developed a

supplementary approach using available toxicity information, primarily (1) lethal dose and concentration

median, and (2) lethal dose and concentration low values (DoE 1997a). 

7.4.2 Our Recommended Hierarchical Approach

After reviewing the existing hierarchical approaches, we recommend the following approach. Because of

the daily operations of most combustion units and the potential for upset conditions to sometimes occur

during operations, we consider acute values that address intermittent exposures more appropriate and

more protective than values that are based on the assumption that acute exposures will be one-time only. 

When available, we recommend using values from all of the sources that are based on one-hour

exposures.
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1. Cal/EPA Acute RELs – the concentration in air at or below which no adverse health

effects are anticipated in the general population, including sensitive individuals, for a

specified exposure period (Cal/EPA 1999)

(On-Line Address – http://www.oehha.ca.gov/air/pdf/acuterel.pdf)

2. Acute inhalation exposure guidelines (AEGL-1) – “the airborne concentration of a

substance above which it is predicted that the general population, including susceptible

individuals, could experience notable discomfort, irritation, or certain asymptomatic

nonsensory effects. However, the effects are not disabling and are transient and

reversible upon cessation of exposure.” (NOAA 2001; U.S. EPA 2001a) (On-Line

Address – http://www.epa.gov/oppt/aegl/)

3. Level 1 emergency planning guidelines (ERPG-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.” (DoE 2001; SCAPA 2001b)

(On-Line Address – http://www.bnl.gov/emergencyservices/)

4. Temporary emergency exposure limits (TEEL-1) – “the maximum concentration in air

below which it is believed nearly all individuals could be exposed without experiencing

other than mild transient adverse health effects or perceiving a clearly defined odor.”

(DoE 2001; SCAPA 2001a) (On-Line Address –

http://orise.orau.gov/emi/scapa/files/Method_for_deriving_TEELs.pdf)

5. AEGL-2 values – “the airborne concentration of a substance above which it is predicted

that the general population, including susceptible individuals, could experience

irreversible or other serious, long-lasting adverse health effects or an impaired ability to

escape.” AEGL-2 values are to be used only if lower ERPG-1 or TEEL-1 values are not

available. (NOAA 2001; U.S. EPA 2001a) (On-Line Address –

http://www.epa.gov/oppt/aegl/)

The hierarchy is presented in order of preference, from 1 (most preferred) to 5 (least preferred). We

generally recommend the Acute Reference Exposure Levels (Acute RELs) developed by Cal/EPA

(Cal/EPA 1999) as the first choice for acute inhalation values. If no acute REL value is available for a

given COPC, you can work down the list in order. If no AEGL-1 value is available, but an AEGL-2

value is available, select the AEGL-2 as the AIEC only if it’s a more protective value (lower in

concentration) than an ERPG-1, or a TEEL-1 value if either of these values is available. If no acute

values are available for a COPC, an acute value can be developed following the toxicity-based approach

used by SCAPA (Tier 5) (DoE 1997a; WSRC 1998). The companion database provides a listing of

AIECs compiled from values currently available following the hierarchical approach presented above.
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Please note that the TEEL-1 values (SCAPA 2001a) are calculated assuming a 15-minute exposure

period. As discussed in Section 3.10, for the purposes of this protocol, we recommend evaluating risks

due to acute exposure based on the highest 1-hour average air concentrations. Therefore, the TEEL-1

values were extrapolated from a 15-minute to a 1-hour exposure basis using a modification to Haber’s

Rule developed by ten Berge et al (1986) and used by Cal/EPA to develop acute RELs (Cal/EPA 1999),

as shown below.

Cn @ T = K Equation 7-8

where

C = Concentration (mg/m3

)

n = Constant greater than zero (unitless)

T = Time of exposure (hour)

K = Constant level or severity of response (unitless)

Where available, chemical-specific values for the exponent n were used to make the extrapolations

(Cal/EPA 1999). For chemicals for which a chemical-specific value of n was not available,

extrapolations were made using a value of n = 1, as recommended by OEHHA, because the extrapolations

were all based on an initial exposure period (15-minutes) of less than 1 hour duration (Cal/EPA 1999).

Using the modified form of Haber’s Rule allows you to consider contributions by both concentration and

time to the overall severity of effect. However, we highly recommend taking special care interpreting the

extrapolated air concentrations, as they aren’t absolutes. For example, chemical-specific values of the

exponent n are sometimes based on a relatively limited set of dose-response data. Also, the majority of

extrapolated TEEL-1 values were calculated using default exponent values and, therefore, are likely to be

even less certain than exponent values based on limited data sets.

The EPA IRIS program is currently developing additional acute reference values that do not exclude

intermittent exposures. When available, we recommend using those values (referred to as Acute

Reference Concentrations [Acute RfCs]) as the first choice, with the Cal/EPA acute RELs second in the

hierarchy.

7.4.3 Characterizing Potential Health Effects from Acute Exposure

We recommend characterizing the potential for adverse health effects from acute exposure to

COPC-specific emissions by comparing the acute air concentration (Cacute) resulting from maximum
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AIEC

C AHQ acute

inh

⋅ 0.001 = Equation 7-9

emissions over a 1-hour period to the COPC-specific AIEC (see Appendix C, Table C-4-1). This

comparison is known as the acute hazard quotient (AHQinh). Chapter 3 discusses air dispersion modeling

related to obtain 1-hour maximum values. Appendix B, Table B-6-1 describes how to calculate Cacute. 

We recommend using Equation 7-9 to calculate the AHQinh:

where

AHQinh = Acute hazard quotient (unitless)

Cacute = Acute air concentration (:g/m3

)

0.001 = Conversion factor (mg/:g)

AIEC = Acute inhalation exposure criteria (mg/m3

)

We recommend calculating acute hazard quotients at the selected acute exposure scenario locations (see

Sections 4.2 and 4.3) for COPCs specific to emissions from each source, and from all facility sources

combined. We recommend summing acute hazard quotients from individual chemicals (e.g. acid gases),

if they have similar effects. Setting target levels for evaluating acute hazard quotients is a risk

management decision made by the permitting authority.
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Chapter 8

Interpreting Uncertainty 

for Human Health Risk Assessment

What’s Covered in Chapter 8:

8.1 Uncertainty and Limitations of the Risk Assessment Process

8.2 Types of Uncertainty

8.3 Qualitative Estimates of Uncertainty

8.4 Quantitative Estimates of Uncertainty

8.5 Risk Assessment Uncertainty Discussion

PLEASE NOTE: for the purposes of this guidance, “we” refers to the U.S. EPA OSW. 

The HHRAP is written for the benefit of a varied audience, including risk assessors,

regulators, risk managers, and community relations personnel. However, the “you” to

which we speak in this chapter is the performer of a risk assessment: the person (or

persons) who will actually put the recommended methods into practice.

This section discusses interpreting uncertainties associated with the risk assessment. The discussion of

uncertainties in Section 8.1 and 8.2 was adopted from the 1996 Risk Assessment Support to the

Development of Technical Standards for Emissions from Combustion Units Burning Hazardous Waste.

8.1 UNCERTAINTY AND LIMITATIONS OF THE RISK ASSESSMENT PROCESS

Uncertainty can be introduced into a health risk assessment at every step of the process outlined in this

document. Uncertainty occurs because risk assessment is a complex process, requiring the integration of

the following:

C Release of pollutants into the environment

C Fate and transport of pollutants, in a variety of different and variable environments, by

processes that are often poorly understood or too complex to quantify accurately
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C Potential for adverse health effects in humans, as extrapolated from animal studies

C Probability of adverse effects in a human population that is highly variable genetically,

and in age, activity level, and lifestyle

Uncertainty is inherent in the process even when using the most accurate data and the most sophisticated

models. The method we recommend in the HHRAP relies on a combination of point values—some

protective and some typical—yielding a point estimate of exposure and risk that falls at an unknown

percentile of the full distributions of exposure and risk. For this reason, the degree of conservatism in risk

estimates cannot be known. Therefore, you need a formal uncertainty analysis to determine the degree of

conservatism. Section 8.2 discusses the types of uncertainty and the areas in which uncertainty can be

introduced into an assessment. The remaining Sections discuss methods for qualitatively and

quantitatively addressing uncertainty in risk assessments.

It should also be noted, variability is often used interchangeably with the term “uncertainty,” but this is

not strictly correct. “Variability” may be tied to variations in physical and biological processes. 

Variability can’t be reduced with additional research or information, although it may be known with

greater certainty (for example, the age distribution of a population may be known and represented by the

mean age and its standard deviation). “Uncertainty” is a description of the imperfect knowledge of the

true value of a particular variable, or its real variability in an individual or a group. 

In general, uncertainty is reducible by additional information-gathering or analysis activities (that is,

better data or better models), whereas real variability won’t change (although it may be more accurately

known) as a result of better or more extensive measurements (Hattis and Burmaster 1994).

8.2 TYPES OF UNCERTAINTY

Finkel (1990) and U.S. EPA (1999f) classified all uncertainty into four types: 

1. variable uncertainty, 

2. model uncertainty, 

3. decision-rule uncertainty, and 

4. variability. 
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Variable uncertainty and model uncertainty are generally recognized by risk assessors as major sources

of uncertainty. Variable uncertainty occurs when variables appearing in equations cannot be measured

precisely or accurately, because of either (1) equipment limitations, or (2) spatial or temporal variances

between the quantities being measured. Random, or sample, errors are common sources of variable

uncertainty that are especially critical for small sample sizes. It is more difficult to recognize nonrandom,

or systematic, errors that result from the basis for sampling, experimental design, or choice of

assumptions.

Model uncertainty is associated with all models used in all phases of a risk assessment, including: 

• animal models used as surrogates for testing human carcinogenicity, 

• the dose-response models used in extrapolations, and 

• the computer models used to predict the fate and transport of chemicals in the

environment. 

Using rodents as surrogates for humans introduces uncertainty into the risk factor because of the

considerable interspecies variability in sensitivity. Computer models are simplifications of reality,

requiring exclusion of some variables that influence predictions but cannot be included in models because

of (1) increased complexity, or (2) a lack of data for these variables. The importance of excluded

variables is generally considered on a case-by-case basis. A specific variable may be important, in terms

of its 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. Finally, choosing the correct model form is often difficult, because conflicting theories appear to

explain a phenomenon equally well.

The models we recommend in the HHRAP were selected based on scientific policy. We selected the air

dispersion and deposition model, and the indirect exposure models, because they provide the information

you need to conduct indirect assessments, and we consider them state-of-the-science. ISCST3—the air

dispersion model we recommend—has not been widely applied in its present form. Few data are

available on atmospheric deposition rates for chemicals other than criteria pollutants, thereby making it

difficult to select input variables related to deposition, or validate modeled deposition rates. Long-range

transport of pollutants into and out of the study areas wasn’t modeled, resulting in an underestimation of

risk attributable to each facility.
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In addition to air dispersion modeling, using other fate and transport models recommended by this

guidance can also result in some uncertainty. For example, the models which estimate COPC

concentrations in waterbodies may be particularly protective for waterbodies located in estuarine

environments with tidal influence. Because tidal influence is not considered in the models presented in

Chapter 5, the resulting dilution of COPC concentrations in water and sediments likely caused by tidal

influence won’t be considered in the risk assessment. Thus, the risk assessment results will likely be

more protective for tidally influenced waterbodies than for those waterbodies that aren’t tidally

influenced. We recommend that permitting decisions based on risk estimates for estuarine environments

consider this uncertainty. The delineation of this uncertainty may be one area that could be addressed in a

more refined site-specific risk assessment, if warranted.

Decision-rule uncertainty is probably of greatest concern to risk managers. This type of uncertainty

arises, for example, out of the need to balance different social concerns when determining an acceptable

level of risk. The uncertainty associated with risk analysis influences many policy and risk management

decisions. Possibly the most important aspect for the risk estimates is the selection of constituents to be

assessed. Constituents that are identified using the process provided in this document will include

compounds that have the potential to pose the greatest risk to human health through indirect exposure

routes. For example, many PICs are highly lipophilic and tend to bioaccumulate in the food chain,

thereby presenting a potentially high risk through the consumption of contaminated food.

A second area of decision-rule uncertainty includes the use of standard Agency default values in the

analysis. These include inhalation rates, body weight, and lifespan, which are standard default values

used in most Agency risk assessments. Inhalation rate is highly correlated to body weight for adults. 

Using a single point estimate for these variables instead of a joint probability distribution ignores a

variability that may influence the results by a factor of up to two or three.

A third area of decision-rule uncertainty is the use of Agency-verified cancer SFs, RfDs, and RfCs. These

health benchmarks are used as single-point estimates throughout the analysis, and uncertainty and

variability are both associated with them. U.S. EPA has developed, however, a process for setting

verified health benchmark values to be used in all Agency risk assessments. This process is used to

account for much of the uncertainty and variability associated with the health benchmarks. With the

exception of the dioxin toxicity equivalency methodology, health benchmarks which can be found on
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IRIS, have been verified through Agency work groups. Estimating the uncertainty in using Agnecyverified health benchmarks or the dioxin toxicity equivalency methodology is beyond the scope of the

HHRAP.

8.3 QUALITATIVE ESTIMATES OF UNCERTAINTY

Often, sources of uncertainty in a risk assessment can be identified but not quantified. For example, this

can occur when you know (or suspect) a factor to vary, but have no data (e.g., presence of COPCs without

toxicity data, amount of time that people at a specific site spend outdoors). In such cases, default data

may be available that can be useful in estimating a possible range of values. Uncertainty also often arises

out of a complete lack of data. A process may be so poorly understood that you can’t quantify the

uncertainty with any confidence. In addition, some sources of uncertainty (such as uncertainty in theories

used to deduce models) are inherent qualifications reflecting subjective modes of confidence rather than

probabilistic arguments. When you can only present the uncertainty qualitatively, you might consider the

possible direction and orders of magnitude of the potential error.

8.4 QUANTITATIVE ESTIMATES OF UNCERTAINTY

It’s also possible to use knowledge of experimental or measurement errors to introduce a degree of

quantitative information into a qualitative presentation of uncertainty. For example, standard laboratory

procedures or field sampling methods may have a known error level that you can use to quantify

uncertainty. In many cases, it’s possible to express the uncertainty associated with particular variable

values or estimated risks quantitatively, and further evaluate them with variations of sensitivity analyses. 

Finkel (1990) identified a six-step process for producing a quantitative uncertainty estimate:

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.
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3. Generate an uncertainty distribution for each variable or equation component. These

uncertainty distributions may be 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. Recalibrate 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.

- Implication of supporting a point estimate produced without considering

uncertainty

- Balance of the costs of under- or over-estimating risks

- Unresolved scientific controversies, and their implications for research

When you need a detailed quantitative treatment of uncertainty, statistical methods are generally

considered the most appropriate. We describe two possible approaches to a statistical treatment of

uncertainty with regard to variable values here, though other methods are certainly available. The

methods described here were used in this analysis where appropriate. 

The first approach is to use an appropriate statistic to express all variables for which uncertainty is a

major concern. For example, if a value comes from a sample (such as yearly emissions from a stack), the

mean and standard deviation may both be presented. If the sample size is very small, it may be

appropriate to 

• give the range of sample values and use a midpoint as a best estimate in the model, or 

• use the smallest and largest measured value to obtain two estimates that bound the

expected true value. 

Selecting the appropriate statistic depends on the amount of data available and the degree of detail you

need. It’s possble to propagate uncertainties by using analytical or numerical methods.

A second approach is to use the probability distributions of major variables to propagate variable value

uncertainties through the equations you use in the risk assessment. You then develop a probability

distribution of expected values for each variable value. These probability distributions are typically
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expressed as either probability density functions (PDF) or cumulative probability density functions

(CPF). The PDF presents the relative probability for discrete variable values, whereas the CPF presents

the cumulative probability that a value is less than or equal to a specific value. 

A composite uncertainty distribution is created by combining the individual distributions with the

equations used to calculate the probability of particular adverse health effects and points. In Monte Carlo

simulations, a computer program is used to repeatedly solve the model equations, under different

selections of variable values, to calculate a distribution of exposure (or risk) values. Each time the

equations are calculated, values are randomly sampled from the specified distributions for each variable. 

The end result is a distribution of exposure (or risk). These can again be expressed as PDFs or, more

appropriately, as CPFs. The distribution enables you to choose the value corresponding to the

appropriate percentile in the overall distribution. For example, you could select an exposure level or risk

level that corresponds to the 95th percentile of the overall risk distribution rather than a point estimate of

risk that is based on the 95th percentile values for each variable. For more information on how to conduct

a quantitative uncertainty analysis, we refer you to Risk Assessment Guidance for Superfund, Volume III:

Part A (Process for Conducting Probabilistic Risk Assessment), which is located at the web address

www.epa.gov/oswer/riskassessment/rags3a/index.htm.

8.5 RISK ASSESSMENT UNCERTAINTY DISCUSSION

The science of risk assessment is evolving. Where the science-base is incomplete and uncertainties exist,

science policy assumptions must me made. It is important for risk assessments to fully explain the areas

of uncertainty in the assessments and to identify the key assumptions used in conducting the assessments. 

Toward that end, one option is to add a table at the end of each section (e.g., stack emissions, air

modeling, exposure assessment, toxicity evaluation, risk characterization) that lists the key assumptions in

that section, the rationale for those assumptions, their effect on estimates of risk (overestimation,

underestimation, neutral), and the magnitude of the effect (high, medium, low). For example, it could

explain that using a particular input variable, such as exit gas temperature, will under- or overestimate

chronic emissions, and the resulting risks and hazards, by a factor of (x). These tables could be used to

evaluate the extent to which you used public health-protective assumptions in the risk assessment. They

could also help determine the nature of the uncertainty analysis to be performed. The assumptions listed
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in the risk characterization section, which synthesizes the data outputs from the exposure and toxicity

analyses, might include the most significant assumptions from each of the previous sections.

Within the HHRAP, we’ve identified uncertainties and limitations within the discussion of specific

technical issues (e.g., TOE, estimates of emission rates, COPC selection process, quantifying non-detects)

as they are presented in their respective sections. We present the limitations associated with parameter

values and inputs to equations in Appendices A, B, and C, respectively.

As an example discussion, the following summarizes some of the uncertainty involved in the air

dispersion modeling component of the risk assessment process.

Although dispersion modeling is a valuable tool for estimating concentration and deposition impacts, it

has many limitations. The accuracy of the models is limited by 

• the ability of the model algorithms to depict atmospheric transport and dispersion of

contaminants, and 

• the accuracy and validity of the input data. 

For example, most refined models require input of representative meteorological data from a single

measuring station. In reality, a release will encounter highly variable meteorological conditions that are

constantly changing as it moves downwind. U.S. EPA’s Guideline on Air Quality Models—Revised (U.S.

EPA 1986b, 1993b; Title 51 CFR Appendix W) describes two types of model uncertainty. Inherent

uncertainty involves deviations in concentrations that occur even if all of the model input is accurate. 

Reducible uncertainty is associated with the model and the uncertain input values that will affect the

results. Although it is important to accurately represent actual conditions by selecting the right model,

and using accurate and representative input data, all model results are subject to uncertainty. 

Nevertheless, models are generally considered reasonably reliable in estimating the magnitude of highest

concentrations resulting from a release, although they may not necessarily be time-and space-specific

(Title 51 CFR Appendix W). When applied properly, air dispersion models are typically accurate to ± 10

to 40 percent and can be used to yield a “best estimate” of air concentrations (Title 51 CFR Appendix W).

As mentioned earlier, uncertainties specific to other technical components of the risk assessment process

(e.g., TOE, quantification of non-detects) are further described in their respective chapters or sections of
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this guidance. For more information on Agency policy and guidelines regarding uncertainty in risk

assessments, please see the U.S. EPA Science Policy Council’s Risk Characterization Handbook (U.S.

EPA 2000f, available at http://www.epa.gov/osa/spc/pdfs/rchandbk.pdf ).
U.S. EPA Region 6 U.S. EPA

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Chapter 9

Completing the Risk Assessment Report

and Follow-On Activities

What’s Covered in Chapter 9:

9.1 Conclusions

9.2 Activities Following Risk Assessment Completion

PLEASE NOTE: for the purposes of this guidance, “we” refers to the U.S. EPA OSW. 

The HHRAP is written for the benefit of a varied audience, including risk assessors,

regulators, risk managers, and community relations personnel. However, the “you” to

which we speak in this chapter is the performer of a risk assessment: the person (or

persons) who will actually put the recommended methods into practice.

Our main purpose in developing the HHRAP was to provide you with the tools you need to efficiently

complete quality, consistent, and defensible risk assessments. You can produce the risk assessment in a

relatively short amount of time, rather than spending years determining which COPCs, exposure

pathways, and receptors to include and evaluate. 

It’s important to note that final risk assessments might include both human health and ecological

evaluations. In addition to available Agency guidance for conducting ecological risk assessments (U.S.

EPA 1997e) and Volume 63, Number 93, of the Federal Register, we are currently finalizing an

ecological risk assessment guidance document titled U.S. EPA OSW Screening Level Ecological Risk

Assessment Protocol (U.S. EPA 1999a), prepared as a companion to this guidance.

9.1 CONCLUSIONS

We recommend that each risk assessment include a Conclusions section. This section is included

primarily to interpret the results of the risk and hazard characterization in light of the uncertainty

analysis. We recommend that, at a minimum, it present and interpret all risk and hazard results
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exceeding target levels. It might also identify receptors having the greatest risks and hazards, in addition

to COPCs and exposure pathways contributing significantly to these risks and hazards. Finally, the

Conclusions section is a place for you to present and defend your position on whether actual or potential

releases from the facility you studied pose significant risks and hazards to human populations.

9.2 ACTIVITIES FOLLOWING RISK ASSESSMENT COMPLETION

As stated previously, we developed the HHRAP to promote a consistent approach for completing risk

assessments that:

• Encourages the use of appropriate site-specific information early in and throughout the

process;

• Provides a tool for completing quality and defensible risk assessments;

• Minimizes inefficient expenditure of time and resources by suggesting up front a process

to determine which COPCs to consider, which exposure pathways, and receptors the risk

assessment report to include and evaluate, and

• Provides a comprehensive explanation of the procedures and uncertainties involved in

the process. 

However, the risk assessment process does not end following the completion, submittal, and approval of

the risk assessment report. 

Facilities burning hazardous waste are also responsible for communicating the results of the risk

assessment process to affected members of the community. One reason for our comprehensive

explanation of the procedures and uncertainties involved in the process was to provide the facilities, risk

assessors, and regulators with the tools they need to clearly communicate the procedures, results, and

limitations of the risk assessment process. Communication is an ongoing process.

Finally, completing the risk assessment process involves using 

• site-specific environmental data, 

• various assumptions, and 

• an evolving procedure for estimating risk. 
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We expect that facilities will periodically review each of these factors, and update the process with the

latest facility-specific operating and emission information. Updating will help determine whether the

best data and procedures are used to estimate the risk resulting from operating the facility hazardous

waste combustor. The permitting authority might establish the period for this review in the operating

permit. However, we recommend reviewing any significant changes involving newly available data or

risk assessment procedures as they become available, to gauge if they significantly affect the outcome of

the risk assessment process.
U.S. EPA Region 6 U.S. EPA

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Carolina. EPA 600/8-82/024. NTIS PB83-114207.
Human Health Risk Assessment Protocol

References September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering R-17

U.S. EPA. 1982b. Pesticides Assessment Guidelines Subdivision O: Residue Chemistry. Office of

Pesticides and Toxic Substances. Washington, D.C. EPA-600-90-003. January.

U.S. EPA. 1982c. Air Quality Criteria for Particulate Matter and Sulfur Oxides (1982) (Second

Addendum): Assessment of Newly Available Health Effects Information. Final Report. U.S.

Environmental Protection Agency, Washington, D.C., EPA/600/8-86/020F (NTIS PB87176574.

U.S. EPA. 1985a. Rapid Assessment of Exposure to Particulate Emissions from Surface Contamination

Sites. Prepared by Midwest Research Institute under Contract 68-0303116. Office of Health and

Environmental Assessment (OHEA). Washington, D.C. EPA/600/8-85/002. NTIS PB

85-192219.

U.S. EPA. 1985b. Water Quality Assessment: A Screening Procedure for Toxic and Conventional

Pollutants in Surface and Ground Water—Part I (Revised). ORD. Athens, Georgia. 

EPA/600/6-85/002a.

U.S. EPA. 1986a. Air Quality Modeling Analysis of Municipal Waste Combustors. Prepared by PEI

Associates. Cincinnati, Ohio.

U.S. EPA. 1986b. Guideline on Air Quality Models (Revised). Office of Air Quality and Planning and

Standards. Research Triangle Park, North Carolina. EPA 450/2-78/072R. NTIS PB86-245248.

U.S. EPA. 1986c. Superfund Public Health Evaluation Manual. Office of Emergency and Remedial

Response (OERR). Washington, D.C. EPA/540/1-86/060.

U.S. EPA. 1986d. “Test Methods for Evaluating Solid Waste—Physical/Chemical Methods.” SW-846,

Third Edition and Update I (July 1992), Update II (September 1994), and Update IIB

(January 1995).

U.S. EPA. 1986e. “Guidelines for the Health Risk Assessment of Chemical Mixtures.” Federal

Register. 51(185):34014-34025. September 24.

U.S. EPA. 1987a. Air Dispersion Modeling of a Municipal Waste Combustor in Rutland, Vermont.

Prepared by PEI Associates. Cincinnati, Ohio.

U.S. EPA. 1987b. On-Site Meteorological Program Guidance for Regulatory Modeling Applications.

Office of Air Quality Planning and Standards. Research Triangle Park, North Carolina.

U.S. EPA. 1987c. “Technical Guidance for Hazards Analysis.” EPA-OSWER-88-0001. December.

U.S. EPA. 1988a. Drinking Water Criteria Document for Polychlorinated Biphenyls (PCBs).

PB89-199256. April.

U.S. EPA. 1988b. Superfund Exposure Assessment Manual. Office of Emergency and Remedial

Response. Washington, D.C. EPA/540/1-88/001. NTIS PB 89-167985.
Human Health Risk Assessment Protocol

References September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering R-18

U.S. EPA. 1988c. Limiting Values of Radionuclide Intake and Air Concentration and Dose Conversion

Factors for Inhalation, Submersion, and Ingestion. Federal Guidance Report No. 11. 

EPA-520/1-88-020. September.

U.S. EPA. 1989a. Development of Risk Assessment Methodology for Land Application and Distribution

and Marketing of Municipal Sludge. ORD. OHEA. Environmental Criteria and Assessment

Office. Cincinnati, Ohio. EPA 600/6-89/001. NTIS PB90-135740/AS.

U.S. EPA. 1989b. Hazardous Waste Treatment, Storage, and Disposal Facilities: Background

Information for Proposed Resource Conservation and Recovery Act (RCRA) Air Emission

Standards. EPA/450/3-89-023.

U.S. EPA. 1989c. Hazardous Waste Treatment, Storage, and Disposal Facilities: Fugitive Particulate

Matter Air Emissions Guidance Document. Office of Air Quality Planning and Standards. 

EPA/450/3-89-019.

U.S. EPA. 1989d. Interim Procedures for Estimating Risks Associated with Exposures to Mixtures of

Chlorinated Dibenzo-p-Dioxins (CDD) and Dibenzofurans.

U.S. EPA. 1989e. Risk Assessment Guidance for Superfund: Volume I. Human Health Evaluation

Manual (Part A). OERR. Washington, D.C. OERR 9200 6-303-894.

U.S. EPA. 1989f. Handbook: Guidance on Setting Permit Conditions and Reporting Trial Burn Results. 

Volume II of the Hazardous Waste Incineration Guidance Series. ORD. EPA/625/6-89/019. 

January.

U.S. EPA. 1989g. Handbook: Hazardous Waste Incineration Measurement Guidance Manual. Volume

III of the Hazardous Waste Incineration Guidance Series. Office of Solid Waste and Emergency

Response (OSWER). EPA/625/6-89/021. June.

U.S. EPA. 1990a. Operations and Research at the U.S. EPA Incineration Research Facility. Annual

Report for FY 89. Risk Reduction Engineering Laboratory. ORD. Cincinnati, Ohio. 

EPA/600/9-90/012.

U.S. EPA. 1990b. “Standards for Owners and Operators of Hazardous Waste Incinerators and Burning

of Hazardous Wastes in Boilers and Industrial Furnaces.” Federal Register. 55:17862-17921.

U.S. EPA. 1990c. Technical Support Document for Lead. Final Draft. Environmental Criteria and

Assessment Office (ECAO)-CIN-757. Cincinnati, Ohio.

U.S. EPA. 1990d. User’s Manual for the PM-10 Open Fugitive Dust Source Computer Model Package.

EPA-450/3-90-010.

U.S. EPA. 1990e. Interim Final Methodology for Assessing Health Risks Associated with Indirect

Exposure to Combustor Emissions. Environmental Criteria and Assessment Office. ORD. 

EPA-600-90-003. January.
Human Health Risk Assessment Protocol

References September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering R-19

U.S. EPA. 1990f. Exposure Factors Handbook. OHEA. Exposure Assessment Group. Washington,

D.C. March.

U.S. EPA. 1990g. “National Oil and Hazardous Substances Pollution Contingency Plan.” Federal

Register. 55(46). March 8.

U.S. EPA. 1990h. Development of Relative Potency Estimates for Polycyclic Aromatic Hydrocarbons

(PAH) and Hydrocarbon Combustion Product Fractions Compared to Benzo(a)pyrene and Their

Use in Carcinogenic Risk Assessments. OHEA. EPA/600/R-92/134. September.

U.S. EPA 1990i. Handbook: Quality Assurance/Quality Control (QA/QC) Procedures for Hazardous

Waste Incineration. Office of Research and Development. EPA/625/6-89/023. January. 

U.S. EPA. 1991a. “Burning of Hazardous Waste in Boilers and Industrial Furnaces: Final Rule.” 

Federal Register. 56:7134-7240.

U.S. EPA. 1991b. Memorandum Regarding Human Health Evaluation Manual, Supplemental Guidance:

“Standard Default Exposure Factors.” From Timothy Fields, Jr., Acting Director, OERR and

Bruce Diamond, Director, Office of Waste Programs Enforcement (OWPE). To Various

Regional EPA Directors. OSWER Directive 9285.6-03. March 25.

U.S. EPA. 1991c. Dose-Response Analysis of Ingested Benzo(a)pyrene (Chemical Abstract Service

(CAS) No. 50-32-8). ORD. EPA/600/R-92/045. December.

U.S. EPA. 1991d. Risk Assessment Guidance for Superfund: Volume I—Human Health Evaluation

Manual (Part B, Development of Risk-Based Preliminary Remediation Goals).” Interim Final. 

December.

U.S. EPA. 1992a. “Implementation of Boiler and Industrial Furnace Regulations, New Toxicological

Data.” Memorandum from Shiva Garg, OSWER. February 11.

U.S. EPA. 1992b. “An Science Advisory Board (SAB) Report: Review of the Uptake Biokinetics

Model for Lead.” EPA-SAB-IAQC-92016. March.

U.S. EPA. 1992c. Technical Implementation Document for EPA’s Boiler and Industrial Furnace

Regulations. OSWER. EPA-530-R-92-011. March.

U.S. EPA. 1992d. “Estimating Exposure to Dioxin-Like Compounds. Draft Report.” OHEA. 

Washington, D.C. EPA/600/6-88/005B. August.

U.S. EPA. 1992e. Health Reassessment of Dioxin-Like Compounds, Chapters 1 to 8. Workshop Review

Draft. OHEA. Washington, D.C. EPA/600/AP-92/001a through 001h. August.

U.S. EPA. 1992f. National Study of Chemical Residues in Fish. Office of Science and Technology. 

September.
Human Health Risk Assessment Protocol

References September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering R-20

U.S. EPA. 1992g. Guidance for Data Useability in Risk Assessment (Part A): Final. NTIS

PB92-963356/XAB. Office of Emergency and Remedial Response. U.S. EPA. Washington,

D.C. April.

U.S. EPA. 1993a. Development and Testing of Dry Deposition Algorithms. Office of Air Quality

Planning and Standards. Research Triangle Park, North Carolina. EPA/4504/R-92/017.

U.S. EPA. 1993b. Guideline on Air Quality Models (Revised). Office of Air Quality Planning and

Standards. Research Triangle Park, North Carolina. EPA/450/2-78/072R.

U.S. EPA. 1993c. Technical Support Document for Land Application of Sewage Sludge. Volumes I and

II. EPA 822/R-93-001a. Office of Water. Washington, D.C.

U.S. EPA. 1993d. Provisional Guidance for Quantitative Risk Assessment of Polycyclic Aromatic

Hydrocarbons. EPA/600/R-93/089. July.

U.S. EPA. 1993e. “Addendum to the Methodology for Assessing Heath Risks Associated with Indirect

Exposure to Combustor Emissions.” Working Group Recommendations. Office of Solid Waste. 

ORD. Washington D.C. September 24.

U.S. EPA. 1993f. Review Draft Addendum to the Methodology for Assessing Health Risks Associated

with Indirect Exposure to Combustor Emissions. OHEA. ORD. EPA/600-AP-93-003. 

November 10.

U.S. EPA. 1993g. “Report to Congress on Cement Kiln Dust.” OSWER. EPA/530-R-94-001. 

December.

U.S. EPA. 1993h. “Report to Congress on Cement Kiln Dust.” Executive Summary. OSWER. 

EPA/530-S-94-001. December.

U.S. EPA. 1993i. “Handbook of Chemical Incinerator Trial Burn Risk Assessment.” Volume 1. 

Prepared by Roy F. Weston for EPA Region 3. June 21.

U.S. EPA. 1993j. External Exposure to Radionuclides in Air, Water, and Soil. Federal Guidance Report

No. 12. EPA 402-R-93-081. September. http://www.epa.gov/radiation/docs/federal/402-r-93-081.pdf

U.S. EPA. 1994a. Health Assessment Document for 2,3,7,8-TCDD and Related Compounds. Volume

III. Review Draft. ORD. Washington, D.C. EPA/600/BP-92/001c.

U.S. EPA. 1994b. Health Effects Assessment Summary Tables. Annual Update. ORD. 

OHEA-ECAO-CIN-909. Environmental Criteria and Assessment Office. Cincinnati, Ohio.

U.S. EPA. 1994c. User's Guide for the Industrial Source Complex Dispersion Models (Revised). Office

of Air Quality Planning and Standards. Research Triangle Park, North Carolina. Draft.

U.S. EPA. 1994d. Air/Superfund National Technical Guidance Study Series. Volume V—Procedures

For Air Dispersion Modeling At Superfund Sites. Office of Air Quality Planning and Standards.

Research Triangle Park, North Carolina. February.
Human Health Risk Assessment Protocol

References September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering R-21

U.S. EPA. 1994e. Guidance Manual for the Integrated Exposure Uptake Biokinetics Model for Lead in

Children. OERR. Washington, D.C. EPA/540/R-93/081. February.

U.S. EPA. 1994f. Draft Exposure Assessment Guidance for RCRA Hazardous Waste Combustion

Facilities. OSWER. EPA-530-R-94-021. April 22.

U.S. EPA. 1994g. Draft Guidance for Performing Screening Level Risk Analyses at Combustion

Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. April 15.

U.S. EPA. 1994h. Table 1, “Chemicals Recommended for Identification,” and Table 2, “Chemicals for

Potential Identification.” Attachment A, Draft Exposure Assessment Guidance for RCRA

Hazardous Waste Combustion Facilities. April 15.

U.S. EPA. 1994i. Draft Revision, Implementation Guidance for Conducting Indirect Exposure Analysis

at RCRA Combustion Units. Attachment, Draft Exposure Assessment Guidance for RCRA

Hazardous Waste Combustion Facilities. April 22.

U.S. EPA. 1994j. Draft Guidance on Trial Burns. Attachment B, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. May 2.

U.S. EPA. 1994k. Estimating Exposure to Dioxin-Like Compounds. Volume I: Executive Summary. 

Review Draft. ORD. Washington, D.C. EPA/600/6-88/005Ca. June.

U.S. EPA. 1994l. Estimating Exposure to Dioxin-Like Compounds. Volume II: Properties, Sources,

Occurrence, and Background Exposures. Review Draft. ORD. Washington, D.C. 

EPA/600/6-88/005Cb. June.

U.S. EPA. 1994m. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-Specific

Assessment Procedures. Review Draft. ORD. Washington, D.C. EPA/600/6-88/005Cc. June.

U.S. EPA. 1994n. Draft Revision of Guidance on Trial Burns. Attachment B, Draft Exposure

Assessment Guidance for RCRA Hazardous Waste Combustion Facilities. OSWER. June 2.

U.S. EPA. 1994o. “Memorandum Regarding Revised Interim Soil Lead Guidance for CERCLA Sites

and RCRA Corrective Action Facilities.” OSWER Directive 9355.4-12. From Elliot P. Laws,

Assistant Administrator. To Regional Administrators Regions I - X. July 14.

U.S. EPA. 1994p. Errata, Draft Guidance for Performing Screening Level Risk Analyses at Combustion

Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. October 4.

U.S. EPA. 1994q. Draft Technical Background Document for Soil Screening Guidance.

EPA/540/R-94/106. OSWER. Washington, D.C. December.

U.S. EPA. 1994r. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion

Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. OERR. OSW. December 14.
Human Health Risk Assessment Protocol

References September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering R-22

U.S. EPA. 1994s. Estimating Radiogenic Cancer Risks. Office of Radiation and Indoor Air. U.S. EPA. 

Washington, DC. EPA 402-R-93-076. June.

U.S. EPA. 1995a. Compilation of Air Pollutant Emission Factors: Volume I, Stationary Point and Area

Sources. Research Triangle Park, North Carolina. 5th Edition. AP-42. January.

U.S. EPA. 1995b. Further Issues for Modeling the Indirect Exposure Impacts from Combustor

Emissions. ORD. Washington, D.C. January 20.

U.S. EPA. 1995c. User's Guide to the Building Profile Input Program. EPA-454/R-93-038. Office of

Air Quality Planning and Standards, Technical Support Division. Research Triangle Park, North

Carolina. February.

U.S. EPA. 1995d. “Regulatory Determination on Cement Kiln Dust; Final Rule.” Federal Register.

February 7.

U.S. EPA. 1995e. Review Draft Development of Human Health-Based and Ecologically-Based Exit

Criteria for the Hazardous Waste Identification Project. Volumes I and II. Office of Solid

Waste. March 3.

U.S. EPA. 1995f. User’s Guide For The Industrial Source Complex Dispersion Models, Volumes I and

II. Office of Air Quality Planning and Standards. Emissions, Monitoring, and Analysis Division. 

Research Triangle Park, North Carolina. EPA-454/B-95-003a. September.

U.S. EPA. 1995g. PCRAMMET User’s Guide. Office of Air Quality Planning and Standards. 

Emissions, Monitoring, and Analysis Division. Research Triangle Park, North Carolina. 

October.

U.S. EPA. 1995h. “Waste Technologies Industries Screening Human Health Risk Assessment 

(SHHRA): Evaluation of Potential Risk from Exposure to Routine Operating Emissions.” 

Volume V. External Review Draft. U.S. EPA Region 5, Chicago, Illinois.

U.S. EPA. 1995i. Development of Compliance Levels from Analytical Detection and Quantitation

Levels. U.S. EPA, Washington, DC. NTIS PB95-216321.

U.S. EPA. 1995j. 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. U.S. EPA, Washington, DC. October 20.

U.S. EPA. 1995k. Protocol for Equipment Leak Emission Estimates. Office of Air Quality Planning and

Standards. Emissions, Monitoring, and Analysis Division. Research Triangle Park, North

Carolina. EPA/453/R-95-017. November http://www.epa.gov/ttn/chief/efdocs/lks95_ch.pdf

U.S. EPA. 1996b. “Response to Comments Regarding the Screening Level Risk Assessment for the

Drake Chemical Company Superfund Site Incinerator.”
Human Health Risk Assessment Protocol

References September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering R-23

U.S. EPA. 1996c. Review and Comments of EPA’s Peer Review Panel on the Risk Assessment in

Support of a Proposed Rule for Technical Standards for Emissions from Combustion Units

Burning Hazardous Wastes.

U.S. EPA. 1996d. Guidance for Total Organics. Final Report. Radian Corporation. Contract

68-D4-0022, Work Assignment 8. EPA/600/R-96/033. March.

U.S. EPA. 1996e. “Proposed Guidelines for Carcinogen Risk Assessment.” Federal Register. 61

Federal Register (FR) 17960. Volume 61. Number 79. April 23.

U.S. EPA. 1996f. “Accidental Release Prevention Requirements: Risk Management Programs Under

Clean Air Act Section 112(r)(7).” Federal Register. 61FR31667. Volume 61. Number 120. 

June 20.

U.S. EPA. 1996g. Public Participation Record for Screening Risk Assessment for Operation of the

Tooele Chemical Demilitarization Facility at the Tooele Chemical Activity and Resulting Permit

Modification. June 20.

U.S. EPA. 1996h. “Formation of Dioxin-Like PICs During Incineration of Hazardous Wastes.” 

Memorandum to the Record. Dorothy Canter. June 21.

U.S. EPA. 1996i. “Memorandum regarding Johnston Atoll Chemical Agent Disposal System (JACADS)

Risk Assessment Issues.” From Dorothy Canter to Patrick Wilson. July 24.

U.S. EPA. 1996j. "Meteorological Processor For Regulatory Models User's Guide." 

EPA-454/B-96-002. Office of Air Quality Planning and Standards, Emissions Monitoring and

Analysis Division. Research Triangle Park, North Carolina. August.

U.S. EPA. 1996k. Guideline on Air Quality Models. Title 40 Code of Federal Regulations Part 51,

Appendix W. September.

U.S. EPA. 1996m. Internal Memorandum Regarding JACADS Risk-Related Issues. From Timothy

Fields, Jr., Deputy Assistant Administrator, OSWER. To Julie Anderson, Director, Waste

Management Division. October 2.

U.S. EPA. 1996n. Telefax Memorandum Regarding Evaluation of Acute Inhalation Exposure to Kalama

Chemical Company Upset Incinerator Emissions. From Cathy Massimino, U.S. EPA Region 10. 

To David Weeks, U.S. EPA Region 6. December 5.

U.S. EPA. 1996o. “Region 10 Tiered Approach for Developing Acute Inhalation Exposure Values.” 

Facsimile Transmission from Cathy Massimino, EPA Region 10 to David Weeks, EPA Region 6. 

December 16, 1996.

U.S. EPA. 1996p. “Drake Chemical Incinerator Trial Burn Risk Assessment, Volume 1.” Prepared by

Roy F. Weston for EPA Region 3. June 21.
Human Health Risk Assessment Protocol

References September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering R-24

U.S. EPA. 1996q. "PCBs: Cancer Dose-Response Assessment and Application to Environmental

Mixtures." National Center for Environmental Assessment, Office of Research and

Development. EPA/600/P-96/001F. September.

U.S. EPA. 1996r. Recommendations for the Technical Review Workgroup for Lead for an Interim

Approach to Assessing Risks Associated with Adult Exposures to Lead in Soil. Technical Review

Workgroup for Lead. December.

U.S. EPA. 1996s. Mercury Study Report to Congress, Volume III, SAB Review Draft. Office of Air

Quality Planning and Standards and ORD. EPA/452/R-96-001c. April.

U.S. EPA. 1997a. “Development of a Hazardous Waste Incinerator Target Analyte List of Products of

Incomplete Combustion, Draft Final Report”. National Risk Management Research Laboratory,

Air Pollution Prevention and Control Division, U.S. EPA. Research Triangle Park, North

Carolina. July 25.

U.S. EPA. 1997b. Exposure Factors Handbook. Office of Research and Development.

EPA/600/P-95/002Fc. August.

U.S. EPA. 1997c. Mercury Study Report to Congress, Volumes I through VIII. Office of Air Quality

Planning and Standards and ORD. EPA/452/R-97-001. December.

U.S. EPA. 1997d. Ecological Risk Assessment Guidance for Superfund: Process for Designing and

Conducting Ecological Risk Assessments. Interim Final. OSWER, U.S. EPA. 

EPA 540-R-97-006. June.

U.S. EPA. 1997e. Notice of Draft Source Category Listing for Section 112(d)(2) Rulemaking Pursuant

to Section 112(c)(6) Requirements. Federal Register. 62: 33625. June 20.

U.S. EPA. 1997f. Model Parameter Sensitivity Analysis. Prepared by The Air Group - Dallas for U.S.

EPA Region 6 Center for Combustion Science and Engineering.

U.S. EPA. 1997g. Special Report on Environmental Endocrine Disruption: An Effects Assessment and

Analysis. U.S. EPA, Risk Assessment Forum, Washington, DC. USEPA 630/R-96/012. Feb

1997.

U.S. EPA. 1998a. The Inventory of Sources of Dioxin in the United States. External Review Draft. 

Office of Research and Development, National Center for Environmental Assessment, U.S. EPA. 

EPA/600/P-98/002As. April.

U.S. EPA. 1998b. Region 6 Risk Management Addendum - Draft Human Health Risk Assessment

Protocol for hazardous Waste Combustion Facilities. U.S. EPA Region 6. EPA-R6-98-002. 

July.

U.S. EPA. 1998c. Methodology for Assessing Health Risks Associated with Multiple Pathways of

Exposure to Combustor Emissions (MPE). Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. 

December.
Human Health Risk Assessment Protocol

References September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering R-25

U.S. EPA. 1998d. Supplement to the Second Addendum (1986) to Air Quality Criteria for Particulate

Matter and Sulfur Oxides: Assessment of New Findings on Sulfur Dioxide and Acute Exposure

Health Effects in Asthmatic Individuals. U.S. Environmental Protection Agency, Washington,

DC, EPA 600/AP-93/002, 1986.

U.S. EPA. 1999a. Screening Level Ecological Risk Assessment Protocol for Hazardous Waste

Combustion Facilities. Peer Review Draft. Office of Solid Waste and Emergency Response. 

Washington, D.C. August.

U.S. EPA. 1999b. Guideline on Air Quality Models (GAQM)(Revised 7-1-99). Office of Air Quality and

Planning and Standards. Research Triangle Park, North Carolina. As published in 40 CFR Part

51, Appendix W.

U.S. EPA. 1999c. Addendum to Meteorological Processor for Regulatory Models (MPRM). 

EPA-454/B-96-002. June. http://www.epa.gov/scram001/userg/relat/mprmadd.pdf

U.S. EPA. 1999d. Cancer Risk Coefficients for Environmental Exposure to Radionuclides. Federal

Guidance Report No. 13. EPA 402-R-99-001. September. 

http://www.epa.gov/radiation/federal/docs/fgr13.pdf

U.S. EPA. 1999e. Addendum to Meteorological Processor for Regulatory Models (MPRM). 

EPA-454/B-96-002. June. http://www.epa.gov/scram001/userg/relat/mprmadd.pdf

U.S. EPA. 1999f. OAQPS Economic Analysis Resource Document, Section 8.4 Addressing

Uncertainty. April. http://www.epa.gov/ttn/ecas/econdata/Rmanual2/index.html

U.S. EPA. 2000a. “RCRA Site-Specific Risk Assessment Policy for Hazardous Waste Combustion

Facilities Fact Sheet”. Hazardous Waste Combustion NESHAP Toolkit. July.

U.S. EPA. 2000b. Exposure and Human Health Reassessment of 2, 3, 7, 8- Tetrachlorodibenzo-p-Dioxin

(TCDD) and Related Compounds. Parts 1, 2, and 3. Draft Report for Science Advisory Board

Review. Washington, DC: National Center for Environmental Assessment, Office of Research

and Development. EPA/600/P-00/001B(b-e).

U.S. EPA. 2000c. Draft Methodology for Deriving Ambient Water Quality Criteria for Protection of

Human Health. Technical Support Document Volume III: Bioaccumulation Part 1 - Development

of National Bioaccumulation Factors. Office of Science and Technology in the Office of Water. 

U.S. EPA. 2000d. Air Quality Criteria for Carbon Monoxide. U.S. Environmental Protection Agency,

Office of Research and Development, National Center for Environmental Assessment,

Washington Office, Washington, DC, EPA 600/P-99/001F, 2000.

U.S. EPA 2000e. Supplementary Guidance for Conducting Health Risk Assessment of Chemical Mixtures.

EPA/630/R-00/002. Risk Assessment Forum, Washington DC.
Human Health Risk Assessment Protocol

References September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering R-26

U.S. EPA 2000f. Risk Characterization Handbook. Prepared for the U.S. Environmental Protection

Agency by members of the Risk Characterization Implementation Core Team, a group of EPA’s

Science Policy Council. EPA 100/B-00/002. December. Available at

http://www.epa.gov/osa/spc/pdfs/rchandbk.pdf

U.S. EPA. 2001a. Email Memorandum Regarding Summary of AEGL Results as of September 13,

2001. From Paul Tobin, U.S. EPA. To Vicki M. Kier, Combustion Technical Assistance Center

(CTAC). September 20.

U.S. EPA. 2001b. National-Scale Air Toxics Assessment for 1996. Research Triangle Park, NC 27711.

EPA-453/R-01-003. January.

U.S. EPA. 2001c. Risk Burn Guidance for Hazardous Waste Combustion Facilities. Prepared by U.S.

EPA Region 4 and the Office of Solid Waste. EPA 530-R-01-001. 

U.S.EPA. 2002. A Review of the Reference Dose and Reference Concentration Processes.

EPA/630/P-02/002F. Risk Assessment Forum, Washington DC.

U.S.EPA. 2002b. Child-Specific Exposure Factors Handbook. EPA-600-P-00-002B. National Center for

Environmental Assessment (Washington Office) and U.S. EPA ORD. September.

U.S.EPA. 2002c. Guidelines for Ensuring and Maximizing the Quality, Objectivity, Utility, and Integrity,

of Information Disseminated by the Environmental Protection Agency. EPA260R-02-008. Office

of Environmental Information. October.

U.S. EPA. 2004a. The Ozone Report: Measuring Progress through 2003. Prepared by U.S. EPA Office

of Air Quality Planning and Standards Emissions, Monitoring, and Analysis Division. EPA 454/

K-04-001. April 2004.

U.S. EPA. 2004b. The Particle Pollution Report: Current Understanding of Air Quality and Emissions

through 2003 Prepared by U.S. EPA Office of Air Quality Planning and Standards Emissions,

Monitoring, and Analysis Division. EPA 454-R-04-002. December 2004.

U.S. EPA. 2004c. Air Quality Criteria for Particulate Matter (October 2004). U.S. Environmental

Protection Agency, Washington, DC, EPA 600/P-99/002aF-bF, 2004.

EPA, 2004d. Risk Assessment Guidance for Superfund Volume I: Human Health Evaluation Manual

(Part E, Supplemental Guidance for Dermal Risk Assessment). EPA/540/R/99/005. Office of

Superfund Remediation and Technology Innovation, U.S. Environmental Protection Agency

Washington, DC. http://www.epa.gov/oswer/riskassessment/ragse/index.htm

U.S. EPA. 2005. “Air Quality Trends Reports: Six Principal Pollutants.” Prepared by U.S. EPA Office

of Air. World Wide Web Address http://www.epa.gov/airtrends/sixpoll.html. Accessed on

August 15, 2005.

U.S. EPA. 2005b. Integrated Risk Information System (IRIS): Lead and compounds (inorganic)

(CASRN 7439-92-1). http://www.epa.gov/iris/. Accessed August 9, 2005.
Human Health Risk Assessment Protocol

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U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

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U.S. EPA. 2005c. Integrated Risk Information System (IRIS): Nickel Refinery Dust. 

http://www.epa.gov/iris/. Accessed August 9, 2005.

U.S. EPA. 2005d. Integrated Risk Information System (IRIS): Nickel carbonyl (CASRN 13463-39-3). 

http://www.epa.gov/iris/. Accessed August 9, 2005.

U.S. EPA. 2005e. Integrated Risk Information System (IRIS): Nickel subsulfide (CASRN 12035-72-2). 

http://www.epa.gov/iris/. Accessed August 9, 2005.

U.S. EPA. 2005f. Guidelines for Carcinogen Risk Assessment. EPA/630/P-03/001F. Risk Assessment

Forum, Washington DC. Available at

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=116283

U.S. EPA. 2005g. Supplemental Guidance for Assessing Susceptibility from Early-Life Exposure to

Carcinogens. EPA/630/R-03/003F. Risk Assessment Forum, Washington DC. Available at

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=116283

U.S. EPA 2005h. Regulatory Impact Analysis of the Clean Air Mercury Rule Final Report. U.S. EPA

Office of Air Quality Planning and Standards Emissions, Monitoring, and Analysis Division, Air

Quality Strategies and Standards Division. EPA-452/R-05-003. March.

U.S. EPA. 2005i. Integrated Risk Information System (IRIS). http://www.epa.gov/iris/. Accessed

August 10, 2005.

Valentine, R.L. 1986. “Nonbiological Transformation.” Vadose Zone Modeling of Organic Pollutants.

S.C. Hern and S.M. Melacon, Editors. Lewis Publishers, Inc. Chelsea, Michigan.

Valentine, R.L., and Schnoor. 1986. “Biotransformation.” Vadose Zone Modeling of Organic

Pollutants. S.C. Hern and S.M. Melancon, Editors. Lewis Publishers, Inc. Chelsea, Michigan.

Van den Berg et al. 1998. “Toxic Equivalency Factors (TEFs) for PCBs, PCDDs, PCDFs for Humans

and Wildlife”. Environmental Health Perspectives, Volume 106, Number 12:775-792.

Vanoni, V.A. 1975. Sediment Engineering. American Society of Civil Engineers. New York, New

York. Pages 460-463.

Watras, C.J., and N.S. Bloom. 1992. “Mercury and Methylmercury in Individual Zooplankton: 

Implications for Bioaccumulation.” Limnol. Oceanogr. Volume 37(6). Pages 1313-1318.

Watras, C.J., K.A. Morrison, and J.S. Host. 1995. “Concentration of Mercury Species in Relationship to

Other Site-Specific Factors in the Surface Waters of Northern Wisconsin Lakes.” Limnology and

Oceanography. 40(3): 556-565.

Weast, R.C. 1986. Handbook of Chemistry and Physics. 66th Edition. Cleveland, Ohio. CRC Press.

Westinghouse Savannah River Company (WSRC). 1998. “Methodology for Deriving Temporary

Emergency Exposure Limits (TEELs) (U).” Prepared for the U.S. Department of Energy. 

WSRC-TR-98-00080. On-Line Address: http://www.bnl.gov/scapa/teel2.pdf
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U.S. EPA Region 6 U.S. EPA

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Center for Combustion Science and Engineering R-28

Wikström, Evalena, G. Löfvenius, C. Rappe, and S. Marklund. 1996. “Influence of Level and Form of

Chlorine on the Formation of Chlorinated Dioxins, Dibenzofurans, and Benzenes during

Combustion of an Artificial Fuel in a Laboratory Reactor.” Environmental Science and

Technology. Volume 30. Pages 1637-1644. May.

Wipf, H.K., E. Homberger, N. Neuner, U.B. Ranalder, W. Vetter, and J.P. Vuilleumier. 1982. “TCDD

Levels in Soil and Plant Samples from the Seveso Area.” In: Chlorinated Dioxins and Related

Compounds: Impact on the Environment. Eds. Hutzinger, O. et al. Pergamon, New York.

Witby, K.T. 1978. “The Physical Characteristics of Sulfur Aerosols.” Atmospheric Environment.

12:135-159.

World Health Organization (WHO). 1998. “Assessment of the Health Risk of Dioxins: Re-evaluation of

the Tolerable Daily Intake (TDI).” World Health Organization, European Centre for

Environment and Health; International Programme on Chemical Safety. WHO Consultation.

May 25-29, 1998. Geneva, Switzerland.

Wright, D.R. and R.D. Hamilton. 1982. “Release of Methyl Mercury from Sediments: Effects of

Mercury Concentration, Low Temperature, and Nutrient Addition. Can J Fish Aquat Sci 39: 

1459-1466.

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Hygiene and Toxicology. Edited by George D. Clayton and Florence E. Clayton. John Wiley &

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APPENDIX A-1

CHEMICALS OF POTENTIAL INTEREST
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APPENDIX A-1

CHEMICALS OF POTENTIAL INTEREST

Table A-1 presents a comprehensive list of compounds typically found in

• hazardous waste; and 

• hazardous waste combustion stack gas emissions. 

Table A-1 identifies the Chemical Abstracts Service (CAS) number for each compound, and indicates

whether a compound has been identified as a potential COPC by: 

• U.S. EPA and state risk assessment reference documents; 

• Emission test results that have identified the compound in the emissions from hazardous

waste combustion facilities; or 

• Other literature that suggests that the risks from the compound may be significant. 

We provide Table A-1 to help you make sure that the trial/risk burn considers the full range of

compounds potentially emitted from a combustor, and the appropriate analytical method. A risk

assessment won’t necessarily evaluate every metal and potential PIC listed in Table A-1. Once the

trial/risk burn stack tests are completed, the risk assessment COPCs are selected from the stack test data,

rather than Table A-1. 

This discussion lists reference documents for each of the columns in Table A-1 and briefly describes the

quality of data associated with these references. The evaluation of chemical toxicity is also discussed at

the end of this section. This information is presented for informational purposes only.

A1.1 COLUMN 1: CHEMICAL ABSTRACTS SERVICE (CAS) NUMBER

The CAS number is a unique number assigned to each compound in the table. 

A1.2 COLUMN 2: COMPOUND NAME

The most common compound name is listed. Where appropriate, common synonyms are also listed to

help you identify particular compounds.

A1.3 COLUMN 3: COMPOUNDS LISTED IN 40 CFR PART 261 APPENDIX VII OR VIII

Appendix VII of Title 40 Code of Federal Regulations (40 CFR) Part 261 identifies compounds for which

specific hazardous wastes, from specific and nonspecific sources, are listed (U.S. EPA 1995). Appendix

VIII of 40 CFR Part 261 identifies acute hazardous wastes and toxic hazardous wastes associated with

commercial chemical products, manufacturing chemical intermediates, and off-specification commercial

chemical products (U.S. EPA 1995). This column lists hazardous waste codes for the associated

compounds. We provide this list for reference purposes only, because it’s commonly cited by other U.S.

EPA combustion risk assessment documents as an original source of the product of incomplete

combustion (PIC) lists. An explanation of the reasons for including a COPC on this list is beyond the

scope of the HHRAP.
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A1.4 COLUMN 4: CHEMICAL-SPECIFIC DATA AVAILABLE

This column lists those compounds for which the following are available (as presented in Appendix A-2): 

(1) chemical-specific physical and chemical information, and (2) chemical-specific fate-and-transport

information.

A1.5 COLUMN 5: PICS RECOMMENDED BY U.S. EPA (1994a) FOR ALL HUMAN

HEALTH RISK ASSESSMENTS (HHRA)

Compounds marked with an “X” in this column are identified by U.S. EPA (1994a) as PICs to be

included in all HHRAs. U.S. EPA (1994a) does not describe the basis or references for including these

PICs in all HHRAs. More information regarding these compounds is presented in Section 2.2 of the

HHRAP.

A1.6 COLUMN 6: PICS IDENTIFIED IN COMBUSTION UNIT EMISSIONS (U.S. EPA 1993)

Compounds marked with an “X” in this column are identified in U.S. EPA (1993) as PICs. The source

documents cited by U.S. EPA (1993) are described in the following subsections. These references have

been cited by this and other Agency reference documents as “sources” of information regarding PIC

emissions from hazardous waste combustors. U.S. EPA (1993) has, in turn, been cited by later guidance

documents as a “source” of information regarding PIC emissions from hazardous waste combustors. 

However, as is indicated by the listing of the references from Dempsey and Oppelt (1993) (which is a

summary of existing information), many of the reference documents appear to simply cite additional

“sources” of information. We’ve not yet identified the original research and sampling data regarding PIC

emissions but, based on a preliminary review of the information below, the sources of the “original”

information cited by all of the most common reference documents may be limited and may have been

published over 15 years ago.

A1.6.1 Demsey and Oppelt (1993)

The sections of Demsey and Oppelt (1993) regarding PICs from hazardous waste combustion facilities

(“Combustion Byproduct Emissions” and “Table XVII: Organics that Could Potentially be Emitted from

Devices Burning Hazardous Waste”) cite the following references:

C U.S. EPA (1989b) didn’t include a list of PICs from combustion sources. U.S. EPA (1989b)

discussed ways of ensuring that PIC emissions don’t pose an unacceptable risk to human health

and the environment. Stack gas carbon monoxide (CO) concentration is a good indicator of

combustion efficiency; therefore, controlling CO is a prudent and reasonable approach for

minimizing the potential risk from PICs. The destruction and removal efficiency (DRE) standard

of 40 CFR Part 264.242(a) limits stack emissions of principal organic hazardous constituents

(POHCs) to 0.01 percent (or 0.0001 percent for dioxin-containing waste) of the quantity of

POHC in the waste. This standard, however, does not impose a limit on PICs. Therefore, a limit

of 100 parts per million by volume (ppmv) (Tier I) was imposed, below which PIC emissions do

not pose unacceptable risks to human health. The proposed rule allows a waiver to the 100-ppmv

CO limit, by (1) restricting total hydrocarbon (THC) emissions to 20 ppmv (Tier II), or

(2) showing that THC emissions do not pose an unacceptable health risk by using prescribed risk

assessment procedures.
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The above limitations were also provided in the Federal Register, dated January 23, 1981 (U.S.

EPA 1981) and April 27, 1990 (U.S. EPA 1990b)

C U.S. EPA (1981) doesn’t contain any information regarding PICs not contained in U.S. EPA

(1989b). There is no discussion of “risk” in this document. Although the notice deals with

permitting standards, there is no risk-based approach, and it appears to be an entirely technical

discussion. Specifically, it deals with updated material for specific parts of 40 CFR.

- 40 CFR Part 122 (Incinerator Facility Permits)

- 40 CFR Part 264 (General Standards for Hazardous Waste Incineration)

- 40 CFR Part 265 (Interim Status Standards for Hazardous Waste Incineration)

Standards are technology-based, not risk-based.

C U.S. EPA (1990a) describes amendments to the hazardous waste incinerator regulations for the

following purpose:

Improve control of toxic metal emissions, HCl emissions, and residual organic emissions;

amend the definitions of incinerators and industrial furnaces; propose definitions for

plasma arc incinerators and infrared incinerators; propose to regulate carbon regeneration

units as thermal treatment devices; and make a number of minor revisions to permitting

procedures.

U.S. EPA (1990a) also states the following:

The database on PIC emissions is limited therefore, the risk assessments may

under-estimate risk. The assessments consider only the organic compounds that have

been actually identified and quantified. Zero to 60 percent of total unburned hydrocarbon

emissions have been chemically identified at any particular facility. Thus, the bulk of the

hydrocarbon emissions have not been considered in those risk assessments. Although

many of the unidentified, unquantified organic compounds may be non-toxic, some

fraction of the organic emissions is undoubtedly toxic. . . .data on typical PIC emissions

from hazardous waste combustion sources were compiled and assessed in recent EPA

studies. These studies identified 37 individual compounds in the stack gas of the eight

full-scale hazardous waste incinerators tested, out of which 17 were volatile compounds

and 20 semivolatile compounds. Eight volatile compounds (benzene, toluene,

chloroform, trichloroethylene, carbon tetrachloride, tetrachloroethylene, chlorobenzene,

and methylene chloride), and one semivolatile compound (naphthalene) were identified

most frequently in more than 50 percent of the tests. Some of these compounds are

carcinogenic.

The sources for these statements appear to be Wallace et al. (1986) and Trenholm and Lee (1986).

Trenolm and Lee (1986), prepared by Andrew R. Trenholm of Midwest Research Institute and

C.C. Lee at the U.S. EPA Hazardous Waste Engineering Research Laboratory, discussed that

emissions from incinerators are only characterized for constituents listed in Appendix VIII. 

However, constituents not listed in Appendix VIII are also emitted from the stacks.

Data was obtained from HWERL-sponsored tests at eight hazardous waste incinerators, nine

boilers that co-fired hazardous wastes, and five mineral processing kilns that fired hazardous

wastes as fuel. In addition, SVOC emissions data for two municipal solid waste incinerators and
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seven coal-fired power plants were also reviewed. The common PICs are presented in the

following table:

Volatile PICs Most Frequently Present in Stack Gases

VOCs SVOCs

Benzene Naphthalene

Toluene Phenol

Carbon Tetrachloride Bis(2-ethylhexyl)phthalate

Chloroform Diethylphthalate

Methylene Chloride Butylbenzylphthalate

Trichloroethylene Dibutylphathlate

Tetrachloroethylene

1,1,1-Trichloroethane

Chlorobenzene

Tests were conducted for three incinerator runs to search for constituents not listed in

Appendix VIII . These constituents include:

Non-Appendix VIII Constituents Present in Highest Concentrations in Stack Gases

Acetone Ethylbenzaldehyde

Ethylbenzene Ethylbenzoic acid

Acetophenone Ethylphenol

Benzaldehyde Ethylphenyl-ethanone

Benzenedicarboxaldehyde Ethynylbenzene

Benzoic acid Phenylacetylene

Chlorocyclohexanol 1,1'-(1,4-phenylene)bisethanone

Cyclohexane Phenylpropenol

Cyclohexanol Propenylmethylbenzene

Cyclohexene Tetramethyloxirane

Dioctyl adipate Trimethylhexane

Ethenyl ethylbenzene

Emission rates of compounds not in the waste feed were also provided.
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C U.S. EPA (1985) didn’t include a list of PICs from combustion sources. U.S. EPA (1985)

discussed views and reviews by the Environmental Effects, Transport, and Fate Committee of the

Science Advisory Board of issues related to the environmental impacts of the incineration of

liquid hazardous wastes at sea and on land. Several issues were addressed, including issues

concerning the combustion and incineration of hazardous waste. Major findings of the committee

were as follows:

- Fugitive emissions and spills may release as much or more material to the environment

than the direct emissions from waste incineration processes.

- Numerous PICs are formed during the combustion processes. However, only a fraction

of them are identified or detected. It is possible that the aggregate of all compound

emissions that are not categorized as other POHCs or PICs can be more toxic and pose

greater risks than those listed. Although 99.99 percent DRE has been claimed, if the

unburned or undetected hydrocarbon output is included, the DRE may actually be less

than 99.99 percent. Therefore, the concept of destruction efficiency used by EPA was

found to be incomplete and not useful for subsequent exposure assessments. All

emissions and effluents must be identified and quantified, including their physical form

and characteristics.

- Local site-specific conditions must be used in characterizing exposure to receptors from

waste incinerator emissions.

- The evaluation of exposure durations and concentrations should be based on a detailed

assessment of transport processes and the habits of the exposed organisms. The role of

food chains needs particular attention.

- At a minimum, the toxicities of representative emissions and effluents from incinerators

should be tested on sensitive life stages of representative aquatic and terrestrial

vertebrates, invertebrates, and plants of ecological importance.

C U.S. EPA (1990b) does not include a list of PICs from combustion sources. It was prepared by

the PIC subcommittee of the Science Advisory Board to review the OSW proposal to control

emissions of PICs from hazardous waste incinerators by instituting process controls that are based

on CO and THC emission concentrations. U.S. EPA risk assessments indicate that emissions of

PICs at currently measured levels are not likely to produce human effects. However, because the

current DRE standard applies only to designated POHCs, 99.99 percent DRE does not preclude

the possibility that emission of PICs could present significant human health risk. The following

summarizes the major findings of the subcommittee review.

- The concept of using CO and THC as guidance for incinerator operational control is

reasonable.

- At low CO levels, CO correlates well with THC; therefore, limiting CO in order to ensure

high combustion efficiency and low THC levels is reasonable. At high CO

concentrations, CO and THC do not correlate well; therefore, relying solely on the

controlling of CO may not provide a reasonable control for THC. Continuous emissions

monitoring of THC is preferred. Quantification of PICs alone is not practical with the
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sampling techniques that are available, primarily because PICs are normally emitted in

the range of parts per billion (ppb) to parts per trillion (ppt).

- A 100-ppmv limit for CO is reasonable. However, supporting documentation does not

demonstrate that a CO concentration of 100 ppmv is better than 50 ppmv or 150 ppmv.

- Continuous emissions monitoring of THC with a cold system appears to be practical for

routine operations. However, a hot transfer line produces better analysis of THC

concentrations and detection of a larger fraction of the THCs emitted.

- The database characterizing PICs in emissions would not allow a correlation to be

established with CO or THC levels for various combustion devices and conditions. 

Limited data introduces large uncertainties into U.S. EPA’s risk assessment. Therefore,

U.S. EPA’s site-specific risk assessment process is limited in its usefulness in

establishing acceptable THC levels. However, the risk assessment procedures are

risk-based.

C U.S. EPA (1987) is a report prepared by Andrew R. Trenholm, Acurex Corporation, California,

and staff members from the U.S. EPA Hazardous Waste Engineering Research Laboratory in

Cincinnati, Ohio. The paper discussed the lack of information on total emissions from

combustion of hazardous wastes, particularly under conditions of less than optimal performance. 

The focus issue was whether additional constituents that are listed in Appendix VIII or not listed

in Appendix VIII which were not identified in early tests might be emitted from hazardous waste

combustion units. To address this issue and related issues, U.S. EPA initiated this project to

qualitatively and quantitatively study the characteristics of all possible effluents, under

steady-state and transient conditions. The following summarizes the major findings:

- THC emissions detected as specific compounds ranged from 50 to 67 percent for five

runs and were 91 percent for one run. The fraction of THC not detected is most likely

explained by uncertainty in the measurements or other analytical problems.

- Methane accounted for the largest fraction of THC.

- Oxygenated aliphatic compounds made up the largest class of compounds among the

SVOCs, both in total mass and number of compounds.

- Transient upsets did not cause significant increases in the concentration of SVOCs or

most VOCs. Three VOCs that were increased were methane, methylene chloride, and

benzene.

- Particulate and HCl emissions did not change between the steady-state and transient test

runs.

C Duval and Rubey (1976) was prepared by D.S. Duval and W.A. Rubey of the University of

Dayton Research Institute, Ohio. The objective of the study was to provide data from which

requirements can be assigned for the thermal disposal of kepone. This report was primarily

concerned with the high-temperature destruction of kepone, with DDT and Mirex used as

comparative Analog. Laboratory tests were conducted to establish destruction temperature
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characteristics of the vaporized pesticides at preselected residence times. The following

summarizes the major findings.

- Kepone was essentially destroyed at a 1-second residence time and a temperature range

of 500o

C to 700oC, depending on the pesticide.

- Major decomposition products detected were hexachlorocyclopentadiene and

hexachlorobenzene for both kepone and Mirex. These products were formed in different

thermal regions.

- The study demonstrated that the chemical nature of the effluent products depends on the

temperature and residence time that the basic molecule experiences.

C Duval and Rubey (1977) discusses the experimental destruction temperature and residence time

relationships for various PCB compounds and mixtures of PCBs. The document states that “upon

thermal stressing in air, PCBs decompose to low-molecular-weight products.” However, the

document doesn’t identify any of these low-molecular-weight products. In fact, the document

states directly that the products weren’t identified in the study. It further recommends that

additional research be conducted on the “degradation products and effluents.”

C Dellinger et al. (1984) was prepared by Barry Dellinger and others of the University of Dayton,

Ohio. This paper presented the gas-phase thermal stability method under controlled laboratory

conditions to rank the incinerability of compounds. The objective of this study was to determine

the gas-phase thermal decomposition properties of 20 hazardous organic compounds.

The compounds were selected on the basis of (1) frequency of occurrence in hazardous waste

samples, (2) apparent prevalence in stack effluents, and (3) representativeness of the spectrum of

hazardous waste organic waste materials. The following summarizes the major findings.

- Gas-phase thermal stability method is a more effective means of ranking the

incinerability of hazardous compounds in a waste.

- Numerous PICs were formed during the thermal decomposition of most of the

compounds tested. However, PICs were not identified.

- Destruction efficiency of 99.99 percent is achieved at 2 seconds mean residence time in

flowing air at 600o

C to 950 oC.

- No single physical or chemical property describes the ranking scheme for incinerability.

C Dellinger et al. (1986) was prepared by Barry Dellinger, B. Douglas, L. Hall, John L. Graham,

Sueann L. Mazer, and Wayne A. Rubey of the University of Dayton Research Institute, Dayton,

Ohio, and Myron Malanchuk of U.S. EPA, Cincinnati, Ohio. The paper discussed the

development of an incineration model based on laboratory studies conducted by using the

nonflame mode of hazardous waste thermal decomposition. The results of these studies were

compared to the flame-mode studies and field tests to evaluate the incineration model proposed. 

The model was based on the premise that incinerators do not operate continuously at optimum

conditions. As a result, 1 percent or more of the feed and its flame treatment products must
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undergo further decomposition in the nonflame region to meet the DRE criterion of greater than

99.99 percent.

In the past, several methods were used to rank the incinerability of compounds. Nonflame

studies, however, indicated that tests on compounds conducted at low oxygen concentrations

provided a better correlation with field tests to determine the relative incinerability of compounds. 

Four experimental studies were conducted to develop and expand the database on POHCs and

PICs.

Studies were conducted on individual compounds to evaluate degradation compounds and PICs

from the original parent compound. The thermal degradation of 2,3',4,4',5-PCB was studied

under four reaction atmospheres (at varying levels of oxygen) at a constant gas phase residence

time of 2.0 seconds. Tests were conducted at temperatures ranging from 500o

C to 1,000oC. 

Tests indicated that the yield of combustion products decreased with increased oxygen levels. 

Numerous major degradation products were identified from the thermal degradation of

2,3',4,4',5-PCB, including:

- Penta-, tetra-, and trichlorodibenzofurans

- Tetra- and trichlorobiphenyls

- Tri- and dichlorobenzene

- Tetra- and trichloronaphthalene

- Tri- and dichlorochlorophenylethlyene

- Tetrachlorobiphenylenes

- C9H8OCl

- C10H3Cl3

Thermal decomposition of chloroform was studied. Numerous decomposition products were

identified, including:

- CCl4

- C2H4Cl2

- C2HCl3

- C2HCl5

- C2Cl2

- C2Cl4

- C3Cl4

- C4Cl6

Thermal decomposition of polychlorinated phenols was studied in nitrogen (N2) and oxygen

atmospheres because of the potential formation of polychlorinated dibenzodioxins. 

Pentachlorophenol (PCP) thermal decomposition was studied. Numerous decomposition

products of PCP were identified in N2 and/or air atmospheres, including:

- Dichlorobutadiyne (in N2)

- Tetrachloroethylene (in air)

- Tetrachloropropyne (in air)

- Trichlorofuran (in air)

- Tetrachlorofuran (in air)

- Trichlorobenzene (in N2 and air)

- Tetrachlorobenzene (in N2 and air)

- Pentachlorobenzene (in N2 and air)

- Hexachlorobenzene (in N2)
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- Octachlorostyrene (in N2)

- Hexachlorodihydronaphthalene (in N2 and air)

The paper concluded that PICs in the air atmosphere may have formed directly from the parent

material, whereas, in the nitrogen atmosphere, the principal PICs may have evolved from the

thermal decomposition of other PICs.

C Kramlich et al. (1984) doesn’t include a list of PICs from combustion sources. It was prepared by

J.C. Kramlich, W.R. Seeker, and M.P. Heap of Energy and Environmental Research Corporation,

California; and C.C. Lee of the Industrial Waste Combustion Group, U.S. EPA. This paper

presented a research program to study the flame-mode incineration of hazardous waste liquids in

laboratory scale reactors. The objective of this study was to supply the flame-mode data used in

evaluating the applicability of various approaches to ranking the ease of incinerability.

Five compounds were tested—chloroform, 1,1-dichloroethane, benzene, acrylonitrile, and

chlorobenzene—because (1) their range of incinerabilities is broad, and (2) they are

representative of liquid hazardous wastes. The following summarizes the findings.

- The flame section of the incinerator destroys greater than 99.995 percent of the wastes.

- The post-flame region destroys the remainder of the wastes.

- The destruction efficiency is reduced because of flame-related failures.

- Incinerability ranking depends on actual failure condition.

- No incinerability ranking system completely predicts the destruction efficiency of the

compounds tested for all failure conditions.

C Trenholm and Hathaway (1984) was prepared by Andrew Trenholm and Roger Hathaway of

Midwest Research Institute (MRI) in Missouri, and Don Oberacker, U.S. EPA, Cincinnati, Ohio. 

PICs were defined as any Appendix VIII hazardous organic constituent detected in the stack gas

but not present in the waste feed at a concentration of 100 micrograms per gram or higher. 

Benzene and chloroform were the most commonly found PICs. PIC emissions were comparable

to POHC emissions in concentration and total mass output. This document discussed PIC

formation mechanisms and criteria for PIC formations.

MRI conducted a series of tests at eight operating hazardous waste incineration facilities and

analyzed the collected samples for PICs. The tests were part of the technical support of U.S.

EPA’s preparation of a regulatory impact analysis for hazardous waste incinerators. Each

incinerator had a liquid injection burner, and some facilities also included a rotary kiln or hearth. 

Three incinerators had no air pollution control devices. The remaining five had wet scrubbers for

HCl control, and four of these had other particulate control devices. Twenty-nine compounds

were classified as PICs from the eight incinerator tests and are presented in Table A1.6-1. In

general, PIC concentrations were slightly higher than POHC concentrations, although this ratio

varied from site to site. PIC output rate very rarely exceeded 0.01 percent of the POHC input

rate. The document stated that the measurement of Appendix VIII compounds at low

concentrations in the waste feed, auxiliary fuel, and inflow streams to control systems is often

necessary to explain the presence of PICs.
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TABLE A1.6-1

PICS IDENTIFIED BY TRENHOLM AND HATHAWAY (1984)

PICs Found In Stack Effluents

PIC Number of Facilities Low Concentration (ng/L) High Concentration (ng/L)

Benzene 6 12 670

Bromochloromethane 1 14 14

Bromodichloromethane 4 3 32

Bromoform 3 0.2 24

Bromomethane 1 1 1

Carbon disulfide 1 32 32

Chlorobenzene 3 1 10

Chloroform 5 1 1,330

Chloromethane 1 3 3

Chlorophenol, o- 1 22 22

Dibromochloromethane 4 1 12

Dichlorobenzene 1 4 4

Diethyl phthalate 1 7 7

Dimethylphenol, 2,4- 1 21 21

Fluoranthene 1 1 1

Hexachlorobenzene 1 7 7

Methyl ethyl ketone 1 3 3

Methylene chloride 2 2 27

Methylene bromide 1 18 18

Naphthalene 3 5 100

Nitrophenol, o- 2 2 50

Pentachlorophenol 1 6 6

Phenol 2 4 22

Pyrene 1 1 1

Tetrachloroethylene 3 0.1 2.5

Toluene 2 2 75

Trichlorobenzene 1 7 7

Trichloroethane, 1,1,1,- 3 0.1 1.5

Trichlorophenol, 2,4,6- 1 110 110

Notes:

ng/L = Nanograms per liter

PIC = Product of incomplete combustion

C Olexsey et al. (1985) was prepared by Robert A. Olexsey and others of the U.S. EPA Hazardous

Waste Engineering Research Laboratory in Cincinnati, Ohio. This document discussed PIC

generation mechanisms and criteria for PIC formations. The paper provided data on emissions of

PICs during full-scale tests conducted on incinerators and boilers burning hazardous waste

(Trenholm et al. 1984; Castaldini et al. 1984). The documents referenced by this paper
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summarized a series of full-scale tests conducted on seven incinerators and five boilers conducted

by U.S. EPA to support its regulatory development for incinerators and boilers. Commonly

found PICs identified in these tests are presented in Tables A1.6-2 and A1.6-3.

TABLE A1.6-2

VOLATILE PICS MOST FREQUENTLY IDENTIFIED IN BOILER EMISSIONS

(OLEXSY, HUFFMAN, AND EVANS 1985)

PIC Number of Facilities Low Concentration (ng/L) High Concentration (ng/L)

Benzene 3 9.4 270

Chloroform 5 4.2 1,900

Chloromethane 4 4.6 410

Dichloroethane, 1,2- 3 1.3 1,200

Methylene chloride 4 83 2,000

Tetrachloroethylene 5 0.3 760

Trichloroethane, 1,1,1- 3 5.9 270

Notes:

ng/L = Nanograms per liter

PIC = Product of incomplete combustion

TABLE A1.6-3

VOLATILE PICS MOST FREQUENTLY IDENTIFIED IN INCINERATOR EMISSIONS

(OLEXSY, HUFFMAN, AND EVANS 1985)

PIC Number of Facilities Low Concentration (ng/L) High Concentration (ng/L)

Benzene 6 12 670

Chloroform 5 1 1,330

Methylene chloride 2 2 27

Tetrachloroethylene 3 0.1 2.5

Toluene 2 2 75

Trichloroethane, 1,1,1- 3 0.1 1.5

Notes:

ng/L = Nanograms per liter

PIC = Product of incomplete combustion

C For incinerators, ratios of PIC emissions to POHC input ranged from 0.00007 to 0.0028 percent;

and ratios of PIC emissions to POHC emissions ranged from 0.01 to 3.89. For boilers, ratios of

PIC emissions to POHC input ranged from 0.0032 to 0.3987 percent, and ratios of PIC emissions

to POHC emissions ranged from 5.44 to 22.5. These data indicated that PIC emissions were

higher for boilers than for incinerators; that is, PIC emissions were reduced with increased POHC
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DRE which is higher for incinerators. The document proposed seven methods to control PICs

and recommended further research on PIC generation mechanisms and control technologies.

C Trenholm et al. (1992) was prepared by Andrew R. Trenholm and David W. Kapella of MRI in

North Carolina and Gary D. Hinshaw of MRI in Missouri. The paper discusses the following

issues regarding emissions from incinerators that burn hazardous waste: 

• emissions of specific constituents presented in Appendix VIII, 

• emissions of specific compounds or types of compounds, and 

• data on the size and molecular weight of compounds emitted. 

The following were among the major issues discussed.

- PICs were studied through U.S. EPA-sponsored tests at eight incinerators, nine industrial

boilers, and five mineral processing kilns. The study was limited to compounds

presented in Appendix VIII. In all, 52 organic compounds (32 VOCs and 20 SVOCs)

were identified. The VOC concentrations were significantly higher than the SVOC

concentrations. PICs listed in this paper included: 

• benzene, 

• toluene, 

• carbon tetrachloride, 

• trichloromethane, 

• dichloromethane, 

• trichloroethene, 

• tetrachloroethene, 

• 1,1,1-trichloroethane, 

• cholorobenzene, 

• naphthalene, and 

• phenol.

- From the U.S. EPA-sponsored tests, (1) volatile compounds listed in Appendix VIII

identified were only a fraction—sometimes about one-half—of the total organic

compounds identified, and (2) semivolatile compounds not listed in Appendix VIII

identified were three to 30 times the quantity of organic compounds listed in Appendix

VIII . Table A1.6-4 lists the compounds identified by the U.S. EPA-sponsored tests.
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TABLE A1.6-4

MOST FREQUENTLY IDENTIFIED PICS

(TRENHOLM, KAPELLA, AND HINSHAW 1992)

Appendix VIII

Volatile Organic

Compounds

Appendix VIII

Semivolatile Organic

Compounds

Compounds Not Listed 

in Appendix VIII 

Benzene Bis(2-Ethylhexyl)phthalate (1,4-Phenylene)bisethanone, 1,1'-

Carbon tetrachloride Butylbenzylphthalate Acetone

Chlorobenzene Dibutylphtahlate Acetophenone

Chloroform Diethylphthalate Benzaldehyde

Methylene chloride Naphthalene Benzenedicarboxaldehyde

Tetrachloroethylene Phenol Benzoic acid

Toluene Chlorocyclohexanol

Trichloroethane, 1,1,1- Cyclohexane

Trichloroethylene Cyclohexanol

Ethylbenzene

Ethylbenzoic acid

Ethylphenol

Ethylphenyl-ethanone

Ethynylbenzene

Phenylpropenol

Propenylmethylbenzene

Tetramethyloxirane

Trimethylhexane

- A study of hazardous waste incinerator stack effluent was conducted to characterize the

types of compounds emitted. Twenty-nine compounds were identified at a concentration

range of 0.1 to 980 nanograms per liter. Methane, chloromethane, and chloroform

accounted for more than one-half of the total mass of VOCs detected. Other than

methane, oxygenated aliphatic hydrocarbons formed the highest fraction of the total

emissions.

- Based on the incinerator stack effluent study, it was found that as combustion conditions

deteriorate, increases in mass emissions are first noted with VOCs. Emissions of these

compounds, most notably C1 to C3 compounds, increase proportionately more than

larger compounds. For larger compounds, available data indicate that emission increases

are more likely to be aromatic compounds.

A1.6.3 CARB (1990b)

CARB prepared “Technical Support Document of Proposed Dioxins Control Measures for Medical Waste

Incinerators” to meet the requirements of California Health and Safety Code Section 39666 that a needs

report be prepared for proposed rules. The report presents a proposed airborne toxic control measure for
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dioxin emissions from medical waste-burning facilities. The report concentrates on dioxin, furan, and

cadmium emissions, although other pollutants detected during the tests are listed. Table A1.6-5 lists these

pollutants.

TABLE A1.6-5

COPCS IDENTIFIED BY CARB (1990b)

COPC

Ammonia Dibromoethane, 1,2- Nickel

Arsenic Dichloroethane Nitrogen oxides

Benzene Dichloromethane PM

Bromodichloromethane Dichloropropane, 1,2- PAHs

Cadmium Ethylbenzene Sulfur dioxide

Carbon dioxide Freon Tetrachloroethene

Carbon monoxide Hydrocarbon, total Tetratrichloromethylene

Carbon tetrachloride Hydrogen chloride Toluene

Chlorobenzenes Hydrogen fluoride Tribromomethane

Chlorodibromomethane Iron Trichlorethane

Chloroform Lead Trichloroethane, 1,1,1-

Chlorophenols Manganese Trichloroethylene

Chromium, hexavalent Mercury Trichlorotrifluroethane

Chromium, total Mesitylene Vinyl chloride

Copper Methyl isobutyl ketone Xylenes

Cumene Napthalene Zinc

Notes:

PAH = Polynuclear aromatic hydrocarbons

PM = Particulate matter

A1.6.4 CARB (1991)

CARB prepared “Air Pollution Control at Resource Recovery Facilities 1991 Update” to update

information presented in its 1984 report, entitled “Air Pollution Control at Resource Recovery Facilities.” 

Specifically, the document updates available guidelines concerning incinerator technology, emissions

control technology, and emission limits for municipal waste, hospital waste, biomass, tire, manure,

landfill and digester gas, and sewer sludge incinerators. The document states that its guidelines represent

levels that have been achieved by existing facilities.

In addition, the document summarizes the ultimate analysis of waste types undergoing treatment in the

facilities described above. An appendix summarizes stack gas analysis data for numerous operating

facilities. Pollutants identified in the analyses are summarized in Table A1.6-6.
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TABLE A1.6-6

STACK GAS ANALYSIS DATA (CARB 1991)

Pollutant

Incinerator Type a

Municipal

Waste

(5)

Hospital

Waste

(7)

Biomass

(4)

Manure

(1)

Tire

(1)

Landfill

Gas 

(20)

Sewage

Sludge and

Digester Gas

(5)

Nitrogen oxides U U U UU U U

Sulfur oxides U U ND UU U U

Particulate matter U U U UU U U

Carbon monoxide U U U UU U U

Total hydrocarbons U U U UU U U

Hydrogen chloride U U NA NA U NA NA

Hydrogen fluoride U NA NA NA NA NA NA

Amonnia NA NA U NA U NA NA

Carbon dioxide U U U UU NA U

Oxygen U U U UU NA U

Arsenic UU U NA UU U

Beryllium U NA NA NA U U b U

Cadmium UU U NA ND U b U

Chromium (total) UU U NA UU U

Chromium (hexavalent) ND U NA NA U NA NA

Copper U NA NA NA NA U NA

Mercury U U NA NA ND U U

Iron NA NA U NA NA NA NA

Manganese NA NA U NA NA NA NA

Nickel UU U NA ND U U

Lead UU U NA ND U U

Zinc NA NA NA NA NA U NA

Polyaromatic

hydrocarbons b

U NA U NA U NA NA

Polychlorinated

biphenyls b

U ND U NA U NA NA

CP b U NA U NA U NA NA

CB b U NA U NA U NA NA

Benzene UU U NA NA NA NA

Polychlorinated

dibenzo(p) dioxins b

UU U NA U NA NA

Polychlorinated

dibenzofurans b

UU U NA U NA NA

2,3,7,8-Tetrachloro

dibenzo(p)dioxin

equivalents b

UU U NA U NA U

Notes:

U = Detected in at least one emission test

ND = Not detected in any emission test

NA = No analysis

a Number in parentheses indicates the number of facilities for which data were tabulated. b Isomers and/or homologues that were not detected were added to total values at one-half the detection limit;

pollutant may not have actually been detected.
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A1.6.5 U.S. EPA (1988)

This document, referenced by some documents as a 1989 document, was prepared in 1988.

U.S. EPA prepared “Hospital Waste Combustion Study: Data Gathering Phase” to assemble available

information on hospital waste combustion so that U.S. EPA can evaluate whether airborne pollutant

emissions from hospital waste combustion should be regulated. While preparing this document, U.S.

EPA reviewed the pertinent literature to determine which studies would be helpful in completing the

database on toxic emissions from medical waste incinerators. The report clearly addresses only those

pollutants for which emissions data were found. The data reviewed were mostly for larger, controlled air

incinerators; and the more commonly used retort incinerators were not evaluated.

The study identified several categories of pollutants that were measured in stack gases; these are

discussed in the following paragraphs.

Where evaluated, acid gases were detected in stack gases. For example, HCl was detected in 24 of 28

tests; HCl concentration not recorded in the remaining four tests.

Particulate matter (PM) was detected in all stack tests for 30 facilities at concentrations ranging from

0.001 grains per dry standard cubic foot (gr/dscf), at a facility with PM add-on control devices, to

0.22 gr/dscf at facilities without such control devices.

Trace metals were detected in stack tests for three medical waste incineration facilities. Metals detected

include arsenic, cadmium, chromium, iron, manganese, nickel, and lead. The document also states that

fine-particle enrichment processes could lead to emissions of molybdenum, tin, selenium, vanadium, and

zinc. However, test results for these trace metals are not presented.

With respect to organic emissions, dioxins and furans were detected in emissions from three facilities,

both with and without pollution control devices. Other organic emissions detected in stack tests cited in

this report include CO, THC, trichlorotrifluoroethane, tetrachloromethane, tetrachloroethene, and

trichloroethylene.

In a stack testing conducted on three Canadian biomedical waste incinerators, PCBs and PAHs were

either not detected (one facility) or not analyzed (two facilities).

A1.6.6 CARB (1996)

In May 1996, CARB prepared “Proposed Amendments to the Emission Inventory Criteria and Guidelines

Report Published in Accordance with the Air Toxics ‘Hot Spots’ Information and Assessment Act of

1987.” The purpose of the report is to present the basis of CARB’s recommended amendments to the Air

Toxics Hot Spots Program. The report states that California Health and Safety Code (HSC) 44321

requires CARB to compile the list of toxic substances that must be monitored from “designated reference

lists of substances.” Therefore, the document is not a primary source of toxics emission information. The

primary sources of information are mandated by California HSC 44321, as follows: 

• California HSC 44321(a): National Toxicology Program, International Agency for

Research on Cancer

• California HSC 44321(b): Governor’s List of Carcinogens and Reproductive Toxicants
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• California HSC 44321(c): CARB

• California HSC 44321(d): Hazard Evaluation System and Information Service

• California HSC 44321(e): U.S. EPA

• California HSC 44321(f): California HSC

The lists of toxic substances presented in the document are not restricted to incinerator facilities, but

apply to any facility discharging airborne pollutants to the atmosphere. The document also removes

numerous substances, primarily medicinal compounds, from lists of toxic chemicals that must always be

evaluated, and places them on lists of toxic compounds that require evaluation only if a facility

manufactures that substance.

A1.7 COLUMN 7: U.S. EPA-RECOMMENDED AND POTENTIAL PICS (1994a; 1994b)

Compounds marked with an “X” in the appropriate cells are identified in U.S. EPA (1994a and 1994b). 

Based on information presented in U.S. EPA (1994b), these tables were developed from available U.S.

EPA data and from lists of toxic compounds from various U.S. EPA programs. Because the source lists

were not developed as lists of toxic PICs, U.S. EPA deleted compounds that were not appropriate (U.S.

EPA 1994b). U.S. EPA acknowledged the importance of using focused studies to develop a PIC list that

is (1) appropriately protective of the environment, and (2) not excessively burdensome on the regulated

community. Nevertheless, Tables 1 and 2 in U.S. EPA (1994b) were compiled as draft lists for use during

the interim period. Tables in U.S. EPA (1994b) were to be revised as additional PIC data were collected. 

U.S. EPA Permits and State Program Division is currently updating these tables; however, a target

completion date is not available. Tables 1 and 2 are based on the following (U.S. EPA 1994b):

C Hazardous waste constituent list in 40 CFR Part 261, Appendix VIII

C hazardous air pollutants (HAP) list

C Office of Research and Development list of organic compounds found in combustion

devices developed for U.S. EPA (1993) 

The following compounds were deleted from this list:

C Pesticide compounds not likely to be a PIC

C Federal Drug Administration-regulated drugs

C Carcinogenic sugar substitutes

C Compounds without chemical-specific listings (for example, “coal tar”)

C Compounds without U.S. EPA-established sampling and analysis methods

C Metallic compounds (because of difficulty in analyzing the specific compounds; metals

are still included in elemental totals)
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C Compounds with low octanol-water partition coefficients and no inhalation toxicity data

C Compounds with low toxicity values

C Naturally-occurring plant toxins

Specific compounds were retained on Tables 1 and 2 on the following basis:

C Pesticides with a molecular structure simple enough to be of concern as a PIC

C Compounds with very high octanol-water partition coefficients

A1.8 COLUMN 8: PICS ACTUALLY DETECTED IN STACK EMISSIONS

Compounds marked by an “X” in the appropriate cells are PICs that have actually been detected in stack

emissions. U.S. EPA compiled this list by evaluating the studies highlighted in Section A1.6. 
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REFERENCES

APPENDIX A-1

California Air Resources Board (CARB). 1990a. “Health Risk Assessment Guidelines for Nonhazardous

Waste Incinerators.” Prepared by the Stationary Source Division of the CARB and the California

Department of Health Services.

CARB. 1990b. “Technical Support Document of Proposed Dioxins Control Measures for Medical Waste

Incinerators.” May 25.

CARB. 1991. “Air Pollution Control at Resource Recovery Facilities. Update.”

CARB. 1996. “Proposed Amendments to the Emission Inventory Criteria and Guidelines Report

Published in Accordance with the Air Toxics ‘Hot Spots’ Information and Assessment Act of

1987.” May.

Castaldini, C., and others. 1984. “Engineering Assessment Report—Hazardous Waste Cofiring in

Industrial Boilers.” Report to U.S. Environmental Protection Agency under Contract No.

68-02-3188. June.

Dellinger, B., D.L. Hall, J.L. Graham, S.L. Mazer, W.A. Rubey, and M. Malanchuk. 1986. PIC

Formation Under Pyrolytic and Starved Air Conditions.. Prepared for the U.S. EPA Industrial

Environmental Research Laboratory. Prepared by the University of Dayton Research Institute. 

EPA/600/2-86/006. NTIS PB-86-145422. January.

Dellinger, B., J.L. Torres, W.A. Rubey, D.L. Hall, and J.L. Graham. 1984. Determination of the Thermal

Decomposition Properties of 20 Selected Hazardous Organic Compounds. Prepared for the U.S.

EPA Industrial Environmental Research Laboratory. Prepared by the University of Dayton

Research Institute. EPA-600/2-84-138. NTIS PB-84-232487. August.

Demsey, C.R., and E.T. Oppelt. 1993. “Incineration of Hazardous Waste: A Critical Review Update.” 

Air and Waste. 43:25-73.

Duval, D.S., and W.A. Rubey. 1976. Laboratory Evaluation of High-Temperature Destruction of

Kepone and Related Pesticides. EPA-600/2-76-299. NTIS PB-264892/1. December.

Duval, D.S., and W.A. Rubey. 1977. Laboratory Evaluation of High-Temperature Destruction of

Polychlorinated Biphenyls and Related Compounds. EPA-600/2-77-228. NTIS PB-279139/0. 

December.

Kramlich, J.C., W.R. Seeker, and M.P. Heap. 1984. “Laboratory-Scale Flame Mode Study of Hazardous

Waste Incineration.” Proceedings of the Ninth Annual Research Symposium on Incineration

and Treatment of Hazardous Waste. Fort Mitchell, Kentucky. May 2 through 4, 1983. 

EPA-600/9-84/015. NTIS PB-84-234525. Pages 79-94. July.

Olexsey, R.A., G.L. Huffman, and G.M. Evans. 1985. “Emission and Control of By-Products from

Hazardous Waste Combustion Processes.” Proceedings of the 11th Annual Research Symposium
Human Health Risk Assessment Protocol

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on Incineration and Treatment of Hazardous Waste. Cincinnati, Ohio. April 29 to May 1, 1985. 

EPA-600/9-85/028. NTIS PB-86-199403. Pages 8-15. September.

Trenholm, A., and R. Hathaway. 1984. “Products of Incomplete Combustion from Hazardous Waste

Incinerators.” Proceedings of the 10th Annual Research Symposium on Incineration and

Treatment of Hazardous Waste. Fort Mitchell, Kentucky. April 3-5. EPA-600/9-84/022. NTIS

PB-85-116291. Pages 84-95. September.

Trenholm, Andrew R., David W. Kapella, and Gary D. Hinshaw. 1992. “Organic Products of Incomplete

Combustion from Hazardous Waste Combustion.” Proceedings of the Air and Waste

Management Association 85th Annual Meeting and Exhibition. Kansas City, Missouri. June

21-26.

Trenholm, A., and C.C. Lee. 1986. “Analysis of PIC and Total Mass Emissions from an Incinerator.” 

Proceedings of the Twelfth Annual Research Symposium on Land Disposal, Remedial Action,

Incineration, and Treatment of Hazardous Waste. Cincinnati, Ohio. April 21 to 23, 1986. 

EPA/60-9-86/022. Pages 376-381. August.

Trenholm, A., and others. 1984. “Performance Evaluation of Full-Scale Hazardous Waste Incinerators.” 

Report to U.S. EPA under Contract No. 68-02-3177.

U.S. Environmental Protection Agency (EPA). 1981. “Incinerator Standards for Owners and Operators

of Hazardous Waste Management Facilities; Interim Final Rule and Proposed Rule.” Federal

Register. 46(15):7666-7690. January 23.

U.S. EPA. 1985. Report on the Incineration of Liquid Hazardous Wastes. Science Advisory Board. 

Environmental Effects, Transport, and Fate Committee. April.

U.S. EPA. 1987. Total Mass Emissions from a Hazardous Waste Incinerator. Final Report. Midwest

Research Institute. EPA-600/S2-87/064. NTIS PB-87-228508/AS. June 12.

U.S. EPA. 1988. “Hospital Waste Combustion Study: Data Gathering Phase.” Office of Air Quality

Planning and Standards. Research Triangle Park, North Carolina. EPA-450/3-88-008. 

December.

U.S. EPA. 1989. Guidance of PIC Controls for Hazardous Waste Incinerators. Volume V of the

Hazardous Waste Incineration Guidance Series. EPA/530-SW-90-040. April 3.

U.S. EPA. 1990a. “Standards for Owners and Operators of Hazardous Waste Incinerators and Burning

of Hazardous Wastes in Boilers and Industrial Furnaces; Proposed Rule, Supplemental Proposed

Rule, Technical Corrections, and Request for Comments.” Federal Register. 

55(82):17862-17921. April 27.

U.S. EPA. 1990b. Report of the Products of Incomplete Combustion Subcommittee of the Science

Advisory Board; Review of OSW Proposed Controls for Hazardous Waste Incineration Products

of Incomplete Combustion. EPA-SAB EC-90-004. October 24.

U.S. EPA. 1993. Review Draft Addendum to the Methodology for Assessing Health Risks Associated

with Indirect Exposure to Combustor Emissions. OHEA. ORD. EPA-600-AP-93-003. 

November 10.
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U.S. EPA. 1994a. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion

Facilities Burning Hazardous Wastes: Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response

(OERR). OSW. December 14.

U.S. EPA. 1994b. “Table 1—Chemicals Recommended for Identification and Table 2—Chemicals for

Potential Identification.” Draft Exposure Assessment Guidance for Resource Conservation and

Recovery Act Hazardous Waste Combustion Facilities: Attachment. April 15.

U.S. EPA. 1995. “Basis for Listing Hazardous Waste.: Title 40, Code of Federal Regulations, Part 261, 

Appendices VII and VIII.
APPENDIX A-2

CHEMICAL-SPECIFIC PARAMETER VALUES
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CONTENTS

Section Page

LIST OF VARIABLES AND COMPOUND-SPECIFIC PARAMETERS . . . . . . . . . . . . . . . . . A-2-ii

A2-1 GENERAL ANALYSIS AND METHODOLOGY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-2-1

A2-2 PHYSICAL AND CHEMICAL PROPERTIES

A2-2.1 Molecular Weight (MW) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-2-1

A2-2.2 Melting Point Temperature (Tm) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-2-2

A2-2.3 Vapor Pressure (Vp) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-2-3

A2-2.4 Aqueous Solubility (S) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-2-5

A2-2.5 Fraction of Contaminant Air Concentration in the Vapor Phase (Fv) . . . . . . A-2-6

A2-2.6 Henry’s Law Constant (H) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-2-7

A2-2.7 Diffusivity in Air (Da) and Water (Dw) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-2-8

A2-2.8 Octanol/Water Partitioning Coefficient (Kow) . . . . . . . . . . . . . . . . . . . . . . . . A-2-9

A2-2.9 Soil Organic Carbon-Water Partition Coefficient (Koc) . . . . . . . . . . . . . . . A-2-10

A2-2.9.1 Ionizing Organic Compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-2-10

A2-2.9.2 Nonionizing Organic Compounds . . . . . . . . . . . . . . . . . . . . . . . . . A-2-11

A2-2.10 Partitioning Coefficients for Soil-Water (Kds), Suspended Sediment-Surface

Water (Kdsw), and Bottom Sediment-Sediment Pore Water (Kdbs) . . . . . . . A-2-12

A2-2.11 Soil Loss Constant Due to Degradation (ksg) . . . . . . . . . . . . . . . . . . . . . . . A-2-14

A2-2.12 Bioconcentration and Biotransfer Factors for Plants . . . . . . . . . . . . . . . . . A-2-15

A2-2.12.1 Root Concentration Factor (RCF) . . . . . . . . . . . . . . . . . . . . . . . . . A-2-15

A2-2.12.2 Plant-Soil BCFs in Root Vegetables (Brrootveg) . . . . . . . . . . . . . . . . A-2-17

A2-2.12.3 Plant-Soil BCFs for Aboveground Produce (Brag) and 

Forage (Brforage) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-2-17

A2-2.12.4 Air-to-Plant BTFs for Aboveground Produce (Bvag) and 

Forage (Bvforage) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-2-19

A2-2.13 Biotransfer Factors for Animals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-2-22

A2-2.13.1 BTFs for Beef (Babeef) and Milk (Bamilk) . . . . . . . . . . . . . . . . . . . . A-2-22

A2-2.13.2 BTFs for Pork (Bapork) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-2-26

A2-2.13.3 BTFs for Chicken (Bachicken) and Poultry Eggs (Baegg) . . . . . . . . . . A-2-26

A2-2.13.4 Bioconcentration and Bioaccumulation Factors for Fish . . . . . . . . A-2-29

A2-2.13.4.1 Bioconcentration Factors for Fish (BCFfish) . . . . . . . . . A-2-29

A2-2.13.4.2 Bioaccumulation Factors for Fish (BAFfish) . . . . . . . . . A-2-31

A2-2.13.4.3 Biota-Sediment Accumulation Factor for Fish (BSAFfishA-2-33 )

A2-3 TOXICITY BENCHMARKS

A2-3.1 Prioritization of Data Sources for Chronic Toxicity Benchmarks . . . . . . A-2-33

A2-3.2 Explanation of Calculated Toxicity Benchmark Values . . . . . . . . . . . . . A-2-36

A2-3.3 Uncertainties Involved when using Toxicity Benchmarks Calculated based on

Route-to-Route Extrapolation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-2-37

A2-3.4 Prioritization of Data Sources for Acute Toxicity Benchmarks . . . . . . . A-2-37

REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-2-39

COPCs INCLUDED IN THE COMPANION DATABASE. . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-2-49
Human Health Risk Assessment Protocol

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LIST OF VARIABLES AND COMPOUND-SPECIFIC PARAMETERS

Dair = Density of air (g/cm3)

Dforage = Density of forage (g/cm3)

Babeef = Biotransfer factor in beef 

(mg COPC/kg FW tissue)/(mg COPC/day) OR (day/kg FW tissue)

Bachicken = Biotransfer factor in chicken 

(mg COPC/kg FW tissue)/(mg COPC/day) OR (day/kg FW tissue)

Baegg = Biotransfer factor in eggs 

(mg COPC/kg FW tissue)/(mg COPC/day) OR (day/kg FW tissue)

Bamilk = Biotransfer factor in milk 

(mg COPC/kg FW tissue)/(mg COPC/day) OR (day/kg FW tissue)

Bapork = Biotransfer factor in pork 

(mg COPC/kg FW tissue)/(mg COPC/day) OR (day/kg FW tissue)

BAFfish = Bioaccumulation factor in fish 

(mg COPC/kg FW tissue)/(mg COPC/L total water column) 

OR (L water/kg FW tissue)

BCFfish = Bioconcentration factor in fish (L/kg FW OR unitless)

Brag = Plant-soil bioconcentration factor in aboveground produce

(:g COPC/g DW plant)/(:g COPC/g DW soil)—unitless

Brforage/silage = Plant-soil bioconcentration factor in forage and silage

(:g COPC/g DW plant)/(:g COPC/g DW soil)—unitless

Brgrain = Plant-soil bioconcentration factor in grain

(:g COPC/g DW grain)/(:g COPC/g DW soil)—unitless

Brrootveg = Plant-soil bioconcentration factor for belowground produce 

(:g COPC/g DW plant)/(:g COPC/g DW soil)—unitless

BSAFfish = Biota-sediment accumulation factor in fish

(mg COPC/kg lipid tissue)/(mg COPC/kg sediment)—unitless

Bvol = Volumetric air-to-leaf biotransfer factor in leaf

(:g COPC/L FW plant)/(:g COPC/L air)—unitless

Bvag = COPC air-to-plant biotransfer factor for aboveground produce 

(:g COPC/g DW plant)/(:g COPC/g air)—unitless

Bvforage/silage = Air-to-plant biotransfer factor in forage and silage

(:g COPC/g DW plant)/(:g COPC/g air)—unitless

c = Junge constant = 1.7 x 10-04 (atm-cm)

Da = Diffusivity of COPC in air (cm2

/s)

Dw = Diffusivity of COPC in water (cm2

/s)

foc,bs = Fraction of organic carbon in bottom sediment (unitless)

foc,s = Fraction of organic carbon in soil (unitless)

foc,sw = Fraction of organic carbon in suspended sediment (unitless)

fwater = Fraction of COPC in water (unitless)

Fv = Fraction of COPC air concentration in vapor phase (unitless)

Fw = Fraction of wet deposition that adheres to plant surfaces (unitless)

H = Henry’s law constant
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Inhalation CSF = Inhalation cancer slope factor (mg/kg-day)-1

Inhalation URF = Inhalation unit risk factor (:g/m3)

-1

Kds = Soil-water partition coefficient (mL water/g soil OR cm3 water/g soil)

Kdsw = Suspended sediment-surface water partition coefficient 

(L water/kg suspended sediment OR cm3 water/g suspended sediment)

Kdbs = Bed sediment-sediment pore water partition coefficient 

(L water/kg bottom sediment OR cm3 water/g bottom sediment)

Kow = Octanol/water partitioning coefficient 

(mg COPC/L octanol)/(mg COPC/L octanol)—unitless

Koc = Soil organic carbon-water partition coefficient (mL water/g soil)

ksg = COPC soil loss constant due to biotic and abiotic degradation (yr-1)

MW = Molecular weight of COPC (g/mole)

p°

L = Liquid-phase vapor pressure of COPC (atm)

p°

S = Solid-phase vapor pressure of COPC (atm)

Oral CSF = Oral cancer slope factor (mg/kg-day)-1

R = Universal gas constant (atm-m3/mol-K)

RCF = Root concentration factor 

(:g COPC/g DW plant)/(:g COPC/mL soil water)

RfC = Reference concentration (mg/m3

)

RfD = Reference dose (mg/kg/day)

Rp = Interception factor of edible portion of plant (unitless)

S = Solubility of COPC in water (mg COPC/L water)

)Sf = Entropy of fusion [)Sf /R = 6.79 (unitless)]

ST = Whitby’s average surface area of particulates (aerosols)

= 3.5 x 10-06 cm2

/cm3 air for background plus local sources

= 1.1 x 10-05 cm2

/cm3 air for urban sources

t1/2 = Half-time of COPC in soil (days)

Ta = Ambient air temperature (K) 

Tm = Melting point temperature (K)

TEF = Toxicity equivalency factor (unitless)

Vp = Vapor pressure of COPC (atm)
Human Health Risk Assessment Protocol

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APPENDIX A-2

The following sections provide the general methodology and references we used to determine our

recommended parameter values. You can find the recommended parameter values themselves in the

HHRAP Companion Database (also known as the HHRAP database). In the HHRAP database we

provide compound-specific values for 

1. physical and chemical properties;

2. fate-and-transport parameters; and

3. Health benchmarks for chronic and acute exposure.

A2-1 GENERAL ANALYSIS AND METHODOLOGY

This section describes the general analysis and criteria we followed to determine our recommended

contaminant-specific parameter values. 

1. We compared parameter values among primary and available sources of applicable data,

placing priority for selection on sources that are (1) U.S. EPA or State agency peer

reviewed, (2) recent, (3) original sources of the values, and (4) generally accessible. 

2. We further further researched and evaluated sources of parameter values, and to the

extent possible, included observations affecting usability in parameter-specific

discussions for each compound.

3. We selected only parameter values from sources that could be verified and cited. 

4. We generally preferred source-recommended parameter values. As necessary, we

determined parameter values using correlations or equations, using input parameter

values provided in the HHRAP database.

5. When multiple parameter values were reported in a particular source (e.g., CHEMFATE),

we selected the source-recommended value in most cases. If more than one parameter

value is recommended by the source, then we selected the recommended value that falls

closest to the average of the source-recommended values. 

6. When reviewing and selecting parameter values from published literature or studies, we

preferred using measured values over other types of data.

A2-2 PHYSICAL AND CHEMICAL PROPERTIES

A2-2.1 Molecular Weight (MW)

Molecular weight (MW) of a compound is defined as the sum of atomic weights of all atoms in the

compound’s molecule.

For most compounds (except PCDDs and PCDFs, and methyl mercury), we obtained MW values from

one of the following sources, as cited:
Human Health Risk Assessment Protocol

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C U.S. EPA. 2004b. Superfund Chemical Data Matrix (SCDM). OERR. Washington,

D.C. January.

C Syracuse Research Corporation (SRC). 2003a. CHEMFATE Database. SRC. Syracuse,

NY.

C Syracuse Research Corporation (SRC). 2003b. PHYSPROP Database. SRC. Syracuse,

NY.

C Lide, D.R. 2003. CRC Handbook of Chemistry and Physics, 83rd Edition. CRC Press. 

Boca Raton, Florida.

C O’Neil, M., and A. Smith. 2001. The Merck Index: An Encyclopedia of Chemicals,

Drugs, and Biologicals. 13th Edition. Merck and Company, Inc. Rahway, New Jersey.

C Recommended value reported in published literature. When multiple parameter values

were reported in a particular source (e.g., database), we selected the recommended value

in most cases.

PCDDs and PCDFs We obtained MW values for PCDDs and PCDFs from U.S. EPA (2000). 

C U.S. EPA. 2000. Exposure and Human Health Reassessment of 2,3,7,8-

Tetrachlorodibenzo-p-Dioxin (TCDD) and Related Compounds. Draft Final Report. 

Office of Research and Development. Washington, D.C. EPA/600/P-00/001 Bc. 

September.

Mercuric Compounds We obtained MW values for elemental mercury and mercuric chloride from the

preferred sources listed above. We obtained the MW value for methyl mercury from U.S. EPA (1997b).

C U.S. EPA. 1997b. Mercury Study Report to Congress. Volume III: Fate and Transport

of Mercury in the Environment. OAQPS and ORD. EPA-452/R-97-005. December.

A2-2.2 Melting Point Temperature (Tm) 

Melting point temperature (Tm) is the temperature of the compound (in degrees Kelvin [K]) at which the

solid state of the compound undergoes a phase change to a liquid phase. At ambient temperatures and at

an atmospheric pressure of 1 atmosphere, compounds are generally in either a solid or liquid state.

For most compounds (except PCDDs and PCDFs), we obtained values for Tm from one of the following

sources, as cited:

C U.S. EPA. 2004b. Superfund Chemical Data Matrix (SCDM). OERR. Washington,

D.C. January.

C Syracuse Research Corporation (SRC). 2003a. CHEMFATE Database. SRC. Syracuse,

NY.

C Syracuse Research Corporation (SRC). 2003b. PHYSPROP Database. SRC. Syracuse,

NY.
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C Lide, D.R. 2003. CRC Handbook of Chemistry and Physics, 83rd Edition. CRC Press. 

Boca Raton, Florida.

C O’Neil, M., and A. Smith. 2001. The Merck Index: An Encyclopedia of Chemicals,

Drugs, and Biologicals. 13th Edition. Merck and Company, Inc. Rahway, New Jersey.

C Recommended value reported in published literature. When multiple parameter values

were reported in a particular source (e.g., database), we selected the recommended value

in most cases.

When a recommended range is provided instead of a singe numerical value, we selected the average of

the range.

PCDDs and PCDFs We obtained Tm values for PCDDs and PCDFs from U.S. EPA (2000).

U.S. EPA (2000) provides Tm values for PCDDs and PCDFs, and states that the values were obtained 

from various cited literature sources. We selected the midpoint of the range of values provided in U.S.

EPA (2000). 

Metals We obtained Tm values for metals, if available and except for mercury, from the preferred sources

listed above. 

Mercuric Compounds We obtained Tm values for elemental mercury and mercuric chloride from the list

of preferred sources noted above. A Tm value for methyl mercury wasn’t available in preferred sources

or literature.

A2-2.3 Vapor Pressure (Vp)

The vapor pressure (Vp) of a substance is defined as the pressure in atmospheres exerted by the vapor

(gas) of a compound when it is under equilibrium conditions. It provides a semi-quantitative rate at

which it will volatilize from soil and/or water. 

For most compounds (except PCDDs and PCDFs), we obtained values for Vp from the following

preferred sources:

C U.S. EPA. 2004b. Superfund Chemical Data Matrix (SCDM). OERR. Washington,

D.C. January.

C Syracuse Research Corporation (SRC). 2003a. CHEMFATE Database. SRC. Syracuse,

NY.

C Syracuse Research Corporation (SRC). 2003b. PHYSPROP Database. SRC. Syracuse,

NY.

C Lide, D.R. 2003. CRC Handbook of Chemistry and Physics, 83rd Edition. CRC Press. 

Boca Raton, Florida.

C O’Neil, M., and A. Smith. 2001. The Merck Index: An Encyclopedia of Chemicals,

Drugs, and Biologicals. 13th Edition. Merck and Company, Inc. Rahway, New Jersey.
Human Health Risk Assessment Protocol

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C Calculated using procedures set forth by:

Lyman et al. 1990. Handbook of Chemical Property Estimation Methods.

American Chemical Society. Washington, DC.

• Recommended value reported in published literature. When multiple parameter values

were reported in a particular source (e.g., database), we selected the recommended value

in most cases.

If a Vp value wasn’t available in SCDM, then we obtained a vapor pressure value from CHEMFATE,

PHYSPROP, CRC Handbook of Chemistry and Physics, or The Merck Index. If more than one value

was recommended by the source, then we selected the recommended value that fell closest to the average

of the recommended values. If a recommended value wasn’t available, we selected a value measured at

25/C. If more than one value measured at 25/C was available, then we selected the value falling closest

to the average of the available values. If no value was available at 25/C, then we followed the same

method using values determined within the range of 20 to 30/C.

If no vapor pressure values were available in any of the preferred references, then we used the procedures

described in Lyman et al. (1990) to calculate vapor pressure.

For nonmetallic substances, if vapor pressure wasn’t available, we obtained a normal boiling point from

the sources and used it to assign a default vapor pressure. If the boiling point is <25/C at 1 atmosphere

(atm) , we selected a default vapor pressure of 760 Torr, and we assume the substance is a gas at 25/C. 

As with SCDM, if no vapor pressure is available for a substance and the normal boiling point is equal or

greater than 25/C, we assume the substance is in a particulate form, rather than a gaseous form, and we

assigned a vapor pressure of zero in order to calculate Fv. We made this assumption because the absence

of a vapor pressure value often reflects an extremely low and difficult to measure (under standard

conditions) value for nongaseous substances (U.S. EPA 2004b).

SCDM prefers CHEMFATE-recommended values over estimated or calculated values. If more than one

recommended value is in CHEMFATE, SCDM selected the highest of the values. If a recommended

value is not available, SCDM uses a value measured at 25/C. If more than one value measured at 25/C is

available, SCDM uses the highest one. If no value is available at 25/C, values determined within the

range of 20 to 30/C are used. If more than one value measured at the same temperature is available and

none is recommended, SCDM uses the highest value. If no temperature is specified in CHEMFATE for

all vapor pressure measurements for a substance, SCDM uses the highest value. For values not available

in CHEMFATE, SCDM followed a similar approach to that outlined above. 

PCDDs and PCDFs We obtained Vp values for PCDDs and PCDFs from U.S. EPA (2000). Congener

group average values were substituted for missing individual congener specific values.

Metals Except for mercury compounds, metals that do not have Vp values in the references above we

assigned a Vp value of zero since they are assumed to be (1) nonvolatile at ambient temperatures, and

(2) insoluble in water, except as certain weak acids. 

Mercuric Compounds Mercury is a relatively volatile compound. We obtained the Vp value for

elemental mercury from a preferred source listed above. We obtianed the Vp value for mercuric chloride

from U.S. EPA (1997b). The Vp value for methyl mercury was not available in preferred sources or

literature.
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A2-2.4 Aqueous Solubility (S)

The aqueous solubility (S) of a compound is defined as the saturated concentration of the compound in

water (mg COPC/L water) at a given temperature and pressure, usually at soil/water temperatures and

atmospheric pressure (Montgomery and Welkom 1991).

For most compounds (except PCDDs and PCDFs and metals), we obtained values for S from the

following preferred sources:

C U.S. EPA. 2004b. Superfund Chemical Data Matrix (SCDM). OERR. Washington,

D.C. January.

C Syracuse Research Corporation (SRC). 2003a. CHEMFATE Database. SRC. Syracuse,

NY.

C Syracuse Research Corporation (SRC). 2003b. PHYSPROP Database. SRC. Syracuse,

NY.

C Dean, J.A. 2002. Lange’s Handbook of Chemistry. 15th Edition. McGraw-Hill. New

York.

C Calculated using procedures set forth by:

Lyman et al. 1990. Handbook of Chemical Property Estimation Methods.

American Chemical Society. Washington, DC.

• Recommended value reported in published literature. When multiple parameter values

were reported in a particular source (e.g., database), we selected the recommended value

in most cases.

If a S value wasn’t available in SCDM, then we obtained solubility values from CHEMFATE,

PHYSPROP, or Lange’s Handbook of Chemistry. If more than one value was recommended by the

source, then we selected the recommended value falling closest to the average of the recommended

values. If a recommended value wasn’t available, we selected a value measured at 25/C. If more than

one value measured at 25/C is available, then we selected the value falling closest to the average of the

available values. If no value was available at 25/C, we used the same method using values determined

within the range of 20 to 30/C. 

If no solubility values were available in any of the preferred references, we used the procedures described

in Lyman et al. (1990) to calculate vapor pressure.

SCDM prefers CHEMFATE-recommended values over estimated or calculated values. If more than one

recommended value is in CHEMFATE, SCDM selected the highest of the values. If a recommended

value is not available, SCDM uses a value measured at 25/C. If more than one value measured at 25/C is

available, SCDM uses the highest one. If no value is available at 25/C, values determined within the

range of 20 to 30/C are used. If more than one value measured at the same temperature is available and

none is recommended, SCDM uses the highest value. If no temperature is specified in CHEMFATE for

all vapor pressure measurements for a substance, SCDM uses the highest value. For values not available

in CHEMFATE, SCDM followed a similar approach to that outlined above for determining values

reported in Table A-1. 
Human Health Risk Assessment Protocol

Appendix A-2 September 2005

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Equation A-2-1

Equation A-2-2

PCDDs and PCDFs We obtained S values for PCDDs and PCDFs from U.S. EPA (2000). Congener

group average values were substituted for missing individual congener specific values.

Metals We obtained S values for metallic compounds, if available and except for mercury, from the

preferred sources listed for organic and inorganic compounds. 

Mercuric Compounds Mercury is a relatively volatile compound. We obtained S values for elemental

mercury and mercuric chloride from the preferred sources listed above. Methyl mercury is stated in the

Merck Index as being insoluble in water. Therefore, we assigned an S value of zero for methyl mercury.

A2-2.5 Fraction of Contaminant Air Concentration in the Vapor Phase (Fv)

Organics For most compounds (except metals and some mercury compounds), we calculated the fraction

of contaminant air concentration in the vapor phase (Fv) using the following equation:

C Junge, C. E. 1977. Fate of Pollutants in the Air and Water Environments, Part I; Suffet,

I. H., Ed.; Wiley; New York. Pages 7-26.

If the contaminant is a liquid at ambient temperatures (that is, when p°

L is known), we used Equation A-2-

1 to calculate Fv using the Vp value recommended for that contaminant in the HHRAP database. If the

contaminant is a solid at ambient temperatures (that is, when p°

S is known), we used the following

equation (Bidleman 1988) calculate p°

L from p°S, for use in Equation A-2-1 (using Vp and Tm values

presented for each contaminant in the HHRAP database):

where

c = Junge constant = 1.7 x 10-04 (atm-cm)

p°

L = Liquid phase vapor pressure of compound (atm)

p°

s = Solid phase vapor pressure of compound (atm)

R = Universal ideal gas constant (atm-m3

/moleK)

)Sf = Entropy of fusion [)Sf /R = 6.79 (unitless)]

ST = Whitby’s average surface area of particulates (aerosols)

Ta = Ambient air temperature (K)—assumed to be 25°

C or 298 K 

C Bidleman, T.F. 1988. “Atmospheric Processes.” Environmental Science and

Technology. Volume 22. Number 4. Pages 361-367.
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According to Bidleman (1988), Equation A-2-1 assumes that the Junge constant (c) is constant for all

compounds. However, c can depend on (1) the compound (sorbate) molecular weight, (2) the surface

concentration for monolayer coverage, and (3) the difference between the heat of desorption from the

particle surface and the heat of vaporization of the liquid-phase sorbate.

Metals As in U.S. EPA (1994b), we assumed all metals (except mercury) are present predominately in

the particulate phase and not in the vapor phase (Vp = 0), and therefore, assigned Fv values of zero.

Mercuric Compounds Elemental mercury and mercuric chloride are relatively volatile and exist in the

vapor phase (U.S. EPA 1997b). Therefore, we calculated the Fv value for elemental mercury using

Equation A-2-1. 

Based on discussions in U.S. EPA (1997b), we assigned mercuric chloride an Fv value of 0.85. Also, 

consistent with information provided in U.S. EPA (1997b), we assumed methyl mercury doesn’t exist in

the air phase and, therefore, assigned it an Fv of zero. 

A2-2.6 Henry’s Law Constant (H)

Henry’s Law constant (H) is also referred to as the air-water partition coefficient, and is defined as the

ratio of the partial pressure of a compound in air to the concentration of the compound in water at a given

temperature under equilibrium conditions. Henry’s Law constant values generally can be (1) calculated

from the theoretical equation defining the constant, (2) measured, or (3) estimated from the compound

structure. 

For most compounds (excluding PCDDs and PCDFs), we obtained H values from the following preferred

sources:

C U.S. EPA. 2004b. Superfund Chemical Data Matrix (SCDM). OERR. Washington,

D.C. January.

C Syracuse Research Corporation (SRC). 2003a. CHEMFATE Database. SRC. Syracuse,

NY.

C Syracuse Research Corporation (SRC). 2003b. PHYSPROP Database. SRC. Syracuse,

NY.

C Calculated using procedures set forth by:

Lyman et al. 1990. Handbook of Chemical Property Estimation Methods.

American Chemical Society. Washington, DC.
Human Health Risk Assessment Protocol

Appendix A-2 September 2005

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Equation A-2-3

Equation A-2-5

Equation A-2-4

where

H = Henry’s Law constant (atm-m3

/mole)

Vp = Vapor pressure of COPC (atm)

S = Solubility of COPC in water (mg COPC/L water)

H values calculated with Equation A-2-3 used MW, S, and Vp values found in the HHRAP database.

PCDDs and PCDFs We obtained H values for PCDDs and PCDFs from U.S. EPA (2000). We

substituted congener group average values for missing individual congener specific values.

Metals We obtained H values for metallic compounds, if available and except for mercury, from the

preferred sources listed above. Metals that do not have H values in the references above we assigned a

value of zero since the subject metals are assumed to be (1) nonvolatile at ambient temperatures, and

(2) insoluble in water, except as certain weak acids. 

Mercuric Compounds We obtained H values for elemental mercury, mercuric chloride, and methyl

mercury from U.S. EPA (1997b). 

A2-2.7 Diffusivity in Air (Da) and Water (Dw)

Diffusivity or diffusion coefficients in air (Da) and water (Dw) are used to calculate the liquid or gas phase

transfer of a contaminant into a water body.

For most compounds (except PCDDs and PCDFs), we obtained diffusion coefficients in air (Da) and

water (Dw) values from the following preferred source:

C U.S. EPA. 2004c. WATER9—Air Emissions Models Wastewater Treatment. 

Version 2.0.0. OAQPS. Research Triangle Park. North Carolina. July 1.

If values weren’t available in U.S. EPA (2004c), we calculated values using procedures set forth by:

• U.S. EPA. 1997b. Mercury Study Report to Congress. Volume III: Fate and Transport

of Mercury in the Environment. OAQPS and ORD. EPA-452/R-97-005. December.
Human Health Risk Assessment Protocol

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Equation A-2-6

Dw and Da values calculated with Equations A-2-4 and A-2-5 used MW values

recommended in the HHRAP database.

PCDDs and PCDFs We obtained Diffusivity values in air and water for 2,3,7,8-TCDD and

2,3,7,8-TCDF from U.S. EPA (2004c). For all other congeners of PCDDs and PCDFs, (1) we

recommend a default Dw value of 8 x 10-06 cm2

/s, and (2) we estimated Da values from PCDD and PCDF

values using the following equation recommended by U.S. EPA (2000) and obtained from Thibodeaux

(1979):

where

Dx,y = Diffusivities in air of compounds x and y (cm2

/s)

MWx,y = Molecular weights of compounds x and y (g/mol)

We calculated Da values for PCDD congeners using the Da value and MW for 2,3,7,8-TCDD. We

calculated Da values for PCDF congeners using the Da value and MW for 2,3,7,8-TCDF. This approach

is consistent with the methodology specified in U.S. EPA (2000). Values for diffusivity in water range

from 1 x 10-06 to 1 x 10-05 cm2

/s; therefore, U.S. EPA (1995b) recommended a default value of

8 x 10-06 cm2

/s. Diffusivity values calculated using Equations A-2-4 and A-2-5 were within the range

specified by U.S. EPA (1995b).

Metals We obtained dDiffusivity values for metallic compounds, if available and except for mercury,

from the preferred sources listed for organic and inorganic compounds. If values for metals were not

available in the preferred sources, we assigned a default value of zero since metals (except mercury and

chromium) are generally considered (1) nonvolatile at ambient temperatures, and (2) insoluble in water,

except as certain weak acids. 

Mercuric Compounds We obtained the diffusivity value for elemental mercury from the WATER9

database (U.S. EPA 2004c). We calculated diffusivity values for mercuric chloride and methyl mercury

using Equations A-4 and A-5. 

A2-2.8 Octanol/Water Partitioning Coefficient (Kow)

The n-octanol/water partitioning coefficient (Kow) is defined as the ratio of the solute concentration in the

water-saturated n-octanol phase to the solute concentration in the n-octanol-saturated water phase

(Montgomery and Welkom 1991). 

For most compounds (except PCDDs and PCDFs, and mercuric chloride), we obtained Kow values from

the following preferred sources:

C U.S. EPA. 2004b. Superfund Chemical Data Matrix (SCDM). OERR. Washington,

D.C. January.
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C Syracuse Research Corporation (SRC). 2003a. CHEMFATE Database. SRC. Syracuse,

NY.

C Syracuse Research Corporation (SRC). 2003b. PHYSPROP Database. SRC. Syracuse,

NY.

C Lide, D.R. 2003. CRC Handbook of Chemistry and Physics, 83rd Edition. CRC Press. 

Boca Raton, Florida.

C Recommended value reported in published literature. When multiple parameter values

were reported in a particular source (e.g., database), we selected the recommended value

in most cases.

PCDDs and PCDFs We obtained Kow values for the PCDDs and PCDFs from U.S. EPA (2000). 

Congener group average values were substituted for missing individual congener specific values.

Metals We obtained Kow values for metals, if available and except for mercury, from the preferred sources

listed above. Kow values for metals not reported in the above sources we assumed to be zero. This

assumption is based on the affinity of most metals to octanol approaches zero.

Mercuric Compounds We obtained the Kow value for elemental mercury from the list of preferred sources

above. The Kow value for mercuric chloride comes from U.S. EPA (1997b). We couldn’t find a Kow value

for methyl mercury.

A2-2.9 Soil Organic Carbon-Water Partition Coefficient (Koc)

The soil organic carbon-water partition coefficient (Koc) or the organic carbon normalized soil sorption

coefficient is defined as the ratio of adsorbed compound per unit weight of organic carbon to the aqueous

solute concentration (Montgomery and Welkom 1991).

The partitioning of ionizing organic compounds can be significantly influenced by soil pH. Because of

the soil mechanisms that are inherently involved, we discuss Koc values for the ionizing organics and

nonionizing organics separately. 

A2-2.9.1 Ionizing Organic Compounds 

Ionizing organic compounds include amines, carboxylic acids, and phenols. These compounds contain

the functional groups that ionize under specific pH conditions, and include the following: 

C Organic acids (2,4,6-trichlorophenol; pentachlorophenol; 2,3,4,5-tetrachlorophenol;

2,3,4,6-tetrachlorophenol; 2,4,5-trichlorophenol; 2,4-dichlorophenol; 2-chlorophenol;

phenol; 2,4-dimethylphenol; 2-methylphenol; 2,4-dinitrophenol; and benzoic acid) 

C Organic bases—n-nitroso-di-n-propylamine; n-nitrosodiphenylamine, and

4-chloroaniline)

We obtained Koc values for ionizing organic compounds from the following:
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Equation A-2-7

Equation A-2-8

C U.S. EPA. 1996. Soil Screening Guidance: Technical Background Document and

User’s Guide. Office of Solid Waste and Emergency Response. Washington, DC. 

EPA/540/R-95/128. May.

The Koc values for ionizing organic compounds provided by U.S. EPA (1996) were estimated on the basis

of the degree of ionization and the relative proportions of neutral and ionized species. Koc values for

ionizing compounds can vary vastly, depending on the pH conditions in the environment. Therefore, for

the aforementioned ionizing organic compounds, Koc values in the HHRAP database are based on a pH

value of 6.8 to correlate with typical environmental soils. 

Koc values were estimated on the basis of the assumption that the sorption of ionizing organic compounds

is similar to hydrophobic organic sorption, because the soil organic carbon is the dominant sorbent. 

According to U.S. EPA (1996), for low pH conditions, these estimated values may overpredict sorption

coefficients, because they ignore sorption to components other than organic carbon.

A2-2.9.2 Nonionizing Organic Compounds 

Nonionizing organic compounds include volatile organics, chlorinated pesticides, polynuclear aromatic

hydrocarbons (PAHs), and phthalates. We obtained Koc values for nonionizing organic compounds from

the following:

C U.S. EPA. 1996. Soil Screening Guidance: Technical Background Document and

User’s Guide. Office of Solid Waste and Emergency Response. Washington, DC. 

EPA/540/R-95/128. May.

U.S. EPA (1996) calculated the geometric mean value from various measured values. For compounds for

which Koc values are not directly provided by U.S. EPA (1996), we calculated Koc values using Kow

correlation equations provided in U.S. EPA (1996), as obtained from DiToro (1985). We used Kow values

recommended in the HHRAP database to calculate Koc values.

For most semi-volatile nonionizing organic compounds -

C DiToro, D.M. 1985. “A Particle Interaction Model of Reversible Organic Chemical

Sorption” Chemosphere. 14(10):1503-1538.

For the purposes of applying Equation A-2-7, we define semi-volatile compounds as having a Henry’s

Law Constant (H) value less than 10-3, consistent with general descriptions provided in Lyman et al.

(1990).

For volatile nonionizing organics, chlorinated benzenes, and certain chlorinated pesticides - 
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Center for Combustion Science and Engineering A-2-12

Equation A-2-9

For the purposes of applying Equation A-2-8, we define volatile compounds as having a Henry’s Law

Constant (H) value greater than 10-3, consistent with general descriptions provided in Lyman et al.

(1990).

PCDDs and PCDFs For PCDDs and PCDFs, we used the following correlation equation obtained from

Karickhoff, et al. (1979), as cited by U.S. EPA (2000), , and Kow values provided in the HHRAP database

to calculate Koc values.

C Karickhoff, S.W., D.S. Brown, and T.A. Scott. 1979. “Sorption of Hydrophobic

Pollutants on Natural Sediments.” Water Resources. 13:241-248. 

Metals We couldn’t find Koc values for metals within the preferred sources or available literature.

Mercuric Compounds We couldn’t find Koc values for mercury compounds within the preferred sources

or available literature.

A2-2.10 Partitioning Coefficients for Soil-Water (Kds), Suspended Sediment-Surface Water

(Kdsw), and Bottom Sediment-Sediment Pore Water (Kdbs)

Partition coefficients (Kd) describe the partitioning of a compound between sorbing material, such as soil,

soil pore-water, surface water, suspended solids, and bed sediments. For organic compounds, Kd is

estimated to be a function of the organic-carbon partition coefficient and the fraction of organic carbon in

the partitioning media. For metals, Kd is assumed to be independent of the organic carbon in the

partitioning media and, therefore, partitioning is similar in all sorbing media. 

The soil-water partition coefficient (Kds) describes the partitioning of a compound between soil

pore-water and soil particles, and strongly influences the release and movement of a compound into the

subsurface soils and underlying aquifer. The suspended sediment-surface water partition coefficient

(Kdsw) describes the partitioning of a compound between surface water and suspended solids or sediments. 

The bed sediment-sediment pore-water partition coefficient (Kdbs) describes the partitioning of a

compound between the bed sediments and bed sediment pore-water. 

For most compounds (including PCDDs and PCDFs), we obtained Kds values from the following

preferred sources:

C U.S. EPA. 2004b. Superfund Chemical Data Matrix (SCDM). OERR. Washington,

D.C. January.

C U.S. EPA. 1996. Soil Screening Guidance: Technical Background Document and

User’s Guide. Office of Solid Waste and Emergency Response. Washington, DC. 

EPA/540/R-95/128. May.
Human Health Risk Assessment Protocol

Appendix A-2 September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering A-2-13

Equation A-2-10

Equation A-2-11

Equation A-2-12

C Baes, C.F., R.D. Sharp, A.L. Sjoreen, and R.W. Shor. 1984. “Review and Analysis of

Parameters and Assessing Transport of Environmentally Released Radionuclides through

Agriculture.” Oak Ridge National Laboratory. Oak Ridge, Tennessee.

C RTI. 1996. Chemical Properties for SCDM Development. Prepared for U.S. EPA

Office of Emergency and Remedial Response. Washington, DC.

C Calculated using procedures consistent with:

U.S. EPA. 1993d. Review Draft Addendum to the Methodology for Assessing

Health Risks Associated with Indirect Exposure to Combustor Emissions. 

Office of Health and Environmental Assessment. Office of Research and

Development. EPA-600-AP-93-003. November 10.

We assume that soil organic carbon is the dominant sorbing component in soils and sediments. 

Therefore, Kd values not directly available in the preferred sources were calculated using the following

fraction organic carbon (fOC) correlation equations provided in U.S. EPA (1993d):

C U.S. EPA. 1993d. Review Draft Addendum to the Methodology for Assessing Health

Risks Associated with Indirect Exposure to Combustor Emissions. Office of Health and

Environmental Assessment. Office of Research and Development. 

EPA-600-AP-93-003. November 10.

U.S. EPA (1993d), based on literature searches, states that fOC could range as follows: 

C 0.002 to 0.024 in soils—for which a mid-range value of foc,s = 0.01 generally can be used. 

C 0.05 to 0.1 in suspended sediments—for which a mid-range value of foc,sw = 0.075

generally can be used. 

C 0.03 to 0.05 in bottom sediments—for which a mid-range value of foc,bs = 0.04 generally

can be used. 

We calculated Kd values using the Koc values recommended in the HHRAP database, and mid-range foc

values recommended by U.S. EPA (1993d).
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Appendix A-2 September 2005

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Equation A-2-13

Metals For metals (except mercury), Kd is governed by factors other than organic carbon, such as pH,

redox, iron content, cation exchange capacity, and ion-chemistry. Therefore, Kd values for metals can’t

be calculated using the same correlation equations specified for organic compounds. We obtained Kd

values, except lead and mercury, from the preferred sources listed above. SCDM obtained its values from

U.S. EPA (1996), which provides values for Kd that are based on pH and are estimated using the

MINTEQ2 geochemical speciation model. The MINTEQ2 model analyses were conducted under a

variety of geochemical conditions and metal concentrations. The MINTEQ2 pH-dependent Kd values

were estimated by holding constant the iron oxide at a medium value and the foc at 0.002.

Because organic carbon does not play a major role in partitioning for the metals, U.S. EPA (1994b)

assumed that the partitioning is the same, regardless of the soil, suspended sediment, or bottom sediment

phase. Therefore, we assumed that the values for partitioning coefficients Kds, Kdsw, and Kdbs for the

metals are the same. 

We obtained the Kd value for lead from the following:

C Baes, C.F., R.D. Sharp, A.L. Sjoreen, and R.W. Shor. 1984. “Review and Analysis of

Parameters and Assessing Transport of Environmentally Released Radionuclides

Through Agriculture.” Oak Ridge National Laboratory, Oak Ridge, Tennessee.

Mercuric Compounds We obtained Kds, Kdsw, and Kdbs values for mercury , mercuric chloride, and

methyl mercury from U.S. EPA (1997b).

A2-2.11 Soil Loss Constant Due to Degradation (ksg)

Soil loss constant due to degradation (ksg) reflects loss of a compound from the soil by processes other

than leaching. Degradation rates in the soil media include biotic and abiotic mechanisms of

transformation. Abiotic degradation includes photolysis, hydrolysis, and redox reactions. Hydrolysis and

redox reactions can be significant abiotic mechanisms in soil (U.S. EPA 1990).

Lyman et al. (1990) states that degradation rates can be assumed to follow first order kinetics in a

homogenous media. Therefore, the half-life (t1⁄2) of compounds can be related to the degradation rate

constant (ksg) as follows:

Ideally, ksg is the sum of all biotic and abiotic rate constants in the soil. Therefore, if the t1⁄2 for all of the

mechanisms of transformation are known, the degradation rate can be calculated using Equation A-2-13. 

However, literature sources don’t generally provide sufficient data for all such mechanisms, especially for

soil. 

For most compounds (except PCDDs and PCDFs, PCBs, metals, and mercury), we calculated ksg values

using half-life soil values obtained from the following preferred sources:
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C Howard, P.H., Boethling, R.S., Jarvis, W.F., Meylan, W.M., and Michalenko, E.M. 

1991. Handbook of Environmental Degradation Rates. Lewis Publishers. Chelsea,

Michigan. 

C Recommended value reported in published sources or literature other than the preferred

sources listed above. When multiple parameter values were reported in a particular

source (e.g., database), we selected the recommended value in most cases.

Half-life values provided in Howard et al. (1991) indicate the disappearance of a substance in ground

water or soil; with the principal degradation mechanisms being biodegradation and hydrolysis. Values

reported were highly variable because of the different methods used for measurements, in addition to the

various controlling factors that could affect them. Therefore, Howard et al. (1991) provided a range of

half-life values found in the literature, usually for the fastest reaction mechanism. We used high-end

half-life values to calculate ksg values.

For half-life values obtained from literature sources, if more than one value was recommended by the

source, then we selected the value falling closest to the average of the recommended values. This value

was used to calculate the ksg value recommended in the HHRAP database. If no recommended values

were available, we used a value measured at 25/C. If more than one value measured at 25/C was

available, then we used the value falling closest to the average of the available values to calculate the ksg

value recommended in the HHRAP database. If no value was available at 25/C, we used values

determined within the range of 20 to 30/C following the same method. 

For contaminants with no reported soil degradation rates, we recommend a default value of zero. 

PCDDs, PCDFs, and PCBs For PCDDs, PCDFs, and PCBs, we obtained ksg values from

U.S. EPA (2000); which discussed experimental studies that were conducted on PCDDs and PCDFs

degradation mechanisms. U.S. EPA (2000) stated that based on available studies, it appears reasonable to

assign a uniform rate of degradation for all PCDD/F congeners, and PCBs. The specific degradation rate

provided by U.S. EPA (2000) was 0.0277 yr-1, which translates to a half-life of 25 years. 

Metals For the metals, literature states that the metals are transformed, but not degraded, by such

mechanisms; therefore, we assume ksg values are zero for metals with no reported half-life values in soil.

Mercuric Compounds For mercury, mercuric chloride, and methylmercury, U.S. EPA (1997b)

recommended ksg values of zero.

A2-2.12 BIOCONCENTRATION AND BIOTRANSFER FACTORS FOR PLANTS

A2-2.12.1 Root Concentration Factor (RCF)

The root concentration factor (RCF) is used to calculate the belowground transfer of contaminants from

soil to a root vegetable. The RCF was developed based on experiments conducted by Briggs et al. (1982)

which measured uptake of compounds into barley roots from growth solution. 

For compounds with log Kow values of 2.0 and higher, we used the following correlation equation to

obtain RCF values:
Human Health Risk Assessment Protocol

Appendix A-2 September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering A-2-16

Equation A-2-14

Equation A-2-15

For compounds with log Kow values less than 2.0, we used the following correlation equation to obtain

RCF values:

We obtained these equations from the following document:

C Briggs, G.G., R.H. Bromilow, and A.A. Evans, 1982. “Relationships Between

Lipophilicity and Root Uptake and Translocation of Non-ionized Chemicals by Barley.” 

Pesticide Science. Volume 13. Pages 495-504.

These equations estimate a RCF value in fresh weight (FW) units, which was then converted to dry

weight (DW) units using a moisture content of 87 percent in root vegetables (U.S. EPA 1997c;

Pennington 1994). 

Briggs et al. (1982) derived the correlation equations above from studies using 18 compounds with

log Kow values ranging from -0.57 to 4.6. In addition, a validation exercise, in which predictions of

dioxin-like compounds (log Kow values from 6.0 to 8.2) in carrots were compared with observations,

shows this factor to adequately perform for this class of compounds (Muller et al. 1994). Therefore, RCF

values for compounds with outlying log Kow values have been capped in line with the test data used to

formulate the correlation equation. We assigned compounds with log Kow values less than -0.57 an RCF

value corresponding to a log Kow value of -0.57. At the high end of the range, we assigned compounds

with log Kow values greater than 8.2 (considering the validation studies using dioxin-like compounds) an

RCF value corresponding to a log Kow value of 8.2.

As in previous U.S. EPA guidance (U.S. EPA 1994a), we recommend using Equation A-2-14 in

calculating exposure to dioxin-like compounds. We used Kow values available in the HHRAP database to

calculate each RCF value. 

Metals For metals, no referenced RCF values were available in published literature. However, plant-soil

biotransfer factors for root vegetables (Brrootveg) were available in the literature and, therefore, RCF values,

normally used to calculate Brrootveg values, aren’t needed for the metals.

Mercuric Compounds No RCF values were available in the literature for mercury, mercuric chloride,

and methyl mercury. However, plant-soil biotransfer factors for root vegetables (Brrootveg) were available

in U.S. EPA (1997b) and, therefore, RCF values, normally used to calculate Brrootveg values, aren’t needed

for the mercuric compounds.
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Appendix A-2 September 2005

U.S. EPA Region 6 U.S. EPA

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Center for Combustion Science and Engineering A-2-17

Equation A-2-16

A2-2.12.2 Plant-Soil BCFs in Root Vegetables (Brrootveg)

The plant-soil bioconcentration factor for compounds in root vegetables (Brrootveg) accounts for uptake

from soil to the belowground root vegetables or produce. 

For most compounds, we used the following equation from U.S. EPA (1995b) to calculate values for

Brrootveg on a dry weight basis:

We calculated Brrootveg values using the RCF and Kds values listed in the HHRAP database.

Metals We obtained the Brrootveg values for metals (except nickel, cadmium, selenium, and arsenic) from

Baes et al. (1984). Br values in Baes et al. (1984) are dry weight values provided for nonvegetative

(reproductive) growth, such as tubers. 

For nickel, cadmium, selenium, and arsenic, we obtained Brrootveg values from the following document:

C U.S. EPA. 1992b. Technical Support Document for the Land Application of Sewage

Sludge. Volumes I and II. EPA 822/R-93-001a. Office of Water. Washington, D.C.

For nickel, cadmium, selenium, and arsenic—Brroot veg values were calculated by multiplying the uptake

slope factors [(:g COPC/g DW plant)/(kg COPC applied/hectare)] for root vegetables by a conversion

factor of 2x109

 g/hectare soil. In deriving the conversion factor, U.S. EPA (1992b) assumed a soil

average dry bulk density of 1.33 g/cm3

 and a soil incorporation depth of 15 cm. 

Mercuric Componds We obtained Brrootveg values for mercuric chloride and methyl mercury from

U.S. EPA (1997b) on a dry weight basis. The HHRAP methodolgy assumes elemental mercury doesn’t

deposit onto soils, and therefore there’s no plant uptake through the soil. Therefore, a Brrootveg value for

elemental mercury isn’t applicable.

A2-2.12.3 Plant-Soil BCFs for Aboveground Produce (Brag) and Forage (Brforage) 

The plant-soil bioconcentration factor (Br) for aboveground produce accounts for the uptake from soil

and the subsequent transport of contaminants through the roots to the aboveground plant parts. As

addressed in U.S. EPA (1995b), the Br value for most compounds is a function of water solubility, which

is inversely proportional to Kow. The Br value for metals is a function of the bioavailability of the metals

in soil.

For all compounds, including PCDDs and PCDFs, (1) the subscript “ag” represents aboveground produce

which applies to exposed fruits and vegetables, and protected fruits and vegetables, and (2) the subscript

“forage” represents forage, but the values also apply to silage and grain. For metals, (1) aboveground

fruits (both exposed and protected) are represented by Brag (fruit); (2) aboveground vegetables (both

exposed and protected) are represented by Brag(veg), (3) forage is represented by Brforage, but the values also

apply to silage, and (4) grains are represented by Brgrain.
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Equation A-2-18

Equation A-2-17

For most compounds, we used the following correlation equations to calculate values for Brag and Brforage

on a dry weight basis:

We obtained these correlation equations from;

C Travis, C.C. and A.D. Arms. 1988. Bioconcentration of Organics in Beef, Milk, and

Vegetation. Environmental Science and Technology. 22:271-274.

Travis and Arms (1988) developed a correlation equation for vegetation that doesn’t distinguish between

aboveground produce and forage or silage or grain. Due to lack of literature data, we used the Travis and

Arms (1988) correlation equation to calculate Br values for both aboveground produce and forage. 

The above correlation equations for Br values were derived from experiments conducted on compound

classes such as DDT, pesticides, PCDDs, PCDFs, and PCBs, representing compounds with log Kow values

ranging from 1.15 to 9.35. Therefore, Br values for compounds with outlying log Kow values have been

capped in line with the test data used to formulate the correlation equation. Compounds with log Kow

values less than 1.15 we assigned a Br value corresponding to a log Kow value of 1.15. At the high end of

the range, compounds with log Kow values greater than 9.35 we assigned a Br value corresponding to a

log Kow value of 9.35. We used the log Kow values listed in the HHRAP database to calculate each Br

value. 

Metals For metals, we derived Br values from uptake slope factors provided in the following document:

C U.S. EPA. 1992b. Technical Support Document for the Land Application of Sewage

Sludge. Volumes I and II. EPA 822/R-93-001a. Office of Water. Washington, DC.

Uptake slopes provided in U.S. EPA (1992b) are the ratio of contaminant concentration in dry weight

plant tissue to the mass of contaminant applied per hectare soil. These uptake slopes were multiplied by

2 x 109

 g/hectare soil to convert to Br values. The conversion factor was derived using the U.S. EPA

(1992b) assumed soil bulk density of 1.33 g/cm3

, and an incorporation depth of 15 cm. 

For other metals, we obtained Br values from Baes et al. (1984). Baes et al. (1984) described biotransfer

factors (on a dry weight basis) from plant-soil uptake for (1) vegetative growth (leaves and stems) “Bv”;

and (2) nonvegetative or reproductive growth (fruits, seeds, and tubers) “Br”. Note that Bv is defined as

the air-to-plant biotransfer factor.

We used the following methodology to derive Br values on a dry weight basis:

a. For nickel, cadmium, selenium, zinc, and arsenic, Brag (fruit) values were calculated by

multiplying the uptake slope factors with a conversion factor of 2 x109

 g/ha soil (uptake
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slope factor and the conversion factor were obtained from U.S. EPA (1992b) for garden

fruits). All other metals were obtained by selecting “Br” values for nonvegetative growth

(reproductive) provided in Baes et al. (1984). 

b. For nickel, cadmium, selenium, zinc, and arsenic, Brag (veg) values were calculated by

weighting the uptake slope factors for garden fruits (75%) and leafy vegetables (25%)

and multiplying the result with a conversion factor of 2 x109

 g/ha soil. The uptake slope

factors and the conversion factor were obtained from U.S. EPA (1992b). For other

metals, “Br” values for nonvegetative (reproductive) growth and “Bv” values for

vegetative growth—obtained from Baes et al. (1984)—were weighted as 75%

(reproductive) and 25% vegetative. The resulting values were adopted as Brag (veg) values. 

c. For nickel, cadmium, selenium, zinc, and arsenic, Brforage values were calculated by

multiplying the uptake slope factors with a conversion factor of 2x109

 g/ha soil. The

uptake slope factors and the conversion factor were obtained from U.S. EPA (1992b) for

leafy vegetables. For other metals, Brforage values were obtained from Baes et al. (1984). 

“Bv” values for vegetative growth (such as leaves and stems) in Baes et al. (1984) were

used for Brforage.

d. For nickel, cadmium, selenium, zinc, and arsenic, Brgrain values were calculated by

multiplying the uptake slope factors with a conversion factor of 2 x109

 g/ha soil. The

uptake slope factors and the conversion factor were obtained from U.S. EPA (1992b) for

grains/cereals. For other metals, Brgrain value was obtained from Baes et al. (1984). “Br”

values for nonvegetative growth as recommended by Baes et al. (1984) were used for

Brgrain.

e. Consumption rates used to obtain the weighted average Brag value for aboveground

produce are as follows: (1) Brag values for fruits combined with a human consumption

rate of fruits of 1.44E-03 kg/kg/day, and (2) Brag values for vegetables combined with a

human consumption rate of vegetables of 1.49E-03 kg/kg/day.

Mercuric Compounds We obtained Brag values for mercuric chloride and methyl mercury as described

above. We obtained Brforage values on a dry weight basis for mercuric chloride and methyl mercury from

U.S. EPA (1997b). The HHRAP methodology assumes that elemental mercury doesn’t deposit onto

soils. Therefore, it’s assumed that there’s no plant uptake through the soil. 

A2-2.12.4 Air-to-Plant BTFs for Aboveground Produce (Bvag) and Forage (Bvforage)

The air-to-plant biotransfer factor (Bv) is defined as the ratio of contaminant concentration in

aboveground plant parts to the contaminant concentration in air. We calculated Bv values only for

aboveground exposed produce (both fruits and vegetables). We assume that aboveground protected

produce (both fruits and vegetables) and belowground produce are protected from air-to-plant transfer. 

According to U.S. EPA (1995b), root vegetables are assumed to be also protected from air-to-plant

transfer.

For most compounds (excluding PCDDs and PCDFs), we calculated the air-to-plant biotransfer factor for

aboveground produce (Bvag) and forage (Bvforage) using correlation equations derived for azalea leaves in

the following documents:
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Equation A-2-19

Equation A-2-20

C Bacci E., D. Calamari, C. Gaggi, and M. Vighi. 1990. “Bioconcentration of Organic

Chemical Vapors in Plant Leaves: Experimental Measurements and Correlation.” 

Environmental Science and Technology. Volume 24. Number 6. Pages 885-889.

C Bacci E., M. Cerejeira, C. Gaggi, G. Chemello, D. Calamari, and M. Vighi. 1992. 

“Chlorinated Dioxins: Volatilization from Soils and Bioconcentration in Plant Leaves.” 

Bulletin of Environmental Contamination and Toxicology. Volume 48. Pages 401-408.

Bacci et al. (1992) developed a correlation equation using data collected for the uptake of

1,2,3,4-tetrachlorodibenzo-p-dioxin (TCDD) in azalea leaves, and data obtained from Bacci et al. (1990). 

The Bv obtained was then evaluated for 14 organic compounds to develop a correlation equation with Kow

and H. Bacci et al. (1992) derived the following equations without distinguishing between forage and

aboveground produce:

where

Bvol = Volumetric air-to-plant biotransfer factor (fresh-weight basis)

Bv = Mass-based air-to-plant biotransfer factor (dry-weight basis)

Dair = 1.19 g/L (Weast 1981)

Dforage = 770 g/L (Macrady and Maggard 1993)

fwater = 0.85 (fraction of forage that is water—Macrady and Maggard

[1993])

We calculated Bv vlaues using Equations A-2-19 and A-2-20, and the values for H and Kow listed in the

HHRAP database; based on a T of 25°C or 298.1 K. We adopted the resulting Bv values for both forage

(Bvforage) and aboveground produce (Bvag). Please note the following uncertainty associated with these

variables:

C For organics (except PCDDs and PCDFs), U.S. EPA (1993d) recommended reducing Bv

values by a factor of 10 before use. This was based on the work conducted by U.S. EPA

(1993d) for U.S. EPA (1994a) as an interim correction factor. Welsch-Pausch et al

(1995) conducted experiments to determine concentrations of PCDDs and PCDFs in air

and resulting biotransfer to welsh ray grass. This was documented in the following: 

- Welsch-Pausch, K.M. McLachlan, and G. Umlauf. 1995. “Determination of

the Principal Pathways of Polychlorinated Dibenzo-p-dioxins and

Dibenzofurans to Lolium Multiflorum (Welsh Ray Grass)”. Environmental

Science and Technology. 29: 1090-1098.
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A follow-up study based on Welsch-Pausch et al. (1995) was conducted by Lorber (1995)

(see discussion below for PCDDs and PCDFs). In a following publication, Lorber (1997)

concluded that the Bacci factor reduced by a factor of 100 was close in line with

observations made by him through various studies, including the Welsch-Pausch et al.

(1995) experiments. Therefore, we calculated Bv values using the Bacci et al. (1992)

correlation equations and then reduced by a factor of 100 for all organics, excluding

PCDDs and PCDFs.

PCDDs and PCDFs For PCDDs and PCDFs, we obtained Bv values, on a dry weight basis, from the

following:

C Lorber, M. and P. Pinsky. 1999. “An Evaluation of Three Empirical Air-to-Leaf Models

for Polychlorinated Dibenzo-p-Dioxins and Dibenzofurans”. National Center for

Environmental Assessment (NCEA). U.S. EPA. Washington D.C. Accepted for

publication in Chemosphere. 

U.S. EPA (1993d) stated that, for dioxin-like compounds, using the Bacci et al. (1992) equations may

overpredict Bv values by a factor of 40. This was because the Bacci et al. (1990) and Bacci et al. (1992)

experiments did not take photodegradation effects into account. Therefore, U.S. EPA (1993d)

recommended that Bv values calculated using Equations A-2-19 and A-2-20 be reduced by a factor of 40

for dioxin-like compounds. 

However, according to Lorber (1995), the Bacci algorithm divided by 40 may not be appropriate because 

• the physical and chemical properties of dioxin congeners are generally outside the range

of the 14 organic compounds used by Bacci (1990), and 

• the factor of 40 derived from one experiment on 2,3,7,8-TCDD may not apply to all

dioxin congeners.

Welsch-Pausch et al. (1995) conducted experiments to obtain data on uptake of PCDDs and PCDFs from

air to Lolium Multiflorum (Welsh Ray grass). The data includes grass concentrations and air

concentrations for dioxin congener groups, but not the invidual congeners. Lorber (1995) used data from

Welsch-Pausch et al.(1995) to develop an air-to-leaf transfer factor for each dioxin-congener group. Bv

values developed by Lorber (1995) were about an order of magnitude less than values calculated using

the Bacci et al. (1990) and (1992) correlation equations. Lorber (1995) speculated that this difference

could be attributed to several factors including experimental design, climate, and lipid content of plant

species used. 

We obtained the Br values for PCDDs and PCDFs listed in the HHRAP database from the experimentally

derived values of Lorber (1995). However, Lorber (1995) stated that these values should be considered

carefully by users of this methodology because of the inherent uncertainties associated with the data. 

Metals For metals, we found no literature sources for the Bv values. U.S. EPA (1995b) quoted from the

following document, that metals were assumed not to experience air to leaf transfer:

C Belcher, G.D., and C.C. Travis. 1989. “Modeling Support for the RURA and Municipal

Waste Combustion Projects: Final Report on Sensitivity and Uncertainty Analysis for

the Terrestrial Food Chain Model.” Interagency Agreement No. 1824-A020-A1. Office

of Risk Analysis, Health and Safety Research Division. Oak Ridge National Laboratory. 

Oak Ridge, Tennessee. October.
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As with the above cited references, we assumed Bv values for metals (excluding elemental mercury) are

zero.

Mercury The HHRAP assumes that mercury emissions consist of both the elemental and divalent forms. 

However, only small amounts of elemental mercury is assumed to be deposited based on its behavior in

the atmosphere. Elemental mercury either dissipates into the global cycle or is converted to the divalent

form. The HHRAP assumes methyl mercury doesn’t exist in air emissions or in the air phase. Additional

basis for the assumption regarding mercury transfer from air to plants includes 

• elemental mercury reaching or depositing onto the plant surfaces is negligible, and 

• biotransfer of methyl mercury from air is zero. 

This is based on assumptions made regarding speciation and fate and transport of mercury from

emissions. Therefore, we assume the Bv values for elemental and methyl mercury are zero. The Bv value

for mercuric chloride (dry weight basis) comes from U.S. EPA (1997b). 

If field data suggests otherwise, Bv values (1) provided in U.S. EPA (1997b) for methyl mercury can be

used, and (2) need to be determined for elemental mercury. Please note that uptake of mercury from air

into the aboveground plant tissue is primarily in the divalent form. We assume that a part of the divalent

form of mercury is converted to methyl mercury once in the plant tissue.

A2-2.13 BIOTRANSFER FACTORS FOR ANIMALS

The biotransfer factor for animals (Ba) is the ratio of contaminant concentration in fresh weight animal

tissue to the daily intake of contaminant by the animal.

A2-2.13.1 BTFs for Beef (Babeef) and Milk (Bamilk) 

The main route of human exposure to many highly lipophilic compounds is through ingestion of

contaminated agricultural products such as beef and milk (McLachlan 1993). The transfer of

contaminants from environmental media (e.g., air, soil, water) and food (e.g. grain, silage) into livestock

products (e.g., beef, milk) has historically been either determined by direct measurement of contaminants

in livestock products, or predicted using regression models. 

Organic Compounds

When empirical data are lacking for biotransfer of organc chemicals, one of the most widely used

approaches to predict contaminant transfer from environmental media and food to beef tissue and milk are

the regression models developed by Travis and Arms (1988), which relate chemical octanol-water

partition coefficient (Kow) to biotransfer into beef and milk. These regressions, however, are hampered by

the limited log Kow range and questions surrounding the validity of the underlying biotransfer data set. In

response, EPA developed a new methodology for predicting beef and milk biotransfer factors (See report

entitled: “Methodology for Predicting Cattle Biotransfer Factors” (RTI 2005) for complete documentation

of the approach).

Using EPA’s updated methodology, we predicted biotransfer factors for organic chemicals with the

following single equation: 
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Equation A-2-21

where

Bafat = Biotransfer factor ([mg /kg Fat]/[mg/day])

Kow = Octanol-water partition coefficient (unitless). 

Values for Bafat were adjusted to account for the assumed fat content of milk and beef as shown below: 

Bamilk

Ba fat = × 10 0 04 log . Equation A-2-22

Babeef

Ba fat = × 10 019 log . Equation A-2-23

The log Kow’s of the chemicals used to derive the equation ranged from -0.67 to 8.2. Therefore we used

equation A-2-21 for organic chemicals having a log Kow between -0.67 and 8.2. Compounds with

log Kow values less than -0.67 were assigned Babeef and Bamilk values corresponding to a log Kow value of -

0.67. At the high end of the range, compounds with log Kow values greater than 8.2 were assigned Babeef

and Bamilk values corresponding to a log Kow value of 8.2. We used the Kow values in the HHRAP database

to calculate Babeef and Bamilk values.

Highly Metabolized Organic Compounds

As discussed in RTI (2005), Equation A-2-21 might overestimate biotransfer of highly metabolized

chemicals, producing an upper bound estimate for these chemicals. Of those chemicals relevant to the

HHRAP (and therefore included in the HHRAP companion database), Phthalates and PAHs fall within

this group (see HHRAP Chapter 2 for more information on the phthalate and PAH chemical categories). 

One way to account for this potential overestimation is to rely upon a metabolism factor to improve

model predictions. For example, EPA developed a metabolism factor of 0.01 (i.e., 99% of the chemical

ingested is metabolized) for bis-ethylhexyl phthalate (BEHP, See Chapter 2). When this factor is applied

to the biotransfer factors predicted using the regression equation recommended above for BEHP, the

biotransfer factors are reduced by two orders of magnitude. These metabolism-adjusted predicted

biotransfer factors are close in magnitude to the empirically derived biotransfer factors found in the

literature, which supports using this metabolism factor. Unfortunately, EPA has not developed

metabolism factors for other organic chemicals, due to limited availability of empirically derived data (see

Chapter 2).

For those highly metabolized chemicals that don’t have metabolism factors, we still consider it reasonable

to use estimated Ba values for the following reasons:

• Few chemicals have had all their degradation products identified; 

• If identified, the degradation products may in fact be as toxic as, or even more toxic than,

the parent compound (the degradation products of PAHs, for example, are toxic). Unless

data demonstrates that all degradation products are nontoxic (as is the case for BEHP),

the only way to address toxic degradation products in the HHRAP is to include their mass

in the mass of the parent chemical; and
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• the metabolic degradation products may themselves be persistent. For example, DDT is

metabolized to DDD and DDE, which remain persistent.

It should also be noted that not all chemicals are metabolized at the same rate and may remain in animal

tissue as the parent compound through establishment of steady state concentrations. In fact, many of the

chemicals in the biotransfer data set that are well predicted by Equation A-2-21 are metabolized to other

compounds. DDT is metabolized to DDE, and lindane (used to derive the regression, but not in the

HHRAP) is metabolized to many different compounds. For DDT and lindane, biotransfer factors are well

predicted using Equation A-2-21. Thus, just because a chemical undergoes biotransformation to other

compounds, doesn’t necessarily mean Equation A-2-21over-estimates its biotransfer.

Lacking sufficient data to identify all degradation products, characterize all degradation products as

nontoxic, and ensure that all potentially toxic degradation products are less persistent than the parent

chemical, we consider it reasonably protective to use the Babeef and Bamilk values for the parent chemical as

predicted, without adjustment. If a highly metabolized chemical is found to drive the risk assessment,

then we recommend re-evaluating the appropriateness of the Babeef and Bamilk values.

Ionizing Organic Compounds

To improve BTF estimates for organic acids, we used the first-order dissociation constant (pKa) to

account for chemical ionization. For these chemicals, Kow is a weighted value calculated based on the

fraction of the chemical in the neutral form such that:

K K n FracNeutral K i FracNeutral ow ow ow = × ( )( ) + × 1− Equation A-2-24

where

Kown = partition coefficient for the neutral species (unitless),

Kowi = partition coefficient for the ionized species (mol/L),

FracNeutral = fraction of neutral species present for organic acids (unitless).

Accounting for the fraction of ionizable organics in the neutral form is important because Kow can vary

considerably depending on pH. The cow’s small intestine, where chemicals can be absorbed, has a near

neutral pH (Umphrey and Staples, 1992). Thus, the neutral fraction is determined using a pH equal to 7 in

the following equation (Lee et al., 1990):

[ ]

[ ][ ] FracNeutral ( ) HA

HA A = pH pKa − − =+ − 1 10 Equation A-2-25

where

[HA] = equilibrium concentration of organic acid (mol/L),

[A-] = equilibrium concentration of anion (mol/L), and

pKa = acid dissociation constant (unitless).

If a value for log Kowi wasn’t available, we estimated log Kowi assuming a ratio of log Kowi to log Kown of

0.015. This ratio is a conservative value developed by EPA to apply to organic acids without data for log

Kowi (U.S. EPA, 1996). 
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Metals

We obtained Babeef and Bamilk values for metals (except cadmium, mercury, selenium, and zinc), on a fresh

weight basis, from Baes et al. (1984). For cadmium, selenium, and zinc, U.S. EPA (1995a) cited Ba

values derived by dividing uptake slopes [(g COPC/kg DW tissue)/(g COPC/kg DW feed)], obtained

from U.S. EPA (1992b), by a daily consumption rate of 20 kg DW per day for beef and dairy cattle.

We obtained our recommended values from Baes et al. (1984) for all metals except cadmium, selenium,

and zinc. We calculated Ba values for cadmium, selenium, and zinc using uptake slope factors and

consumption rates provided in U.S. EPA (1992b) and U.S. EPA (1995a), converting the result to a fresh

weight basis by assuming a moisture content of 87 percent in milk and 70 percent in beef. Moisture

content in beef and milk were obtained from the following:

C U.S. EPA. 1997c. Exposure Factors Handbook. “Food Ingestion Factors”. Volume II. 

EPA/600/P-95/002Fb. August.

C Pennington, J.A.T. 1994. Food Value of Portions Commonly Used. Sixteenth Edition. 

J.B. Lippincott Company, Philadelphia. 

We provide the calculated fresh weight Babeef and Bamilk values in the HHRAP database.

Mercuric Compounds

The HHRAP assumes that elemental mercury neither deposits onto soils nor transfers to aboveground

plant parts. Therefore, there’s no transfer of elemental mercury into animal tissue. Therefore, we

recommend Ba values of zero for elemental mercury. This based on assumptions made regarding

speciation and fate and transport of mercury from emission sources.

If field data suggests otherwise, Babeef and Bamilk values for elemental mercury can be derived from the

uptake slope factors provided in U.S. EPA (1992b) and U.S. EPA (1995a); using the same consumption

rates discussed earlier for metals like cadmium, selenium, and zinc.

We derived the Babeef and Bamilk values listed in the HHRAP database for mercuric chloride and methyl

mercury from data in U.S. EPA (1997b). U.S. EPA (1997b) provided Babeef and Bamilk values for mercury,

but did not specify for which form of mercury. As in U.S. EPA (1997b), we assume mercury speciates

into 87 percent divalent mercury and 13 percent methyl mercury in herbivore animal tissue. Also,

assuming that the Babeef and Bamilk values provided in U.S. EPA (1997b) were for total mercury in animal

tissue, the biotransfer factors in U.S. EPA (1997b) can be apportioned in the fractions assumed to be

found in animal tissue. Therefore, we based the values reported in the HHRAP database on the

following: 

C We converted the default Bamilk value of 0.02 day/kg DW for mercury to a fresh weight

basis assuming a 87 percent moisture content in milk (U.S. EPA 1997c; and

Pennington 1994). We multiplied the resulting Bamilk (fresh weight) value by (1) 0.13 to

obtain a value for methyl mercury, and (2) 0.87 to obtain a value for mercuric chloride

(divalent mercury).

C We converted the default Babeef value of 0.02 day/kg DW for mercury to a fresh weight

basis assuming a 70 percent moisture content in beef (U.S. EPA 1997c; and

Pennington 1994). We multiplied the resulting Babeef (fresh weight) value by (1) 0.13 to

obtain a value for methyl mercury, and (2) 0.87 to obtain a value for mercuric chloride

(divalent mercury). 
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A2-2.13.2 Biotransfer Factors for Pork (Bapork)

For most compounds we derived Bapork values using the same method used to estimate Babeef values (see

Section A2-2.13.1 above for a detailed description of the method & its limitations), modifying to reflect

an assumed fat content of pork of 23%. Specifically, we used equation A-2-21 to generate Bafat values,

which were then adjusted to account for the assumed fat content of pork as shown below: 

Bapork

Ba fat = × 10 0 23 log . Equation A-2-26

The log Kow’s of the chemicals used to derive the equation ranged from -0.67 to 8.2. Therefore we used

equation A-2-21 for organic chemicals having a log Kow between -0.67 and 8.2. Compounds with

log Kow values less than -0.67 were assigned Bapork values corresponding to a log Kow value of -0.67. At

the high end of the range, compounds with log Kow values greater than 8.2 were assigned Bapork values

corresponding to a log Kow value of 8.2. We used the Kow values in the HHRAP database to calculate

Bapork values.

This calculation is limited by the assumptions that:

• contaminants bioconcentrate in the fat tissues; and

• effects from differences in metabolism, digestive system, and feeding characteristics

between beef cattle and pigs are minimal.

Metals For metals (except cadmium, selenium, and zinc), no data was available in the literature to

calculate Bapork values. 

For cadmium, selenium, and zinc, U.S. EPA (1995b) reported Ba values derived by dividing uptake

slopes [(g COPC/kg DW tissue)/(g COPC/kg DW feed)], obtained from U.S. EPA (1992b), by a daily

consumption rate of 4.7 kg DW per day for pigs provided in U.S. EPA (1995a). The dry weight Bapork

values (for cadmium, selenium, and zinc) were converted to a fresh weight basis assuming a moisture

content of 70 percent in pork (U.S. EPA 1997c; and Pennington 1994). 

Mercuric Compounds The HHRAP assumes that elemental mercury neither deposits onto soils nor

transfers to the aboveground plant parts; therefore, there’s no transfer of elemental mercury into the

animal tissue. Therefore, we recommend Ba values of zero for elemental mercury. This is based on the

assumptions made regarding speciation and fate and transport of mercury from emissions.

If field data suggests otherwise, Bapork values for elemental mercury can be derived from the uptake slope

factors provided in U.S. EPA (1992b) and U.S. EPA (1995a), using the same consumption rates discussed

earlier for metals like cadmium, selenium, and zinc. 

We derived Bapork values for mercuric chloride and methyl mercury from data in U.S. EPA (1997b). U.S.

EPA (1997b) provided Bapork values for mercury, but did not specify for which form of mercury. As in

U.S. EPA (1997b), the HHRAP assumes that mercury speciates into 87 percent divalent mercury and

13 percent methyl mercury in herbivore animal tissue. Also, assuming that the Bapork values provided in

U.S. EPA (1997b) were for total mercury in animal tissue, biotransfer factors in U.S. EPA (1997b) can be

apportioned in the fractions it is assumed to be found in animal tissue. 

Therefore, we converted the U.S. EPA (1997b) Bapork value of 0.00013 day/kg DW for mercury to a fresh

weight basis assuming a 70 percent moisture content in pork (U.S. EPA 1997c; and Pennington 1994). 
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Bachicken

Ba fat = × 10 014 log . Equation A-2-27

Baegg

Ba fat = × 10 0 08 log . Equation A-2-28

We multiplied the resulting Bapork (fresh weight) value by (1) 0.13 to obtain a value for methyl mercury,

and (2) 0.87 to obtain a value for mercuric chloride (divalent mercury). 

A2-2.13.3 BTFs for Chicken (Bachicken) and Poultry Eggs (Baegg)

Biotransfer factors for chicken (Bachicken) and poultry eggs (Baegg) are expressed as the ratio of the

contaminant concentration in the fresh weight tissue to the contaminant intake from the feed. Biotransfer

factors are calculated from bioconcentration factors for chicken and poultry eggs. BCFs are expressed as

the ratio of the contaminant concentration in the fresh weight tissue to the contaminant concentration in

dry weight soil. 

For most compounds we derived Bapork values using the same method used to estimate Babeef values (see

Section A2-2.13.1 above for a detailed description of the method & its limitations), modifying to reflect

an assumed fat content of chicken of 14%, and eggs of 8%. Specifically, we used equation A-2-21 to

generate Bafat values, which were then adjusted to account for the assumed fat content of chicken and

eggs as shown below: 

The log Kow’s of the chemicals used to derive the equations ranged from -0.67 to 8.2. Therefore we used

equation A-2-21 for organic chemicals having a log Kow between -0.67 and 8.2. Compounds with

log Kow values less than -0.67 were assigned Bachicken and Baegg values corresponding to a log Kow value of -

0.67. At the high end of the range, compounds with log Kow values greater than 8.2 were assigned

Bachicken and Baegg values corresponding to a log Kow value of 8.2. We used the logKow values in the

HHRAP database to calculate Bachicken and Baegg values.

These calculations are limited by the assumptions that:

• contaminants bioconcentrate in the fat tissues; and 

• effects from differences in metabolism, digestive system, or feeding characteristics

between beef cattle and chickens are minimal. 

Please note that the scenario of principal concern for chicken and egg contamination is for home grown

chickens. The raising of home grown chickens would be characteristic of free range and semi-free range

housing conditions where poultry do come in contact with soil, and possibly vegetation, insects, and

benthic organisms. The applicability of this scenario to commercial poultry operations characterized by

housing conditions that do not provide chickens access to soil would need to be assessed on a

case-by-case basis.

Metals Bachicken and Baegg values for all metals except cadmium, selenium, and zinc, weren’t available in

the literature. For cadmium, selenium, and zinc, U.S. EPA (1995a) cited Ba values that were derived by

dividing uptake slopes [(g COPC/kg DW tissue)/(g COPC/kg DW feed)], obtained from U.S. EPA

(1992b), by a daily consumption rate of 0.2 kilograms DW per day by chicken. To obtain values listed in

the HHRAP database, we converted the dry weight Ba value to a fresh weight value by assuming a

moisture content of 75 percent in eggs and chicken (U.S. EPA 1997c; and Pennington 1994).
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Mercury The HHRAP assumes that elemental mercury neither deposits onto soils nor transfers to the

aboveground plant parts or grains. Therefore, there’s no transfer of elemental mercury into animal tissue. 

Therefore, we recommend Ba values of zero for elemental mercury. This is based on the assumptions

made regarding speciation and fate and transport of mercury from emission sources. 

If field data suggests otherwise, Bachicken and Baegg values for elemental mercury can be derived from the

uptake slope factors provided in U.S. EPA (1992b) and U.S. EPA (1995a), using the same consumption

rates discussed earlier for metals like cadmium, selenium, and zinc. 

We derived Bachicken and Baegg values for mercuric chloride and methyl mercury from data in U.S. EPA

(1997b). U.S. EPA (1997b) provided Bachicken and Baegg values for mercury, but did not specify for which

form of mercury. As in U.S. EPA (1997b), the HHRAP assumes mercury speciates into 87 percent

divalent mercury and 13 percent methyl mercury in herbivore animal tissue. Also, assuming that the

Bachicken and Baegg values provided in U.S. EPA (1997b) were for total mercury in animal tissue, then

biotransfer factors in U.S. EPA (1997b) can be apportioned in the fractions it is assumed to be found in

animal tissue. 

Therefore, we based the values reported in the HHRAP database on the following: 

C We converted the U.S. EPA (1997b) Bachicken value of 0.11 day/kg DW for mercury to a

fresh weight basis assuming a 75 percent moisture content in chicken (U.S. EPA 1997c;

and Pennington 1994). We multiplied the resulting Bachicken (fresh weight) value by

(1) 0.13 to obtain a value for methyl mercury, and (2) 0.87 to obtain a value for mercuric

chloride (divalent mercury). 

C We converted the U.S. EPA (1997b) Baegg value of 0.11 day/kg DW for mercury to a

fresh weight basis assuming a 75 percent moisture content in eggs (U.S. EPA 1997c; and

Pennington 1994). We multiplied the resulting Baegg (fresh weight) value by (1) 0.13 to

obtain a value for methyl mercury, and (2) 0.87 to obtain a value for mercuric chloride

(divalent mercury).

A2-2.13.4 Bioconcentration and Bioaccumulation Factors for Fish

Bioconcentration and bioaccumulation factors for fish are used for various compounds, depending on the

Kow value of the compound. We recommend using bioconcentration factors for fish (BCFfish) for

compounds (except PCDDs, PCDFs, and PCBs) with a log Kow value less than 4.0; and for metals (except

lead and mercury). We recommend using bioaccumulation factors for fish (BAFfish) for compounds

(except PCDDs, PCDFs, and PCBs) with a log Kow value greater than 4.0, lead, and mercuric compounds.

We recommend also using biota-sediment accumulation factors for fish (BSAFfish) for PCDDs, PCDFs,

and PCBs.

A2-2.13.4.1 Bioconcentration Factors for Fish (BCFfish)

BCFfish is the ratio of the contaminant concentration in fish to the contaminant concentration in the water

column where the fish is exposed. It accounts for uptake of contaminants by fish from water passing

across the gills. We derived BCF values for fish for all organic compounds with a log Kow of less than 4.0

(cutoff value with BAFfish) and for all metals, except lead and mercury, as cited in U.S. EPA (1995b). 

This implies that the concentration of contaminant in the fish is only due to water intake by the fish, and

compounds with a log Kow of less than 4.0 are assumed not to significantly bioaccumulate. 
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Equation A-2-27

Equation A-2-28

Equation A-2-29

Equation A-2-30

It is generally assumed that field measured BCFs are based on total (dissolved and suspended) water

column concentrations, and laboratory measured BCFs are based on dissolved water column

concentrations. This distinction is important for compounds with a log Kow of greater than or equal to 4.0,

because significant amounts of a contaminant can partition into the suspended sediment organic carbon

(or particulate phase) of the water column. For compounds with a log Kow of less than 4.0, most of the

contaminant is associated with the dissolved phase of the water column and negligible amounts of the

contaminant is associated with the suspended sediment phase in the water column. Therefore, for

compounds with a log Kow of less than 4.0, BCF values based on dissolved contaminant water

concentrations in the water column are essentially the same as BCF values based on total (dissolved +

suspended) contaminant water concentrations in the water column. 

Our recommended BCF values don’t recognize differences in total versus dissolved water concentrations

when calculating fish concentrations from BCFfish values for compounds with a log Kow of less than 4.0. 

Since, dissolved water concentrations is the major contributing factor from compounds with a log Kow of

less than 4.0, all BCFfish values (regardless of whether they were derived using total or dissolved water

concentrations) can be multiplied by the contaminant concentration in the dissolved water column (Cdw) to

calculate fish concentrations. This assumption is necessary because (1) literature data is often unclear if

the water concentrations are dissolved or total concentrations, and (2) most of the literature reviewed

indicated that laboratory experiments were conducted using filtered or distilled water; or the experiments

were conducted using fresh water, but were filtered before analyses for water concentrations.

For most compounds, we calculated BCF values using best fit log Kow correlation equations derived by

Meylan et al. (1999):

C Meylan, W., P.H. Howard, R.S. Boethling, D. Aronson, H. Printup, and S. Gouchie. 

1999. “Improved Method for Estimating Bioconcentration/Bioaccumulation Factor from

Octanol/Water Partition Coefficient”. Environmental Toxicology and Chemistry. 

18(4):664-672.

Meylan et al. (1999) collected information on measured BCF and other key experimental details for 694

chemicals. Log BCF was then regressed against log Kow , and chemicals with significant deviations from

the line of best fit were analyzed by chemical structure. The resulting algorithm classifies a substance as

either nonionic or ionic, the latter group including carboxylic acids, sulfonic acids and their salts, and

quaternary N compounds. Log BCF for nonionics was estimated from log Kow and a series of correction

factors if applicable; different equations apply for log Kow 1.0 to 7.0 and >7.0 (Meylan et al. 1999). These

equations are as follows:

For log Kow < 1 :

For log Kow 1 to 7:

For log Kow > 7:

For log Kow

>10.5:
Human Health Risk Assessment Protocol

Appendix A-2 September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering A-2-30

Equation A-2-31

Equation A-2-32

Equation A-2-33

Equation A-2-34

Equation A-2-35

For ionic compounds (carboxylic acids, sulfonic acids and salts, compounds with N of +5 valence), were

categorized by log Kow, and a log BCF in the range 0.5 to 1.75 was assigned as follows:

For log Kow < 5 :

For log Kow 5 to 6:

For log Kow 6 to 7:

For log Kow 7 to 9:

For log Kow > 9:

We assume that BCFfish values calculated using the above correlation equations were (1) based on

dissolved water concentrations, and (2) not lipid-normalized.

Metals We obtained measured BCFfish values for metals (except lead and mercury) from various literature

studies, as cited in U.S. EPA (1999a). Values not available in U.S. EPA (1999a) we estimated using the

correlation equations above. BCFfish values obtained from U.S. EPA (1999a) were characterized as

follows:

C Field-measured or laboratory-measured values from various experimental studies were

evaluated by U.S. EPA (1999a). This information is summarized in the following

document: 

U.S. EPA. 1999a. Screening Level Ecological Risk Assessment Protocol for

Hazardous Waste Combustion Facilities. Peer Review Draft. August.

Field-measured data is only (1) available for a limited number of compounds, and

(2) based on a single study. In such cases, the field-measured value or the geometric

mean of field-measured values were compared with the geometric mean of

laboratory-measured values, and the higher one used. A detailed discussion on sources of

BCF values and methodology followed were provided in Appendix C of U.S. EPA

(1999a). 

Measured values from various experimental studies were evaluated by U.S. EPA (1999a). Detailed

discussion and sources of measured values were provided in U.S. EPA (1999a). For lead and some

mercury compounds, a BAF was determined to be more applicable than a BCF, since those compounds

tends to bioaccumulate. 

Mercury As in U.S. EPA (1997b), elemental mercury isn’t expected to deposit significantly onto soils

and surface water. Therefore, it’s assumed that there is no transfer of elemental mercury into fish. Fish

are assumed to be exposed only to the divalent and organic forms of mercury that exist in the water and

soil/sediment media. However, as with the conservative approach adopted by previous guidance

documents, all of mercury in the fish is assumed to exist or be converted to the methyl mercury (organic)

form after uptake into the fish tissue. Therefore, BCF and BAF values are not considered applicable for
Human Health Risk Assessment Protocol

Appendix A-2 September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering A-2-31

Equation A-2-36

divalent mercury (mercuric chloride). For methyl mercury, a BAF was determined to be more applicable

than a BCF, since mercury tends to bioaccumulate.

A2-2.13.4.2 Bioaccumulation Factors for Fish (BAFfish)

BAFfish is the ratio of the contaminant concentration in fish to the contaminant concentration in the water

body where the fish are exposed. The BAFfish accounts for uptake of contaminants by fish from water and

sediments passing across the gills, and from consumption of various foods including plankton, daphnids,

and other fish.

For compounds with a log Kow of greater than or equal to 4.0, contaminants can significantly partition into

the suspended sediment organic carbon (or particulate phase) of the water column. Therefore, BAF

values should generally be based on total (dissolved and suspended) water column concentrations. BAF

values for fish reported in the HHRAP database were used for organic compounds (except PCBs, PCDDs,

and PCDFs) with a log Kow greater than 4.0, lead and some mercuric compounds. 

In general we assumed that:

• Field-measured BAFs were based on total (dissolved and suspended) water column

concentrations;

• Laboratory-measured BCFs, and therefore the BAFs predicted from them, were based on

dissolved water column concentrations; and 

• BCFs estimated using correlation Equations A-2-24 through A-2-32, and therefore the

BAFs predicted from them, were based on dissolved water column concentrations. 

In addition, we assumed that field-measured BCFs for compounds with a log Kow greater than 4.0 were

equal to BAFs, because the tissue concentrations are a result of uptake of water (dissolved and

suspended), sediment, and various trophic level food.

For most organic compounds (except PCBs, PCDDs and PCDFs) with a log Kow greater than 4.0, the

FCM, which accounts for accumulation through the food chain in addition to water, becomes greater than

1. Therefore, a BAFfish, which takes the food chain into consideration, is more appropriate than a BCFfish

(U.S. EPA 1995c; 1998). As in U.S. EPA (1995c; 1998), we assumed that BAF values for inorganic

chemicals equal BCFs (i.e., the FCM is 1.0), unless chemical specific biomagnification data support using

a FCM other than 1.0.

For consistency, we adjusted all field-measured BAF (or BCF) values using the methodology suggested

in U.S. EPA (1998), to include only the dissolved water column fractions; (i.e., the BAFs based on total

water concentrations were converted to BAFs based on dissolved water concentrations). This was done

so that all BAFfish values (based on dissolved water concentrations) can be multiplied by the contaminant

concentration in the dissolved water column (Cdw) to calculate fish concentrations. 

We used the following equation cited in U.S. EPA (1998) to convert the BAF based on total water

concentrations to a BAF based on dissolved water concentrations:
Human Health Risk Assessment Protocol

Appendix A-2 September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering A-2-32

Equation A-2-37

where

f fd = fraction of COPC that is freely dissolved in water

DOC = concentration of dissolved organic carbon, kg organic carbon / L water

POC = concentration of particulate organic carbon, kg organic carbon / L water

Since, the Gobas (1993) model was derived from a study conducted at Lake Ontario, DOC and POC

values for Lake Ontario were used. Values cited in U.S. EPA (1998) were: 

DOC = 2 x 10-6 kg/L

POC = 7.5 x 10-9 kg/L

A BAF based on dissolved water concentrations can be calculated from a BAF based on total water

concentrations as follows:

Metals (lead) For lead, the food-chain multiplier becomes greater than 1; therefore, a BAF is more

appropriate. We obtained the BAFfish value reported in the HHRAP database for lead as a geometric mean

from various literature sources described in U.S. EPA (1999a). Since we recommend assuming that

metals are insoluble under neutral conditions, the dissolved and total water concentrations are almost

equal. However, for consistency, we adjusted the BAFfish value for lead for dissolved fractions.

Mercuric Compounds As in U.S. EPA (1997b), we don’t expect elemental mercury to deposit

significantly onto soils and surface water. Therefore, there it is assumed that there is no transfer of

elemental mercury into fish. Fish are assumed to be exposed only to the divalent and organic forms of

mercury that exists in the water and soil/sediment media. However, consistent with the conservative

approach adopted by previous guidance documents, all of mercury in the fish is assumed to exist or be

converted to the methyl mercury (organic) form after uptake into the fish tissue. Therefore, we obtained

the BAFfish value for methyl mercury from U.S. EPA (1997b) for a trophic level 4 fish.

A2-2.13.4.3 Biota-Sediment Accumulation Factor for Fish (BSAFfish)

PCDDs, PCDFs, and PCBs BSAFfish accounts for the transfer of contaminants from the bottom sediment

to the lipid in fish. U.S. EPA (2000) and (1993d) recommended using BSAFfish values for dioxin-like

compounds, including PCBs, because of their lipophilic nature. U.S. EPA (1995b) also stated that

BSAFfish values (1) were used for 2,3,7,8-TCDD and PCBs to estimate protective sediment concentrations

instead of surface water concentrations, and (2) were a more reliable measure of bioaccumulation

potential because of the analytical difficulties in measuring dissolved concentrations in surface water. 

Therefore, for PCDDs, PCDFs, and PCBs, The HHRAP database includes BSAFfish values instead of

BAFs for fish. We obtained the BSAFfish values from U.S. EPA (2000). 

U.S. EPA (2000) provided exposure scenarios for conducting site-specific assessments to dioxin-like

compounds. For each scenario, U.S. EPA (2000) recommended the use of the following BSAFfish values

based on the amount of chlorination of the PCDD or PCDF:

C For TetraCDDs and TetraCDFs, BSAFfish = 9.0 x 10-02

C For PentaCDDs and PentaCDFs, BSAFfish = 9.0 x 10-02
Human Health Risk Assessment Protocol

Appendix A-2 September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering A-2-33

C For HexaCDDs and HexaCDFs, BSAFfish = 4.0 x 10-02

C For HeptaCDDs and HeptaCDFs, BSAFfish = 5.0 x 10-03

C For OctaCDDs and OctaCDFs, BSAFfish = 1.0 x 10-04

Homologue group BSAFfish values obtained from U.S. EPA (2000) were either measured or estimated

values that were based on a whole fish lipid content of 7 percent and an organic carbon content of

3 percent. 

A2-3 TOXICITY BENCHMARKS

The following sections discuss carcinogenic and noncarcinogenic toxicity benchmarks of compounds. 

The toxicity information provided in the HHRAP is for informational purposes to help permitting

authorities explain the basis for selecting contaminants of concern. Since toxicity benchmarks and slope

factors may change as additional toxicity research is conducted, we highly recommend consulting with

the most current versions of the sources listed below before completing a risk assessment, to ensure that

the toxicity data used in the risk assessment is based upon the most current Agency consensus.

A2-3.1 Prioritization of Data Sources for Chronic Toxicity Benchmarks

In December 2003, the Office of Superfund Remediation and Technology Innovation distributed OSWER

Directive 9285.7-53, (U.S. EPA 2004a) updating the hierachy of sources of human health toxicity values

originally distributed in Risk Assessment Guidance for Superfund Volume I, Part A, Human Health

Evaluation Manual (RAGS) (U.S. EPA 1989). We recommend using the same heirarchy of sources for

acquiring human health toxicity data to be used in performing risk assessments of hazardous waste

combustion facilities. 

We gathered the following parameter values for the database:

• Chronic Oral Toxicity Benchmarks:

S Oral Reference Doses (RfDs) for effects other than cancer (non-cancer)

S Oral Cancer Slope Factors (CSFs) for cancer

• Chronic Inhalation Toxicity Benchmarks:

S Inhalation Reference Concentrations (RfCs) for effects other than cancer

(non-cancer)

S Unit Risk Factors (URFs) for cancer 

As with other Agency applications (i.e., U.S. EPA Superfund, Resource Conservation and Recovery

Act [RCRA] , and Air Toxics), toxicity benchmarks available in the U.S. EPA Integrated Risk

Information System (IRIS) (U.S. EPA 2005) were given first priority. For contaminants lacking current

IRIS assessments, we obtained toxicity benchmark values from one of the following data sources:

• Provisional Peer-Reviewed Toxicity Values (PPRTVs)

• Other Peer Reviewed Values:
Human Health Risk Assessment Protocol

Appendix A-2 September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering A-2-34

S California Environmental Protection Agency (CalEPA) chronic Reference

Exposure Levels (RELs) and Unit Risk Estimate (UREs)

S U.S. Agency for Toxic Substances and Disease Registry (ATSDR) chronic

Minimum Risk Levels (MRLs)

S U.S. EPA. 1997a. Health Effects Assessment Summary Tables (HEAST) and

older health effects assessment documents not incorporated into HEAST - U.S.

EPA Office of Research and Development (ORD)-National Center for

Environmental Assessment (EPA-NCEA)

Dose-response assessments that have achieved full intra-agency consensus are incorporated in IRIS,

which is regularly updated and available on-line (U.S. EPA 2005). As of 1996, benchmark values placed

on IRIS have undergone external peer review and Agency consensus review. Both the U.S. EPA

Superfund and RCRA programs accept the primacy of human health toxicity values contained in U.S.

EPA's IRIS. The primacy of IRIS toxicity values is also identified in Risk Assessment Guidance for

Superfund (RAGS) hierarchy (U.S. EPA 1989).

A Provisional Peer-Reviewed Toxicity Value (PPRTV) is a toxicity value derived for use in the U.S. EPA

Superfund Program when such value is not available in U.S. EPA's IRIS (PPRTVs currently represent the

second tier of human health toxicity values for the U.S. EPA Superfund and RCRA hazardous waste

programs). PPRTVs are derived after a review of the relevant scientific literature using the methods,

sources of data, and guidance for value derivation used by the U.S. EPA IRIS Program. All provisional

toxicity values receive internal review by two EPA scientists and external peer review by at least two

scientific experts. A third scientific review is performed if there is a conflict between the two original

external reviewers. PPRTVs differ in part from IRIS values in that PPRTVs do not receive the multiprogram consensus review provided for IRIS values. This is because IRIS values are generally intended

to be used in all U.S. EPA programs, while PPRTVs are developed specifically for the Superfund

Program. In general, the need for a PPRTV is eliminated once an analogous IRIS value becomes

available. Once IRIS values become available, PPRTVs are generally removed from the PPRTV

database. 

U.S. EPA ORD is concerned that PPRTV’s may be seen (and used) as equivalent to IRIS values, and has

restricted direct access to the PPRTV values database to only EPA employees. EPA employees can

access the PPRTV database directly via the EPA intranet web site. All others wishing to gain access to

PPRTV values need to register as approved users.

If you are on an approved or registered user list, and contact the EPA Center which derives PPRTVs they

would email PPRTV assessments you request to you. Plus, if you are on this list, they would periodically

email you a list of what contaminants are in the PPRTV database. If you think that you would like to be

on this list, please contact a risk assessor or toxicologist in an EPA Superfund or hazardous waste

program in the EPA Regional Office containing sites you are working on or expect to work on. You may

also apply to be put on the list by sending an email, with “PPRTV Approved User Application” in the

subject line, to HHRAPFeedback@EPA.GOV. Please include the following information in the body of

the email:

• Your name

• Your affiliation (e.g. company or regulatory agency you work for, or civic/public

organization, or other entity interested in a risk assessment using PPRTVs)

• Email address (if it’s different than the address form which you send the application)
Human Health Risk Assessment Protocol

Appendix A-2 September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering A-2-35

As described on the U.S. EPA ORD Air Toxics web site (http://www.epa.gov/ttn/atw), the California

Environmental Protection Agency (CalEPA) Office of Environmental Health Hazard Assessment 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 U.S.

EPA to develop IRIS values and incorporates significant external scientific peer review. The non-cancer

information includes available inhalation health risk guidance values expressed as chronic inhalation and

oral 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 U.S. EPA's non-cancer

dose-response assessment perspective. The HHRAP database shows the chronic REL when no IRIS

RfC/RfD or PPRTV exists.

CalEPA's quantitative dose-response information on carcinogenicity by inhalation exposure is expressed

in terms of the URE, defined similarly to EPA's URE. The HHRAP database shows specific CalEPA

UREs where no IRIS or PPRTV values exist. CalEPA's dose response assessments for carcinogens and

noncarcinogens are available on-line. 

As with U.S. EPA ORD Air Toxics, ATSDR chronic MRL values were listed in the HHRAP database for

assessing noncancer effects. As described on the U.S. EPA ORD Air Toxics web site

(http://www.epa.gov/ttn/atw), U.S. Agency for Toxic Substances and Disease Registry (ATSDR)

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 can be derived for

chronic exposures by the 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 1 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. ATSDR publishes MRLs as part of pollutant-specific toxicological profile documents,

and also in a regularly updated on-line table. 

Health Effects Assessment Summary Tables (HEAST) (U.S. EPA. 1997a) consist of dose-response

assessments for some substances that were prepared by the EPA Office of Research and Development

(ORD), but not submitted for internal U.S. EPA consensus. For some substances, older health effects

assessment documents omitted from HEAST also exist and are generally cited in Table A-1 as ORDNational Center for Environmental Assessment (EPA-NCEA) values. In 1989 and for several years

thereafter, HEAST was updated on a quarterly basis. HEAST is no longer updated with new values, but

existing values are deleted as revised values become available on IRIS.

A2-3.2 Explanation of Calculated Toxicity Benchmark Values

In the assessment of risk from contaminants, EPA-derived or reviewed toxicity benchmarks values are

recommended. However, for numerous compounds, a complete set of inhalation and oral EPA-derived

toxicity benchmarks are not available. In such cases, toxicity benchmark values were calculated based on

available EPA-derived benchmarks values. For instance, if the oral RfD (mg/kg/day) was available and

the inhalation RfC (mg/m3

) was not; the RfC was calculated by dividing the RfD by an average human

inhalation rate of 20 m3

/day and multiplying by the average human body weight of 70 kg. This

conversion is based on a route-to-route extrapolation, which assumes that the toxicity of the given

chemical is equivalent over all routes of exposure. 
Human Health Risk Assessment Protocol

Appendix A-2 September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering A-2-36

Equation A-2-38

Equation A-2-39

Although conversion based on a route-to-route extrapolation of oral dose-response or inhalation

information is not optimal risk assessment practice, the alternative would be to omit these substances

altogether from any quantitative risk estimate, and thereby, providing a de facto false negative result of

potential risk for the considered route or pathway. Therefore, using route-to-route extrapolation of oral

dose-response or inhalation information when applying the HHRAP is preferable when no toxicological

benchmark value is available in the peer reviewed data sources listed. However, assumptions and

uncertainties involved when using toxicity benchmarks calculated based on route-to-route extrapolation

should limit their use to screening-level or priority type risk assessments.

The following methodology was used to calculate missing toxicity benchmark values using available

benchmarks that are based on route-to-route extrapolation:

1) Oral RfDs presented in the peer reviewed sources cited above were used if available.

Missing Oral RfDs were calculated from the RfC assuming route-to-route extrapolation

using the following equation:

RfCs presented in the peer reviewed sources cited above were used when available. If

RfCs were not available they were calculated from the RfD assuming route-to-route

extrapolation and using the inverse of the equation above.

2) For Inhalation URFs, values were obtained from the peer reviewed sources cited above. 

If the Inhalation URFs were not available they were calculated from Oral CSF, using the

following equation:

Oral CSFs presented in the peer reviewed sources cited above were used when available. 

Missing Oral CSFs were calculated from Inhalation URF values assuming route-to-route

extrapolation and using the inverse of the equation above.

A2-3.3 Uncertainties Involved when using Toxicity Benchmarks Calculated based on

Route-to-Route Extrapolation 

The conversion based on a route-to-route extrapolation, which assumes that the toxicity of the given

chemical is equivalent over all routes of exposure, does introduce uncertainty into the assessment. By

using this method, it is assumed that the qualitative data supporting the benchmark value for a certain

route also applies to the route in question. For example, if an RfD is available and the RfC is calculated

from that value, the assumption is made that the toxicity seen following oral exposure will be equivalent

to toxicity following inhalation exposure. This assumption could overestimate or underestimate the

toxicity of the given chemical following inhalation exposure. 
Human Health Risk Assessment Protocol

Appendix A-2 September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering A-2-37

Additional information regarding what to consider in the evaluation of route-to-route

extrapolations can be found in the U.S. EPA (1994c) document Methods for Derivation of Inhalation

Reference Concentrations and Application of Inhalation Dosimetry.

A2-3.4 Prioritization of Data Sources for Acute Toxicity Benchmarks

Acute inhalation exposure guidelines and criteria are (1) designed to protect a variety of exposure groups

including occupational workers, military personnel, and the general public, (2) based on varying

exposure durations up to 24 hours in length, and (3) intended to protect against a variety of toxicity

endpoints ranging from discomfort or mild adverse health effects to serious, debilitating, and potentially

life-threatening effects, up to and including death. 

Because of the daily operations of most emission sources and the potential for upset conditions to

sometimes occur during operations, acute values developed to include intermittent exposures were

considered more appropriate and more protective than values which are based on the strict assumption

that acute exposures will be one-time only. Therefore, we recommend the Acute Reference Exposure

Levels (Acute REL) developed by Cal/EPA, as the first choice for acute inhalation values (Cal/EPA

1999). Additional acute reference values which also do not exclude intermittent exposures are anticipated

to be available from the EPA Office of Research and Development. When available, we recommend

using those values (referred to as Acute Reference Concentrations [A-RfCs]) as the first choice, with the

Cal/EPA acute RELs second in the hierarchy. Please note that the values we recommend using from all

of the sources are based on one-hour exposures.

1. Cal/EPA Acute RELs – an acute REL represents the concentration in air at or below

which no adverse health effects are anticipated in the general population, including

sensitive individuals, for a specified exposure period (Cal/EPA 1999)

2. Acute inhalation exposure guidelines (AEGL-1) – an AEGL-1 value represents “the

airborne concentration of a substance above which it is predicted that the general

population, including susceptible individuals, could experience notable discomfort,

irritation, or certain asymptomatic nonsensory effects. However, the effects are not

disabling and are transient and reversible upon cessation of exposure.” (NAC 2002)

3. Level 1 emergency planning guidelines (ERPG-1) – an ERPG-1 value represents “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.” (AIHA 2004; SCAPA 2004)

4. Temporary emergency exposure limits (TEEL-1) – a TEEL-1 value represents “the

maximum concentration in air below which it is believed nearly all individuals could be

exposed without experiencing other than mild transient adverse health effects or

perceiving a clearly defined odor.” (SCAPA 2004)

It should be noted that the TEEL-1 values (SCAPA 2004) are calculated based on an assumed exposure

period of 15-minutes. To evaluate risks due to acute exposure based on the highest 1-hour average air

concentrations, the TEEL-1 values were extrapolated from a 15-minute to a 1-hour exposure basis using a

modification to Haber’s Rule developed by ten Berge (1986) and used by Cal/EPA to develop acute RELs

(Cal/EPA 1999), as shown below.
Human Health Risk Assessment Protocol

Appendix A-2 September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering A-2-38

C T K n × = Equation A-2-40

where

C = Concentration (mg/m3

)

n = Constant greater than zero (unitless)

T = Time of exposure (hour)

K = Constant level or severity of response (unitless)

Where available, chemical-specific values for the parameter n as selected and recommended by

Cal/EPA’s Office of Environmental Health Hazard Assessment (OEHHA) based on the work of ten Berge

(1986) and the open literature were used to make the extrapolations (Cal/EPA 1999). For chemicals for

which a chemical-specific value of n was not available, extrapolations were made using a value of n = 1,

as recommended by OEHHA, because the extrapolations were all based on an initial exposure period (15-

minutes) of less than 1 hour duration (Cal/EPA 1999).

Use of the modified form of Haber’s Rule allows contributions by both concentration and time to the

overall severity of effect to be considered. However, the extrapolated air concentrations are to be

interpreted carefully, and should not be interpreted to be absolutes. For example, chemical-specific

values of the exponent n are sometimes based on a relatively limited set of dose-response data. Also, the

majority of extrapolated TEEL-1 values were calculated using default exponent values and, therefore, are

likely to be even less certain than exponent values based on limited data sets.

The hierarchy is presented in order of preference, from 1 (most preferred) to 4 (least preferred). If no

acute REL value is available for a given contaminant, one can work down the list in order. If no AEGL-1

value is available, but an AEGL-2 value is available, the AEGL-2 can be selected as the AIEC only if it is

a more protective value (lower in concentration) than an ERPG-1 or a TEEL-1 value if either of these

values is available. 
U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering A-2-39

REFERENCES

APPENDIX A-2

Agency for Toxic Substances and Disease Registry (ATSDR). 1987. Draft Toxicological Profile for

Di(2-ethylhexyl) Phthatlate. Oak Ridge National Laboratory. December.

ATSDR. 1993. Toxicological Profile for Selected PCBs (Aroclor-1260, -1254, -1248, -1242, -1232,

–1221, and -1016). ATSDR. Atlanta, GA.

Bacci E., D. Calamari, C. Gaggi, and M. Vighi. 1990. “Bioconcentration of Organic Chemical Vapors in

Plant Leaves: Experimental Measurements and Correlation.” Environmental Science and

Technology. Volume 24. Number 6. Pages 885-889.

Bacci E., M. Cerejeira, C. Gaggi, G. Chemello, D. Calamari, and M. Vighi. 1992. “Chlorinated Dioxins: 

Volatilization from Soils and Bioconcentration in Plant Leaves.” Bulletin of Environmental

Contamination and Toxicology. Volume 48. Pages 401-408.

Baes, C.F. 1982. “Prediction of Radionuclide Kd values from Soil-Plant Concentration Ratios.” 

Tran. American Nuclear Society. 41:53-54.

Baes, C.F., R.D. Sharp, A.L. Sjoreen, and R.W. Shor. 1984. “Review and Analysis of Parameters and

Assessing Transport of Environmentally Released Radionuclides through Agriculture.” 

Oak Ridge National Laboratory. Oak Ridge, Tennessee.

Banerjee, S., P.H. Howard, and S.S. Lande. 1990. “General Structure Vapor Pressure Relationships for

Organics.” Chemosphere. 21(10-11). Pages 1173-1180.

Belcher, G.D., and C.C. Travis. 1989. “Modeling Support for the RURA and Municipal Waste

Combustion Projects: Final Report on Sensitivity and Uncertainty Analysis for the Terrestrial

Food Chain Model.” Interagency Agreement No. 1824-A020-A1. Office of Risk Analysis,

Health and Safety Research Division. Oak Ridge National Laboratory. Oak Ridge, Tennessee. 

October.

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U.S. EPA Region 6 U.S. EPA

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Human Health Risk Assessment Protocol

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Human Health Risk Assessment Protocol

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U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering A-2-46

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Human Health Risk Assessment Protocol

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U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering A-2-47

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Human Health Risk Assessment Protocol

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U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering A-2-48

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CHEMICALS OF POTENTIAL CONCERN 

INCLUDED IN THE COMPANION DATABASE

CAS# Compound CAS# Compound

Human Health Risk Assessment Protocol

Appendix A-2 September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering A-2-49

83-32-9 Acenaphthene

75-07-0 Acetaldehyde

67-64-1 Acetone

75-05-8 Acetonitrile

98-86-2 Acetophenone

107-02-8 Acrolein

107-13-1 Acrylonitrile

309-00-2 Aldrin

62-53-3 Aniline

120-12-7 Anthracene

7440-36-0 Antimony compounds

12674-11-2 Aroclor 1016

11097-69-1 Aroclor 1254

7440-38-2 Arsenic Compounds

1912-24-9 Atrazine

7440-39-3 Barium

100-52-7 Benzaldehyde

71-43-2 Benzene

56-55-3 Benzo(a)anthracene

50-32-8 Benzo(a)pyrene

205-99-2 Benzo(b)fluoranthene

207-08-9 Benzo(k)fluoranthene

65-85-0 Benzoic acid

100-47-0 Benzonitrile

100-51-6 Benzyl alcohol

100-44-7 Benzyl chloride

7440-41-7 Beryllium compounds

319-84-6 BHC, alpha-

(alpha-Hexachlorocyclohexane)

319-85-7 BHC, beta-

(beta-Hexachlorocyclohexane)

111-44-4 Bis(2-chlorethyl)ether

75-27-4 Bromodichloromethane

75-25-2 Bromoform (Tribromomethane)

101-55-3 Bromophenyl-phenylether, 4-

7440-43-9 Cadmium compounds

75-15-0 Carbon disulfide

56-23-5 Carbon tetrachloride

57-74-9 Chlordane

7782-50-5 Chlorine

59-50-7 Chloro-3-methylphenol, 4-

106-47-8 Chloroaniline, p108-90-7 Chlorobenzene

510-15-6 Chlorobenzilate

75-45-6 Chlorodifluoromethane

75-00-3 Chloroethane

67-66-3 Chloroform (Trichloromethane)

39638-32-9 Chloroisopropyl ether, bis-1,2-

91-58-7 Chloronaphthalene,2-

95-57-8 Chlorophenol, 2-

7005-72-3 Chlorophenyl-phenylether, 4-

2921-88-2 Chlorpyrifos

7440-47-3 Chromium compounds

18540-29-9 Chromium, hexavalent

218-01-9 Chrysene

108-39-4 Cresol, m- (3-Methylphenol)

95-48-7 Cresol, o106-44-5 Cresol, p98-82-8 Cumene (Isopropylbenzene)

57-12-5 Cyanide Compounds

72-54-8 DDD, 4,4'-

72-55-9 DDE, 4,4'-

50-29-3 DDT, 4-4'-

333-41-5 Diazinon

53-70-3 Dibenz(a,h)anthracene

96-12-8 Dibromo-3-chloropropane, 1,2-

124-48-1 Dibromochloromethane

95-50-1 Dichlorobenzene, 1,2-

541-73-1 Dichlorobenzene, 1,3-

106-46-7 Dichlorobenzene,1,4-

91-94-1 Dichlorobenzidine, 3,3'-

75-71-8 Dichlorodifluoromethane

75-34-3 Dichloroethane 1,1-

107-06-2 Dichloroethane, 1,2- 

(Ethylene Dichloride)

75-35-4 Dichloroethylene 1,1-

156-59-2 Dichloroethylene, cis-1,2-

156-60-5 Dichloroethylene-1,2 (trans)

120-83-2 Dichlorophenol, 2,4-

78-87-5 Dichloropropane, 1,2-

542-75-6 Dichloropropene, 1,3-

62-73-7 Dichlorvos

60-57-1 Dieldrin

84-66-2 Diethyl phthalate

131-11-3 Dimethyl phthalate

105-67-9 Dimethylphenol, 2,4-

119-90-4 Dimethyoxybenzidine, 3,3'-
CHEMICALS OF POTENTIAL CONCERN 

INCLUDED IN THE COMPANION DATABASE

CAS# Compound CAS# Compound

Human Health Risk Assessment Protocol

Appendix A-2 September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering A-2-50

84-74-2 Di-n-butyl phthalate

99-65-0 Dinitrobenzene, 1,3-

51-28-5 Dinitrophenol, 2,4-

121-14-2 Dinitrotoluene, 2,4-

606-20-2 Dinitrotoluene, 2,6-

117-84-0 Di-n-octylphthalate

123-91-1 Dioxane, 1,4-

646-06-0 DIOXOLANE,1,3-

122-66-7 Diphenylhydrazine,1,2-

298-04-4 Disulfoton

115-29-7 Endosulfan I

72-20-8 Endrin

106-89-8 Epichlorohydrin 

(1-Chloro-2,3- epoxypropane)

97-63-2 Ethyl methacrylate

62-50-0 Ethyl methanesulfonate

100-41-4 Ethylbenzene

106-93-4 Ethylene Dibromide

75-21-8 Ethylene oxide

117-81-7 Ethylhexyl phthalate, bis-2-

206-44-0 Fluoranthene

86-73-7 Fluorene

50-00-0 Formaldehyde

64-18-6 Formic acid

35822-46-9 HeptaCDD, 1,2,3,4,6,7,8-

67562-39-4 HeptaCDF, 1,2,3,4,6,7,8-

55673-89-7 HeptaCDF, 1,2,3,4,7,8,9-

76-44-8 Heptachlor

1024-57-3 Heptachlor epoxide

39227-28-6 HexaCDD, 1,2,3,4,7,8-

57653-85-7 HexaCDD, 1,2,3,6,7,8-

19408-74-3 HexaCDD, 1,2,3,7,8,9-

70648-26-9 HexaCDF, 1,2,3,4,7,8-

57117-44-9 HexaCDF, 1,2,3,6,7,8-

72918-21-9 HexaCDF, 1,2,3,7,8,9-

60851-34-5 HexaCDF, 2,3,4,6,7,8-

87-68-3 Hexachloro-1,3-butadiene

(Perchlorobutadiene)

118-74-1 Hexachlorobenzene

77-47-4 Hexachlorocyclopentadiene

67-72-1 Hexachloroethane

(Perchloroethane)

70-30-4 Hexachlorophene

7647-01-0 Hydrogen chloride

(Hydrochloric acid)

193-39-5 Indeno(1,2,3-cd) pyrene

78-59-1 Isophorone

7439-92-1 Lead compounds

121-75-5 Malathion

7487-94-7 Mercuric chloride

7439-97-6 Mercury (elemental)

126-98-7 Methacrylonitrile

67-56-1 Methanol

72-43-5 Methoxychlor

79-20-9 Methyl acetate

74-83-9 Methyl bromide

(Bromomethane)

74-87-3 Methyl chloride

(Chloromethane)

78-93-3 Methyl ethyl ketone

(2-Butanone)

108-10-1 Methyl isobutyl ketone

22967-92-6 Methyl mercury

298-00-0 Methyl parathion

74-95-3 Methylene bromide

75-09-2 Methylene chloride

91-20-3 Naphthalene

7440-02-0 Nickel 

88-74-4 Nitroaniline, 2-

99-09-2 Nitroaniline, 3-

100-01-6 Nitroaniline, 4-

98-95-3 Nitrobenzene

88-75-5 Nitrophenol, 2-

100-02-7 Nitrophenol, 4-

924-16-3 Nitroso-di-n-butylamine, n86-30-6 Nitrosodiphenylamine, n621-64-7 Nitrosodipropylamine, n3268-87-9 OctaCDD, 1,2,3,4,6,7,8,9-

39001-02-0 OctaCDF, 1,2,3,4,6,7,8,9-

40321-76-4 PentaCDD, 1,2,3,7,8-
CHEMICALS OF POTENTIAL CONCERN 

INCLUDED IN THE COMPANION DATABASE

CAS# Compound CAS# Compound

Human Health Risk Assessment Protocol

Appendix A-2 September 2005

U.S. EPA Region 6 U.S. EPA

Multimedia Planning and Permitting Division Office of Solid Waste

Center for Combustion Science and Engineering A-2-51

57117-41-6 PentaCDF, 1,2,3,7,8-

57117-31-4 PentaCDF, 2,3,4,7,8-

608-93-5 Pentachlorobenzene

82-68-8 Pentachloronitrobenzene

(PCNB)

87-86-5 Pentachlorophenol

85-01-8 Phenanthrene

108-95-2 Phenol

298-02-2 Phorate

85-44-9 Phthalic anhydride

(1,2-Benzene dicarboxylic anhydride)

23950-58-5 Pronamide

129-00-0 Pyrene

110-86-1 Pyridine

299-84-3 Ronnel

94-59-7 Safrole

7782-49-2 Selenium 

7440-22-4 Silver 

57-24-9 Strychnine

100-42-5 Styrene

1746-01-6 TetraCDD, 2,3,7,8-

51207-31-9 TetraCDF, 2,3,7,8-

95-94-3 Tetrachlorobenzene, 1,2,4,5-

630-20-6 Tetrachloroethane, 1,1,1,2-

79-34-5 Tetrachloroethane, 1,1,2,2-

127-18-4 Tetrachloroethylene

(Perchloroethylene)

58-90-2 Tetrachlorophenol, 2,3,4,6-

109-99-9 Tetrahydrofuran

7440-28-0 Thallium (l)

108-88-3 Toluene

95-53-4 Toluidine, o87-61-6 Trichlorobenzene, 1,2,3-

120-82-1 Trichlorobenzene, 1,2,4-

71-55-6 Trichloroethane, 1,1,1-

79-00-5 Trichloroethane, 1,1,2-

79-01-6 Trichloroethylene

75-69-4 Trichlorofluoromethane 

(Freon 11)

95-95-4 Trichlorophenol, 2,4,5-

88-06-2 Trichlorophenol, 2,4,6-

96-18-4 Trichloropropane, 1,2,3-

108-67-8 Trimethylbenzene, 1,3,5-

99-35-4 Trinitrobenzene, 1,3,5 (sym-)

118-96-7 Trinitrotoluene, 2,4,6-

108-05-4 Vinyl acetate

75-01-4 Vinyl chloride

108-38-3 Xylene, m95-47-6 Xylene, o106-42-3 Xylene, p7440-66-6 Zinc
B - i

APPENDIX B

ESTIMATING MEDIA CONCENTRATION EQUATIONS AND VARIABLE VALUES

Table Equation

SOIL INGESTION EQUATIONS

B-1-1 Soil Concentration Due to Deposition

B-1-2 COPC Soil Loss Constant 

B-1-3 COPC Loss Constant Due to Soil Erosion

B-1-4 COPC Loss Constant Due to Soil Runoff

B-1-5 COPC Loss Constant Due to Soil Leaching

B-1-6 COPC Loss Constant Due to Soil Volatilization

PRODUCE INGESTION EQUATIONS

B-2-1 Soil Concentration Due to Deposition

B-2-2 COPC Soil Loss Constant 

B-2-3 COPC Loss Constant Due to Soil Erosion

B-2-4 COPC Loss Constant Due to Soil Runoff

B-2-5 COPC Loss Constant Due to Soil Leaching

B-2-6 COPC Loss Constant Due to Soil Volatilization

B-2-7 Aboveground Produce Concentration Due to Direct Deposition

B-2-8 Aboveground Produce Concentration Due to Air-to-Plant Transfer

B-2-9 Aboveground Produce Concentration Due to Root Uptake

B-2-10 Belowground Produce Concentration Due to Root Uptake

ANIMAL PRODUCTS INGESTION EQUATIONS

B-3-1 Soil Concentration Due to Deposition

B-3-2 COPC Soil Loss Constant 

B-3-3 COPC Loss Constant Due to Soil Erosion

B-3-4 COPC Loss Constant Due to Soil Runoff

B-3-5 COPC Loss Constant Due to Soil Leaching

B-3-6 COPC Loss Constant Due to Soil Volatilization

B-3-7 Forage and Silage Concentration Due to Direct Deposition

B-3-8 Forage and Silage Concentration Due to Air-to-Plant Transfer

B-3-9 Forage/Silage/Grain Concentration Due to Root Uptake

B-3-10 Beef Concentration Due to Plant & Soil Ingestion

B-3-11 Milk Concentration Due to Plant & Soil Ingestion

B-3-12 Pork Concentration Due to Plant & Soil Ingestion

B-3-13 COPC Concentration in Eggs

B-3-14 Concentration in Chicken

DRINKING WATER AND FISH INGESTION EQUATIONS

B-4-1 WATERSHED Soil Concentration Due to Deposition

B-4-2 COPC Soil Loss Constant 

B-4-3 COPC Loss Constant Due to Soil Erosion

B-4-4 COPC Loss Constant Due to Soil Runoff

B-4-5 COPC Loss Constant Due to Soil Leaching

B-4-6 COPC Loss Constant Due to Soil Volatilization

B-4-7 Total Water Body Load

B-4-8 Deposition to Water Body

B-4-9 Impervious Runoff Load to Water Body

B-4-10 Pervious Runoff Load to Water Body

B-4-11 Erosion Load to Water Body
B-ii

DRINKING WATER AND FISH INGESTION EQUATIONS (cont’d)

B-4-12 Diffusion Load to Water Body

B-4-13 Universal Soil Loss Equation (USLE)

B-4-14 Sediment Delivery Ratio

B-4-15 Total Water Body Concentration

B-4-16 Fraction in Water Column & Benthic Sediment

B-4-17 Overall Total Water Body Dissipation Rate Constant

B-4-18 Water Column Volatilization Loss Rate Constant

B-4-19 Overall COPC Transfer Rate Coefficient

B-4-20 Liquid Phase Transfer Coefficient

B-4-21 Gas Phase Transfer Coefficient

B-4-22 Benthic Burial Rate Constant

B-4-23 Total Water Column Concentration

B-4-24 Dissolved Phase Water Concentration

B-4-25 COPC Concentration Sorbed to Bed Sediment

B-4-26 Fish Concentration From Bioconcentration Factors Using Dissolved-Phase Water

Concentration

B-4-27 Fish Concentration From Bioaccumulation Factors Using Dissolved-Phase Water

Concentration

B-4-28 Fish Concentration From Biota-to-Sediment Accumulation Factors Using COPC Sorbed

to Bed Sediment

DIRECT INHALATION EQUATION

B-5-1 Air Concentration

ACUTE EQUATION

B-6-1 Acute Air Concentration
TABLE B-1-1

SOIL CONCENTRATION DUE TO DEPOSITION

(SOIL INGESTION EQUATIONS)

(Page 1 of 9)

B-1

 Description

Use the equations in this table to calculate an average COPC soil concentration resulting from wet and dry deposition of particles and vapors to soil over the exposure duration. We recommend

assuming that COPCs are incorporated only to a finite depth (the soil mixing zone depth, Zs). Use the COPC soil concentration averaged over the exposure duration, represented by Cs, for

carcinogenic COPCs, where risk is averaged over the lifetime of an individual. Because the hazard quotient associated with noncarcinogenic COPCs is based on a reference dose rather than a

lifetime exposure, we recommend using the highest annual average COPC soil concentration occurring during the exposure duration period for noncarcinogenic COPCs. The highest annual

average COPC soil concentration would most likely occur at the end of the time period of combustion and is represented by CstD.

The following uncertainties are associated with this variable:

(1) We assume that the time period for deposition of COPCs resulting from hazardous waste combustion is a conservative, long-term value. This assumption may overestimate Cs and CstD.

(2) Exposure duration values (T2) are based on historical mobility studies and won’t necessarily remain constant. Specifically, mobility studies indicate that most receptors that move

remain in the vicinity of the combustion unit; however, it is impossible to accurately predict the probability that these short-distance moves will influence exposure, based on factors

such as atmospheric transport of pollutants.

(3) A value of zero for T1

 doesn’t account for exposure that may have occurred from historic operations and emissions from hazardous waste combustion. This may underestimate Cs and

CstD.

(4) For soluble COPCs, leaching might lead to movement below the 2 centimeters, resulting in lower concentrations within the mixing depth. This uncertainty may overestimate Cs and

CstD. 

(5) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in situ materials) compared to other residues. This may

underestimate Cs and CstD. 

Equation for Carcinogens

Soil Concentration Averaged Over Exposure Duration
TABLE B-1-1

SOIL CONCENTRATION DUE TO DEPOSITION

(SOIL INGESTION EQUATIONS)

(Page 2 of 9)

B-2

Equation for Noncarcinogens

Highest Annual Average Soil Concentration

where

For mercury modeling

Use 0.48Q for total mercury and Fv = 0.85 in the mercury modeling equation to calculate Ds. Apportion the calculated Ds value into the divalent mercury (Hg2+) and methyl mercury (MHg)

forms based on the assumed 98% Hg2+ and 2% MHg speciation split in soils (see Chapter 2). Elemental mercury (Hg0

) occurs in very small amounts in the vapor phase and does not exist in the

particle or particle-bound phase. Therefore, assume elemental mercury deposition onto soils is negligible or zero. Evaluate elemental mercury for the direct inhalation pathway only (Table

B-5-1).

Ds (Hg2+) = 0.98 Ds (Mercu ry)

Ds (MHG) = 0.02 Ds (Mercu ry)

Ds (Hg0) = 0.0

Evaluate divalent and methyl mercury as individual COPCs. Calculate Cs for divalent and methyl mercury using the corresponding (1) fate and transport parameters for mercuric chloride

(divalent mercury, Hg2+) and methyl mercury provided in Appendix A-2, and (2) Ds (Hg2+) and Ds (MHg) as calculated above. 
TABLE B-1-1

SOIL CONCENTRATION DUE TO DEPOSITION

(SOIL INGESTION EQUATIONS)

(Page 3 of 9)

B-3

Variable Description Units Value

Cs Average soil concentration over

exposure duration 

mg COPC/kg

soil

CstD

Soil concentration at time tD mg COPC/kg

soil

Ds Deposition term mg COPC/kg

soil-yr

Varies

U.S. EPA (1994a) and NC DEHNR (1997) recommend incorporating a deposition term into the Cs equation. 

Uncertainties associated with this variable include the following:

(1) Five of the variables in the equation for Ds (Q, Cywv, Dywv, Dydp, and Dywp) are COPC- and site-specific. 

Values for these variables are estimated through modeling. The direction and magnitude of any uncertainties

shouldn’t be generalized. 

(2) Based on the narrow recommended ranges, we expect uncertainties associated with Vdv, Fv

, and BD to be low.

(3) Values for Zs vary by about one order of magnitude. Uncertainty is greatly reduced if you know whether soils

are tilled or untilled.

tD Time period over which deposition

occurs (time period of combustion)

yr 30

U.S. EPA (1998) suggests that tD can be $30 years. We recommend using 30 years unless site-specific information is

available indicating that this assumption is unreasonable (see Chapter 6 of the HHRAP). 

ks COPC soil loss constant due to all

processes

yr-1 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-1-2. The COPC soil loss constant

is the sum of all COPC removal processes. 

Uncertainty associated with this variable includes the following:

COPC-specific values for ksg (one of the variables in the equation in Table B-1-2) are empirically determined

from field studies. No information is available regarding the application of these values to the site-specific

conditions associated with affected facilities.
TABLE B-1-1

SOIL CONCENTRATION DUE TO DEPOSITION

(SOIL INGESTION EQUATIONS)

(Page 4 of 9)

Variable Description Units Value

B-4

T2

Length of exposure duration yr 6, 30, or 40

We recommend reasonable maximum exposure (RME) values for T2

:

Exposure Duration RME Reference

Child Resident 6 years U.S. EPA (1997b)

Farmer Child

Fisher Child

Adult Resident and 30 years U.S. EPA (1997b)

Fisher

Farmer 40 years U.S. EPA (1994b)

U.S. EPA (1994c) recommended the following unreferenced values:

Exposure Duration Years 

Subsistence Farmer 40

Adult Resident 30

Subsistence Fisher 30

Child Resident 9

Uncertainties associated with this variable include the following:

(1) Exposure duration rates are based on historical mobility rates and may not remain constant. This assumption

may overestimate or underestimate Cs and CstD.

(2) Mobility studies indicate that most receptors that move remain in the vicinity of the emission sources. However,

it is impossible to accurately predict the likelihood that these short-distance moves will influence exposure, based

on factors such as atmospheric transport of pollutants. This assumption may overestimate or underestimate Cs

and CstD.

T1

Time period at the beginning of

combustion

yr 0

Consistent with U.S. EPA (1994c), we recommend a value of 0 for T1. 

The following uncertainty is associated with this variable:

A T1

 of 0 does not account for exposure that may have occurred from historical operations or emissions from

burning hazardous waste. This may underestimate Cs and CstD. 
TABLE B-1-1

SOIL CONCENTRATION DUE TO DEPOSITION

(SOIL INGESTION EQUATIONS)

(Page 5 of 9)

Variable Description Units Value

B-5

100 Units conversion factor mg-cm2

/kg-cm2

Q COPC-specific emission rate g/s Varies

This variable is COPC- and site-specific. See Chapters 2 and 3 of the HHRAP for guidance on calculating this variable. 

Uncertainties associated with this variable are site-specific.

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs

:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with

U.S. EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A

default value of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil

(Brzuzy et al. 1995). A default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below Zs, resulting in lower concentrations within the

Zs

. This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution compared to other residues. 

This uncertainty may underestimate Cs and CstD. 

BD Soil bulk density g soil/cm3

 soil 1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value

of 1.5 g soil/cm3

 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that

a value of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended BD value may not accurately represent site-specific soil conditions; and may under- or

overestimate site-specific soil conditions to an unknown degree.
TABLE B-1-1

SOIL CONCENTRATION DUE TO DEPOSITION

(SOIL INGESTION EQUATIONS)

(Page 6 of 9)

Variable Description Units Value

B-6

Fv

Fraction of COPC air concentration

in vapor phase 

unitless 0 to 1

This variable is COPC-specific. We discuss this variable and offer COPC-specific values in Appendix A-2. The range is

based on the values presented in Appendix A-2. Values are also presented in U.S. EPA (1994c) and NC DEHNR (1997).

Fv was calculated using an equation presented in Junge (1977) for all organic COPCs, including PCDDs and PCDFs. U.S.

EPA (1994c) states that Fv = 0 for all metals (except mercury).

The following uncertainties are associated with this variable:

(1) Our Fv calculations assume a default ST value for background plus local sources, rather than an ST value for urban

sources. If your site is located in an urban area, using the latter ST value may be more appropriate. Specifically,

the ST value for urban sources is about one order of magnitude greater than that for background plus local

sources, and it would result in a lower calculated Fv value; however, the Fv value is likely to be only a few

percent lower.

(2) According to Bidleman (1988), the equation used to calculate Fv assumes that the variable c (Junge constant) is

constant for all chemicals; however, the value of c depends on the chemical (sorbate) molecular weight, the

surface concentration for monolayer coverage, and the difference between the heat of desorption from

the particle surface and the heat of vaporization of the liquid-phase sorbate. To the extent that site- or

COPC-specific conditions may cause the value of c to vary, uncertainty is introduced if a constant value

of c is used to calculate Fv

.

Dydv Unitized yearly average dry

deposition from vapor phase 

s/m2

-yr Varies

This variable is COPC- and site-specific, and is determined by air modeling (see Chapter 3). Uncertainties associated with

this variable are site-specific.

Dywv Unitized yearly average wet

deposition from vapor phase 

s/m2

-yr Varies

This variable is COPC- and site-specific, and is determined by air modeling (see Chapter 3). Uncertainties associated with

this variable are site-specific.

Dydp Unitized yearly average dry

deposition from particle phase

s/m2-yr Varies

This variable is COPC- and site-specific, and is determined by air modeling (see Chapter 3). Uncertainties associated with

this variable are site-specific.

Dywp Unitized yearly average wet

deposition from particle phase

s/m2

-yr Varies

This variable is COPC- and site-specific, and is determined by air modeling (see Chapter 3). Uncertainties associated with

this variable are site-specific.
TABLE B-1-1

SOIL CONCENTRATION DUE TO DEPOSITION

(SOIL INGESTION EQUATIONS)

(Page 7 of 9)

B-7

REFERENCES AND DISCUSSION

Bidleman, T.F. 1988. “Atmospheric Processes.” Environmental Science and Technology. Volume 22. Number 4. Pages 361-367.

This reference is for the statement that the equation used to calculate the fraction of air concentration in vapor phase (Fv) assumes that the variable c (the Junge constant) is constant for all

chemicals. However, Bidleman (1988) notes that the value of c depends on the chemical (sorbate) molecular weight, the surface concentration for monolayer coverage, and the difference

between the heat of desorption from the particle surface and the heat of vaporization of the liquid phase sorbate. The following equation, presented in Bidleman (1988), is cited by U.S.

EPA (1994b) and NC DEHNR (1997) for calculating the variable Fv

:

where

Fv = Fraction of chemical air concentration in vapor phase (unitless)

c = Junge constant = 1.7 x 10-04 (atm-cm)

ST = Whitby’s average surface area of particulates = 3.5 x 10-06 cm2/cm3 air (corresponds to background plus local sources)

= Liquid-phase vapor pressure of chemical (atm) (see Appendix A-2)

If the chemical is a solid at ambient temperatures, the solid-phase vapor pressure is converted to a liquid-phase vapor pressure as follows:

where

= Solid-phase vapor pressure of chemical (atm) (see Appendix A-2)

= Entropy of fusion over the universal gas constant = 6.79 (unitless)

Tm = Melting point of chemical (K) (see Appendix A-2)

Ta = Ambient air temperature = 284 K (11°C)

Brzuzy, L.P. and R.A. Hites. 1995. “Estimating the Atmospheric Deposition of Polychlorinated Dibenzo-p-dioxins and Dibenzofurans from Soils.” Environmental Science and Technology. 

Volume 29. Pages 2090-2098.

This reference presents soil profiles for dioxin measurements.
TABLE B-1-1

SOIL CONCENTRATION DUE TO DEPOSITION

(SOIL INGESTION EQUATIONS)

(Page 8 of 9)

B-8

Carsel, R.F., R.S. Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2.

Pages 11-24.

Cited by U.S. EPA (1994b) as the source for a mean soil bulk density value, BD, of 1.5 g soil/cm3

 soil for loam soil. 

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York.

Cited by U.S. EPA (1998) for the statement that BD is affected by the soil structure, such as looseness or compaction of the soil, depending on the water and clay content of the soil.

Junge, C.E. 1977. Fate of Pollutants in Air and Water Environments, Part I. Suffet, I.H., Ed. Wiley. New York. Pages 7-26.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This is one of the source documents for the equation in Table B-1-1. This document also recommends using (1) a deposition term, Ds, and (2) COPC-specific Fv values.

Research Triangle Institute (RTI). 1992. Preliminary Soil Action Level for Superfund Sites. Draft Interim Report. Prepared for U.S. EPA Hazardous Site Control Division, Remedial Operations

Guidance Branch. Arlington, Virginia. EPA Contract 68-W1-0021. Work Assignment No. B-03, Work Assignment Manager Loren Henning. December.

This document is a reference source for COPC-specific Fv values.

U.S. EPA. 1992. Estimating Exposure to Dioxin-Like Compounds. Draft Report. Office of Research and Development. Washington, D.C. EPA/600/6-88/005b.

The External Review Draft of the MPE document (the final is U.S. EPA 1998) cites this document as the source of values for soil mixing zone depth, Zs

, for tilled and untilled soils.

U.S. EPA. 1993. Addendum to the Methodology for Assessing Health Risks Associated with Indirect Exposure to Combustor Emissions. Working Group Recommendations. Office of Solid Waste. 

Office of Research and Development. Washington, D.C. September.

This document is a reference for the equation in Table B-1-1. It recommends using a deposition term, Ds, and COPC-specific Fv values in the Cs equation.

U.S. EPA 1994a. Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. April.

This document is a reference for the equation in Table B-1-1; it recommends using the following in the Cs equation: (1) a deposition term, Ds, and (2) a default soil bulk density value of

1.5 g soil/cm3

 soil, based on a mean value for loam soil from Carsel et al. (1988).

U.S. EPA. 1994b. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-Specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This document recommends values for length of exposure duration, T2

, for the farmer.
TABLE B-1-1

SOIL CONCENTRATION DUE TO DEPOSITION

(SOIL INGESTION EQUATIONS)

(Page 9 of 9)

B-9

U.S. EPA. 1994c. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Office of Emergency and Remedial Response.

Office of Solid Waste. December.

This document recommends the following:

C Values for the length of exposure duration, T2

C Value of 0 for the time period of the beginning of combustion, T1

C Fv values that range from 0.27 to 1 for organic COPCs

C Default soil bulk density value of 1.5 g soil/cm3 soil, based on a mean for loam soil from Carsel et al. (1988)

 U.S. EPA. 1997a. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research

and Development. EPA 452/R-97-005. December.

U.S. EPA. 1997b. Exposure Factors Handbook. Office of Research and Development. EPA/600/P-95/002Fc. August.

This document is a reference source for values for length of exposure duration, T2.

 U.S. EPA. 1998. Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions (MPE). Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.
TABLE B-1-2

COPC SOIL LOSS CONSTANT 

(SOIL INGESTION EQUATIONS)

(Page 1 of 4)

B-10

Description

This equation calculates the COPC soil loss constant, which accounts for the loss of COPCs from soil by several mechanisms. 

Uncertainties associated with this equation include the following:

(1) COPC-specific values for ksg are empirically determined from field studies. No information is available regarding the application of these values to the site-specific conditions

associated with affected facilities.

(2) The source of the equations in Tables B-1-3 through B-1-5 have not been identified.

Equation

Variable Description Units Value

ks COPC soil loss constant due to all

processes

yr-1

ksg COPC loss constant due to biotic

and abiotic degradation

yr-1 Varies

This variable is COPC-specific. Values are available in the COPC tables in Appendix A-2. 

“Degradation rate” values are also presented in NC DEHNR (1997); however, no reference or source is provided for the values. 

U.S. EPA (1994a) and U.S. EPA (1994b) state that ksg values are COPC-specific; however, all ksg values are presented as zero

(U.S. EPA 1994a) or as “NA” (U.S. EPA 1994b); the basis of these assumptions is not addressed. 

The following uncertainty is associated with this variable:

COPC-specific values for ksg are determined empirically from field studies; no information is available on applying these

values to the site-specific conditions associated with affected facilities.
TABLE B-1-2

COPC SOIL LOSS CONSTANT 

(SOIL INGESTION EQUATIONS)

(Page 2 of 4)

Variable Description Units Value

B-11

kse COPC loss constant due to soil

erosion

yr-1 0

This variable is COPC- and site-specific, and is further discussed in Table B-1-3. Consistent with U.S. EPA (1994a), U.S. EPA

(1994b) and NC DEHNR (1997), we recommend a default value of zero for kse because contaminated soil erodes both onto the site

and away from the site.

Uncertainties associated with this variable include the following:

(1) The source of the equation in Table B-1-3 has not been identified.

(2) For soluble COPCs, leaching might lead to movement to below Zs, resulting in lower concentrations within the Zs. This

uncertainty may overestimate kse.

(3) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in

situ materials) compared to other residues. This uncertainty may underestimate kse.

ksr COPC loss constant due to surface

runoff

yr-1 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-1-4. No reference document is cited for

this equation; however, using this equation is consistent with U.S. EPA (1998). U.S. EPA (1994a) assumed that all ksr values are

zero but didn’t explain the basis for this assumption.

Uncertainties associated with this variable (calculated by using the equation in Table B-1-4) include the following:

(1) The source of the equation in Table B-1-4 has not been identified.

(2) For soluble COPCs, leaching might lead to movement to below Zs, resulting in lower concentrations within the Zs. This

uncertainty may overestimate ksr.

(3) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in

situ materials) compared to other residues. This uncertainty may underestimate ksr.

ksl COPC loss constant due to leaching yr-1 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-1-5. Using this equation is consistent with

U.S. EPA (1998), U.S. EPA (1994b), and NC DEHNR (1997). U.S. EPA (1994a) assumed that ksl is zero but didn’t explain the

basis of this assumption.

Uncertainties associated with this variable (calculated by using the equation in Table B-1-5) include the following:

(1) The source of the equation in Table B-1-5 has not been identified.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in

situ materials) compared to other residues. This uncertainty may underestimate ksl.
TABLE B-1-2

COPC SOIL LOSS CONSTANT 

(SOIL INGESTION EQUATIONS)

(Page 3 of 4)

Variable Description Units Value

B-12

ksv COPC loss constant due to

volatilization

yr-1 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-1-6. This equation calculates the COPC

loss constant from soil due to volatilization, and was obtained from U.S. EPA (1998). The soil loss constant due to volatilization

(ksv) is based on gas equilibrium coefficients and gas phase mass transfer. The first order decay constant, ksv, is obtained by

adapting the Hwang and Falco equation for soil vapor phase diffusion (Hwang and Falco 1986).

Uncertainties associated with this equation include the following:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeter in untilled soils, resulting in a greater mixing

depth. This uncertainty may overestimate ksv.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in

situ materials) compared to other residues. This uncertainty may underestimate ksv.

REFERENCES AND DISCUSSION

Hwang S. T. and Falco, J. W. 1986. “Estimation of multimedia exposures related to hazardous waste facilities”, In: Pollutants in a Multimedia Environment. Yoram Cohen, Ed. Plenum Publishing

Corp. New York.

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the reference documents for the equations in Tables B-1-4 and B-1-5. This document is also cited as (1) the source for a range of COPC-specific degradation rates

(ksg), and (2) one of the sources that recommend assuming that the loss resulting from erosion (kse) is zero because of contaminated soil eroding both onto the site and away from the site.

U.S. EPA. 1994a. Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. April.

This document is cited as a source for the assumptions that losses resulting from erosion (kse), surface runoff (ksr), degradation (ksg), leaching (ksl), and volatilization (ksv) are all zero.

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

This document is one of the reference documents for the equations in Tables B-1-4 and B-1-5. This document is also cited as one of the sources that recommend using the assumption that

the loss resulting from erosion (kse) is zero and the loss resulting from degradation (ksg) is “NA” or zero for all compounds.
TABLE B-1-2

COPC SOIL LOSS CONSTANT 

(SOIL INGESTION EQUATIONS)

(Page 4 of 4)

B-13

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document is one of the reference documents for the equations for ksr, ksl, and ksv.
TABLE B-1-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(SOIL INGESTION EQUATIONS)

(Page 1 of 5)

B-14

Description

This equation calculates the constant for COPC loss resulting from erosion of soil. Consistent with U.S. EPA (1994), U.S. EPA (1994b), and NC DEHNR (1997), we recommend a default value

of zero for kse because of contaminated soil eroding onto the site and away from the site. In site-specific cases where the permitting authority considers it appropriate to calculate a kse, we

recommend using the equation presented in this table along with associated uncertainties. You can find additional discussion on determining kse in U.S. EPA (1998). Uncertainties associated

with this equation include:

(1) For soluble COPCs, leaching might lead to movement below 2 centimeter in untilled soils, resulting in a greater mixing depth. This uncertainty may overestimate kse.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in situ materials) in comparison to that of other residues. This

uncertainty may underestimate kse.

Equation

Variable Description Units Value

kse COPC loss constant due to soil

erosion

yr-1 0

Consistent with U.S. EPA (1994), U.S. EPA (1994b), and NC DEHNR (1997), we recommend that the default value assumed

for kse is zero because contaminated soil erodes both onto the site and away from the site. uncertainty may overestimate kse.

0.1 Units conversion factor g-kg/cm2

-

m2

Xe

Unit soil loss kg/m2-yr Varies

This variable is site-specific and is calculated by using the equation in Table B-4-13.

The following uncertainty is associated with this variable:

All of the equation variables are site-specific. Using default values rather than site-specific values for any or all of

these variables will result in unit soil loss (Xe) estimates that are under- or overestimated to some degree. Based on

default values, we expect Xe estimates to vary over a range of less than two orders of magnitude.
TABLE B-1-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(SOIL INGESTION EQUATIONS)

(Page 2 of 5)

Variable Description Units Value

B-15

SD Sediment delivery ratio unitless Varies

This value is site-specific, and is calculated by using the equation in Table B-4-14.

Uncertainties associated with this variable include the following: 

(1) The recommended default values for the empirical intercept coefficient, a, are average values based on studies of

sediment yields from various watersheds. Therefore, those default values may not accurately represent site-specific

watershed conditions. As a result, using these default values may under- or overestimate SD.

(2) The recommended default value for the empirical slope coefficient, b, is based on a review of sediment yields from

various watersheds. This single default value may not accurately represent site-specific watershed conditions. As a

result, using the default value may under- or overestimate SD.

ER Soil enrichment ratio unitless Inorganics: 1

Organics: 3

COPC enrichment occurs because (1) lighter soil particles erode more quickly than heavier soil particles, and (2) concentration

of organic COPCs—which is a function of organic carbon content of sorbing media—is expected to be higher in eroded

material than in in-situ soil (U.S. EPA 1998). In the absence of site-specific data, we recommend a default value of 3 for

organic COPCs and 1 for inorganic COPCs. This is consistent with other Agency guidance (1998), which recommends a

range of 1 to 5 and a value of 3 as a “reasonable first estimate.” This range has been used for organic matter, phosphorus, and

other soil-bound COPCs (U.S. EPA 1998); however, no sources or references were provided for this range. ER is generally

higher in sandy soils than in silty or loamy soils (U.S. EPA 1998).

The following uncertainty is associated with this variable:

The default ER value may not accurately reflect site-specific conditions; therefore, kse may be over- or

underestimated to an unknown extent. Using county-specific ER values will reduce the extent of any uncertainties.

BD Soil bulk density g soil/cm3

soil

1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value of

1.5 g soil/cm3 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that a

value of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended BD value may not accurately represent site-specific soil conditions. It may under- or

overestimate site-specific soil conditions to an unknown degree.
TABLE B-1-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(SOIL INGESTION EQUATIONS)

(Page 3 of 5)

Variable Description Units Value

B-16

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs

:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with U.S.

EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A default

value of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil (Brzuzy et al.

1995). A default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below Zs, resulting in lower concentrations within the Zs. 

This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution compared to other residues. 

This uncertainty may underestimate Cs and CstD.

Kds

Soil-water partition coefficient ml water/g

soil

 (or cm3

water/g soil)

Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in Appendix A2.

2sw

Soil volumetric water content ml

water/cm3

soil

0.2

This variable is site-specific, and depends on the available water and on soil structure; you can estimate 2sw as the midpoint

between a soil’s field capacity and wilting point, if you can identify a representative watershed soil. However, we recommend 

using 0.2 ml/cm3

 as a default value. This value is the midpoint of the range 0.1 (very sandy soils) to 0.3 (heavy loam/clay

soils) recommended by U.S. EPA (1998) (no source or reference is provided for this range) and is consistent with U.S. EPA

(1994b).

The following uncertainty is associated with this variable:

The default 2sw value may not accurately reflect site-specific or local conditions; therefore, kse may be under- or

overestimated to a small extent, based on the limited range of values.
TABLE B-1-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(SOIL INGESTION EQUATIONS)

(Page 4 of 5)

B-17

REFERENCES AND DISCUSSION

Carsel, R.F., R.S. Parish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2. 

Pages 11-24.

This document is cited by U.S. EPA (1994b) as the source for a mean soil bulk density, BD, value of 1.5 g soil/cm3 soil for loam soil. 

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York.

This document is cited by U.S. EPA (1998) for the statement that soil bulk density, BD, is affected by the soil structure, such as looseness or compaction of the soil, depending on the water

and clay content of the soil.

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the sources that recommend assuming that the loss resulting from erosion (kse) is zero because contaminated soil erodes both onto the site and away from the site.

U.S. EPA. 1994. Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. April.

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This document is the source of values for soil mixing zone depth, Zs

, for tilled and untilled soil. 

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment

Guidance for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document recommends (1) a default soil bulk density value of 1.5 g soil/cm3 soil, based on a mean value for loam soil that is taken from Carsel et al. (1988), and (2) a default soil

volumetric water content, 2sw, value of 0.2 ml water/cm3 soil.
TABLE B-1-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(SOIL INGESTION EQUATIONS)

(Page 5 of 5)

B-18

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document is the source of a range of COPC enrichment ratio, ER, values. The recommended range, 1 to 5, was used for organic matter, phosphorous, and other soul-bound COPCs. 

This document recommends a value of 3 as a “reasonable first estimate,” and states that COPC enrichment occurs because lighter soil particles erode more quickly than heavier soil

particles. Lighter soil particles have higher ratios of surface area to volume and are higher in organic matter content. Therefore, concentration of organic COPCs, which is a function of the

organic carbon content of sorbing media, is expected to be higher in eroded material than in in situ soil.

This document is also a source of the following:

C A range of soil volumetric water content (2sw) values of 0.1 ml water/cm3 soil (very sandy soils) to 0.3 ml water/cm3 soil (heavy loam/clay soils). However, no source or reference

is provided for this range.

C A range of values for soil mixing zone depth, Zs, for tilled and untilled soil

C The equations in Tables B-1-3 and B-1-5.
TABLE B-1-4

COPC LOSS CONSTANT DUE TO RUNOFF

(SOIL INGESTION EQUATIONS)

(Page 1 of 4)

B-19

Description

This equation calculates the COPC loss constant due to runoff of soil. Uncertainties associated with this equation include the following:

(1) For soluble COPCs, leaching might result in movement to below 2 centimeter in untilled soils, resulting in a greater mixing depth. This uncertainty may overestimate ksr.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution in comparison to that of other residues. This uncertainty may underestimate ksr.

Equation

Variable Description Units Value

ksr COPC loss constant due to runoff yr-1

RO Average annual surface runoff from

pervious areas

cm/yr Varies

This variable is site-specific. According to U.S. EPA (1998), U.S. EPA (1994b), and NC DEHNR (1997), you can estimate RO

by using the Water Atlas of the United States (Geraghty et al. 1973). According to NC DEHNR (1997), you can also use more

detailed, site-specific procedures for estimating the amount of surface runoff, such as those based on the U.S. Soil Conservation

Service curve number equation (CNE). U.S. EPA (1985) is cited as an example of such a procedure.

The following uncertainty is associated with this variable:

To the extent that site-specific or local average annual surface runoff information is not available, default or

estimated values may not accurately represent site-specific or local conditions. As a result, ksr may be under- or

overestimated to an unknown degree.
TABLE B-1-4

COPC LOSS CONSTANT DUE TO RUNOFF

(SOIL INGESTION EQUATIONS)

(Page 2 of 4)

Variable Description Units Value

B-20

2sw

Soil volumetric water content ml

water/cm3

soil

0.2

This variable is site-specific, and depends on the available water and on soil structure; you can estimate 2sw as the midpoint

between a soil’s field capacity and wilting point, if you can identify a representative watershed soil. We recommend using 0.2

ml/cm3 as a default value. This value is the midpoint of the range 0.1 (very sandy soils) to 0.3 (heavy loam/clay soils),

recommended by U.S. EPA (1998) (no source or reference is provided for this range), and is consistent with U.S. EPA (1994b)

and NC DEHNR (1997).

The following uncertainty is associated with this variable:

The default 2sw value may not accurately reflect site-specific or local conditions; therefore, ksr may be under- or

overestimated to a small extent, based on the limited range of values.

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with U.S.

EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A default

value of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil (Brzuzy et al.

1995). A default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below Zs, resulting in lower concentrations within the Zs. 

This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution compared to other residues. This

uncertainty may underestimate Cs and CstD. 

Kds

Soil-water partition coefficient ml water/g

soil (or cm3

water/g

soil)

Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in Appendix A-2.
TABLE B-1-4

COPC LOSS CONSTANT DUE TO RUNOFF

(SOIL INGESTION EQUATIONS)

(Page 3 of 4)

Variable Description Units Value

B-21

BD Soil bulk density g soil/cm3

soil

1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value of

1.5 g soil/cm3 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that a value

of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended soil bulk density value may not accurately represent site-specific soil conditions.

REFERENCES AND DISCUSSION

Carsel, R.F., R.S. Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2. 

Pages 11-24.

This document is cited by U.S. EPA (1994b) as the source of a mean soil bulk density, BD, value of 1.5 (g soil/cm3 soil) for loam soil. 

Geraghty, J.J., D.W. Miller, F. Van der Leeden, and F.L. Troise. 1973. Water Atlas of the United States. Water Information Center, Port Washington, New York.

This document is cited by U.S. EPA (1998), U.S. EPA (1994), and NC DEHNR (1997) as a reference to calculate average annual runoff, RO. This reference provides maps with isolines of

annual average surface water runoff, which is defined as all flow contributions to surface water bodies, including direct runoff, shallow interflow, and ground water recharge. Because these

values are total contributions and not only surface runoff, U.S. EPA (1994) recommends that the volumes be reduced by 50 percent in order to estimate surface runoff.

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York.

This document is cited by U.S. EPA (1998) for the statement that soil bulk density, BD, is affected by the soil structure, such as looseness or compaction of the soil, depending on the water

and clay content of the soil.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the source documents that recommends using Table B-1-4; however, this document is not the original source of this equation (the source is unknown). This

document also recommends the following:

C Estimating annual current runoff, RO (cm/yr), by using the Water Atlas of the United States (Geraghty et al. 1973) or site-specific procedures, such as using the U.S. Soil

Conservation Service curve number equation (CNE); U.S. EPA (1985) is cited as an example of such a procedure.

C Default value of 0.2 (ml water/cm3 soil) for soil volumetric water content (2sw)
TABLE B-1-4

COPC LOSS CONSTANT DUE TO RUNOFF

(SOIL INGESTION EQUATIONS)

(Page 4 of 4)

B-22

U.S. EPA. 1985. Water Quality Assessment: A Screening Procedure for Toxic and Conventional Pollutants in Surface and Ground Water—Part I (Revised. 1985). Environmental Research

Laboratory. Athens, Georgia. EPA/600/6-85/002a. September.

This document is cited by NC DEHNR (1997) as an example of the use of the U.S. Soil Conservation Service CNE to estimate site-specific surface runoff. 

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This document presents a range of values for soil mixing zone depth, Zs, for tilled and untilled soil.

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment

Guidance for RCRA Hazardous Waste Combustion Facilities. Offices of Emergency and Remedial Response. Office of Solid Waste. December.

This document recommends the following:

C Estimation of average annual runoff, RO, by using the Water Atlas of the United States (Geraghty et al. 1973)

C Default soil bulk density, BD, value of 1.5 g soil/cm3

 soil, based on the mean for loam soil that is taken from Carsel et al. (1988)

C Default soil volumetric water content, 2sw, value of 0.2 (ml water/cm3 soil)

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document recommends the following:

C A range of soil volumetric water content, 2sw, values of 0.1 (very sandy soils) to 0.3 (heavy loam/clay soils) (the original source of, or reference for, these values is not identified)

C A range of values for soil mixing depth, Zs

, for tilled and untilled soil (the original source of, or reference for, these values is not identified)

C Using the Water Atlas of the United States (Geraghty et al. 1973) to calculate average annual runoff, RO
TABLE B-1-5

COPC LOSS CONSTANT DUE TO LEACHING

(SOIL INGESTION EQUATIONS)

(Page 1 of 5)

B-23

Description

This equation calculates the constant for COPC loss resulting from leaching of soil. Uncertainties associated with this equation include the following:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeter in untilled soils, resulting in a greater mixing depth. This uncertainty may overestimate ksl.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in situ materials) compared to that of other residues. This

uncertainty may underestimate ksl.

(3) The original source of this equation has not been identified. U.S. EPA (1998) presents the equation as shown here. U.S. EPA (1994b) and NC DEHNR (1997) replaced the numerator as

shown with “q”, defined as average annual recharge (cm/yr).

Equation

Variable Description Units Value

ksl COPC loss constant due leaching yr-1

P Average annual precipitation cm/yr 18.06 to 164.19

This variable is site-specific. This range is based on information presented in U.S. EPA (1998), representing data for 69 selected

cities (U.S. Bureau of Census 1987; Baes et al. 1984). The 69 selected cities are not identified; however, they appear to be

located throughout the continental United States. We recommend using site-specific data.

The following uncertainty is associated with this variable:

To the extent that a site is not located near an established meteorological data station, and site-specific data are not

available, default average annual precipitation data may not accurately reflect site-specific conditions. As a result, ksl

may be under- or overestimated. However, average annual precipitation data are reasonably available; therefore, we

expect uncertainty introduced by this variable to be minimal.
TABLE B-1-5

COPC LOSS CONSTANT DUE TO LEACHING

(SOIL INGESTION EQUATIONS)

(Page 2 of 5)

Variable Description Units Value

B-24

I Average annual irrigation cm/yr 0 to 100

This variable is site-specific. This range is based on information presented in U.S. EPA (1998), representing data for 69 selected

cities (Baes et al. 1984). The 69 selected cities are not identified; however, they appear to be located throughout the continental

United States.

The following uncertainty is associated with this variable:

To the extent that site-specific or local average annual irrigation information is not available, default values (generally

based on the closest comparable location) may not accurately reflect site-specific conditions. As a result, ksl may be

under- or overestimated to an unknown degree.

RO Average annual surface runoff from

pervious areas

cm/yr Varies

This variable is site-specific. According to U.S. EPA (1998), U.S. EPA (1994b), and NC DEHNR (1997), you can estimate RO

by using the Water Atlas of the United States (Geraghty et al. 1973). According to NC DEHNR (1997), you can also use more

detailed, site-specific procedures, such as those based on the U.S. Soil Conservation Service CNE. U.S. EPA (1985) is cited as

an example of such a procedure.

The following uncertainty is associated with this variable:

To the extent that site-specific or local average annual surface runoff information is not available, default or estimated

values may not accurately represent site-specific or local conditions. As a result, ksl may be under- or overestimated

to an unknown degree.

Ev

Average annual evapotranspiration cm/yr 35 to 100

This variable is site-specific. This range is based on information presented in U. S. EPA (1998), representing data from 69

selected cities. The 69 selected cities are not identified; however, they appear to be located throughout the continental United

States.

The following uncertainty is associated with this variable:

To the extent that site-specific or local average annual evapotranspiration information is not available, default values

may not accurately reflect site-specific conditions. As a result, ksl may be under- or overestimated to an unknown

degree.
TABLE B-1-5

COPC LOSS CONSTANT DUE TO LEACHING

(SOIL INGESTION EQUATIONS)

(Page 3 of 5)

Variable Description Units Value

B-25

2sw

Soil volumetric water content ml

water/cm3

soil

0.2

This variable is site-specific, and depends on the available water and on soil structure. You can estimate 2sw as the midpoint

between a soil’s field capacity and wilting point, if you can identify a representative watershed soil. We recommend using 0.2

ml/cm3 as a default value. This value is the midpoint of the range of 0.1 (very sandy soils) to 0.3 (heavy loam/clay soils)

recommended by U.S. EPA (1998) (no source or reference is provided for this range) and is consistent with U.S. EPA (1994b)

and NC DEHNR (1997).

The following uncertainty is associated with this variable:

The default 2sw value may not accurately reflect site-specific or local conditions; therefore, ksl may be under- or

overestimated to a small extent, based on the limited range of values.

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with U.S.

EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A default

value of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil (Brzuzy et al.

1995). A default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in lower

concentrations within the Zs. This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution compared to other residues. This

uncertainty may underestimate Cs and CstD. 
TABLE B-1-5

COPC LOSS CONSTANT DUE TO LEACHING

(SOIL INGESTION EQUATIONS)

(Page 4 of 5)

Variable Description Units Value

B-26

BD Soil bulk density g soil/cm3

soil

1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value of 1.5

g soil/cm3 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that a value of

1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended soil bulk density value may not accurately represent site-specific soil conditions. 

Kds

Soil-water partition coefficient cm3 water/g

soil

Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2. 

The following uncertainty is associated with this variable:

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in Appendix A-2.

REFERENCES AND DISCUSSION

Baes, C.F., R.D. Sharp, A.L. Sjoreen and R.W. Shor. 1984. “A Review and Analysis of Parameters for Assessing Transport of Environmentally Released Radionuclides through Agriculture.” 

Prepared for the U.S. Department of Energy under Contract No. DEAC05-840R21400.

For the continental United States, as cited in U.S. EPA (1998), this document is the source of a series of maps showing: (1) average annual precipitation (P), (2) average annual irrigation

(I), and (3) average annual evapotranspiration isolines.

Carsel, R.F., R.S. Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2. 

Pages 11-24.

This document is cited by U.S. EPA (1994b) as the source for a mean soil bulk density value, BD, of 1.5 g soil/cm3 soil for loam soil. 

Geraghty, J.J., D.W. Miller, F. Van der Leeden, and F.L. Troise. 1973. Water Atlas of the United States. Water Information Center, Port Washington, New York.

This document is cited by U.S. EPA (1998), U.S. EPA (1994b), and NC DEHNR (1997) as a reference for calculating average annual runoff, RO. This document provides maps with

isolines of annual average surface runoff, which is defined as all flow contributions to surface water bodies, including direct runoff, shallow interflow, and ground water recharge. Because

these volumes are total contributions and not only surface runoff, U.S. EPA (1994b) recommends that the volumes be reduced by 50 percent in order to estimate average annual surface

runoff.
TABLE B-1-5

COPC LOSS CONSTANT DUE TO LEACHING

(SOIL INGESTION EQUATIONS)

(Page 5 of 5)

B-27

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York, New York.

This document is cited by U.S. EPA (1998) for the statement that soil bulk density, BD, is affected by the soil structure, such as looseness or compaction of the soil, depending on the water

and clay content of the soil.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the source documents that cites the use of the equation in Table B-1-5. However, the document is not the original source of this equation. This document also

recommends the following:

C Estimation of average annual surface runoff, RO (cm/yr), by using the Water Atlas of the United States (Geraghty et al. 1973) or site-specific procedures, such as using the U.S.

Soil Conservation Service CNE; U.S. EPA 1985 is cited as an example of such a procedure.

C A default value of 0.2 (ml water/cm3 soil) for soil volumetric water content, 2sw

U.S. Bureau of the Census. 1987. Statistical Abstract of the United States: 1987. 107th edition. Washington, D.C.

This document is a source of average annual precipitation (P) information for 69 selected cites, as cited in U.S. EPA (1990); these 69 cities are not identified. 

U.S. EPA. 1985. Water Quality Assessment: A Screening Procedure for Toxic and Conventional Pollutants in Surface and Groundwater. Part I (Revised 1985). Environmental Research

Laboratory. Athens, Georgia. EPA/600/6-85/002a. September.

This document is cited by NC DEHNR (1997) as an example of the use of the U.S. Soil Conservation Service CNE to estimate RO. 

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This document presents values for soil mixing depth, Zs

, for tilled and untilled soil. 

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

This document recommends (1) a default soil volumetric water content, 2sw, value of 0.2 (ml water/cm3

 soil), and (2) a default soil bulk density, BD, value of 1.5 (g soil/cm3 soil), based on a

mean value for loam soil from Carsel et al. (1988).

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document is one of the reference source documents for the equation in Table B-1-5. The original source of this equation is not identified. This document also presents a range of

values for soil mixing depth, Z, for tilled and untilled soil; the original source of these values is not identified.
TABLE B-1-6

COPC LOSS CONSTANT DUE TO VOLATILIZATION

(SOIL INGESTION EQUATIONS)

(Page 1 of 5)

B-28

Description

This equation calculates the COPC loss constant from soil due to volatilization, and comes from Methodology for Assessing Health Risks Associated with Multiple Exposure Pathways to Combustor

Emissions (U.S. EPA 1998). The soil loss constant due to volatilization (ksv) is based on gas equilibrium coefficients and gas phase mass transfer. The first order decay constant, ksv, is obtained

by adapting the Hwang and Falco equation for soil vapor phase diffusion (Hwang and Falco 1986).

Uncertainties associated with this equation include the following:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeter in untilled soils, resulting in a greater mixing depth. This uncertainty may overestimate ksv.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in situ materials) compared to that of other residues. This

uncertainty may underestimate ksv.

Equation

Variable Definition Units Value

ksv COPC loss constant due to 

volatilization 

yr-1

3.1536 x 10+7 Units conversion factor s/yr

H Henry’s Law constant atmm3

/mol

Varies

This variable is COPC-specific. We discuss this variable in detail, and offer COPC-specific values in Appendix A-2. 

The following uncertainty is associated with this variable:

Values for this variable, estimated by using the parameters and algorithms in Appendix A-2, may under- or

overestimate the actual COPC-specific values. As a result, ksv may be under- or overestimated.
TABLE B-1-6

COPC LOSS CONSTANT DUE TO VOLATILIZATION

(SOIL INGESTION EQUATIONS)

(Page 2 of 5)

Variable Definition Units Value

B-29

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs

:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with U.S.

EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. Additional

information on this subject can be obtained from Brzuzy and Hites (1995), which presents soil profiles for dioxin

measurements. A default value of 2 cm for soil mixing depth for untilled soils is based on a study that profiled dioxin

measurements within soil (Brzuzy et al. 1995). A default value of 20 cm for soil mixing depth for tilled soils is based on U.S.

EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeter in untilled soils, resulting a greater

mixing depth. This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution in comparison to that of other

residues. This uncertainty may underestimate Cs and CstD. 

Kds

Soil-water partition coefficient cm3

water/g

soil

Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in Appendix A2.

R Universal gas constant atmm3

/mol-K

8.205 x 10-5

There are no uncertainties associated with this parameter.
TABLE B-1-6

COPC LOSS CONSTANT DUE TO VOLATILIZATION

(SOIL INGESTION EQUATIONS)

(Page 3 of 5)

Variable Definition Units Value

B-30

Ta

Ambient air temperature K 298

This variable is site-specific. U.S. EPA (1998) recommends a default ambient air temperature of 298 K.

The following uncertainty is associated with this variable:

To the extent that site-specific or local values for the variable are not available, default values may not accurately

represent site-specific conditions. We expect the uncertainty associated with the selection of a single value from

within the temperature range at a single location to be more significant than the uncertainty associated with choosing

a single ambient temperature to represent all localities. 

BD Soil bulk density g soil/cm3

soil

1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value of

1.5 g soil/cm3 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that a

value of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended soil bulk density value may not accurately represent site-specific soil conditions.

Dsoil

Solids particle density g/cm3

2.7

We recommend using this value, based on Blake and Hartage (1996) and Hillel (1980). 

The solids particle density will vary with location and soil type.

Da

Diffusivity of COPC in air cm2/s Varies

This value is COPC-specific. We discuss this variable in detail, and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

The default Da values may not accurately represent the behavior of COPCs under site-specific conditions. However,

we expect the degree of uncertainty to be minimal.
TABLE B-1-6

COPC LOSS CONSTANT DUE TO VOLATILIZATION

(SOIL INGESTION EQUATIONS)

(Page 4 of 5)

Variable Definition Units Value

B-31

2sw

Soil volumetric water content ml

water/cm3

soil

0.2

This variable depends on the available water and on soil structure. You can estimate 2sw as the midpoint between a soil’s field

capacity and wilting point, if you can identify a representative watershed soil. However, we recommend using 0.2 ml/cm3 as a

default value. This value is the midpoint of the range 0.1 (very sandy soils) to 0.3 (heavy loam/clay soils) recommended by

U.S. EPA (1998) (no source or reference is provided for this range) and is consistent with U.S. EPA (1994b).

The following uncertainty is associated with this variable:

(1) The default 2sw values may not accurately reflect site-specific or local conditions; therefore, ksv may be under- or

overestimated to a small extent, based on the limited range of values.

REFERENCES AND DISCUSSION

Blake, GR. and K.H. Hartge. 1996. Particle Density. Methods of Soil Analysis, Part 1: Physical and Mineralogical Methods. Second Edition. Arnold Klute, Ed. American Society of Agronomy,

Inc. Madison, WI., p. 381. 

Carsel, R.F., R.S, Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2. 

Pages 11-24.

This document is cited by U.S. EPA (1994b) as the source of a mean soil bulk density value, BD, of 1.5 (g soil/cm3 soil) for loam soil.

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York, New York.

Hwang S. T. and Falco, J. W. 1986. “Estimation of multimedia exposures related to hazardous waste facilities”, In: Pollutants in a Multimedia Environment. Yoram Cohen, Ed. Plenum Publishing

Corp. New York.

Miller, R.W. and D.T. Gardiner. 1998. In: Soils in Our Environment. J.U. Miller, Ed. Prentice Hall. Upper Saddle River, NJ. pp. 80-123.

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-specific Assessment Procedures External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This document presents value for soil, mixing depth, Zs, for tilled and untilled soil. 
TABLE B-1-6

COPC LOSS CONSTANT DUE TO VOLATILIZATION

(SOIL INGESTION EQUATIONS)

(Page 5 of 5)

B-32

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Waste. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

This document recommends a default soil density, BD, value of 1.5 (g soil/cm3

 soil), based on a mean value for loam soil that is taken from Carsel et al. (1988).

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document recommends the following:

C A range of values for soil mixing zone depth, Zs, for tilled and untilled soil; however, the source or basis for these values is not identified

C A default ambient air temperature of 298 K

C A range of soil volumetric water content, 2sw
TABLE B-2-1

SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 1 of 8)

B-33

Description

Use the equations in this table to calculate an average COPC soil concentration resulting from wet and dry deposition of particles and vapors to soil over the exposure duration. We recommend

assuming that COPCs are incorporated only to a finite depth (the soil mixing zone depth, Zs). Use the COPC soil concentration averaged over the exposure duration, represented by Cs, for

carcinogenic COPCs, where risk is averaged over the lifetime of an individual. Because the hazard quotient associated with noncarcinogenic COPCs is based on a reference dose rather than a

lifetime exposure, we recommend using the highest annual average COPC soil concentration occurring during the exposure duration period for noncarcinogenic COPCs. The highest annual

average COPC soil concentration would most likely occur at the end of the time period of combustion and is represented by CstD. 

The following uncertainties are associated with this variable:

(1) We assume that the time period for deposition of COPCs resulting from hazardous waste combustion is a conservative, long-term value. This assumption may overestimate Cs and CstD.

(2) Exposure duration values (T2) are based on historical mobility studies and won’t necessarily remain constant. Specifically, mobility studies indicate that most receptors that move

remain in the vicinity of the combustion unit; however, it is impossible to accurately predict the probability that these short-distance moves will influence exposure, based on factors

such as atmospheric transport of pollutants.

(3) A value of zero for T1

 doesn’t account for exposure that may have occurred from historic operations and emissions from burning hazardous waste. This may underestimate Cs and CstD.

(4) For soluble COPCs, leaching might lead to movement to below the mixing depth, resulting in lower concentrations within the mixing depth. This may overestimate Cs and CstD. 

(5) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in situ materials) compared to other residues. This may

underestimate Cs and CstD. 

Equation for Carcinogens

Soil Concentration Averaged Over Exposure Duration
TABLE B-2-1

SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 2 of 8)

B-34

Equation for Noncarcinogens

Highest Annual Average Soil Concentration

where

For mercury modeling

Use 0.48Q for total mercury and Fv = 0.85 in the mercury modeling equation to calculate Ds. Apportion the calculated Ds value into the divalent mercury (Hg2+) and methyl mercury (MHg)

forms based on the assumed 98% Hg2+ and 2% MHg speciation split in soils (see Chapter 2). Elemental mercury (Hg0) occurs in very small amounts in the vapor phase and does not exist in the

particle or particle-bound phase. Therefore, assume elemental mercury deposition onto soils is negligible or zero. Evaluate elemental mercury for the direct inhalation pathway only (Table

B-5-1).

Ds (Hg2+) = 0.98 Ds (Mercu ry)

Ds (MHg) = 0.02 Ds (Mercu ry)

Ds (Hg0) = 0.0

Evaluate divalent and methyl mercury as individual COPCs. Calculate Cs for divalent and methyl mercury using the corresponding (1) fate and transport parameters for mercuric chloride

(divalent mercury, Hg2+) and methyl mercury provided in Appendix A-2, and (2) Ds (Hg2+) and Ds (MHg) as calculated above. 
TABLE B-2-1

SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 3 of 8)

B-35

Variable Description Units Value

Cs Average soil concentration over

exposure duration 

mg COPC/kg

soil

CstD

Soil concentration at time tD mg COPC/kg

soil

Ds Deposition term mg COPC/kg

soil-yr

Varies

U.S. EPA (1994a) and NC DEHNR (1991) recommend incorporating the use of a deposition term into the Cs equation. 

Uncertainties associated with this variable include the following:

(1) Five of the variables in the equation for Ds (Q, Cyv, Dywv, Dywp, and Dydp) are COPC- and site-specific. 

Values of these variables are estimated through modeling. The direction and magnitude of any uncertainties

shouldn’t be generalized.

(2) Based on the narrow recommended ranges, we expect uncertainties associated with Vdv, Fv

, and BD to be low.

(3) Values for Zs vary by about one order of magnitude. Uncertainty is greatly reduced if you know whether soils

are tilled or untilled.

tD Time period over which deposition

occurs (time period of combustion)

yr 30

U.S. EPA (1998) suggests that this period of time can be $30 years. We recommend using 30 years unless site-specific

information is available indicating that this assumption is unreasonable (see Chapter 6 of the HHRAP). 

ks COPC soil loss constant due to all

processes

yr-1 Varies

This variable is COPC- and site-specific, and is calculated by using the equation in Table B-1-2. The COPC soil loss

constant is the sum of all COPC removal processes. 

Uncertainty associated with this variable includes the following:

COPC-specific values for ksg (one of the variables in the equation in Table B-1-2) are empirically determined

from field studies. No information is available on applying these values to the site-specific conditions associated

with affected facilities.
TABLE B-2-1

SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 4 of 8)

Variable Description Units Value

B-36

T2

Length of exposure duration yr 6, 30, or 40

We recommend the following reasonable maximum exposure (RME) values for T2

:

Exposure Duration RME Reference

Child Resident 6 years U.S. EPA (1997b)

Farmer Child

Fisher Child

Adult Resident and 30 years U.S. EPA (1997b)

Fisher

Farmer 40 years U.S. EPA (1994b)

U.S. EPA (1994c) recommended the following unreferenced values:

Exposure Duration Years 

Subsistence Farmer 40

Adult Resident 30

Subsistence Fisher 30

Child Resident 9

Uncertainties associated with this variable include the following:

(1) Exposure duration rates are based on historical mobility rates and may not remain constant. This assumption

may overestimate or underestimate Cs and CstD.

(2) Mobility studies indicate that most receptors that move remain in the vicinity of the emission sources; however,

it is impossible to accurately predict the likelihood that these short-distance moves will influence exposure, based

on factors such as atmospheric transport of pollutants. This assumption may overestimate or underestimate Cs

and CstD.

T1

Time period at the beginning of

combustion

yr 0

Consistent with U.S. EPA (1994bc), we recommend a value of 0 for T1.

The following uncertainty is associated with this variable:

A T1 of zero doesn’t account for exposure that may have occurred from historical operation or emissions from

the combustion of hazardous waste. This may underestimate Cs and CstD.

100 Units conversion factor mg-cm2

/kg-cm2
TABLE B-2-1

SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 5 of 8)

Variable Description Units Value

B-37

Q COPC emission rate g/s Varies

This variable is COPC- and site-specific. See Chapters 2 and 3 of the HHRAP for guidance regarding the calculation of

this variable. 

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs

:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with

U.S. EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A

default value of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil

(Brzuzy et al. 1995). A default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting a greater

mixing depth. This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution in comparison to that of

other residues. This uncertainty may underestimate Cs and CstD. 

BD Soil bulk density g soil/cm3

 soil 1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value

of 1.5 g soil/cm3 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that

a value of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended BD value may not accurately represent site-specific soil conditions; and may under- or

overestimate site-specific soil conditions to an unknown degree.
TABLE B-2-1

SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 6 of 8)

Variable Description Units Value

B-38

Fv

Fraction of COPC air concentration

in vapor phase 

unitless 0 to 1

This variable is COPC-specific. We discuss this variable and offer COPC-specific values in Appendix A-2. This range is

based on the values presented in Appendix A-2. Values are also presented in U.S. EPA (1994c) and NC DEHNR (1997).

Fv was calculated using an equation presented in Junge (1977) for all organic COPCs, including PCDDs and PCDFs. U.S.

EPA (1994c) states that Fv = 0 for all metals (except mercury).

The following uncertainties are associated with this variable:

(1) Our Fv calculations assume a default ST value for background plus local sources, rather than an ST value for urban

sources. If your site is located in an urban area, using the latter ST value may be more appropriate. Specifically,

the ST value for urban sources is about one order of magnitude greater than that for background plus local

sources, and it would result in a lower calculated Fv value; however, the Fv value is likely to be only a few

percent lower.

(2) According to Bidleman (1988), the equation used to calculate Fv assumes that the variable c (Junge constant) is

constant for all chemicals; however, the value of c depends on the chemical (sorbate) molecular weight, the

surface concentration for monolayer coverage, and the difference between the heat of desorption from

the particle surface and the heat of vaporization of the liquid phase sorbate. To the extent that site- or

COPC-specific conditions may cause the value of c to vary, uncertainty is introduced if a constant value

of c is used to calculate Fv

.

Dydv Unitized yearly average dry

deposition from vapor phase

s/m2

-yr Varies

This variable is COPC- and site-specific, and is determined by air modeling (see Chapter 3). Uncertainties associated with

this variable are site-specific.

Dywv Unitized yearly average wet

deposition from vapor phase 

s/m2

-yr Varies

This variable is COPC- and site-specific, and is determined by air modeling (see Chapter 3). Uncertainties associated with

this variable are site-specific.

Dydp Unitized yearly average dry

deposition from particle phase

s/m2-yr Varies

This variable is COPC- and site-specific, and is determined by air modeling (see Chapter 3). Uncertainties associated with

this variable are site-specific.

Dywp Unitized yearly average wet

deposition from particle phase

s/m2

-yr Varies

This variable is COPC- and site-specific, and is determined by air modeling (see Chapter 3). Uncertainties associated with

this variable are site-specific.
TABLE B-2-1

SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 7 of 8)

B-39

REFERENCES AND DISCUSSION

Bidleman, T.F. 1988. “Atmospheric Processes.” Environmental Science and Technology. Volume 22. Number 4. Pages 361-367.

For discussion, see References and Discussion, Table B-1-1.

Brzuzy, L.P. and R.A. Hites. 1995. “Estimating the Atmospheric Deposition of Polychlorinated Dibenzo-p-dioxins and Dibenzofurans from Soils.” Environmental Science and Technology. 

Volume 29. Pages 2090-2098.

This reference presents soil profiles for dioxin measurements.

Carsel, R.F., R.S. Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2.

Pages 11-24.

This reference is cited by U.S. EPA (1994b) as the source for a mean soil bulk density value, BD, of 1.5 (g soil/cm3

 soil) for loam soil.

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York.

Cited by U.S. EPA (1998) for the statement that BD is affected by the soil structure, such as looseness or compaction of the soil, depending on the water and clay content of the soil.

Junge, C.E. 1977. Fate of Pollutants in Air and Water Environments, Part I. Suffet, I.H., Ed. Wiley. New York. Pages 7-26.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This is one of the source documents for the equation in Table B-1-1. This document also recommends using (1) a deposition term, Ds, and (2) COPC-specific Fv

 values.

Research Triangle Institute (RTI). 1992. Preliminary Soil Action Level for Superfund Sites. Draft Interim Report. Prepared for U.S. EPA Hazardous Site Control Division, Remedial Operations

Guidance Branch. Arlington, Virginia. EPA Contract 68-W1-0021. Work Assignment No. B-03, Work Assignment Manager Loren Henning. December.

This document is a reference source for COPC-specific Fv

 values.

U.S. EPA. U.S. EPA. 1992. Estimating Exposure to Dioxin-Like Compounds. Draft. Office of Research and Development. Washington, D.C. EPA/600/6-88/005b. 

The External Review Draft of the MPE document (the final is U.S. EPA 1998) cites this document as the source of values for soil mixing zone depth, Zs

, for tilled and untilled soils.
TABLE B-2-1

SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 8 of 8)

B-40

U.S. EPA. 1993b. Addendum to the Methodology for Assessing Health Risks Associated with Indirect Exposure to Combustor Emissions. Working Group Recommendations. Office of Solid

Waste. Office of Research and Development. Washington, D.C. September 24.

This document is a reference for the equation in Table B-2-1. It recommends using a deposition term, Ds, and COPC-specific Fv values in the Cs equation.

U.S. EPA. 1994a. Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. April 15.

This document is a reference for the equation in Table B-2-1; it recommends that the following be used in the Cs equation: (1) a deposition term, Ds, and (2) a default soil bulk density

value of 1.5 g/cm3, based on a mean value for loam soil from Carsel et al. (1988).

U.S. EPA. 1994b. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-Specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June. 

This document recommends values for length of exposure duration, T2, for the farmer.

U.S. EPA. 1994c. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Office of Emergency and Remedial Response.

Office of Solid Waste. December.

This document recommends the following:

C Values for the length of exposure duration, T2

C Value of 0 for the time period of the beginning of combustion, T1

C Fv

 values that range from 0.27 to 1 for organic COPCs

C Default soil bulk density value of 1.5 g/cm3, based on a mean for loam soil from Carsel et al. (1988)

U.S. EPA. 1997a. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research

and Development. EPA 452/R-97-005. December.

U.S. EPA. 1997b. Exposure Factors Handbook. Office of Research and Development. EPA/600/P-95/002Fc. August.

This document is a reference source for values for length of exposure duration, T2

.

U.S. EPA. 1998. Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions (MPE). Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.
TABLE B-2-2

COPC SOIL LOSS CONSTANT

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 1 of 4)

B-41

Description

This equation calculates the COPC soil loss constant, which accounts for the loss of COPCs from soil by several mechanisms. 

Uncertainties associated with this equation include the following:

(1) COPC-specific values for ksg are empirically determined from field studies. No information is available regarding the application of these values to the site-specific conditions

associated with affected facilities.

(2) The source of the equations in Tables B-2-3 through B-2-5 has not been identified.

Equation

Variable Description Units Value

ks COPC soil loss constant due to all

processes

yr-1

ksg COPC loss constant due to biotic

and abiotic degradation

yr-1 Varies

This variable is COPC-specific. Values are available in the COPC tables in Appendix A-2.

“Degradation rate” values are also presented in NC DEHNR (1997); however, no reference or source is provided for the values. 

U.S. EPA (1994a) and U.S. EPA (1994b) state that ksg values are COPC-specific; however, all ksg values are presented as zero

(U.S. EPA 1994a) or as “NA” (U.S. EPA 1994b); the basis of these assumptions is not addressed. 

The following uncertainty is associated with this variable:

COPC-specific values for ksg are empirically determined from field studies; no information is available regarding the

application of these values to the site-specific conditions associated with affected facilities.
TABLE B-2-2

COPC SOIL LOSS CONSTANT

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 2 of 4)

Variable Description Units Value

B-42

kse COPC loss constant due to soil

erosion

yr-1 0

This variable is COPC- and site-specific, and is further discussed in Table B-2-3. Consistent with U.S. EPA (1994a), U.S. EPA

(1994b) and NC DEHNR (1997), we recommend a default value of zero for kse because contaminated soil erodes both onto the site

and away from the site.

Uncertainties associated with this variable include the following:

(1) The source of the equation in Table B-2-3 has not been identified.

(2) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in a greater mixing

depth. This uncertainty may overestimate kse.

(3) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in

situ materials) compared to other residues. This uncertainty may underestimate kse.

ksr COPC loss constant due to surface

runoff

yr-1 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-2-4. No reference document is cited for

this equation. Using this equation is consistent with U.S. EPA (1998) and NC DEHNR (1997). U.S. EPA (1994a) assumes that all

ksr values are zero but does not explain the basis of this assumption. 

Uncertainties associated with this variable (calculated by using the equation in Table B-2-4) include the following:

(1) The source of the equation in Table B-2-4 has not been identified.

(2) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in a greater mixing

depth. This uncertainty may overestimate ksr.

(3) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in

situ materials) compared to other residues. This uncertainty may underestimate ksr.

ksl COPC loss constant due to leaching yr-1 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-2-5. Using this equation is consistent with

U.S. EPA (1998), U.S. EPA (1994b), and NC DEHNR (1997). U.S. EPA (1994a) states that ksl is zero but doesn’t explain the basis

of this assumption.

Uncertainties associated with this variable (calculated by using the equation in Table B-2-5) include the following:

(1) The source of the equation in Table B-2-5 wasn’t identified.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in

situ materials) compared to other residues. This uncertainty may underestimate ksl.
TABLE B-2-2

COPC SOIL LOSS CONSTANT

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 3 of 4)

Variable Description Units Value

B-43

ksv COPC loss constant due to

volatilization

yr-1 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-2-6. This equation calculates the COPC

loss constant from soil due to volatilization, and was obtained from U.S. EPA (1998). The soil loss constant due to volatilization

(ksv) is based on gas equilibrium coefficients and gas phase mass transfer. The first order decay constant, ksv, is obtained by

adapting the Hwang and Falco equation for soil vapor phase diffusion (Hwang and Falco 1986).

Uncertainties associated with this equation include the following:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in a greater mixing

depth. This uncertainty may overestimate ksv.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in

situ materials) compared to other residues. This uncertainty may underestimate ksv.

REFERENCES AND DISCUSSION

Hwang S. T. and Falco, J. W. 1986. “Estimation of multimedia exposures related to hazardous waste facilities”, In: Pollutants in a Multimedia Environment. Yoram Cohen, Ed. Plenum Publishing

Corp. New York.

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the reference documents for the equations in Tables B-2-4 and B-2-5. This document is also cited as (1) the source for a range of COPC-specific degradation rates

(ksg), and (2) one of the sources that recommend assuming that the loss resulting from erosion (kse) is zero because of contaminated soil eroding both onto the site and away from the site.

U.S. EPA. 1994a. Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. April. 

This document is cited as a source for the assumptions that losses resulting from erosion (kse), surface runoff (ksr), degradation (ksg), leaching (ksl), and volatilization (ksv) are all zero.

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document is one of the reference documents for the equations in Tables B-2-4 and B-2-5. This document is also cited as one of the sources that recommend assuming that the loss

resulting from erosion (kse) is zero and the loss resulting from degradation (ksg) is “NA” or zero for all compounds.
TABLE B-2-2

COPC SOIL LOSS CONSTANT

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 4 of 4)

B-44

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document is one of the reference documents for the equations for ksr, ksl, and ksv.
TABLE B-2-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 1 of 5)

B-45

Description

This equation calculates the constant for COPC loss resulting from erosion of soil. Consistent with U.S. EPA (1994), U.S. EPA (1994b), and NC DEHNR (1997), we recommend a default value

of zero for kse because of contaminated soil eroding onto the site and away from the site. In site-specific cases where the permitting authority considers it appropriate to calculate a kse, we

recommend using the equation presented in this table along with associated uncertainties. You can find additional discussion on determining kse in U.S. EPA (1998). Uncertainties associated

with this equation include:

(1) For soluble COPCs, leaching might lead to movement below 2 centimeter in untilled soils, resulting in a greater mixing depth. This uncertainty may overestimate kse.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in situ materials) in comparison to that of other residues. This

uncertainty may underestimate kse.

Equation

Variable Description Units Value

kse COPC loss constant due to soil

erosion

yr-1 0

Consistent with U.S. EPA (1994), U.S. EPA (1994b), and NC DEHNR (1997), we recommend assuming a default value for

kse of zero because contaminated soil erodes both onto the site and away from the site. Uncertainty may overestimate kse.

0.1 Units conversion factor g-kg/cm2

-

m2

Xe

Unit soil loss kg/m2-yr Varies

This variable is site-specific and is calculated by using the equation in Table B-4-13.

The following uncertainty is associated with this variable:

All of the equation variables are site-specific. Using default values rather than site-specific values for any or all of

these variables will result in unit soil loss (Xe) estimates that are under- or overestimated to some degree. Based on

default values, Xe estimates can vary over a range of less than two orders of magnitude.
TABLE B-2-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 2 of 5)

Variable Description Units Value

B-46

SD Sediment delivery ratio unitless Varies

This value is site-specific and is calculated by using the equation in Table B-4-14.

Uncertainties associated with this variable include the following: 

(1) The recommended default values for the empirical intercept coefficient, a, are average values that are based on

studies of sediment yields from various watersheds. Therefore, those default values may not accurately represent

site-specific watershed conditions. As a result, use of these default values may under- or overestimate SD.

(2) The recommended default value for the empirical slope coefficient, b, is based on a review of sediment yields from

various watersheds. This single default value may not accurately represent site-specific watershed conditions. As a

result, use of this default value may under- or overestimate SD.

ER Soil enrichment ratio unitless Inorganics: 1

Organics: 3

COPC enrichment occurs because (1) lighter soil particles erode more quickly than heavier soil particles, and (2) concentration

of organic COPCs—which is a function of organic carbon content of sorbing media—is expected to be higher in eroded

material than in in-situ soil (U.S. EPA 1998). In the absence of site-specific data, we recommend a default value of 3 for

organic COPCs and 1 for inorganic COPCs. This is consistent with other Agency guidance (1998), which recommends a

range of 1 to 5 and a value of 3 as a “reasonable first estimate.” This range has been used for organic matter, phosphorus, and

other soil-bound COPCs (U.S. EPA 1998); however, no sources or references were provided for this range. ER is generally

higher in sandy soils than in silty or loamy soils (U.S. EPA 1998).

The following uncertainty is associated with this variable:

The default ER value may not accurately reflect site-specific conditions; therefore, kse may be over- or

underestimated to an unknown extent. Using county-specific ER values will reduce the extent of any uncertainties.

BD Soil bulk density g soil/cm3

soil

1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value of

1.5 g soil/cm3 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that a

value of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended BD value may not accurately represent site-specific soil conditions; and may under- or

overestimate site-specific soil conditions to an unknown degree.
TABLE B-2-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 3 of 5)

Variable Description Units Value

B-47

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs

:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with U.S.

EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A default

value of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil (Brzuzy et al.

1995). A default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting a greater

mixing depth. This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution compared to other residues. 

This uncertainty may underestimate Cs and CstD. 

Kds

Soil-water partition coefficient ml water/g

soil 

(or cm3

water/g soil)

Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in Appendix A2.

2sw

Soil volumetric water content ml

water/cm3

soil

0.2

This variable is site-specific, and depends on the available water and on soil structure; you can estimate 2sw as the midpoint

between a soil’s field capacity and wilting point, if you can identify a representative watershed soil. However, we recommend 

using 0.2 ml/cm3 as a default value. This value is the midpoint of the range 0.1 (very sandy soils) to 0.3 (heavy loam/clay

soils) recommended by U.S. EPA (1998) (no source or reference is provided for this range) and is consistent with U.S. EPA

(1994b).

The following uncertainty is associated with this variable:

The default 2sw value may not accurately reflect site-specific or local conditions; therefore, kse may be under- or

overestimated to a small extent, based on the limited range of values.
TABLE B-2-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 4 of 5)

B-48

REFERENCES AND DISCUSSION

Carsel, R.F., R.S. Parish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2. 

Pages 11-24.

This document is cited by U.S. EPA (1994b) as the source for a mean soil bulk density, BD, value of 1.5 (g soil/cm3 soil) for loam soil. 

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York.

This document is cited by U.S. EPA (1998) for the statement that soil bulk density, BD, is affected by the soil structure, such as looseness or compaction of the soil, depending on the water

and clay content of the soil.

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the sources that recommend assuming that the loss resulting from erosion (kse) is zero because contaminated soil erodes both onto the site and away from the site.

U.S. EPA. 1994. Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. April. 

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This document is the source of values for soil mixing zone depth, Zs

, for tilled and untilled soil, as cited in U.S. EPA (1993). 

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment

Guidance for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document recommends (1) a default soil bulk density value of 1.5 (g soil/cm3 soil), based on a mean value for loam soil that is taken from Carsel et al. (1988), and (2) a default soil

volumetric water content, 2sw, value of 0.2 (ml water/cm3 soil), based on U.S. EPA (1993).
TABLE B-2-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 5 of 5)

B-49

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document is the source of a range of COPC enrichment ratio, ER, values. The recommended range, 1 to 5, was used for organic matter, phosphorous, and other soul-bound COPCs. 

This document recommends a value of 3 as a “reasonable first estimate,” and states that COPC enrichment occurs because lighter soil particles erode more quickly than heavier soil

particles. Lighter soil particles have higher ratios of surface area to volume and are higher in organic matter content. Therefore, concentration of organic COPCs, which is a function of the

organic carbon content of sorbing media, is expected to be higher in eroded material than in in situ soil.

This document is also a source of the following:

C A range of soil volumetric water content (2sw) values of 0.1 ml water/cm3 soil (very sandy soils) to 0.3 ml water/cm3 soil (heavy loam/clay soils). However, no source or reference

is provided for this range.

C A range of values for soil mixing zone depth, Zs, for tilled and untilled soil

C The equations in Tables B-1-3 and B-1-5.
TABLE B-2-4

COPC LOSS CONSTANT DUE TO RUNOFF

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 1 of 4)

B-50

Description

This equation calculates the COPC loss constant due to runoff of soil. Uncertainties associated with this equation include the following:

(1) For soluble COPCs, leaching might result in movement to below 2 centimeter in untilled soils, resulting in a greater mixing depth. This uncertainty may overestimate ksr.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution in comparison to that of other residues. This uncertainty may underestimate ksr.

Equation

Variable Description Units Value

ksr COPC loss constant due to runoff yr-1

RO Average annual surface runoff from

pervious areas

cm/yr Varies

This variable is site-specific. According to U.S. EPA (1998), U.S. EPA (1994b), and NC DEHNR (1997), you can estimate RO

by using the Water Atlas of the United States (Geraghty et al. 1973). According to NC DEHNR (1997), you can also use more

detailed, site-specific procedures for estimating the amount of surface runoff, such as those based on the U.S. Soil Conservation

Service curve number equation (CNE). U.S. EPA (1985) is cited as an example of such a procedure.

The following uncertainty is associated with this variable:

To the extent that site-specific or local average annual surface runoff information is not available, default or

estimated values may not accurately represent site-specific or local conditions. As a result, ksl may be under- or

overestimated to an unknown degree.
TABLE B-2-4

COPC LOSS CONSTANT DUE TO RUNOFF

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 2 of 4)

Variable Description Units Value

B-51

2sw

Soil volumetric water content ml

water/cm3

soil

0.2

This variable is site-specific, and depends on the available water and on soil structure; you can estimate 2sw as the midpoint

between a soil’s field capacity and wilting point, if you can identify a representative watershed soil. We recommend using 0.2

ml/cm3 as a default value. This value is the midpoint of the range 0.1 (very sandy soils) to 0.3 (heavy loam/clay soils),

recommended by U.S. EPA (1998) (no source or reference is provided for this range), and is consistent with U.S. EPA (1994b)

and NC DEHNR (1997).

The following uncertainty is associated with this variable:

The default 2sw value may not accurately reflect site-specific or local conditions; therefore, ksr may be under- or

overestimated to a small extent, based on the limited range of values.

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with U.S.

EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A default

value of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil (Brzuzy et al.

1995). A default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998).

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting a greater

mixing depth. This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution in comparison to that of other

residues. This uncertainty may underestimate Cs and CstD. 

Kds

Soil-water partition coefficient ml water/g

soil 

(or cm3

water/g

soil)

Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in Appendix A-2.
TABLE B-2-4

COPC LOSS CONSTANT DUE TO RUNOFF

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 3 of 4)

Variable Description Units Value

B-52

BD Soil bulk density g soil/cm3

soil

1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value of

1.5 g soil/cm3 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that a value

of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended soil bulk density value may not accurately represent site-specific soil conditions.

REFERENCES AND DISCUSSION

Carsel, R.F., R.S. Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2. 

Pages 11-24.

This document is cited by U.S. EPA (1994b) as the source of a mean soil bulk density, BD, value of 1.5 (g soil/cm3 soil) for loam soil. 

Geraghty, J.J., D.W. Miller, F. Van der Leeden, and F.L. Troise. 1973. Water Atlas of the United States. Water Information Center, Port Washington, New York.

This document is cited by U.S. EPA (1998), U.S. EPA (1994), and NC DEHNR (1997) as a reference to calculate average annual runoff, RO. This reference provides maps with isolines of

annual average surface water runoff, which is defined as all flow contributions to surface water bodies, including direct runoff, shallow interflow, and ground water recharge. Because these

values are total contributions and not only surface runoff, U.S. EPA (1994) recommends that the volumes be reduced by 50 percent in order to estimate surface runoff.

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York.

This document is cited by U.S. EPA (1998) for the statement that soil bulk density, BD, is affected by the soil structure, such as looseness or compaction of the soil, depending on the water

and clay content of the soil.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the source documents that recommends using Table B-2-4; however, this document is not the original source of this equation (this source is unknown). This

document also recommends the following:

C Estimating annual current runoff, RO (cm/yr), by using the Water Atlas of the United States (Geraghty et al. 1973) or site-specific procedures, such as using the U.S. Soil

Conservation Service curve number equation (CNE); U.S. EPA (1985) is cited as an example of such a procedure.

C Default value of 0.2 (ml water/cm3 soil) for soil volumetric water content (2sw)
TABLE B-2-4

COPC LOSS CONSTANT DUE TO RUNOFF

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 4 of 4)

B-53

U.S. EPA. 1985. Water Quality Assessment: A Screening Procedure for Toxic and Conventional Pollutants in Surface and Ground Water—Part I (Revised. 1985). Environmental Research

Laboratory. Athens, Georgia. EPA/600/6-85/002a. September.

This document is cited by NC DEHNR (1997) as an example of the use of the U.S. Soil Conservation Service CNE to estimate site-specific surface runoff. 

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc June..

This document presents a range of values for soil mixing zone depth, Zs, for tilled and untilled soil as cited in U.S. EPA (1993). 

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment

Guidance for RCRA Hazardous Waste Combustion Facilities. Offices of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document recommends the following:

C Estimation of average annual runoff, RO, by using the Water Atlas of the United States (Geraghty et al. 1973)

C Default soil bulk density, BD, value of 1.5 (g soil/cm3

 soil), based on the mean for loam soil that is taken from Carsel et al. (1988)

C Default soil volumetric water content, 2sw, value of 0.2 (ml water/cm3soil), based on U.S. EPA (1993)

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document recommends the following:

C A range of soil volumetric water content, 2sw, values of 0.1 (very sandy soils) to 0.3 (heavy loam/clay soils) (the original source of, or reference for, these values is not identified)

C A range of values for soil mixing depth, Zs, for tilled and untilled soil (the original source of, or reference for, these values is not identified)

C Using the Water Atlas of the United States (Geraghty et al. 1973) to calculate average annual runoff, RO
TABLE B-2-5

COPC LOSS CONSTANT DUE TO LEACHING

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 1 of 5)

B-54

Description

This equation calculates the constant for COPC loss resulting from leaching of soil. Uncertainties associated with this equation include the following:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in a greater mixing depth. This uncertainty may overestimate ksl.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in situ materials) compared to other residues. This uncertainty

may underestimate ksl.

(3) The original source of this equation hasn’t been identified. U.S. EPA (1998) presents the equation as shown here. U.S. EPA (1994b) and NC DEHNR (1997) replaced the numerator as

shown with “q”, defined as average annual recharge (cm/yr).

Equation

Variable Description Units Value

ksl COPC loss constant due to leaching yr-1

P Average annual precipitation cm/yr 18.06 to 164.19

This variable is site-specific. This range is based on information presented in U.S. EPA (1998), representing data for 69

selected cities (U.S. Bureau of Census 1987; Baes et al. 1984). The 69 selected cities are not identified; however, they appear

to be located throughout the continental United States. We recommend using site-specific data.

The following uncertainty is associated with this variable:

(1) To the extent that a site is not located near an established meteorological data station, and site-specific data are not

available, default average annual precipitation data may not accurately reflect site-specific conditions. As a result, ksl

may be under- or overestimated. However, average annual precipitation data are reasonably available; therefore, we

expect uncertainty introduced by this variable to be minimal.
TABLE B-2-5

COPC LOSS CONSTANT DUE TO LEACHING

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 2 of 5)

Variable Description Units Value

B-55

I Average annual irrigation cm/yr 0 to 100

This variable is site-specific. This range is based on information presented in U.S. EPA (1998), representing data for 69

selected cities (Baes et al. 1984). The 69 selected cities are not identified; however, they appear to be located throughout the

continental United States.

The following uncertainty is associated with this variable:

To the extent that site-specific or local average annual irrigation information is not available, default values

(generally based on the closest comparable location) may not accurately reflect site-specific conditions. As a result,

ksl may be under- or overestimated to an unknown degree.

RO Average annual surface runoff from

pervious areas

cm/yr Varies

This variable is site-specific. According to U.S. EPA (1998), U.S. EPA (1994b), and NC DEHNR (1997), you can estimate

RO by using the Water Atlas of the United States (Geraghty et al. 1973). According to NC DEHNR (1997), you can also use

more detailed, site-specific procedures, such as those based on the U.S. Soil Conservation Service CNE. U.S. EPA (1985) is

cited as an example of such a procedure.

The following uncertainty is associated with this variable:

To the extent that site-specific or local average annual surface runoff information is not available, default or

estimated values may not accurately represent site-specific or local conditions. As a result, ksl may be under- or

overestimated to an unknown degree.

Ev

Average annual evapotranspiration cm/yr 35 to 100

This variable is site-specific. This range is based on information presented in U. S. EPA (1998), representing data from 69

selected cities. The 69 selected cities are not identified; however, they appear to be located throughout the continental United

States.

The following uncertainty is associated with this variable:

To the extent that site-specific or local average annual evapotranspiration information is not available, default values

may not accurately reflect site-specific conditions. As a result, ksl may be under- or overestimated to an unknown

degree.
TABLE B-2-5

COPC LOSS CONSTANT DUE TO LEACHING

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 3 of 5)

Variable Description Units Value

B-56

2sw

Soil volumetric water content (ml

water/cm3

soil)

0.2

This variable is site-specific, and depends on the available water and on soil structure. You can estimate 2sw as the midpoint

between a soil’s field capacity and wilting point, if you can identify a representative watershed soil. We recommend using 0.2

ml/cm3 as a default value. This value is the midpoint of the range of 0.1 (very sandy soils) to 0.3 (heavy loam/clay soils)

recommended by U.S. EPA (1998) (no source or reference is provided for this range) and is consistent with U.S. EPA (1994b)

and NC DEHNR (1997).

The following uncertainty is associated with this variable:

The default 2sw value may not accurately reflect site-specific or local conditions; therefore, ksl may be under- or

overestimated to a small extent, based on the limited range of values.

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with U.S.

EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A default

value of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil (Brzuzy et al.

1995). A default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting a greater

mixing depth. This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution in comparison to that of other

residues. This uncertainty may underestimate Cs and CstD. 
TABLE B-2-5

COPC LOSS CONSTANT DUE TO LEACHING

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 4 of 5)

Variable Description Units Value

B-57

BD Soil bulk density g soil/cm3

soil

1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value of

1.5 g soil/cm3 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that a value

of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended BD value may not accurately represent site-specific soil conditions.

Kds

Soil-water partition coefficient cm3 water/g

soil

Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in Appendix A-2.

REFERENCES AND DISCUSSION

Baes, C.F., R.D. Sharp, A.L. Sjoreen and R.W. Shor. 1984. “A Review and Analysis of Parameters for Assessing Transport of Environmentally Released Radionuclides through Agriculture.” 

Prepared for the U.S. Department of Energy under Contract No. DEAC05-840R21400.

For the continental United States, as cited in U.S. EPA (1998), this document is the source of a series of maps showing: (1) average annual precipitation (P), (2) average annual irrigation

(I), and (3) average annual evapotranspiration isolines.

Carsel, R.F., R.S. Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2. 

Pages 11-24.

This document is cited by U.S. EPA (1994b) as the source for a mean soil bulk density value, BD, of 1.5 g/cm3 for loam soil. 

Geraghty, J.J., D.W. Miller, F. Van der Leeden, and F.L. Troise. 1973. Water Atlas of the United States. Water Information Center, Port Washington, New York.

This document is cited by NC DEHNR (1997), U.S. EPA (1994b), and U.S. EPA (1998) as a reference for calculating average annual runoff, RO. This document provides maps with

isolines of annual average surface runoff, which is defined as all flow contributions to surface water bodies, including direct runoff, shallow interflow, and ground water recharge. Because

these volumes are total contributions and not only surface runoff, U.S. EPA (1994b) recommends that the volumes be reduced by 50 percent in order to estimate average annual surface

runoff.
TABLE B-2-5

COPC LOSS CONSTANT DUE TO LEACHING

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 5 of 5)

B-58

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York, New York.

This document is cited by U.S. EPA (1998) for the statement that soil bulk density, BD, is affected by the soil structure, such as looseness or compaction of the soil, depending on the water

and clay content of the soil.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the source documents that cites the use of the equation in Table B-2-5. However, the document is not the original source of this equation. This document also

recommends the following:

C Estimation of average annual surface runoff, RO (cm/yr), by using the Water Atlas of the United States (Geraghty et al. 1973) or site-specific procedures, such as using the U.S.

Soil Conservation Service CNE; U.S. EPA 1985 is cited as an example of such a procedure.

C A default value of 0.2 (ml water/cm3 soil) for soil volumetric water content, 2sw

U.S. Bureau of the Census. 1987. Statistical Abstract of the United States: 1987. 107th edition. Washington, D.C.

This document is a source of average annual precipitation (P) information for 69 selected cites, as cited in U.S. EPA (1990); these 69 cities are not identified. 

U.S. EPA. 1985. Water Quality Assessment: A Screening Procedure for Toxic and Conventional Pollutants in Surface and Groundwater. Part I (Revised 1985). Environmental Research

Laboratory. Athens, Georgia. EPA/600/6-85/002a. September.

This document is cited by NC DEHNR (1997) as an example of the use of the U.S. Soil Conservation Service CNE to estimate RO. 

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-specific Assessment Procedures. External Review Draft Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc June..

This document presents values for soil mixing depth, Zs

, for tilled and untilled soil, as cited in U.S. EPA (1998). 

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document recommends (1) a default soil volumetric water content, 2sw, value of 0.2 (ml water/cm3

 soil), and (2) a default soil bulk density, BD, value of 1.5 (g soil/cm3 soil), based on a

mean value for loam soil from Carsel et al. (1988).

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document is one of the reference source documents for the equation in Table B-2-5. The original source of this equation is not identified. This document also presents a range of

values for soil mixing depth, Z, for tilled and untilled soil; the original source of these values is not identified.
TABLE B-2-6

COPC LOSS CONSTANT DUE TO VOLATILIZATION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 1 of 4)

B-59

Description

This equation calculates the COPC loss constant from soil due to volatilization, and was obtained from Methodology for Assessing Health Risks Associated with Multiple Exposure Pathways to

Combustor Emissions (U.S. EPA 1998). The soil loss constant due to volatilization (ksv) is based on gas equilibrium coefficients and gas phase mass transfer. The first order decay constant, ksv,

is obtained by adapting the Hwang and Falco equation for soil vapor phase diffusion (Hwang and Falco 1986).

Uncertainties associated with this equation include the following:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in a greater mixing depth. This uncertainty may overestimate ksv.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in situ materials) compared to other residues. This uncertainty

may underestimate ksv.

Equation

Variable Definition Units Value

ksv COPC loss constant due to 

volatilization 

yr-1

3.1536 x 10+07 Units conversion factor s/yr

H Henry’s Law constant atmm3

/mol

Varies

This variable is COPC-specific. We discuss this variable in detail, and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

Values for this variable, estimated by using the parameters and algorithms in Appendix A-2, may under- or

overestimate the actual COPC-specific values. As a result, ksv may be under- or overestimated.
TABLE B-2-6

COPC LOSS CONSTANT DUE TO VOLATILIZATION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 2 of 4)

Variable Definition Units Value

B-60

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs

:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with U.S.

EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A default

value of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil (Brzuzy et al.

1995). A default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in a greater

mixing depth. This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution compared to other residues. 

This uncertainty may underestimate Cs and CstD. 

Kds

Soil-water partition coefficient cm3

water/g

soil

Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in Appendix A2.

R Universal gas constant atmm3

/mol-K

8.205 x 10-5

There are no uncertainties associated with this parameter.

Ta

Ambient air temperature K 298

This variable is site-specific. U.S. EPA (1990) also recommends an ambient air temperature of 298 K.

The following uncertainty is associated with this variable:

To the extent that site-specific or local values for the variable are not available, default values may not accurately

represent site-specific conditions. We expect the uncertainty associated with the selection of a single value from

within the temperature range at a single location to be more significant than the uncertainty associated with choosing

a single ambient temperature to represent all localities. 
TABLE B-2-6

COPC LOSS CONSTANT DUE TO VOLATILIZATION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 3 of 4)

Variable Definition Units Value

B-61

BD Soil bulk density g soil/cm3

soil

1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value of

1.5 g soil/cm3 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that a

value of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended soil bulk density value may not accurately represent site-specific soil conditions.

Dsoil

Solids particle density g/cm3

2.7

We recommend using this value, based on Blake and Hartage (1996) and Hillel (1980). 

The solids particle density will vary with location and soil type.

Da

Diffusivity of COPC in air cm2/s Varies

This value is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in the

HHRAP companion database. 

The following uncertainty is associated with this variable:

The default Da values may not accurately represent the behavior of COPCs under site-specific conditions. However,

we expect the degree of uncertainty to be minimal.

2sw

Soil volumetric water content ml/cm3 soil 0.2

This variable depends on the available water and on soil structure. You can estimate 2sw as the midpoint between a soil’s field

capacity and wilting point, if you can identify a representative watershed soil. However, we recommend using 0.2 ml/cm3 as a

default value. This value is the midpoint of the range 0.1 (very sandy soils) to 0.3 (heavy loam/clay soils) recommended by

U.S. EPA (1998) (no source or reference is provided for this range) and is consistent with U.S. EPA (1994b).

The following uncertainty is associated with this variable:

(1) Default 2sw values may not accurately reflect site-specific or local conditions; therefore, ksv may be under- or

overestimated to a small extent, based on the limited range of values.
TABLE B-2-6

COPC LOSS CONSTANT DUE TO VOLATILIZATION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 4 of 4)

B-62

REFERENCES AND DISCUSSION

Blake, GR. and K.H. Hartge. 1996. Particle Density. Methods of Soil Analysis, Part 1: Physical and Mineralogical Methods. Second Edition. Arnold Klute, Ed. American Society of Agronomy,

Inc. Madison, WI., p. 381. 

Carsel, R.F., R.S, Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2. 

Pages 11-24.

This document is cited by U.S. EPA (1994b) as the source of a mean soil bulk density value, BD, of 1.5 (g soil/cm3 soil) for loam soil.

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York, New York.

Hwang S. T. and Falco, J. W. 1986. “Estimation of multimedia exposures related to hazardous waste facilities”, In: Pollutants in a Multimedia Environment. Yoram Cohen, Ed. Plenum Publishing

Corp. New York.

Miller, R.W. and D.T. Gardiner. 1998. In: Soils in Our Environment. J.U. Miller, Ed. Prentice Hall. Upper Saddle River, NJ. pp. 80-123.

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This document presents value for soil, mixing depth, Zs, for tilled and untilled soil.

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Waste. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

This document recommends a default soil density, BD, value of 1.5 (g soil/cm3 soil), based on a mean value for loam soil that is taken from Carsel et al. (1988).

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document recommends the following:

C A range of values for soil mixing zone depth, Zs, for tilled and untilled soil; however, the source or basis for these values is not identified

C A default ambient air temperature of 298 K

C A range of soil volumetric water content, 2sw
TABLE B-2-7

ABOVEGROUND PRODUCE CONCENTRATION DUE TO DIRECT DEPOSITION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 1 of 12)

B-63

Description

This equation calculates the COPC concentration in aboveground vegetation, due to wet and dry deposition of COPCs onto plant surfaces. The limitations and uncertainty in calculating this value

include the following:

(1) Uncertainties associated with the variables Q, Dydp, and Dywp are site-specific.

(2) The recommended equation for calculating kp values does not consider chemical degradation processes. Including chemical degradation would decrease the amount of time that a

chemical remains on plant surfaces (half-life) and thereby increase kp values. Pd decreases with increased kp values. Reduction of half-life from the assumed 14 days to 2.8 days, for

example, would decrease Pd about 5-fold.

(3) Calculating other parameter values (for example, Fw and Rp) is based directly or indirectly on studies of vegetation other than aboveground produce (primarily grasses). To the extent

that the calculated parameter values don’t accurately represent aboveground produce-specific values, uncertainty is introduced. 

(4) The uncertainties associated with the variables Fv

, Tp, and Yp are not expected to be significant.

As highlighted above, Pd is most significantly affected by the values assumed for kp and the extent to which parameter values (assumed based on studies of pasture grass) accurately reflect

aboveground produce-specific values.

Equation

For mercury modeling

Use 0.48Q for total mercury and Fv = 0.85 in the mercury modeling equation above to calculate Pd. Apportion the calculated Pd value into the divalent mercury (Hg2+) and methyl mercury

(MHg) forms based on the 78% Hg2+ and 22% MHg speciation split in aboveground produce (see Chapter 2). 

Pd (Hg2+) = 0.78 Pd (Mercu ry)

Pd (MHG) = 0.22 Pd (Mercu ry)

Evaluate divalent and methyl mercury as individual COPCs. Calculate Pd for divalent and methyl mercury using the corresponding equations above.
TABLE B-2-7

ABOVEGROUND PRODUCE CONCENTRATION DUE TO DIRECT DEPOSITION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 2 of 12)

B-64

Variable Description Units Value

Pd Concentration of COPC in

aboveground produce due to direct

(wet and dry) deposition

mg COPC/kg

DW

1000 Units conversion factor mg/g

Q COPC-specific emission rate g/s Varies

This value is COPC- and site-specific and is determined by air dispersion modeling. See Chapters 2 and 3 for guidance

on calculating this variable. Uncertainties associated with this variable are also COPC- and site-specific.

 Fv

Fraction of COPC air concentration

in vapor phase

unitless 0 to 1

This variable is COPC-specific. We discuss Fv

 in detail in Appendix A-2, and offer COPC-specific values in the

HHRAP companion database. This range is based on values presented in Appendix A-2. U.S. EPA (1994b) and NC

DEHNR (1997) also present values.

Fv was calculated using an equation presented in Junge (1977) for all organic COPCs, including PCDDs and PCDFs. 

U.S. EPA (1994c) states that Fv = 0 for all metals (except mercury).

The following uncertainties are associated with this variable:

(1) The Fv calculation uses a default ST value for background plus local sources, rather than an ST value for urban

sources. If a specific site is located in an urban area, using the latter ST

 value may be more appropriate. 

Specifically, the ST

 value for urban sources is about one order of magnitude greater than that for background

plus local sources, and it would result in a lower calculated Fv

 value; however, the Fv

 value is likely to be

only a few percent lower.

(2) According to Bidleman (1988), the Fv equation assumes that the variable c (Junge constant) is constant

for all chemicals; however, the value of c depends on the chemical (sorbate) molecular weight, the

surface concentration for monolayer coverage, and the difference between the heat of desorption from

the particle surface and the heat of vaporization of the liquid phase sorbate. To the extent that site- or

COPC-specific conditions may cause the value of c to vary, uncertainty is introduced if a constant value

of c is used to calculate Fv

.

(3) Based on U.S. EPA (1994a), the Fv

 value for dioxins (PCDD/PCDF) is intended to represent 2, 3, 7, 8-TCDD

TEQs by weighting data for all dioxin and furan congeners with nonzero TEFs. Uncertainty is introduced,

because the Agency has been unable to verify the recommended Fv value for dioxins.

Dydp Unitized yearly average dry

deposition from particle phase

s/m2-yr Varies

This variable is COPC- and site-specific, and is determined by air dispersion modeling (see Chapter 3). Uncertainties

associated with this variable are site-specific.
TABLE B-2-7

ABOVEGROUND PRODUCE CONCENTRATION DUE TO DIRECT DEPOSITION

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(Page 3 of 12)

Variable Description Units Value

B-65

Rp Interception fraction of the edible

portion of plant

unitless 0.39

We recommend using this default Rp value because it represents the most current information available; specifically,

productivity and relative ingestion rates. 

As summarized in Baes et al. (1984), experimental studies of pasture grasses identified a correlation between initial Rp

values and productivity (standing crop biomass [Yp]) (Chamberlain 1970):

Rp = 1 - e -(@ Yp

where

Rp = Interception fraction of the edible portion of plant (unitless)

( = Empirical constant. Chamberlain (1970) presented a range of 2.3 to 3.3; Baes et al. (1984) used

2.88, the midpoint for pasture grasses.

Yp = Yield or standing crop biomass (productivity) (kg WW/m2

); the use of Yp value on a wet weight

basis is in contrast to the equation presented in this table, which presents Yp on a dry weight basis.

Baes et al. (1984) proposed using the same empirical relationship developed by Chamberlain (1970) for other

vegetation classes. Class-specific estimates of the empirical constant, (, were developed by forcing an exponential

regression equation through several points, including average and theoretical maximum estimates of Rp and Yp (Baes et

al. 1984) . The class-specific Rp estimates were then weighted, by relative ingestion of each class, to arrive at the

weighted average Rp value of 0.39.

U.S. EPA (1994b) and U.S. EPA (1995) recommended a weighted average Rp value of 0.05. However, the relative

ingestion rates used in U.S. EPA (1994b) and U.S. EPA (1995) to weight the average Rp value were derived from U.S.

EPA (1992) and U.S. EPA (1994b). The most current guidance available for ingestion rates of homegrown produce is

the 1997 Exposure Factors Handbook (U.S. EPA 1997). The default Rp value of 0.39 was weighted by relative

ingestion rates of homegrown exposed fruit and exposed vegetables found in U.S. EPA (1997).

Uncertainties associated with this variable include the following:

(1) The empirical relationship developed by Chamberlain (1970) on the basis of a study of pasture grass may not

accurately represent aboveground produce.

(2) The empirical constants developed by Baes et al. (1984) for use in the empirical relationship developed by

Chamberlain (1970) may not accurately represent site-specific mixes of aboveground produce.
TABLE B-2-7

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(Page 4 of 12)

Variable Description Units Value

B-66

Fw Fraction of COPC wet deposition

that adheres to plant surfaces

unitless 0.2 for anions

0.6 for cations and most organics

We recommend using the chemical class-specific values of 0.2 for anions and 0.6 for cations and most organics, as

estimated by U.S. EPA (1994b) and U.S. EPA (1995). These values are the best available information, based on a

review of the current scientific literature, with the following exception: We recommend using an Fw value of 0.2 for

the three organic COPCs that ionize to anionic forms. These include (1) 4-chloroaniline, (2) n-nitrosodiphenylamine,

and (3) n-nitrosodi-n-proplyamine (see Appendix A-2).

The values estimated by U.S. EPA (1994b) and U.S. EPA (1995) were based on information presented in Hoffman, et

al. (1992), which presented values for a parameter (r) termed the “interception fraction.” These values were based on a

study in which soluble radionuclides and insoluble particles labeled with radionuclides were deposited onto pasture

grass via simulated rain. The parameter (r) is defined as “the fraction of material in rain intercepted by vegetation and

initially retained” or, essentially, the product of Rp and Fw, as defined:

r = Rp @ Fw

The r values developed by Hoffman, et al. (1992) were divided by an Rp value of 0.5 for forage (U.S. EPA 1994b). 

The Fw values developed by U.S. EPA (1994b) are 0.2 for anions and 0.6 for cations and insoluble particles. U.S.

EPA (1994b) and U.S. EPA (1995) recommended using the Fw value calculated by using the r value for insoluble

particles to represent organic compounds; however, no rationale for this recommendation was provided.

Interception values (r)—as defined by Hoffman, et al. (1992)—have not been experimentally determined for

aboveground produce. Therefore, U.S. EPA (1994b) and U.S. EPA (1995) apparently defaulted and assumed that the

Fw values calculated for pasture grass (similar to forage) also apply to aboveground produce. The rationale for this

recommendation was not provided.

Uncertainties associated with this variable include the following:

(1) Values of r developed experimentally for pasture grass may not accurately represent aboveground

produce-specific r values.

(2) Values of r assumed for most organic compounds, based on the behavior of insoluble polystyrene

microspheres tagged with radionuclides, may not accurately represent the behavior of organic compounds

under site-specific conditions.

Dywp Unitized yearly wet deposition in

particle phase

s/m2-yr Varies

This variable is COPC- and site-specific, and is determined by air dispersion modeling (see Chapter 3). Uncertainties

associated with this variable are site-specific.
TABLE B-2-7

ABOVEGROUND PRODUCE CONCENTRATION DUE TO DIRECT DEPOSITION

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(Page 5 of 12)

Variable Description Units Value

B-67

kp Plant surface loss coefficient yr-1 18

We recommend the kp value of 18 recommended by U.S. EPA (1998) and U.S. EPA (1994b). The recommended 

value is the midpoint of a possible range of values (7.44 to 90.36). U.S. EPA (1998) identified several processes—

including wind removal, water removal, and growth dilution—that reduce the amount of COPC that has been deposited

on a plant surface. The term kp is a measure of the amount of contaminant lost to these physical processes over time. 

U.S. EPA (1998) cites Miller and Hoffman (1983) for the following equation used to estimate kp:

kp = (ln 2 / t

1/2) @ 365 days/yr

where

t

1/2 = half-life (days)

Miller and Hoffman (1983) report half-life values ranging from 2.8 to 34 days for a variety of COPCs on herbaceous

vegetation. These half-life values result in kp values of 7.44 to 90.36 (yr-1). U.S. EPA (1998) and U.S. EPA (1994b)

recommend a kp value of 18, based on a generic 14-day half-life, corresponding to physical processes only. You can

also calculate site- and compound-specific kp values using the equation from Miller and Hoffman (1983). 

Uncertainties associated with this variable include the following:

(1) The recommended equation for calculating kp does not consider chemical degradation processes. Adding

chemical degradation processes would decrease half-lifes and thereby increase kp values; plant concentration

decreases as kp increases. Using a kp value that does not consider chemical degradation processes is

protective.

(2) The half-life values reported by Miller and Hoffman (1983) may not accurately represent the behavior of

compounds on aboveground produce.

(3) Based on this range (7.44 to 90.36), plant concentrations could range from about 1.8 times higher to about 5

times lower than the plant concentrations, based on a kp value of 18.
TABLE B-2-7

ABOVEGROUND PRODUCE CONCENTRATION DUE TO DIRECT DEPOSITION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 6 of 12)

Variable Description Units Value

B-68

Tp Length of plant exposure to

deposition per harvest of edible

portion of plant

yr 0.16

We recommend using a Tp value of 0.16 years; this is consistent with U.S. EPA (1998), U.S. EPA (1994b), and NC

DEHNR (1997), which recommended treating Tp as a constant, based on the average period between successive hay

harvests. Belcher and Travis (1989) estimated this period at 60 days. Tp is calculated as follows:

60 days ÷ 365 days/year = 0.16 years

The following uncertainty is associated with this variable:

The average period between successive hay harvests (60 days) may not reflect the length of the growing

season or the length between successive harvests for site-specific aboveground produce crops. Pd will be

(1) underestimated if the site-specific value of Tp is less than 60 days, or (2) overestimated if the site-specific

value of Tp is more than 60 days.
TABLE B-2-7

ABOVEGROUND PRODUCE CONCENTRATION DUE TO DIRECT DEPOSITION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 7 of 12)

Variable Description Units Value

B-69

Yp Yield or standing crop biomass of

the edible portion of the plant

(productivity)

kg DW/m2 Aboveground Produce: 2.24

We recommend using the Yp value of 2.24. Based on a review of the available literature, this value appears to be

representative of the most complete and thorough information.

U.S. EPA (1998) states that the best estimate of Yp is productivity. Baes et al. (1984) and Shor et al. (1982) define Yp

as follows as:

Yp = Yhi / Ahi

where

Yhi = Harvest yield of ith crop (kg DW)

Ahi = Area planted to ith crop (m2)

U.S. EPA (1994a) and NC DEHNR (1997) recommended using this equation. Class-specific Yp values were estimated

by using average U.S. values for Yh and Ah for a variety of fruits and vegetables for 1993 (USDA 1994a and USDA

1994b). Yh values were converted to dry weight by using average conversion factors for fruits, fruiting vegetables,

legumes, and leafy vegetables (Baes et al. 1984).

Class-specific Yp values were grouped to reflect exposed fruits or exposed vegetables. Exposed fruit and exposed

vegetable Yp values were then weighted by relative ingestion rates derived from the homegrown produce tables in U.S.

EPA (1997). The average ingestion-weighted Yp value was 2.24. U.S. EPA (1994b) and U.S. EPA (1995) recommend

a Yp value of 1.6; however, the produce classes and relative ingestion rates used to derive this Yp value are inconsistent

with U.S. EPA (1997).

The following uncertainty is associated with this variable:

The harvest yield (Yh) and area planted (Ah) may not reflect site-specific conditions. This may under- or

overestimate Yp.
TABLE B-2-7

ABOVEGROUND PRODUCE CONCENTRATION DUE TO DIRECT DEPOSITION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 8 of 12)

B-70

REFERENCES AND DISCUSSION

Baes, C.F., R.D. Sharp, A.L. Sjoreen, and R.W. Shor. 1984. Review and Analysis of Parameters and Assessing Transport of Environmentally Released Radionuclides through Agriculture. 

ORNL-5786. Oak Ridge National Laboratory. Oak Ridge, Tennessee. September.

This document proposed using the same empirical relationship developed by Chamberlain (1970) for other vegetation classes. Class-specific estimates of the empirical constant, (, were 

developed by forcing an exponential regression equation through several points, including average and theoretical maximum estimates of Rp and Yp.

The class-specific empirical constants developed are as follows:

Exposed produce — 0.0324

Leafy vegetables — 0.0846

Silage — 0.769

Beecher, G.D., and C.C. Travis. 1989. “Modeling Support for the RURA and Municipal Waste Combustion Projects: Final Report on Sensitivity and Uncertainty Analysis for the Terrestrial Food

Chain Model.” Interagency Agreement No. 1824-A020-A1, Office of Risk Analysis, Health and Safety Research Division, Oak Ridge National Laboratory. Oak Ridge, Tennessee. 

October.

This document recommends Tp values based on the average period between successive hay harvests and successive grazing.

Bidleman, T.F. 1988. “Atmospheric Processes.” Environmental Science and Technology. Volume 22. Pages 361-367. November 4. 

This document is cited by U.S. EPA (1994a) and NC DEHNR (1997) as the source of the equation for calculating Fv. For discussion, see References and Discussion, Table B-1-1.

Chamberlain, A.C. 1970. “Interception and Retention of Radioactive Aerosols by Vegetation.” Atmospheric Environment. 4:57 to 78.

Experimental studies of pasture grasses identified a correlation between initial Rp values and productivity (standing crop biomass [Yp]):

Rp = 1-e-( @ Yp

where

( = Empirical constant; range provided as 2.3 to 3.3

Yp = Yield or standing crop biomass (productivity) (kg DW/m2)
TABLE B-2-7

ABOVEGROUND PRODUCE CONCENTRATION DUE TO DIRECT DEPOSITION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 9 of 12)

B-71

Hoffman, F.O., K.M. Thiessen, M.L. Frank, and B.G. Blaylock. 1992. “Quantification of the Interception and Initial Retention of Radioactive Contaminants Deposited on Pasture Grass by

Simulated Rain.” Atmospheric Environment. Vol. 26A. 18:3313 to 3321.

This document developed values for a parameter (r) that it termed “interception fraction,” based on a study in which soluble gamma-emitting radionuclides and insoluble particles tagged

with gamma-emitting radionuclides were deposited onto pasture grass (specifically, a combination of fescues, clover, and old field vegetation, including fescue) via simulated rain. The

parameter, r, is defined as “the fraction of material in rain intercepted by vegetation and initially retained” or, essentially, the product of Rp and Fw, as defined for the HHRAP:

r = Rp @ Fw

Experimental r values obtained include the following:

C A range of 0.006 to 0.3 for anions (based on the soluble radionuclide iodide-131 [131I]); when calculating Rp values for anions, U.S. EPA (1994a) used the highest geometric mean

r value (0.08) observed in the study.

C A range of 0.1 to 0.6 for cations (based on the soluble radionuclide beryllium-7 [7Be]; when calculating Rp values for cations, U.S. EPA (1994a) used the highest geometric mean

r value (0.28) observed in the study.

C A geometric range of values from 0.30 to 0.37 for insoluble polystyrene micro spheres (IPM) ranging in diameter from 3 to 25 micrometers, labeled with cerium-141 [

141Ce],

[

95N]b, and strontium-85 85Sr; when calculating Rp values for organics (other than three organics that ionize to anionic forms: 4-chloroaniline, n-nitrosodiphenylamine, and

n-nitrosodi-n-propylamine [see Appendix A-2]), U.S. EPA (1994a) used the geometric mean r value for IPM with a diameter of 3 micrometers; however, no rationale for this

selection was provided.

The authors concluded that, for the soluble 131I anion, interception fraction r is an inverse function of rain amount, whereas for the soluble cation 7Be and the IPMs, r depends more on

biomass than on amount of rainfall. The authors also concluded that (1) the anionic 131I is essentially removed with the water after the vegetation surface has become saturated, and (2) the

cationic 7Be and the IPMs are adsorbed to or settle out onto the plant surface. This discrepancy between the behavior of the anionic and cationic species is consistent with a negative charge

on the plant surface.

As summarized in U.S. EPA (1994a), this document is the source of the recommended Fv

 value of 0.27 for dioxins (polychlorinated dibenzodioxins/polychlorinated dibenzofurans

[PCDD/PCDF]). This value is intended to represent 2,3,7,8-tetrachlorodibenzo-p-dioxin (2,3,7,8-TCDD) equivalents (TEQ) by weighting all dioxin and furan congeners with nonzero

toxicity equivalency factors (TEF). U.S. EPA is investigating the appropriateness of the use of recommended Fv value for PCDD/PCDFs.

Junge, C.E. 1977. Fate of Pollutants in Air and Water Environments, Part I. Suffet, I.H., Ed. Wiley. New York. Pages 7-26.

Miller, C.W. and F.O. Hoffman. 1983. “An Examination of the Environmental Half-Time for Radionuclides Deposited on Vegetation.” Health Physics. 45 (3): 731 to 744.

This document is the source of the equation used to calculate kp:

kp = (ln 2/ t

1/2) @ 365 days/year

where

t

1/2 = half-life (days)

The study reports half-life values ranging from 2.8 to 34 days for a variety of COPCs on herbaceous vegetation. 
TABLE B-2-7

ABOVEGROUND PRODUCE CONCENTRATION DUE TO DIRECT DEPOSITION

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 10 of 12)

B-72

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This is one of the source documents for the equation in Table B-2-7.

Shor, R.W., C.F. Baes, and R.D. Sharp. 1982. Agricultural Production in the United States by County: A Compilation of Information from the 1974 Census of Agriculture for Use in Terrestrial

Food-Chain Transport and Assessment Models. Oak Ridge National Laboratory Publication. ORNL-5786.

This document is the source of the equation used to calculate Yp:

Yp . Pi = Yh/ Ahi

where

Pi = productivity of ith crop (kilogram dry weight [kg DW]/square meter [m2])

Yh = harvest yield of ith crop (kg DW)

Ahi = area planted to crop I (m2)

using the following information:

Produce Category

Empirical

Constant

(unitless)

Rp

(unitless)

Yp

(kg DW/m2)

Yp

(kg WW/m2)

Intake

(g/kg-day)

Exposed Fruits 0.0324 0.053 0.252 1.68 0.19

Exposed Vegetables -- 0.982 5.660 89.4 0.11

Leafy Vegetables 0.0846 0.215 0.246 2.86 --

Fruiting Vegetables 0.0324 0.996 10.52 167 --

Using the empirical relationship developed by Baes et al. (1984) to estimate Rp based on Yp requires that Yp term to be in whole-weight units. However, in Equation B-2-7, the Yp term should be in

dry-weight units.

For exposed vegetables, Rp was derived from a weighted average of leafy vegetable and fruiting vegetable Rp values. This weighted average was based on whole-weight Yp values for

leafy and fruiting vegetables. In addition, the exposed vegetable Yp value, both whole- and dry-weight, was derived by the following:

The following produce items were included in each category:
TABLE B-2-7

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(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 11 of 12)

B-73

Exposed Fruits—apple, apricot, berry, cherry, cranberry, grape, peach, pear, plum/prune, strawberry

Exposed Vegetables—asparagus, cucumber, eggplant, sweet pepper, tomato, snap beans, broccoli, brussel sprouts, cauliflower, celery, lettuce, and spinach

The ingestion rates for exposed fruits and exposed vegetables were based on U.S. EPA (1997), homegrown intake rates.

However, U.S. EPA has reviewed Baes et al. (1984), which also presents and discusses this equation.

U.S. Department of Agriculture (USDA). 1994a. Vegetables 1993 Summary. National Agricultural Statistics Service, Agricultural Statistics Board. Washington, D.C. Vg 1-2 (94).

USDA. 1994b. Noncitrus Fruits and Nuts 1993 Summary. National Agricultural Statistics Service, Agricultural Statistics Board, Washington, D.C. Fr Nt 1-3 (94).

One of the sources of Yh (harvest yield) and Ah (area planted for harvest) values for fruits, fruiting vegetables, legumes, and leafy vegetables used to calculate Yp (yield or standing crop

biomass). Yh values were converted (for use in the equations) to dry weight by using average conversion factors for these same aboveground produce classes, as presented in Baes et al.

(1984). The fruits and vegetables considered in each category are as follows:

Exposed fruits—apple, apricot, berry, cherry, cranberry, grape, peach, pear, plum/prune, and strawberry

Exposed vegetables—asparagus, cucumber, eggplant, sweet pepper, tomato, snap beans, broccoli, brussel sprouts, cauliflower, celery, lettuce, and spinach

U.S. EPA. 1992. Technical Support Document for Land Application of Sewage Sludge, Volumes I and II. Office of Water. Washington, D.C. EPA 822/R-93-001a.

This document is the source of ingestion rates (g DW/day) for aboveground produce classes—fruiting vegetables (4.2), leafy vegetables (2.0), and legumes (8.8)— that U.S. EPA (1994b)

used to calculate Rp and Yp.

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-Specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This is the source of ingestion rate for fruits, based on whole weight (88 g/day) and converted to dry weight by using an average whole-weight to dry-weight conversion factor for fruits

(excluding plums/prunes, which had an extreme value) of 0.15 taken from Baes et al. (1984), used to calculate Rp and Yp.

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

This is one of the source documents for the equation in Table B-2-7.

This document also recommended weighted average Rp and Yp values of 0.05 and 1.6, respectively, based on the empirical relationships identified by Chamberlain (1970) and Shor et al.

(1982).

Rp = 1 - e -( @ Yp

where

( = Empirical constant; range provided as 2.3 to 3.3
TABLE B-2-7

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(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 12 of 12)

B-74

Yp = Standing crop biomass (productivity) (kg DW/m2)

and Shor et al. (1982):

Yp = Yh / Ahi

where

Yh = Harvest yield of ith crop (kg DW)

Ahi = Area planted to crop I (m2)

U.S. EPA. 1995. Review Draft Development of Human Health-Based and Ecologically-Based Exit Criteria for the Hazardous Waste Identification Project. Volumes I and II. Office of Solid

Waste. March 3.

This is one of the source documents for the equation in Table B-2-7.

U.S. EPA. 1997. Exposure Factors Handbook. Office of Research and Development. EPA/600/P-95/002F. August.

This document is the source of relative ingestion rates.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This is one of the source documents for the equation in Table B-2-7. This document also states that the best estimate of Yp (yield or standing crop biomass) is productivity, as defined under

Shor et al. (1982).
TABLE B-2-8

ABOVEGROUND PRODUCE CONCENTRATION DUE TO AIR-TO-PLANT TRANSFER

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 1 of 5)

B-75

Description

This equation calculates the COPC concentration in aboveground produce resulting from direct uptake of vapor phase COPCs onto plant surfaces. 

The limitations and uncertainty introduced in calculating this value include the following:

(1) The range of values for the variable Bv (air-to-plant biotransfer factor) is about 19 orders of magnitude for organic COPCs (this range may change on the basis of the tables in

Appendix A-2). COPC-specific Bv values for nondioxin-like compounds may be overestimated by up to one order of magnitude, based on experimental conditions used to develop the

algorithm used to estimate Bv values.

(2) The algorithm used to calculate values for the variable Fv

 assumes a default value for the parameter ST

 (Whitby’s average surface area of particulates [aerosols]) of background plus local

sources, rather than an ST value for urban sources. If a specific site is located in an urban area, using the latter ST value may be more appropriate. The ST value for urban sources is about

one order of magnitude greater than that for background plus local sources and would result in a lower Fv value; however, the Fv value is likely to be only a few percent lower.

As highlighted by uncertainties described above, Pv is most affected by the value calculated for Bv.

Equation

For mercury modeling

Use 0.48Q for total mercury and Fv = 0.85 in the mercury modeling equation to calculate Pv. Apportion the calculated Pv value into the divalent mercury (Hg2+) and methyl mercury (MHG)

forms based on the 78% Hg2+ and 22% MHG speciation split in aboveground produce. 

Pv (Hg2+) = 0.78 Pv (Mercu ry)

Pv (MHg) = 0.22 Pv (Mercu ry)

Evaluate divalent and methyl mercury as individual COPCs. Calculate Pv for divalent and methyl mercury using the equations above.
TABLE B-2-8

ABOVEGROUND PRODUCE CONCENTRATION DUE TO AIR-TO-PLANT TRANSFER

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 2 of 5)

B-76

Variable Description Units Value

Pv Concentration of COPC in

aboveground produce due to air-toplant transfer

μg COPC/g DW

(equivalent to

mg COPC/kg

DW)

Q COPC-specific emission rate g/s Varies

This variable is COPC- and site-specific, and is determined by air dispersion modeling. See Chapters 2 and 3 of the

HHRAP for guidance on calculating this variable. Uncertainties associated with this variable are site-specific.

Fv

Fraction of COPC air concentration

in vapor phase

unitless 0 to 1

This variable is COPC-specific. We discuss Fv

in detail in Appendix A-2, and offer COPC-specific values in the HHRAP

companion database. This range is based on values presented in Appendix A-2. U.S. EPA (1994b) and NC DEHNR

(1997) also present values. 

Fv was calculated using an equation presented in Junge (1977) for all organic COPCs, including PCDDs and PCDFs. U.S.

EPA (1994c) stated that Fv = 0 for all metals (except mercury).

The following uncertainties are associated with this variable:

(1) It is based on the assumption of a default ST

 value for background plus local sources, rather than an ST

 value for

urban sources. If a specific site is located in an urban area, using the latter ST value may be more appropriate. 

Specifically, the ST

 value for urban sources is about one order of magnitude greater than that for background

plus local sources, and it would result in a lower calculated Fv

 value; however, the Fv

 value is likely to be only a

few percent lower.

(2) According to Bidleman (1988), the equation used to calculate Fv assumes that the variable c (Junge constant) is

constant for all chemicals; however, the value of c depends on the chemical (sorbate) molecular weight, the

surface concentration for monolayer coverage, and the difference between the heat of desorption from

the particle surface and the heat of vaporization of the liquid phase sorbate. To the extent that site- or

COPC-specific conditions may cause the value of c to vary, uncertainty is introduced if a constant value

of c is used to calculate Fv.

Cyv Unitized yearly average air

concentration from vapor phase

:g-s/g-m3 Varies

This variable is COPC- and site-specific, and is determined by air dispersion modeling (see Chapter 3). Uncertainties

associated with this variable are site-specific.
TABLE B-2-8

ABOVEGROUND PRODUCE CONCENTRATION DUE TO AIR-TO-PLANT TRANSFER

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 3 of 5)

Variable Description Units Value

B-77

Bvag

COPC air-to-plant biotransfer factor

for aboveground produce

unitless

([mg COPC/g

DW plant]/[(mg

COPC/g air]) 

Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in the

HHRAP companion database.

Uncertainty associated with this variable include the following:

(1) The studies that formed the basis of the algorithm used to estimate Bv values were conducted on azalea leaves

and grasses, and may not accurately represent Bv for aboveground produce other than leafy vegetables.

VGag

Empirical correction factor for

aboveground produce

unitless 0.01 or 1.0

We recommend using a VGag value of 0.01 for COPCs with a log Kow greater than 4 and a value of 1.0 for COPCs with a

log Kow less than 4.

This variable is an empirical correction factor that reduces aboveground produce concentration. The equation in this table

was developed to estimate the transfer of COPCs into leafy vegetation rather than into bulkier aboveground produce, such

as apples. Because of the protective outer skin, size, and shape of bulky produce, transfer of lipophilic COPCs (log Kow

greater than 4) to the center of the produce is not likely. In addition, typical preparation techniques, such as washing,

peeling, and cooking, will further reduce residues.

U.S. EPA (1994b) recommended a value of 0.01, based on U.S. EPA (1994a), but made no distinction between fruits,

vegetables, and leafy vegetation. NC DEHNR (1997), also citing U.S. EPA (1994a), recommended values of (1) 0.01 for

fruits and fruiting vegetables, and (2) 1.0 for leafy vegetables. The values cited from U.S. EPA (1994a) are also based on

information from Riederer (1990) and Wipf, et al. (1982). 

Uncertainties associated with this variable include the following:

(1) U.S. EPA (1994a) assumed that translocation of compounds deposited on the surface of aboveground vegetation

to inner parts of aboveground produce would be insignificant. This may underestimate Pv.

(2) U.S. EPA (1994a) assumed that the density of the skin and the whole vegetable are equal. This may

overestimate Pv.

(3) U.S. EPA (1994a) assumed that the thickness of vegetable skin and broadleaf tree skin are equal. The effect of

this assumption on Pv is unknown.

Da

Density of air g/m3

1200.0

We recommend using this value based on Weast (1986). This reference indicates that air density varies with temperature. 

The density of air at both 20°C and 25°C (rounded to two significant figures) is 1.2 x 10+3.

U.S. EPA (1994b) and NC DEHNR (1997) recommended this same value but stated that it was calculated at standard

conditions (20°C and 1 atmosphere).
TABLE B-2-8

ABOVEGROUND PRODUCE CONCENTRATION DUE TO AIR-TO-PLANT TRANSFER

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 4 of 5)

B-78

REFERENCES AND DISCUSSION

Bidleman, T.F. 1988. “Atmospheric Processes.” Environmental Science and Technology. Volume 22. Number 4. Pages 361-367.

For discussion, see References and Discussion in Table B-1-1.

Junge, C.E. 1977. Fate of Pollutants in Air and Water Environments, Part I. Suffet, I.H., Ed. Wiley. New York. Pages 7-26.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This is one of the source documents for the equation in Table B-2-8. This document also recommends that (1) Fv values be based on the work of Bidleman (1988), and (2) an empirical

correction factor (VGag) be used to reduce concentrations of COPCs in specific vegetation types—specifically, a VGag value of 0.5 is recommended for silage. However, no rationale is

provided for this value. This factor is used to reduce estimated COPC concentrations in specific vegetation types, because (1) Bv was developed for azalea leaves, and (2) it is assumed that

there is insignificant translocation of compounds deposited on the surface of some vegetation types to the inner parts of this vegetation because of the lipophilicity of the COPC.

Riederer, M. 1990. “Estimating Partitioning and Transport of Organic Chemicals in the Foliage/Atmosphere System: Discussion of a Fugacity-Based Model.” Environmental Science and

Technology. 24: 829 to 837.

This is the source of the leaf thickness estimate used to estimate the empirical correction factor (VGag).

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume II: Properties, Sources, Occurrence, and Background Exposures. External Review Draft. Office of Research and

Development. Washington, DC. EPA/600/6-88/005Cc. June.

This document recommends an empirical correction factor of 0.01 to reduce estimated vegetable concentrations on the basis of the assumption that there is insignificant translocation of

compounds deposited on the surface of aboveground vegetation to inner parts for aboveground produce. No reference or discussion regarding the validity of this assumption was given.

The factor of 0.01 is based on a similar correction factor for belowground produce (VGbg), which is estimated on the basis of a ratio of the vegetable skin mass to vegetable total mass. The

document assumes that the densities of the skin and vegetable are equal. The document also assumes an average vegetable skin leaf that is based on Rierderer (1990). Based on these

assumptions, U.S. EPA (1994a) calculated VGbg for carrots and potatoes of 0.09 and 0.03, respectively. By comparing these values to contamination reduction research completed by Wipf,

et al. (1982), U.S. EPA (1994a) arrived at the recommended VGag value of 0.01.

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This is one of the source documents for the equation in Table B-2-8. This document also presents a range (0.27 to 1) of Fv values for organic COPCs, based on the work of Bidleman

(1988); Fv for all inorganics is set equal to zero.

U.S. EPA. 1995. Review Draft Development of Human Health-Based and Ecologically-Based Exit Criteria for the Hazardous Waste Identification Project. Volumes I and II. Office of Solid

Waste. March 3. 
TABLE B-2-8

ABOVEGROUND PRODUCE CONCENTRATION DUE TO AIR-TO-PLANT TRANSFER

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 5 of 5)

B-79

 U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and

Development. EPA 452/R-97-005. December.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

Based on attempts to model background concentrations of dioxin-like compounds in beef on the basis of known air concentrations, this document recommends reducing, by a factor of 10,

Bv values calculated by using the Bacci,et al. (1992) algorithm The use of this factor “made predictions [of beef concentrations] come in line with observations.”

Weast, R.C. 1986. Handbook of Chemistry and Physics. 66th Edition. Cleveland, Ohio. CRC Press.

This document is a reference for air density values, and is an update of Weast (1981).

Wipf, H.K., E. Homberger, N. Neuner, U.B. Ranalder, W. Vetter, and J.P. Vuilleumier. 1982. “TCDD Levels in Soil and Plant Samples from the Seveso Area.” In: Chlorinated Dioxins and

Related Compounds: Impact on the Environment. Eds. Hutzinger, O. et al. Pergamon, NY.
TABLE B-2-9

ABOVEGROUND PRODUCE CONCENTRATION DUE TO ROOT UPTAKE

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 1 of 3)

B-80

Description

This equation calculates the COPC concentration in aboveground produce due to direct uptake of COPCs from soil through plant roots. The limitations and uncertainty introduced in calculating

this value include the following:

(1) The availability of site-specific information, such as meteorological data, will affect the accuracy of Cs estimates.

(2) Estimated COPC-specific soil-to-plant bioconcentration factors (Br) don’t reflect site-specific conditions. This may be especially true for inorganic COPCs for which you could more

accurately estimate Br by using site-specific BCFs rather than BCFs presented in Baes et al. (1984). We therefore recommend using plant uptake response slope factors derived in U.S.

EPA (1992) for arsenic, cadmium, selenium, nickel, and zinc.

Equation

For mercury modeling, calculate aboveground produce concentration due to root uptake using the respective Cs and Br values for divalent mercury (Hg2+) and methyl mercury (MHg).

Variable Description Units Value

Prag

Concentration of COPC in

aboveground produce due to root

uptake 

mg COPC/kg DW

Cs Average soil concentration over

exposure duration 

mg COPC/kg soil Varies

This value is COPC-and site-specific and calculated using the equation in Table B-2-1. Uncertainties associated with

this variable are site-specific.
TABLE B-2-9

ABOVEGROUND PRODUCE CONCENTRATION DUE TO ROOT UPTAKE

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 2 of 3)

Variable Description Units Value

B-81

Brag

Plant-soil bioconcentration factor

for aboveground produce

unitless

([mg COPC/kg DW

plant]/[mg COPC/

kg soil])

Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in

the HHRAP companion database. 

Uncertainties associated with this variable include the following:

(1) Estimates of Br for some inorganic COPCs, based on plant uptake response slope factors, may be more

accurate than those based on BCFs from Baes et al. (1984).

(2) We recommend that uptake of organic COPCs from soil and transport of the COPCs to aboveground plant

parts be calculated on the basis of a regression equation developed in a study of the uptake of 29 organic

compounds. This regression equation, developed by Travis and Arms (1988), may not accurately represent

the behavior of all organic COPCs under site-specific conditions.

REFERENCES AND DISCUSSION

Baes, C.F., R.D. Sharp, A.L. Sjoreen, and R.W. Shor. 1984. Review and Analysis of Parameters and Assessing Transport of Environmentally Released Radionuclides through Agriculture. 

ORNL-5786. Oak Ridge National Laboratory. Oak Ridge, Tennessee. September.

Element-specific bioconcentration factors (BCF) were developed by Baes et al. (1984)—for both vegetative (stems and leaves) portions of food crops (Bv) and nonvegetative

(reproductive—fruits, seeds, and tubers) portions of food crops (Br)—on the basis of a review and compilation of a wide variety of measured, empirical, and comparative data. 

Inorganic-specific Br values were calculated as a weighted average of vegetative (Bv) and reproductive (Br) BCFs. We recommend calculating inorganic-specific Br values as a weighted

average of vegetative and reproductive BCFs. Relative ingestion rates determined from U.S. EPA (1997a) are 75 percent reproductive and 25 percent vegetative for homegrown produce. 

However, for exposed fruits only the reproductive BCFs should be used.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This is one of the source documents for the equation in Table B-2-9. 

Travis, C.C. and A.D. Arms. 1988. “Bioconcentration of Organics in Beef, Milk, and Vegetation.” Environmental Science and Technology. 22:271 to 274.

Based on paired soil and plant concentration data for 29 organic compounds, this document developed a regression equation relating soil-to-plant BCF (Br) to Kow;

log Br = 1.588 - 0.578 log Kow
TABLE B-2-9

ABOVEGROUND PRODUCE CONCENTRATION DUE TO ROOT UPTAKE

(CONSUMPTION OF ABOVEGROUND PRODUCE EQUATIONS)

(Page 3 of 3)

B-82

U.S. EPA. 1992. Technical Support Document for Land Application of Sewage Sludge, Volumes I and II. Office of Water. Washington, D.C. EPA 822/R-93-001a.

Source of plant uptake response factors for arsenic, cadmium, nickel, selenium, and zinc. Plant uptake response factors are converted to BCFs by multiplying the plant uptake response

factor by 2. 

U.S. EPA. 1994. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-Specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This is the source for ingestion rate for fruits, based on whole weight (88 g/day), and converted to dry weight by using an average whole-weight to dry-weight conversion factor for fruits

(excluding plums/prunes, which had an extreme value) of 0.15 from Baes et al. (1984)—used to calculate Br.

U.S. EPA. 1995. Review Draft Development of Human Health-Based and Ecologically-Based Exit Criteria for the Hazardous Waste Identification Project. Volumes I and II. Office of Solid

Waste. March 3.

This document recommends using the BCFs, Bv, and Br from Baes et al. (1984) for calculating the uptake of inorganics into vegetative growth (stems and leaves) and nonvegetative growth

(fruits, seeds, and tubers), respectively.

Although most BCFs used in this document come from Baes et al. (1984), values for some inorganics were apparently obtained from plant uptake response slope factors. These uptake

response slope factors derived from U.S. EPA (1992).

U.S. EPA. 1997a. Exposure Factors Handbook. Office of Research and Development. EPA/600/P-95/002F. August.

This document is the source for relative intake rate split of 75 percent reproductive and 25 percent vegetative for homegrown produce.

U.S. EPA. 1997b. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research 

and Development. EPA 452/R-97-005. December.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This is one of the source documents for the equation in Table B-2-9.
TABLE B-2-10

BELOWGROUND PRODUCE CONCENTRATION DUE TO ROOT UPTAKE

(CONSUMPTION OF BELOWGROUND PRODUCE EQUATIONS)

(Page 1 of 5)

B-83

Description

This equation calculates the COPC concentration in belowground vegetation due to direct uptake of COPCs from soil. The limitations and uncertainty introduced in calculating this value include

the following:

(1) The availability of site-specific information, such as meteorological data, will affect the accuracy of Cs estimates.

(2) Estimated COPC-specific soil-to-plant biotransfer factors (Br) don’t necessarily reflect site-specific conditions. This may be especially true for inorganic COPCs for which estimates of

Br would be more accurately estimated by using site-specific BCFs from Baes et al. (1984). Hence, for arsenic, cadmium, selenium, nickel, and zinc, we recommend using plant uptake

response slope factors derived from U.S. EPA (1992).

For mercury modeling, belowground produce concentration due to root uptake is calculated using the respective Cs and Br values for divalent mercury (Hg2+) and methyl mercury (MHg). 

Variable Description Units Value

Prbg

Concentration of COPC in

belowground produce due to root

uptake 

mg COPC/kg DW

Cs Average soil concentration over

exposure duration 

mg COPC/kg soil Varies

This value is COPC-and site-specific and calculated using the equation in Table B-2-1. Uncertainties associated with

this variable are site-specific.
TABLE B-2-10

BELOWGROUND PRODUCE CONCENTRATION DUE TO ROOT UPTAKE

(CONSUMPTION OF BELOWGROUND PRODUCE EQUATIONS)

(Page 2 of 5)

Variable Description Units Value

B-84

Brrootveg

Plant-soil bioconcentration factor

for belowground produce

unitless

([mg COPC/kg

plant DW]/[mg

COPC/

kg soil])

Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in

the HHRAP companion database.

Uncertainties associated with this variable include the following:

(1) Estimates of Br for some inorganic COPCs, based on plant uptake response slope factors, may be more

accurate than those based on BCFs from Baes et al. (1984).

(2) We recommend that you calculate uptake of organic COPCs from soil and the transport of COPCs to

belowground produce on the basis of a regression equation developed by Briggs et al (1982). This regression

equation may not accurately represent the behavior of all classes of organic COPCs under site-specific

conditions.
TABLE B-2-10

BELOWGROUND PRODUCE CONCENTRATION DUE TO ROOT UPTAKE

(CONSUMPTION OF BELOWGROUND PRODUCE EQUATIONS)

(Page 3 of 5)

Variable Description Units Value

B-85

VGrootveg

Empirical correction factor for

belowground produce

unitless 0.01 or 1.0

We recommend that you use a VGrootveg value of 0.01 for COPCs with a log Kow greater than 4 and use a VGrootveg value

of 1.0 for COPCS with a log Kow less than 4.

This variable is an empirical correction factor that reduces produce concentration. Because of the protective outer skin,

size, and shape of bulky produce, transfer of lipophilic COPCs (log Kow greater than 4) to the center of the produce isn’t

likely. In addition, typical preparation techniques, such as washing, peeling, and cooking, will further reduce residues.

U.S. EPA (1994) recommended a VGrootveg value of 0.01 for lipophilic COPCs (log Kow greater than 4) to reduce

estimated belowground produce concentrations. This estimate for unspecified vegetables is based on:

where

Mskin = Mass of thin (skin) layer of an below ground vegetable (g)

Mvegetable = Mass of entire vegetable (g)

If you assume that the density of the skin and the whole vegetable are the same, this equation can become a ratio of the

volume of the skin to that of the whole vegetable. With this assumption, U.S. EPA (1994) calculated VGrootveg values of

0.09 and 0.03 for carrots and potatoes, respectively. U.S. EPA (1994) identified other processes, such as peeling,

cooking, and cleaning, that will further reduce the vegetable concentration. Because of these other processes, U.S.

EPA (1994) recommended a VGrootveg value of 0.01 for lipophilic COPCs.

The following uncertainty is associated with this variable:

U.S. EPA (1994) assumed that the density of the skin and the whole vegetable are equal. This may

overestimate Pr. However, based on the limited range of VGrootveg (compared to Br), it appears that in most

cases, these uncertainties will have a limited impact on the calculation of Pr and, ultimately, risk.

Kds

Soil-water partition coefficient cm3 water/g soil Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in

Appendix A-2.
TABLE B-2-10

BELOWGROUND PRODUCE CONCENTRATION DUE TO ROOT UPTAKE

(CONSUMPTION OF BELOWGROUND PRODUCE EQUATIONS)

(Page 4 of 5)

B-86

REFERENCES AND DISCUSSION

Baes, C.F., R.D. Sharp, A.L. Sjoreen, and R.W. Shor. 1984. Review and Analysis of Parameters and Assessing Transport of Environmentally Released Radionuclides through Agriculture. 

ORNL-5786. Oak Ridge National Laboratory. Oak Ridge, Tennessee. September.

For discussion, see References and Discussion in Table B-2-10.

Briggs, G.G., R.H. Bromilow, and A.A. Evans. 1982. Relationships between lipophilicity and root uptake and translocation of non-ionized chemicals by barley. Pesticide Science 13:495-504.

This document presents the relationship between RCF and Kow presented in the equation in Table B-2-10..

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This is a source document for the equation in Table B-2-10. 

Travis, C.C. and A.D. Arms. 1988. “Bioconcentration of Organics in Beef, Milk, and Vegetation.” Environmental Science and Technology. 22:271 to 274.

Based on paired soil and plant concentration data for 29 organic compounds, this document developed a regression equation relating soil-to-plant BCF (Br) to Kow

log Br = 1.588 - 0.578 log Kow

U.S. EPA. 1992. Technical Support Document for Land Application of Sewage Sludge, Volumes I and II. Office of Water. Washington, D.C. EPA 822/R-93-001a.

Source of plant uptake response factors for arsenic, cadmium, nickel, selenium, and zinc. Plant uptake response factors are converted to BCFs by multiplying the plant uptake response

factor by 2.

U.S. EPA. 1993. Review Draft Addendum to the Methodology for Assessing Health Risks Associated with Indirect Exposure to Combustor Emissions. Office of Health and Environmental 

Assessment. Office of Research and Development. EPA-600-AP-93-003. November 10.

This document is a source of COPC-specific Kds

 values.

U.S. EPA. 1994. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-Specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This is a source document for Vgrootveg values.
TABLE B-2-10

BELOWGROUND PRODUCE CONCENTRATION DUE TO ROOT UPTAKE

(CONSUMPTION OF BELOWGROUND PRODUCE EQUATIONS)

(Page 5 of 5)

B-87

U.S. EPA. 1995. Review Draft Development of Human Health-Based and Ecologically-Based Exit Criteria for the Hazardous Waste Identification Project. Volumes I and II. Office of Solid

Waste. March 3.

This document recommends using the BCFs, Bv, and Br from Baes et al. (1984) for calculating the uptake of inorganics into vegetative growth (stems and leaves) and nonvegetative growth

(fruits, seeds, and tubers), respectively.

Although most BCFs used in this document come from Baes et al. (1984), values for some inorganics were apparently obtained from plant uptake response slope factors. These uptake

response slope factors were calculated from field data, such as metal methodologies. References used to calculate the uptake response slope factors are not clearly identified.

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and

Development. EPA 452/R-97-005. December.
TABLE B-3-1

SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 1 of 8)

B-88

Description

Use the equations in this table to calculate an average COPC soil concentration resulting from wet and dry deposition of particles and vapors to soil over the exposure duration. We recommend

assuming that COPCs are incorporated only to a finite depth (the soil mixing zone depth, Zs

). Use the COPC soil concentration averaged over the exposure duration, represented by Cs, for

carcinogenic COPCs, where risk is averaged over the lifetime of an individual. Because the hazard quotient associated with noncarcinogenic COPCs is based on a reference dose rather than a

lifetime exposure, we recommend using the highest annual average COPC soil concentration occurring during the exposure duration period for noncarcinogenic COPCs. The highest annual

average COPC soil concentration would most likely occur at the end of the time period of combustion and is represented by CstD. 

The following uncertainties are associated with this variable:

(1) We assume that the time period for deposition of COPCs resulting from hazardous waste combustion is a conservative, long-term value. This assumption may overestimate Cs and CstD.

(2) Exposure duration values (T2) are based on historical mobility studies and won’t necessarily remain constant. Specifically, mobility studies indicate that most receptors that move

remain in the vicinity of the combustion unit; however, it is impossible to accurately predict the probability that these short-distance moves will influence exposure, based on factors

such as atmospheric transport of pollutants.

(3) Using a value of zero for T1

 doesn’t account for exposure that may have occurred from historic operations and emissions from hazardous waste combustion. This may underestimate Cs

and CstD.

(4) For soluble COPCs, leaching might lead to movement to below the mixing depth, resulting in lower concentrations within the mixing depth. This uncertainty may overestimate Cs and

CstD. 

(5) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in situ materials) compared to other residues. This may

underestimate Cs and CstD. 

Equation for Carcinogens

Soil Concentration Averaged Over Exposure Duration
TABLE B-3-1

SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 2 of 8)

B-89

Equation for Noncarcinogens

Highest Annual Average Soil Concentration

where

For mercury modeling

Use 0.48Q for total mercury and Fv = 0.85 in the mercury modeling equation to calculate Ds. Apportion the calculated Ds value into the divalent mercury (Hg2+) and methyl mercury (MHg)

forms based on the assumed 98% Hg2+ and 2% MHg speciation split in soils (see Chapter 2). Elemental mercury (Hg0) occurs in very small amounts in the vapor phase and does not exist in the

particle or particle-bound phase. Therefore, assume elemental mercury deposition onto soils is negligible or zero. Evaluate elemental mercury for the direct inhalation pathway only (Table

B-5-1).

Ds (Hg2+) = 0.98 Ds (Mercu ry)

Ds (Mhg) = 0.02 Ds (Mercu ry)

Ds (Hg0) = 0.0

Evaluate divalent and methyl mercury as individual COPCs. Calculate Cs for divalent and methyl mercury using the corresponding (1) fate and transport parameters for mercuric chloride

(divalent mercury, Hg2+) and methyl mercury provided in Appendix A-2, and (2) Ds (Hg2+) and Ds (MHg) as calculated above. 
TABLE B-3-1

SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 3 of 8)

B-90

Variable Description Units Value

Cs Average soil concentration over

exposure duration 

mg COPC/kg soil

CstD

Soil concentration at time tD mg COPC/kg soil

Ds Deposition term mg COPC/kg soilyr

Varies

U.S. EPA (1994a) and NC DEHNR (1997) recommended incorporating a deposition term into the Cs equation. 

Uncertainties associated with this variable include the following:

(1) Five of the variables in the equation for Ds (Q, Cyv, Dywv, Dywp, and Dydp) are COPC- and site-specific. 

Values for these variables are estimated through modeling. The direction and magnitude of any uncertainties

shouldn’t be generalized.

(2) Based on the narrow recommended ranges, we expect uncertainties associated with Vdv, Fv, and BD to be low.

(3) Values for Zs vary by about one order of magnitude. Uncertainty is greatly reduced if you know whether soils

are tilled or untilled.

tD Time period over which deposition

occurs (time period of combustion)

yr 30

U.S. EPA (1998) suggests that this period of time can be $30 years. We recommend using 30 years unless site-specific

information is available indicating that this assumption is unreasonable (see Chapter 6 of the HHRAP). 

ks COPC soil loss constant due to all

processes

yr-1 Varies

This variable is COPC- and site-specific, and is calculated by using the equation in Table B-3-2. The COPC soil loss

constant is the sum of all COPC removal processes. 

Uncertainty associated with this variable includes the following:

COPC-specific values for ksg (one of the variables in the equation in Table B-3-2) are empirically determined

from field studies. No information is available regarding the application of these values to the site-specific

conditions associated with affected facilities.
TABLE B-3-1

SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 4 of 8)

Variable Description Units Value

B-91

T2

Length of exposure duration yr 6, 30, or 40

We recommend reasonable maximum exposure (RME) values for T2

:

Exposure Duration RME Reference

Child Resident 6 years U.S. EPA (1997b)

Farmer Child

Fisher Child

Adult Resident and 30 years U.S. EPA (1997b)

Fisher

Farmer 40 years U.S. EPA (1994b)

U.S. EPA (1994c) recommended the following unreferenced values:

Exposure Duration Years 

Subsistence Farmer 40

Adult Resident 30

Subsistence Fisher 30

Child Resident 9

Uncertainties associated with this variable include the following:

(1) Exposure duration rates are based on historical mobility rates and may not remain constant. This assumption

may overestimate or underestimate Cs and CstD.

(2) Mobility studies indicate that most receptors that move remain in the vicinity of the emission sources;

however, it is impossible to accurately predict the likelihood that these short-distance moves will influence

exposure, based on factors such as atmospheric transport of pollutants. This assumption may overestimate or

underestimate Cs and CstD.

T1

Time period at the beginning of

combustion

yr 0

Consistent with U.S. EPA (1994c), we recommend a value of 0 for T1.

The following uncertainty is associated with this variable:

A T1 of zero doesn’t account for exposure that may have occurred from historical operation or emissions from

burning hazardous waste. This may underestimate Cs and CstD.

100 Units conversion factor mg-cm2

/kg-cm2
TABLE B-3-1

SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 5 of 8)

Variable Description Units Value

B-92

Q COPC emission rate g/s Varies

This variable is COPC- and site-specific. See Chapters 2 and 3 of the HHRAP for guidance on calculating this variable. 

Uncertainties associated with this variable are site-specific.

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs

:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with

U.S. EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A

default value of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil

(Brzuzy et al. 1995). A default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in a

greater mixing depth. This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution compared to other

residues. This uncertainty may underestimate Cs and CstD. 

BD Soil bulk density g soil/cm3

 soil 1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD

value of 1.5 g soil/cm3 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998)

stated that a value of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended BD value may not accurately represent site-specific soil conditions; and may under- or

overestimate site-specific soil conditions to an unknown degree. 
TABLE B-3-1

SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 6 of 8)

Variable Description Units Value

B-93

Fv

Fraction of COPC air concentration

in vapor phase 

unitless 0 to 1

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in

the HHRAP companion database. This range is based on values presented in Appendix A-2. Values are also presented

in U.S. EPA (1994b) and NC DEHNR (1997). 

Fv was calculated using an equation presented in Junge (1977) for all organic COPCs, including PCDDs and PCDFs. 

U.S. EPA (1994c) states that Fv = 0 for all metals (except mercury).

The following uncertainties are associated with this variable:

(1) It assumes a default ST

 value or background plus local sources, rather than an ST

 value for urban sources. If

your site is located in an urban area, using the latter ST value may be more appropriate. Specifically, the ST

value for urban sources is about one order of magnitude greater than that for background plus local sources,

and would result in a lower calculated Fv value; however, the Fv value is likely to be only a few percent lower.

(2) According to Bidleman (1988), the Fv equation assumes that the variable c (Junge constant) is constant

for all chemicals; however, the value of c depends on the chemical (sorbate) molecular weight, the

surface concentration for monolayer coverage, and the difference between the heat of desorption from

the particle surface and the heat of vaporization of the liquid-phase sorbate. To the extent that site- or

COPC-specific conditions may cause the value of c to vary, uncertainty is introduced if a constant value

of c is used to calculate Fv.

Dydv Unitized yearly average dry

deposition from vapor phase 

s/m2-yr Varies

This variable is COPC- and site-specific, and is determined by air modeling (see Chapter 3). Uncertainties associated

with this variable are site-specific.

Dywv Unitized yearly average wet

deposition from vapor phase 

s/m2

-yr Varies

This variable is COPC- and site-specific, and is determined by air modeling (see Chapter 3). Uncertainties associated

with this variable are site-specific.

Dydp Unitized yearly average dry

deposition from particle phase

s/m2-yr Varies

This variable is COPC- and site-specific, and is determined by air modeling (see Chapter 3). Uncertainties associated

with this variable are site-specific.

Dywp Unitized yearly average wet

deposition from particle phase

s/m2

-yr Varies

This variable is COPC- and site-specific, and is determined by air modeling (see Chapter 3). Uncertainties associated

with this variable are site-specific.
TABLE B-3-1

SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 7 of 8)

B-94

REFERENCES AND DISCUSSION

Bidleman, T.F. 1988. “Atmospheric Processes.” Environmental Science and Technology. Volume 22. Number 4. Pages 361-367.

For discussion, see References and Discussion, Table B-1-1.

Brzuzy, L.P. and R.A. Hites. 1995. “Estimating the Atmospheric Deposition of Polychlorinated Dibenzo-p-dioxins and Dibenzofurans from Soils.” Environmental Science and Technology. 

Volume 29. Pages 2090-2098.

This reference presents soil profiles for dioxin measurements.

Carsel, R.F., R.S. Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2.

Pages 11-24.

This reference is cited by U.S. EPA (1994b) as the source for a mean soil bulk density value of 1.5 (g soil/cm3 soil) for loam soil.

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York.

Cited by U.S. EPA (1998) for the statement that BD is affected by the soil structure, such as looseness or compaction of the soil, depending on the water and clay content of the soil.

Junge, C.E. 1977. Fate of Pollutants in Air and Water Environments, Part I. Suffet, I.H., Ed. Wiley. New York. Pages 7-26.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This is one of the source documents for the equation in Table B-3-1. This document also recommends using (1) a deposition term, Ds, and (2) COPC-specific Fv values.

Research Triangle Institute (RTI). 1992. Preliminary Soil Action Level for Superfund Sites. Draft Interim Report. Prepared for U.S. EPA Hazardous Site Control Division, Remedial Operations

Guidance Branch. Arlington, Virginia. EPA Contract 68-W1-0021. Work Assignment No. B-03, Work Assignment Manager Loren Henning. December.

This document is a reference source for COPC-specific Fv

 values.

U.S. EPA. 1992. Estimating Exposure to Dioxin-Like Compounds. Draft Report. Office of Research and Development. Washington, D.C. EPA/600/6-88/005b.

The External Review Draft of the MPE document (the final is U.S. EPA 1998) cites this document as the source of values for soil mixing zone depth, Zs, for tilled and untilled soils.
TABLE B-3-1

SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 8 of 8)

B-95

U.S. EPA. 1993b. Addendum to the Methodology for Assessing Health Risks Associated with Indirect Exposure to Combustor Emissions. Working Group Recommendations. Office of Solid

Waste. Office of Research and Development. Washington, D.C. September.

This document is a reference for the equation in Table B-3-1. It recommends using a deposition term, Ds, and COPC-specific Fv values in the Cs equation.

U.S. EPA 1994a. Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for RCRA

Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. April 15.

This document is a reference for the equation in Table B-3-1; it recommends that the following be used in the Cs equation: (1) a deposition term, Ds, and (2) a default soil bulk density

value of 1.5 g/cm3, based on a mean value for loam soil from Carsel et al. (1988).

U.S. EPA. 1994b. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-Specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June. 

This document recommends values for length of exposure duration, T2, for the farmer.

U.S. EPA. 1994c. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Office of Emergency and Remedial Response. Office

of Solid Waste. December 14.

This document recommends the following:

C Values for the length of exposure duration, T2

C Value of 0 for the time period of the beginning of combustion, T1

C Fv values that range from 0.27 to 1 for organic COPCs

C Default soil bulk density value of 1.5 (g soil/cm3

 soil), based on a mean for loam soil from Carsel et al. (1988)

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and

Development. EPA 452/R-97-005. December.

U.S. EPA. 1997b. Exposure Factors Handbook. Office of Research and Development. EPA/600/P-95/002Fc. August.

This document is a reference source for values for length of exposure duration, T2

.

U.S. EPA. 1998. Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions (MPE). Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.
TABLE B-3-2

COPC SOIL LOSS CONSTANT

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 1 of 4)

B-96

Description

This equation calculates the COPC soil loss constant, which accounts for the loss of COPCs from soil by several mechanisms. Uncertainties associated with this equation include the following:

(1) COPC-specific values for ksg are empirically determined from field studies; no information is available regarding the application of these values to the site-specific conditions associated

with affected facilities.

(2) The source of the equations in Tables B-3-3 through B-3-5 has not been identified.

Equation

Variable Description Units Value

ks COPC soil loss constant due to all

processes

yr-1

ksg COPC soil loss constant due to

biotic and abiotic degradation

yr-1 Varies

This variable is COPC-specific and should be determined from the COPC tables in Appendix A-2. 

“Degradation rate” values are also presented in NC DEHNR (1997); however, no reference or source is provided for the values. 

U.S. EPA (1994a) and U.S. EPA (1994b) state that ksg values are COPC-specific; however, all ksg values are presented as zero (U.S.

EPA 1994a) or as “NA” (U.S. EPA 1994b); the basis of these assumptions is not addressed.

The following uncertainty is associated with this variable:

COPC-specific values for ksg are empirically determined from field studies; no information is available on applying these

values to the site-specific conditions associated with affected facilities.
TABLE B-3-2

COPC SOIL LOSS CONSTANT

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 2 of 4)

Variable Description Units Value

B-97

kse COPC loss constant due to soil

erosion

yr-1 0

This variable is COPC- and site-specific, and is further discussed in Table B-3-3. Consistent with U.S. EPA (1994a), U.S. EPA

(1994b) and NC DEHNR (1997), we recommend a default value of zero for kse because contaminated soil erodes both onto the site

and away from the site.

Uncertainties associated with this variable include the following:

(1) The source of the equation in Table B-3-3 has not been identified.

(2) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting a greater mixing

depth. This uncertainty may overestimate kse.

(3) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in

situ materials) compared to other residues. This uncertainty may underestimate kse.

ksr COPC loss constant due to surface

runoff

yr-1 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-3-4. No reference document is cited for

this equation; using this equation is consistent with U.S. EPA (1998). U.S. EPA (1994a) assumes that all ksr values are zero but

does not explain the basis of this assumption. 

Uncertainties associated with this variable (calculated by using the equation in Table B-3-4) include the following:

(1) The source of the equation in Table B-3-4 has not been identified.

(2) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in a greater mixing

depth. This uncertainty may overestimate ksr.

(3) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in

situ materials) compared to other residues. This uncertainty may underestimate ksr.

ksl COPC loss constant due to leaching yr-1 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-3-5. Using this equation is consistent with

U.S. EPA (1998), U.S. EPA (1994b), and NC DEHNR (1997). U.S. EPA (1994a) assumes that ksl is zero but does not explain the

basis of this assumption.

Uncertainties associated with this variable (calculated by using the equation in Table B-3-5) include the following:

(1) The source of the equation in Table B-3-5 has not been identified.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in

situ materials) compared to other residues. This uncertainty may underestimate ksl.
TABLE B-3-2

COPC SOIL LOSS CONSTANT

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 3 of 4)

Variable Description Units Value

B-98

ksv COPC loss constant due to

volatilization

yr-1 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-3-6. This equation calculates the COPC

loss constant from soil due to volatilization, and was obtained from U.S. EPA (1998). The soil loss constant due to volatilization

(ksv) is based on gas equilibrium coefficients and gas phase mass transfer. The first order decay constant, ksv, is obtained by

adapting the Hwang and Falco equation for soil vapor phase diffusion (Hwang and Falco 1986).

Uncertainties associated with this equation include the following:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in a greater mixing

depth. This uncertainty may overestimate ksv.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in

situ materials) compared to other residues. This uncertainty may underestimate ksv.

REFERENCES AND DISCUSSION

Hwang S. T. and Falco, J. W. 1986. “Estimation of multimedia exposures related to hazardous waste facilities”, In: Pollutants in a Multimedia Environment. Yoram Cohen, Ed. Plenum Publishing

Corp. New York.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the reference documents for the equations in Tables B-3-4 and B-3-5. This document is also cited as (1) the source for a range of COPC-specific degradation rates

(ksg), and (2) one of the sources that recommend assuming that the loss resulting from erosion (kse) is zero because of contaminated soil eroding both onto the site and away from the site.

U.S. EPA. 1994a. Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. April. 

This document is cited as a source for the assumptions that losses resulting from erosion (kse), surface runoff (ksr), degradation (ksg), leaching (ksl), and volatilization (ksv) are all zero.

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

This document is one of the reference documents for the equations in Tables B-3-4 and B-3-5. This document is also cited as one of the sources that recommend using the assumption that

the loss resulting from erosion (kse) is zero and the loss resulting from degradation (ksg) is “NA” or zero for all compounds.
TABLE B-3-2

COPC SOIL LOSS CONSTANT

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 4 of 4)

B-99

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December. Environmental Criteria and Assessment Office. ORD. Cincinnati, Ohio.

This document is one of the reference documents for the equations for ksr, ksl, and ksv.
TABLE B-3-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 1 of 5)

B-100

Description

This equation calculates the constant for COPC loss resulting from erosion of soil. Consistent with U.S. EPA (1994), U.S. EPA (1994b), and NC DEHNR (1997), we recommend a default value

of zero for kse because of contaminated soil eroding onto the site and away from the site. In site-specific cases where the permitting authority considers it appropriate to calculate a kse, we

recommend using the equation presented in this table along with associated uncertainties. You can find additional discussion on determining kse in U.S. EPA (1998). Uncertainties associated

with this equation include:

(1) For soluble COPCs, leaching might lead to movement below 2 centimeter in untilled soils, resulting in a greater mixing depth. This uncertainty may overestimate kse.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in situ materials) in comparison to that of other residues. This

uncertainty may underestimate kse.

Equation

Variable Description Units Value

kse COPC loss constant due to soil

erosion

yr-1 0

Consistent with U.S. EPA (1994), U.S. EPA (1994b), and NC DEHNR (1997), we recommend that the default value assumed

for kse is zero because contaminated soil erodes onto the site and away from the site. Uncertainty may overestimate kse.

0.1 Units conversion factor g-kg/cm2

-

m2

Xe

Unit soil loss kg/m2-yr Varies

This variable is site-specific and is calculated by using the equation in Table B-4-13.

The following uncertainty is associated with this variable:

All of the equation variables are site-specific. Using default values rather than site-specific values for any or all of

these variables will result in unit soil loss (Xe) estimates that are under- or overestimated to some degree. Based on

default values, Xe

 estimates can vary over a range of less than two orders of magnitude.
TABLE B-3-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 2 of 5)

Variable Description Units Value

B-101

SD Sediment delivery ratio unitless Varies

This value is site-specific and is calculated by using the equation in Table B-4-14.

Uncertainties associated with this variable include the following: 

(1) The recommended default values for the empirical intercept coefficient, a, are average values that are based on

studies of sediment yields from various watersheds. Therefore, those default values may not accurately represent

site-specific watershed conditions. As a result, using these default values may under- or overestimate SD.

(2) The recommended default value for the empirical slope coefficient, b, is based on a review of sediment yields from

various watersheds. This single default value may not accurately represent site-specific watershed conditions. As a

result, using this default value may under- or overestimate SD.

ER Soil enrichment ratio unitless Inorganics: 1

Organics: 3

COPC enrichment occurs because (1) lighter soil particles erode more than heavier soil particles, and (2) concentration of

organic COPCs—which is a function of organic carbon content of sorbing media—is expected to be higher in eroded material

than in in-situ soil (U.S. EPA 1998). In the absence of site-specific data, we recommend a default value of 3 for organic

COPCs and 1 for inorganic COPCs. This is consistent with other U.S. EPA guidance (1998), which recommends a range of 1

to 5 and a value of 3 as a “reasonable first estimate.” This range has been used for organic matter, phosphorus, and other soilbound COPCs (U.S. EPA 1998); however, no sources or references were provided for this range. ER is generally higher in

sandy soils than in silty or loamy soils (U.S. EPA 1998).

The following uncertainty is associated with this variable:

The default ER value may not accurately reflect site-specific conditions; therefore, kse may be over- or

underestimated to an unknown extent. Using county-specific ER values will reduce the extent of any uncertainties.

BD Soil bulk density g soil/cm3

soil

1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value of

1.5 g soil/cm3 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that a

value of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended soil bulk density value may not accurately represent site-specific soil conditions.
TABLE B-3-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 3 of 5)

Variable Description Units Value

B-102

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs

:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with U.S.

EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A default

value of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil (Brzuzy et al.

1995). A default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting a greater

mixing depth. This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution compared to other residues. 

This uncertainty may underestimate Cs and CstD. 

Kds

Soil-water partition coefficient mL water/g

soil 

(or cm3

water/g soil)

Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in Appendix A2.

2sw

Soil volumetric water content mL

water/cm3

soil

0.2 

This variable is site-specific, and depends on the available water and on soil structure; you can estimate 2sw as the midpoint

between a soil’s field capacity and wilting point, if you can identify a representative watershed soil. However, we recommend 

using 0.2 ml/cm3 as a default value. This value is the midpoint of the range 0.1 (very sandy soils) to 0.3 (heavy loam/clay

soils) recommended by U.S. EPA (1998) (no source or reference is provided for this range) and is consistent with U.S. EPA

(1994b).

The following uncertainty is associated with this variable:

The default 2sw value may not accurately reflect site-specific or local conditions; therefore, kse may be under- or

overestimated to a small extent, based on the limited range of values.
TABLE B-3-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 4 of 5)

B-103

REFERENCES AND DISCUSSION

Carsel, R.F., R.S. Parish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2. 

Pages 11-24.

This document is cited by U.S. EPA (1994b) as the source for a mean soil bulk density, BD, value of 1.5 (g soil/cm3 soil) for loam soil. 

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York.

This document is cited by U.S. EPA (1998) for the statement that soil bulk density, BD, is affected by the soil structure, such as looseness or compaction of the soil, depending on the water

and clay content of the soil.

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the sources that recommend assuming that the loss resulting from erosion (kse) is zero because contaminated soil erodes both onto the site and away from the site.

U.S. EPA. 1994. Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. April. 

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This document is the source of values for soil mixing zone depth, Zs, for tilled and untilled soil. 

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

This document recommends (1) a default soil bulk density value of 1.5 (g soil/cm3

 soil), based on a mean value for loam soil that is taken from Carsel et al. (1988), and (2) a default soil

volumetric water content, 2sw, value of 0.2 (mL water/cm3

 soil).
TABLE B-3-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 5 of 5)

B-104

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document is the source of a range of COPC enrichment ratio, ER, values. The recommended range, 1 to 5, was used for organic matter, phosphorous, and other soul-bound COPCs. 

This document recommends a value of 3 as a “reasonable first estimate,” and states that COPC enrichment occurs because lighter soil particles erode more quickly than heavier soil

particles. Lighter soil particles have higher ratios of surface area to volume and are higher in organic matter content. Therefore, concentration of organic COPCs, which is a function of the

organic carbon content of sorbing media, is expected to be higher in eroded material than in in situ soil.

This document is also a source of the following:

C A range of soil volumetric water content (2sw) values of 0.1 ml water/cm3 soil (very sandy soils) to 0.3 ml water/cm3 soil (heavy loam/clay soils). However, no source or reference

is provided for this range.

C A range of values for soil mixing zone depth, Zs, for tilled and untilled soil

C The equations in Tables B-3-3 and B-3-5.
TABLE B-3-4

COPC LOSS CONSTANT DUE TO RUNOFF

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 1 of 4)

B-105

Description

This equation calculates the COPC loss constant due to runoff of soil. Uncertainties associated with this equation include the following:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeter in untilled soils, resulting in a greater mixing depth. This uncertainty may overestimate ksr.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution in comparison to that of other residues. This uncertainty may underestimate ksr.

Equation

Variable Description Units Value

ksr COPC loss constant due to runoff yr-1

RO Average annual surface runoff from

pervious areas

cm/yr Varies

This variable is site-specific. According to U.S. EPA (1998), U.S. EPA (1994b), and NC DEHNR (1997), you can estimate RO

by using the Water Atlas of the United States (Geraghty et al. 1973). According to NC DEHNR (1997), you can also use more

detailed, site-specific procedures for estimating the amount of surface runoff, such as those based on the U.S. Soil Conservation

Service curve number equation (CNE). U.S. EPA (1985) is cited as an example of such a procedure.

The following uncertainty is associated with this variable:

To the extent that site-specific or local average annual surface runoff information is not available, default or

estimated values may not accurately represent site-specific or local conditions. As a result, ksr may be under- or

overestimated to an unknown degree.
TABLE B-3-4

COPC LOSS CONSTANT DUE TO RUNOFF

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 2 of 4)

Variable Description Units Value

B-106

2sw

Soil volumetric water content mL

water/cm3

soil

0.2

This variable is depends on the available water and soil structure; you can estimate 2sw as the midpoint between a soil’s field

capacity and wilting point, if you can identify a representative watershed soil. We recommend using 0.2 (mL water/cm3 soil)

as a default value. This value is the midpoint of the range 0.1 (very sandy soils) to 0.3 (heavy loam/clay soils), which is

recommended by U.S. EPA (1998) (no source or reference is provided for this range), and is consistent with U.S. EPA (1994b)

and NC DEHNR (1997).

The following uncertainty is associated with this variable:

The default 2sw value may not accurately reflect site-specific or local conditions; therefore, ksr may be under- or

overestimated to a small extent, based on the limited range of values.

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs

:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with U.S.

EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A default

value of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil (Brzuzy et al.

1995). A default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting a greater

mixing depth. This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution compared to other residues. This

uncertainty may underestimate Cs and CstD. 

Kds

Soil-water partition coefficient mL water/g

soil

(or cm3

water/g

soil)

Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2.

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in Appendix A-2.
TABLE B-3-4

COPC LOSS CONSTANT DUE TO RUNOFF

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 3 of 4)

Variable Description Units Value

B-107

BD Soil bulk density g soil/cm3

soil

1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value of

1.5 g soil/cm3 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that a value

of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended soil bulk density value may not accurately represent site-specific soil conditions.

REFERENCES AND DISCUSSION

Carsel, R.F., R.S. Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2. 

Pages 11-24.

This document is cited by U.S. EPA (1994b) as the source of a mean soil bulk density, BD, value of 1.5 (g soil/cm3 soil) for loam soil. 

Geraghty, J.J., D.W. Miller, F. Van der Leeden, and F.L. Troise. 1973. Water Atlas of the United States. Water Information Center, Port Washington, New York.

This document is cited by U.S. EPA (1998), U.S. EPA (1994), and NC DEHNR (1997) as a reference to calculate average annual runoff, RO. This reference provides maps with isolines of

annual average surface water runoff, which is defined as all flow contributions to surface water bodies, including direct runoff, shallow interflow, and ground water recharge. Because these

values are total contributions and not only surface runoff, U.S. EPA (1994) recommends that the volumes be reduced by 50 percent in order to estimate surface runoff.

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York.

This document is cited by U.S. EPA (1998) for the statement that soil bulk density, BD, is affected by the soil structure, such as looseness or compaction of the soil, depending on the water

and clay content of the soil.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the source documents that cites the use of Table B-3-4; however, this document is not the original source of this equation (this source is unknown). This document

also recommends the following:

C Estimation of annual current runoff, RO (cm/yr), by using the Water Atlas of the United States (Geraghty et al. 1973) or site-specific procedures, such as using the U.S. Soil

Conservation Service curve number equation (CNE); U.S. EPA (1985) is cited as an example of such a procedure.

C Default value of 0.2 (mL water/cm3

 soil) for soil volumetric water content (2sw)
TABLE B-3-4

COPC LOSS CONSTANT DUE TO RUNOFF

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 4 of 4)

B-108

U.S. EPA. 1985. Water Quality Assessment: A Screening Procedure for Toxic and Conventional Pollutants in Surface and Ground Water—Part I (Revised. 1985). Environmental Research

Laboratory. Athens, Georgia. EPA/600/6-85/002a. September.

This document is cited by NC DEHNR (1997) as an example of the use of the U.S. Soil Conservation Service CNE to estimate site-specific surface runoff. 

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This document presents a range of values for soil mixing zone depth, Zs, for tilled and untilled soil.

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Offices of Emergency and Remedial Response. Office of Solid Waste. December.

This document recommends the following:

C Estimation of average annual runoff, RO, by using the Water Atlas of the United States (Geraghty et al. 1973)

C Default soil bulk density, BD, value of 1.5 (g soil/cm3 soil), based on the mean for loam soil that is taken from Carsel et al. (1988)

C Default soil volumetric water content, 2sw, value of (0.2 mL water/cm3 soil)

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document recommends the following:

C A range of soil volumetric water content, 2sw, values of 0.1 (very sandy soils) to 0.3 (heavy loam/clay soils) (the original source of, or reference for, these values is not identified)

C A range of values for soil mixing depth, Zs

, for tilled and untilled soil (the original source of, or reference for, these values is not identified)

C Using the Water Atlas of the United States (Geraghty et al. 1973) to calculate average annual runoff, RO
TABLE B-3-5

COPC LOSS CONSTANT DUE TO LEACHING

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 1 of 5)

B-109

Description

This equation calculates the COPC loss constant due to leaching of soil. Uncertainties associated with this equation include the following:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in a greater mixing depth. This uncertainty may overestimate ksl.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in situ materials) compared to other residues. This uncertainty

may underestimate ksl.

(3) The original source of this equation has not been identified. U.S. EPA (1998) presents the equation as shown here. U.S. EPA (1994b) and NC DEHNR (1997) replaced the numerator

as shown with “q”, defined as average annual recharge (cm/yr). 

Equation

Variable Description Units Value

ksl Constant for COPC loss due to soil

leaching

yr-1

P Average annual precipitation cm/yr 18.06 to 164.19

This variable is site-specific. This range is based on information presented in U.S. EPA (1998), representing data for 69

selected cities (U.S. Bureau of Census 1987; Baes et al. 1984). The 69 selected cities are not identified; however, they appear

to be located throughout the continental United States. We recommend using site-specific data.

The following uncertainty is associated with this variable:

To the extent that a site is not located near an established meteorological data station, and site-specific data are not

available, default average annual precipitation data may not accurately reflect site-specific conditions. As a result, ksl

may be under- or overestimated. However, average annual precipitation data are reasonably available; therefore, we

expect uncertainty introduced by this variable to be minimal.
TABLE B-3-5

COPC LOSS CONSTANT DUE TO LEACHING

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 2 of 5)

Variable Description Units Value

B-110

I Average annual irrigation cm/yr 0 to 100

This variable is site-specific. This range is based on information presented in U.S. EPA (1998), representing data for 69

selected cities (Baes et al. 1984). The 69 selected cities are not identified; however, they appear to be located throughout the

continental United States.

The following uncertainty is associated with this variable:

To the extent that site-specific or local average annual irrigation information is not available, default values

(generally based on the closest comparable location) may not accurately reflect site-specific conditions. As a result,

ksl may be under- or overestimated to an unknown degree.

RO Average annual surface runoff from

pervious areas

cm/yr Varies

This variable is site-specific. According to U.S. EPA (1998), U.S. EPA (1994b), and NC DEHNR (1997), you can estimate

RO by using the Water Atlas of the United States (Geraghty et al. 1973). According to NC DEHNR (1997), you can also use

more detailed, site-specific procedures, such as those based on the U.S. Soil Conservation Service CNE. U.S. EPA (1985) is

cited as an example of such a procedure.

The following uncertainty is associated with this variable:

To the extent that site-specific or local average annual surface runoff information is not available, default or

estimated values may not accurately represent site-specific or local conditions. As a result, ksl may be under- or

overestimated to an unknown degree.

Ev

Average annual evapotranspiration cm/yr 35 to 100

This variable is site-specific. This range is based on information presented in U. S. EPA (1998), representing data from 69

selected cities. The 69 selected cities are not identified; however, they appear to be located throughout the continental United

States.

The following uncertainty is associated with this variable:

To the extent that site-specific or local average annual evapotranspiration information is not available, default values

may not accurately reflect site-specific conditions. As a result, ksl may be under- or overestimated to an unknown

degree.
TABLE B-3-5

COPC LOSS CONSTANT DUE TO LEACHING

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 3 of 5)

Variable Description Units Value

B-111

2sw

Soil volumetric water content mL

water/cm3

soil

0.2

This variable is site-specific, and depends on the available water and on soil structure. You can estimate 2sw as the midpoint

between a soil’s field capacity and wilting point, if you can identify a representative watershed soil. We recommend using 0.2

ml/cm3 as a default value. This value is the midpoint of the range of 0.1 (very sandy soils) to 0.3 (heavy loam/clay soils)

recommended by U.S. EPA (1998) (no source or reference is provided for this range) and is consistent with U.S. EPA (1994b)

and NC DEHNR (1997).

The following uncertainty is associated with this variable:

The default 2sw value may not accurately reflect site-specific or local conditions; therefore, ksl may be under- or

overestimated to a small extent, based on the limited range of values.

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs

:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with U.S.

EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A default

value of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil (Brzuzy et al.

1995). A default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting a greater

mixing depth. This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution compared to other residues. This

uncertainty may underestimate Cs and CstD. 

BD Soil bulk density g soil/cm3

soil

1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value of

1.5 g soil/cm3

 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that a value

of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended soil bulk density value may not accurately represent site-specific soil conditions.
TABLE B-3-5

COPC LOSS CONSTANT DUE TO LEACHING

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 4 of 5)

Variable Description Units Value

B-112

Kds

Soil-water partition coefficient cm3

 water/g

soil

Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in Appendix A-2.

REFERENCES AND DISCUSSION

Baes, C.F., R.D. Sharp, A.L. Sjoreen and R.W. Shor. 1984. “A Review and Analysis of Parameters for Assessing Transport of Environmentally Released Radionuclides through Agriculture.” 

Prepared for the U.S. Department of Energy under Contract No. DEAC05-840R21400.

For the continental United States, as cited in U.S. EPA (1998), this document is the source of a series of maps showing: (1) average annual precipitation (P), (2) average annual irrigation

(I), and (3) average annual evapotranspiration isolines.

Carsel, R.F., R.S. Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2. 

Pages 11-24.

This document is cited by U.S. EPA (1994b) as the source for a mean soil bulk density value, BD, of 1.5 g soil/cm3

 soil for loam soil.

Geraghty, J.J., D.W. Miller, F. Van der Leeden, and F.L. Troise. 1973. Water Atlas of the United States. Water Information Center, Port Washington, New York.

This document is cited by U.S. EPA (1998), U.S. EPA (1994b), and NC DEHNR (1997) as a reference for calculating average annual runoff, RO. This document provides maps with

isolines of annual average surface runoff, which is defined as all flow contributions to surface water bodies, including direct runoff, shallow interflow, and ground water recharge. Because

these volumes are total contributions and not only surface runoff, U.S. EPA (1994b) recommends that the volumes be reduced by 50 percent in order to estimate average annual surface

runoff.

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York, New York.

This document is cited by U.S. EPA (1998) for the statement that soil bulk density, BD, is affected by the soil structure, such as looseness or compaction of the soil, depending on the water

and clay content of the soil.
TABLE B-3-5

COPC LOSS CONSTANT DUE TO LEACHING

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 5 of 5)

B-113

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the source documents that cites the use of the equation in Table B-1-5. However, the document is not the original source of this equation. This document also

recommends the following:

C Estimation of average annual surface runoff, RO (cm/yr), by using the Water Atlas of the United States (Geraghty et al. 1973) or site-specific procedures, such as using the U.S.

Soil Conservation Service CNE; U.S. EPA 1985 is cited as an example of such a procedure.

C A default value of 0.2 (mL water/cm3 soil) for soil volumetric water content, 2sw

U.S. Bureau of the Census. 1987. Statistical Abstract of the United States: 1987. 107th edition. Washington, D.C.

This document is a source of average annual precipitation (P) information for 69 selected cites, as cited in U.S. EPA (1998); these 69 cities are not identified. 

U.S. EPA. 1985. Water Quality Assessment: A Screening Procedure for Toxic and Conventional Pollutants in Surface and Groundwater. Part I (Revised 1985). Environmental Research

Laboratory. Athens, Georgia. EPA/600/6-85/002a. September.

This document is cited by NC DEHNR (1997) as an example of the use of the U.S. Soil Conservation Service CNE to estimate RO.

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This document is the source of values for soil mixing zone depth, Zs, for tilled and untilled soil. 

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document recommends (1) a default soil volumetric water content, 2sw, value of 0.2 (mL water/cm3 soil), and (2) a default soil bulk density, BD, value of 1.5 (g soil/cm3 soil), based on

a mean value for loam soil from Carsel et al. (1988).

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document is one of the reference source documents for the equation in Table B-3-5. The original source of this equation is not identified. This document also presents a range of

values for soil mixing depth, Z, for tilled and untilled soil; the original source of these values is not identified.
TABLE B-3-6

COPC LOSS CONSTANT DUE TO VOLATILIZATION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 1 of 4)

B-114

Description

This equation calculates the COPC loss constant from soil due to volatilization, and was obtained from Methodology for Assessing Health Risks Associated with Multiple Exposure Pathways to

Combustor Emissions (U.S. EPA 1998). The soil loss constant due to volatilization (ksv) is based on gas equilibrium coefficients and gas phase mass transfer. The first order decay constant, ksv,

is obtained by adapting the Hwang and Falco equation for soil vapor phase diffusion (Hwang and Falco 1986).

Uncertainties associated with this equation include the following:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in a greater mixing depth. This uncertainty may overestimate ksv.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in situ materials) compared to other residues. This uncertainty

may underestimate ksv.

Equation

Variable Definition Units Value

ksv COPC loss constant due to 

volatilization 

yr-1

3.1536 x 10+7 Units conversion factor s/yr

H Henry’s Law constant atmm3

/mol

Varies

This variable is COPC-specific. We discuss this variable in detail in detail in Appendix A-2, and offer COPC-specific values

in the HHRAP companion database. 

The following uncertainty is associated with this variable:

Values for this variable, estimated using the parameters and algorithms in Appendix A-2, may under- or

overestimate the actual COPC-specific values. As a result, ksv may be under- or overestimated.
TABLE B-3-6

COPC LOSS CONSTANT DUE TO VOLATILIZATION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 2 of 4)

Variable Definition Units Value

B-115

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs

:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with U.S.

EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A default

value of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil (Brzuzy et al.

1995). A default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting a greater

mixing depth. This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution compared to other residues. 

This uncertainty may underestimate Cs and CstD. 

Kds

Soil-water partition coefficient cm3

water/g

soil

Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in Appendix A2.

R Universal gas constant atmm3

/mol-K

8.205 x 10-5

There are no uncertainties associated with this parameter.

Ta

Ambient air temperature K 298

This variable is site-specific. U.S. EPA (1998) recommends an ambient air temperature of 298 K.

The following uncertainty is associated with this variable:

To the extent that site-specific or local values for Ta are not available, default values may not accurately represent

site-specific conditions. We expect the uncertainty associated with the selection of a single value from within the

temperature range at a single location to be more significant than the uncertainty associated with choosing a single

ambient temperature to represent all localities.
TABLE B-3-6

COPC LOSS CONSTANT DUE TO VOLATILIZATION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 3 of 4)

Variable Definition Units Value

B-116

BD Soil bulk density g soil/cm3

soil

1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value of

1.5 g soil/cm3 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that a

value of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended soil bulk density value may not accurately represent site-specific soil conditions.

Dsoil

Solids particle density g/cm3

2.7

We recommend the use of this value, based on Blake and Hartage (1996) and Hillel (1980). 

The solids particle density will vary with location and soil type.

Da

Diffusivity of COPC in air cm2/s Varies

This value is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in the

HHRAP companion database. 

The following uncertainty is associated with this variable:

The default Da

 values may not accurately represent the behavior of COPCs under site-specific conditions. 

However, we expect the degree of uncertainty to be minimal.

2sw

Soil volumetric water content mL/cm3

soil

0.2

This variable depends on the available water and on soil structure. You can estimate 2sw as the midpoint between a soil’s

field capacity and wilting point, if you can identify a representative watershed soil. However, we recommend using 0.2

ml/cm3

 as a default value. This value is the midpoint of the range 0.1 (very sandy soils) to 0.3 (heavy loam/clay soils)

recommended by U.S. EPA (1998) (no source or reference is provided for this range) and is consistent with U.S. EPA

(1994b).

The following uncertainty is associated with this variable:

(1) The default 2sw values may not accurately reflect site-specific or local conditions; therefore, ksv may be under- or

overestimated to a small extent, based on the limited range of values.
TABLE B-3-6

COPC LOSS CONSTANT DUE TO VOLATILIZATION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 4 of 4)

B-117

REFERENCES AND DISCUSSION

Blake, GR. and K.H. Hartge. 1996. Particle Density. Methods of Soil Analysis, Part 1: Physical and Mineralogical Methods. Second Edition. Arnold Klute, Ed. American Society of Agronomy,

Inc. Madison, WI., p. 381. 

Carsel, R.F., R.S, Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2. 

Pages 11-24.

This document is cited by U.S. EPA (1994b) as the source of a mean soil bulk density value, BD, of 1.5 (g soil/cm3 soil) for loam soil.

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York, New York.

Hwang S. T. and Falco, J. W. 1986. “Estimation of multimedia exposures related to hazardous waste facilities”, In: Pollutants in a Multimedia Environment. Yoram Cohen, Ed. Plenum Publishing

Corp. New York.

Miller, R.W. and D.T. Gardiner. 1998. In: Soils in Our Environment. J.U. Miller, Ed. Prentice Hall. Upper Saddle River, NJ. pp. 80-123.

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This document is the source of values for soil mixing zone depth, Zs, for tilled and untilled soil. 

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Waste. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

This document recommends a default soil density, BD, value of 1.5 (g soil/cm3

 soil), based on a mean value for loam soil that is taken from Carsel et al. (1988).

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document recommends the following:

C A range of values for soil mixing zone depth, Zs, for tilled and untilled soil; however, the source or basis for these values is not identified

C A default ambient air temperature of 298 K

C A range of soil volumetric water content, 2sw
TABLE B-3-7

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B-118

Description

This equation calculates the COPC concentration in forage and silage (aboveground vegetation) due to wet and dry deposition of COPCs onto plant surfaces. The limitations and uncertainty

introduced in calculating this variable include the following:

(1) Uncertainties associated with the variables Q, Dydp, and Dywp are COPC- are site-specific.

(2) In calculating the variable Fw, values of r assumed for most organic compounds—based on the behavior of insoluble polystyrene micro spheres tagged with radionuclides— may

accurately represent the behavior of organic compounds under site-specific conditions.

(3) The empirical relationship used to calculate the variable Rp, and the empirical constant for use in the relationship, may not accurately represent site-specific silage types.

(4) The recommended equation for calculating kp does not consider chemical degradation processes. This conservative approach contributes to the possible overestimation of plant

concentrations.

(5) The harvest yield (Yh) and area planted (Ah) values used to estimate the variable Yp may not reflect site-specific conditions.

Equation

For mercury modeling

Forage and silage concentrations due to direct deposition are calculated using 0.48Q for total mercury and Fv = 0.85 in the mercury modeling equation. Apportion the calculated Pd values into

the divalent (Hg2+) and methyl mercury (MHg) forms based on the 78% divalent mercury (Hg2+) and 22% methyl mercury (MHg) speciation split in aboveground produce and forage. 

Pd (Hg2+) = 0.78 Pd (Mercu ry)

Pd (Mhg) = 0.22 Pd (Mercu ry)

Evaluate divalent and methyl mercury as individual COPCs. Calculate Pd for divalent and methyl mercury using the corresponding equations above.
TABLE B-3-7

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B-119

Variable Description Units Value

Pd Concentration of COPC in forage

and silage due to direct deposition 

mg COPC/kg

DW

1000 Units conversion factor mg/g

Q COPC-specific emission rate g/s Varies

This value is COPC- and site-specific, and is determined by air dispersion modeling. See Chapters 2 and 3 for guidance on

calculating this variable. Uncertainties associated with this variable are site-specific.

Fv

Fraction of COPC air concentration

in vapor phase

unitless 0 to 1

This variable is COPC-specific. We discuss Fv

in detail in Appendix A-2, and offer COPC-specific values in the HHRAP

companion database. This range is based on values presented in Appendix A-2. U.S. EPA (1994b) and NC DEHNR (1997)

also present values.

Fv

 was calculated using an equation presented in Junge (1977) for all organic COPCs, including PCDDs and PCDFs. U.S.

EPA (1994c) states that Fv = 0 for all metals (except mercury).

The following uncertainties are associated with this variable:

(1) It assumes a default ST value for background plus local sources, rather than an ST value for urban sources. If a

specific site is located in an urban area, using the latter ST

 value may be more appropriate. Specifically, the ST

value for urban sources is about one order of magnitude greater than that for background plus local sources, and it

would result in a lower calculated Fv value; however, the Fv value is likely to be only a few percent lower.

(2) According to Bidleman (1988), the Fv

 equation assumes that the variable c (Junge constant) is constant

for all chemicals; however, the value of c depends on the chemical (sorbate) molecular weight, the

surface concentration for monolayer coverage, and the difference between the heat of desorption from the particle

surface and the heat of vaporization of the liquid phase sorbate. To the extent that site- or COPC-specific

conditions may cause the value of c to vary, uncertainty is introduced if a constant value of c is used to calculate Fv

.

(3) Based on U.S. EPA (1994a), the Fv

 value for dioxins (PCDD/PCDF) is intended to represent 2, 3, 7, 8-TCDD

TEQs by weighting data for all dioxin and furan congeners with nonzero TEFs. Uncertainty is introduced, because

the Agency has been unable to verify the recommended Fv

 value for dioxins.

Dydp Unitized yearly average dry

deposition from particle phase

s/m2-yr Varies

This variable is COPC- and site-specific and is determined by air dispersion modeling (see Chapter 3). Uncertainties

associated with this variable are site-specific.
TABLE B-3-7

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Variable Description Units Value

B-120

Fw Fraction of COPC wet deposition

that adheres to plant surfaces

unitless 0.2 for anions

0.6 for cations and most organics

We recommend using the chemical class-specific values of 0.2 for anions and 0.6 for cations and most organics, as estimated

by U.S. EPA (1994b) and U.S. EPA (1995). These values are the best available information, based on a review of the current

scientific literature, with the following exception: We recommend using an Fw value of 0.2 for the three organic COPCs that

ionize to anionic forms. These include (1) 4-chloroaniline, (2) n-nitrosodiphenylamine, and (3) n-nitrosodi-n-proplyamine

(see Appendix A-2).

The values estimated by U.S. EPA (1994b) and U.S. EPA (1995) are based on information presented in Hoffman, Thiessen,

Frank, and Blaylock (1992), which presented values for a parameter (r) termed the “interception fraction.” These values

were based on a study in which soluble radionuclides and insoluble particles labeled with radionuclides were deposited onto

pasture grass via simulated rain. The parameter (r) is defined as “the fraction of material in rain intercepted by vegetation

and initially retained” or, essentially, the product of Rp and Fw, as defined:

r = Rp @ Fw

The r values developed by Hoffman, Thiessen, Frank, and Blaylock (1992) were divided by an Rp value of 0.5 for forage

(U.S. EPA 1994b). The Fw values developed by U.S. EPA (1994b) are 0.2 for anions and 0.6 for cations and insoluble

particles. U.S. EPA (1994b) and U.S. EPA (1995) recommended using the Fw value calculated by using the r value for

insoluble particles to represent organic compounds; however, no rationale for this recommendation was provided.

Uncertainties associated with this variable include the following:

Values of r assumed for most organic compounds, based on the behavior of insoluble polystyrene micro spheres

tagged with radionuclides, may not accurately represent the behavior of organic compounds under site-specific

conditions.

Dywp Unitized yearly average wet

deposition from particle phase

s/m2

-yr Varies

This variable is COPC- and site-specific, and is determined by air dispersion modeling (see Chapter 3). Uncertainties

associated with this variable are site-specific.
TABLE B-3-7

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(Page 4 of 10) 

Variable Description Units Value

B-121

Rp Interception fraction of the edible

portion of plant

unitless Forage: 0.5

Silage: 0.46

We recommend using these default Rp values because they represent the most current information available; specifically,

productivity and relative ingestion rates. 

As summarized in Baes et al. (1984), experimental studies of pasture grasses identified a correlation between initial Rp values

and productivity (standing crop biomass [Yp]) (Chamberlain 1970):

Rp = 1 - e -(@ Yp

where

Rp = Interception fraction of the edible portion of plant (unitless)

( = Empirical constant. Chamberlain (1970) presents a range of 2.3 to 3.3; Baes et al. (1984) uses 2.88, the

midpoint for pasture grasses.

Yp = Yield or standing crop biomass (productivity) (kg DW/m2

)

Baes et al. (1984) proposed using the same empirical relationship developed by Chamberlain (1970) for other vegetation

classes. Class-specific estimates of the empirical constant, (, were developed by forcing an exponential regression equation

through several points, including average and theoretical maximum estimates of Rp and Yp (Baes et al. 1984) . The classspecific Rp estimates were then weighted, by relative ingestion of each class, to arrive at the weighted average Rp value of

0.5 for forage and 0.46 for silage.

U.S. EPA (1994b) and U.S. EPA (1995) recommend a weighted average Rp value of 0.05. However, the relative ingestion

rates used in U.S. EPA (1994b) and U.S. EPA (1995) to weight the average Rp value were derived from U.S. EPA (1992)

and U.S. EPA (1994b). The most current guidance available for ingestion rates of homegrown produce is the 1997 Exposure

Factors Handbook (U.S. EPA 1997). The default Rp values of 0.5 for forage and 0.46 for silage were weighted by relative

ingestion rates of homegrown exposed fruit and exposed vegetables found in U.S. EPA (1997).

Uncertainties associated with this variable include the following:

The empirical constants developed by Baes et al. (1984) to use in the empirical relationship developed by

Chamberlain (1970) may not accurately represent site-specific mixes of forage or silage.
TABLE B-3-7

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(Page 5 of 10) 

Variable Description Units Value

B-122

kp Plant surface loss coefficient yr-1 18

This value is site-specific. We recommend the kp value of 18 recommended by U.S. EPA (1998) and U.S. EPA (1994b). 

The kp value selected is the midpoint of a possible range of values (7.44 to 90.36). U.S. EPA (1998) identified several

processes—including wind removal, water removal, and growth dilution—that reduce the amount of COPC that has been

deposited on a plant surface. The term kp is a measure of the amount of contaminant lost to these physical processes over

time. U.S. EPA (1998) cites Miller and Hoffman (1983) for the following equation used to estimate kp:

kp = (ln 2/ t1/2) @ 365 days/year

where

t

1/2 = half-life (days)

Miller and Hoffman (1983) report half-life values ranging from 2.8 to 34 days for a variety of COPCs on herbaceous

vegetation. These half-life values convert to kp values of 7.44 to 90.36 yr-1. U.S. EPA (1998) and U.S. EPA (1994b)

recommend a kp value of 18, based on a generic 14-day half-life, corresponding to physical processes only. The 14-day halflife is approximately the midpoint of the range (2.8 to 34 days) estimated by Miller and Hoffman (1983).

Uncertainties associated with this variable include the following:

(1) the recommended equation for calculating kp does not consider chemical degradation processes. Adding chemical

degradation processes would decrease half-lives and thereby increase kp values; plant concentration decreases as kp

increases. Therefore, using a kp value that does not consider chemical degradation processes is conservative.

(2) Based on this range (7.44 to 90.36), plant concentrations could range from about 1.8 times higher to about 5 times

lower than the plant concentrations, based on a kp value of 18.
TABLE B-3-7

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(Page 6 of 10) 

Variable Description Units Value

B-123

Tp Length of plant exposure to

deposition per harvest of edible

portion of plant

yr Forage: 0.12

Silage: 0.16

This variable is site-specific. We recommend the using these default values in the absence of site-specific information. U.S.

EPA (1998), U.S. EPA (1994b), and NC DEHNR (1997) recommended treating Tp as a constant, based on the average

periods between successive hay harvests and successive grazing.

For forage, the average of the average period between successive hay harvests (60 days) and the average period between

successive grazing (30 days) is used (that is, 45 days). Tp is calculated as follows:

Tp = (60 days + 30 days)/ 2 ÷ 365 days/yr = 0.12 yr

Use these average periods from Beecher and Travis (1989) when calculating the COPC concentration in cattle forage.

When calculating the COPC concentration in silage fed to cattle, the average period between successive hay harvests (60

days) is used (Beecher and Travis 1989). Tp is calculated as follows:

Tp = 60 days ÷ 365 days/year = 0.16 year

The following uncertainty is associated with this variable:

Using hay harvest cycles to estimate silage Tp values may underestimate COPC uptakes if silage types differ

significantly from hay, and have longer actual harvest cycles (for example, if grains or other feeds with longer

harvest cycles are used as silage). This underestimation will increase as actual harvest cycles increase, up to about

3 months. Beyond that time frame, if the kp value remains unchanged at 18. Higher Tp values will have little

effect on predicted COPC concentrations in plants.
TABLE B-3-7

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(Page 7 of 10) 

Variable Description Units Value

B-124

Yp Yield or standing crop biomass of

the edible portion of the plant

kg DW/m2

Forage: 0.24

Silage: 0.8

This variable is site-specific. We recommend the use of these default values in the absence of site-specific information. U.S.

EPA (1990) states that the best estimate of Yp is productivity, which Baes et al. (1984) and Shor et al. (1982) define as

follows:

Yp . Yh /Ahi

where

Yh = Harvest yield of ith crop (kg DW)

Ahi = Area planted to crop i (m2

)

U.S. EPA (1994b) and NC DEHNR (1997) recommended using either previously calculated Yp values or the equation

presented above to calculate a Yp value.

We recommend that the forage Yp value be calculated as a weighted average of pasture grass and hay Yp values. Weights

(0.75 for forage and 0.25 for hay) are based on (1) the fraction of a year during which cattle are assumed to be pastured and

eating grass (9 mo/yr), and (2) the fraction of a year during which cattle are assumed to not be pastured and to be fed hay (3

mo/yr). An unweighted Yp value for pasture grass of 0.15 kg DW/m2

 is assumed (U.S. EPA 1994b). An unweighted Yp

value for hay of 0.5 kg DW is calculated by the above equation, using the following dry harvest yield (Yh) and area harvested

(Ah) values:

Yh = 1.22 x 10+11 kg DW; from 1993 U.S. average wet weight Yh of 1.35 x 1011 kg (USDA 1994)

and conversion factor of 0.9 (Agricultural Research Service 1994)

Ah = 2.45 x 10+11 m2

; from 1993 U.S. average for hay (USDA 1994).

The unweighted pasture grass and hay Yp values are multiplied by 3/4 and 1/4, respectively. They are then added to calculate

the weighted forage Yp of 0.24 kg DW. We recommend that a production weighted U.S. average Yp of 0.8 be assumed for

silage (Shor et al. 1982).

The following uncertainty is associated with this variable:

The harvest yield (Yh) and area planted (Ah) may not reflect site-specific conditions. This may under- or

overestimate Yp.
TABLE B-3-7

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(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 8 of 10) 

B-125

REFERENCES AND DISCUSSION

Agricultural Research Service. 1994. Personal communication regarding the dry weight fraction value for hay between G.F. Fries, and Glenn Rice and Jennifer Windholz, U.S. EPA Office of 

Research and Development. March 22.

This communication is cited by NC DEHNR (1997) for the fraction of 0.9 used to convert wet weight to dry weight for hay.

Baes, C.F., R.D. Sharp, A.L. Sjoreen, and R.W. Shor. 1984. Review and Analysis of Parameters and Assessing Transport of Environmentally Released Radionuclides through Agriculture. 

ORNL-5786. Oak Ridge National Laboratory. Oak Ridge, Tennessee. September.

This document proposes using the empirical relationship developed by Chamberlain (1970) (see further discussion in reference section of Table B-2-7) that identifies a correlation between

initial Rp values and productivity (standing crop biomass [Yp]). It uses this relationship to calculate Rp values for forage and silage.

Beecher, G.D., and C.C. Travis. 1989. Modeling Support for the RURA and Municipal Waste Combustion Projects: Final Report on Sensitivity and Uncertainty Analysis for the Terrestrial Food

Chain Model. Interagency Agreement No. 1824-A020-A1, Office of Risk Analysis, Health and Safety Research Division, Oak Ridge National Laboratory. Oak Ridge, Tennessee. 

October.

This document recommends Tp values based on the average period between successive hay harvests and successive grazing.

Bidleman, T.F. 1988. “Atmospheric Processes.” Environmental Science and Technology. Volume 22. Number 4. Pages 361-367.

For discussion, see References and Discussion, Table B-1-1.

Chamberlain, A.C. 1970. “Interception and Retention of Radioactive Aerosols by Vegetation.” Atmospheric Environment. 4:57 to 78.

Cited by Baes et al. (1984) as a source for an empirical correlation between initial Rp values and productivity (standing crop biomass [Yp])

Hoffman, F.O., K.M. Thiessen, M.L. Frank, and B.G. Blaylock. 1992. “Quantification of the Interception and Initial Retention of Radioactive Contaminants Deposited on Pasture Grass by

Simulated Rain.” Atmospheric Environment. Vol. 26A, 18:3313 to 3321.

For discussion, see References and Discussion, Table B-2-7.

Junge, C.E. 1977. Fate of Pollutants in Air and Water Environments, Part I. Suffet, I.H., Ed. Wiley. New York. Pages 7-26.

Miller, C.W., and F.O. Hoffman. 1983. “An Examination of the Environmental Half-Time for Radionuclides Deposited on Vegetation.” Health Physics. 45 (3): 731 to 744.

For discussion, see References and Discussion, Table B-2-7.
TABLE B-3-7

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B-126

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This a source document for the equation in Table B-3-7.

This document also recommends the following:

C Rp values of 0.5 (forage) and 0.46 (silage), based on the correlation from Chamberlain (1970)

C Treating Tp as a constant, based on the average periods between successive hay harvests and successive grazing

C Bidleman (1988) as source of equation for calculating Fv

Shor, R.W., C.F. Baes, and R.D. Sharp. 1982. Agricultural Production in the United States by County: A Compilation of Information from the 1974 Census of Agriculture for Use in Terrestrial

Food-Chain Transport and Assessment Models. Oak Ridge National Laboratory Publication. ORNL-5786.

For discussion, see References and Discussion in Table B-2-7.

U.S. Department of Agriculture (USDA). 1994. Vegetables 1993 Summary. National Agricultural Statistics Service, Agricultural Statistics Board. Washington, D.C. Vg 1-2 (94).

This document is cited by NC DEHNR (1997) as the source for the average wet weight harvest yield (Yh) for hay. 

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-Specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This document recommends an unweighted estimate of yield or standing crop biomass of 0.15 kg DW/m2 for pasture grass.

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This is one of the source documents for the equation in Table B-3-7. This document also 

(1) developed and recommends Fw values of 0.2 for anions and 0.6 for cations and insoluble particles, based on dividing “r” values developed by Hoffman, Thiessen, Frank, and

Blaylock (1992) and an Rp value of 0.5 for forage; 

(2) recommends Rp values of 0.5 (forage) and 0.46 (silage); 

(3) recommends a kp value of 18, based on a generic 14-day half-time, corresponding to physical processes only;

(4) recommends treating Tp as a constant ,based on the average periods between successive hay harvests and successive grazing; and 

(5) cites Bidleman (1988) as the source of the equation for calculating Fv.

U.S. EPA. 1995. Review Draft Development of Human Health-Based and Ecologically-Based Exit Criteria for the Hazardous Waste Identification Project. Volumes I and II. Office of Solid

Waste. March 3.

This is one of the source documents for the equation in Table B-2-6. This document also recommends (1) using the Fw value calculated by using the r value for insoluble particles (see

Hoffman, Thiessen, Frank, and Blaylock 1992) to represent organic compounds; however, no rationale for this recommendation is provided, and (2) Rp values of 0.5 (forage) and 0.46

(silage), based on the correlation from Chamberlain (1970).
TABLE B-3-7

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(Page 10 of 10) 

B-127

U.S. EPA. 1997. Exposure Factors Handbook. “Food Ingestion Factors”. Volume II. SAB Review Draft. EPA/600/P-95/002F. August. 

This document is the source of relative ingestion rates.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This is one of the source documents for the equation in Table B-3-7. This document also states that the best estimate of Yp (yield or standing crop biomass) is productivity, as defined under

Shor et al. (1982).
TABLE B-3-8

FORAGE AND SILAGE CONCENTRATION DUE TO AIR-TO-PLANT TRANSFER

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 1 of 5)

B-128

 Description

This equation calculates the COPC concentration in forage and silage (aboveground vegetation) resulting from direct uptake of vapor phase COPCs onto plant surfaces. 

Uncertainties associated with the use of this equation include the following:

(1) The range of values for the variable Bv (air-to-plant biotransfer factor) is about 19 orders of magnitude for organic COPCs. COPC-specific Bv values for nondioxin-like compounds

may be overestimated by up to one order of magnitude, based on experimental conditions used to develop the algorithm used to estimate Bv values.

(2) The algorithm used to calculate values for the variable Fv assumes a default value for the parameter ST (Whitby’s average surface area of particulates [aerosols]) of background plus local

sources, rather than an ST value for urban sources. If a specific site is located in an urban area, using the latter ST value may be more appropriate. The ST value for urban sources is about

one order of magnitude greater than that for background plus local sources and would result in a lower Fv value; however, the Fv value is likely to be only a few percent lower.

Equation

For mercury modeling

Use 0.48Q for total mercury and Fv

 = 0.85 in the mercury modeling equation to calculate Pv. Apportion the calculated Pv value into the divalent (Hg2+) and methyl mercury (MHg) forms based

on the 78% Hg2+ and 22% MHg speciation split in aboveground produce and forage. 

Pv (Hg2+) = 0.78 Pv (Mercu ry)

Pv (Mhg) = 0.22 Pv (Mercu ry)

Variable Description Units Value

Pv Forage and silage concentration due

to air-to-plant transfer

μg COPC/g DW

plant tissue

(equivalent to

mg/kg DW)
TABLE B-3-8

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(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 2 of 5)

Variable Description Units Value

B-129

Q COPC-specific emission rate g/s Varies

This variable is COPC- and site-specific. See Chapters 2 and 3 for guidance on calculating this variable. 

Uncertainties associated with this variable are also COPC- and site-specific.

Fv

Fraction of COPC air concentration

in vapor phase

unitless 0 to 1

This variable is COPC-specific. We discuss Fv

in detail in Appendix A-2, and offer COPC-specific values in the

HHRAP companion database. This range is based on values presented in Appendix A-2. U.S. EPA (1994b) and NC

DEHNR (1997) also present values.

Fv was calculated using an equation presented in Junge (1977) for all organic COPCs, including PCDDs and PCDFs. 

U.S. EPA (1994c) states that Fv = 0 for all metals (except mercury).

The following uncertainties are associated with this variable:

(1) It assumes a default ST

 value for background plus local sources, rather than an ST

 value for urban sources. If

a specific site is located in an urban area, using the latter ST

 value may be more appropriate. Specifically, the

ST

 value for urban sources is about one order of magnitude greater than that for background plus local

sources, and it would result in a lower calculated Fv

 value; however, the Fv

 value is likely to be only a few

percent lower.

(2) According to Bidleman (1988), the equation used to calculate Fv

 assumes that the variable c (Junge constant)

is constant for all chemicals; however, the value of c depends on the chemical (sorbate) molecular weight,

the surface concentration for monolayer coverage, and the difference between the heat of desorption from

the particle surface and the heat of vaporization of the liquid-phase sorbate. To the extent that site- or

COPC-specific conditions may cause the value of c to vary, uncertainty is introduced if a constant value

of c is used to calculate Fv

.

Cyv Unitized yearly average air

concentration from vapor phase

:g-s/g-m3 Varies

This variable is COPC- and site-specific, and is determined by air dispersion modeling (see Chapter 3). Uncertainties

associated with this variable are site-specific.
TABLE B-3-8

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(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 3 of 5)

Variable Description Units Value

B-130

Bvforage

Air-to-plant biotransfer factor for

forage and silage

(mg COPC/g plant

tissue DW)/

(mg COPC/g air)

Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values

in the HHRAP companion database.

 

Uncertainty associated with this variable include the following:

The studies that formed the basis of the algorithm used to estimate Bv values were conducted on azalea

leaves and grasses, and may not accurately represent Bv for aboveground produce other than leafy

vegetables.

VGag

Empirical correction factor for

forage and silage

unitless Forage: 1.0

Silage: 0.5

This variable is site-specific. In the absence of site-specific information, we recommend using VGag values of 1.0 for

forage and 0.5 for silage.

U.S. EPA (1994a), U.S. EPA (1994b), and NC DEHNR (1997) recommended an empirical correction factor to reduce

estimated concentrations of constituents in specific vegetation types. This factor is used to reduce estimated bulky

silage concentrations, because (1) Bv was developed for azalea leaves, and (2) it was assumed that there is insignificant

translocation of compounds deposited on the surface of specific vegetation types (such as bulky silage) to the inner

parts of this vegetation.

U.S. EPA (1994a) and U.S. EPA (1994b) recommended a VGag of 1.0 for pasture grass and other leafy vegetation

because of a direct analogy to exposed azalea and grass leaves. Pasture grass is described as “leafy vegetation.”

U.S. EPA (1994a) and U.S. EPA (1994b) didn’t recommend a VGag value for silage. NC DEHNR (1997)

recommended a VGag factor of 0.5 for bulky silage but didn’t present a specific rationale for this recommendation.

U.S. EPA (1995) noted that a volume ratio of outer surface area volume to whole vegetation volume could be used to

assign a value to VGag for silage, if specific assumptions concerning the proportions of each type of vegetation of

which silage may consist of were known (for example, corn and other grains). In the absence of specific assumptions

concerning hay/silage/grain intake, however, U.S. EPA (1995) recommended assuming a VGag of 0.5 for silage

without rigorous justification.

The following uncertainty is associated with this variable:

The VGag value of 0.5 for silage is recommended without vigorous justification. Depending on the

composition of site-specific silage, the recommended value may under- or overestimate the actual value.
TABLE B-3-8

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(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 4 of 5)

Variable Description Units Value

B-131

Da

Density of air g/m3

1200.0

We recommend using this value based on Weast (1986). This reference indicates that air density varies with

temperature. The density of air at both 20°C and 25°C (rounded to two significant figures) is 1.2 x 10+3.

U.S. EPA (1998) also recommends this value, but states that is was based on a temperature of 25°C. U.S. EPA

(1994b) and NC DEHNR (1997) recommended this same value but stated that it was calculated at standard conditions

(20°C and 1 atmosphere). Both documents cited Weast (1981).

REFERENCES AND DISCUSSION

Bidelman, T.F. 1988. “Atmospheric Processes.” Environmental Science and Technology. Volume 22. Number 4. Pages 361-367

For discussion, see References and Discussion in Table B-1-1.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This is a source document for the equation in Table B-3-8. This document also recommended (1) that Fv values be based on the work of Bidleman (1988) , and (2) the use of an empirical

correction factor (VGag) to reduce concentrations of COPCs in some vegetation types- (specifically, a VGag value of 0.5 is recommended for silage; however, no rationale is provided for this

value). This factor is used to reduce estimated COPC concentrations in specific vegetation types, because (1) Bv was developed for azalea leaves, and (2) it is assumed that there is

significant translocation of compounds deposited on the surface of specific vegetation types to the inner parts of this vegetation.

Riederer, M. 1990. “Estimating Partitioning and Transport of Organic Chemicals in the Foliage/Atmosphere: Discussion of a Fugacity-Based Model.” Environmental Science and Technology. 

24: 829 to 837.

This is the source of the leaf thickness used to estimate the empirical correction factor (VGag). 
TABLE B-3-8

FORAGE AND SILAGE CONCENTRATION DUE TO AIR-TO-PLANT TRANSFER

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 5 of 5)

B-132

U. S. EPA 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume II: Properties, Sources, Occurrence, and Background Exposures. External Review Draft. Office of Research and

Development. Washington, D.C. EPA/600/6-88/005Cb. June.

This document recommends an empirical correction factor of 0.01 to reduce estimated vegetable concentrations, based on the assumption that there is insignificant translocation of

compounds deposited on the surface of aboveground vegetation to inner parts for aboveground produce. The document provides no reference or discussion regarding the validity of this

assumption.

The factor of 0.01 is based on a similar correction factor for below ground produce (VGag), which is estimated based on a ratio of the vegetable skin mass to vegetable total mass. The

document assumes that the density of the skin and vegetable are equal. The document also assumes an average vegetable skin leaf based on Rierderer (1990). Based on these assumptions,

U.S. EPA (1994a) calculated VGag for carrots and potatoes of 0.09 and 0.03, respectively. By comparing these values to contamination reduction research completed by Wipf, et al. (1982),

U.S. EPA (1994a) arrived at the recommended VGag of 0.01.

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

This is one of the source documents for the equation in Table B-3-8. This document also presents a range (0.27 to 1) of Fv values for organic COPCs, calculated on the basis of Bidleman

(1988); Fv for all inorganics is set equal to zero.

U.S. EPA. 1995. Review Draft Development of Human-Health Based and Ecologically-Based Exit Criteria for the Hazardous Waste Identification Project. Volumes I and II. Office of Solid

Waste. March 3.

This document presents estimated VGag values. U.S. EPA (1995) notes that a volume ratio of outer surface area volume to whole vegetation volume could be used to assign a value to VGag

for silage, if specific assumptions (concerning the proportions of each type of vegetation of which silage may consist of) were known (for example, corn and other grains). In the absence of

specific assumptions concerning hay/silage/grain intake, however, U.S. EPA (1995) recommends assuming a VGag value of 0.5 for silage (for COPCs with a log Kow greater than 4) without

rigorous justification.

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and 

Development. EPA 452/R-97-005. December.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

Based on attempts to model background concentrations of dioxin-like compounds in beef on the basis of known air concentrations, this document recommends reducing, by a factor of 10,

Bv values calculated by using the Bacci, et al. (1992) algorithm The use of this factor “made predictions [of beef concentrations] come in line with observations.”

Weast, R.C. 1981. Handbook of Chemistry and Physics. 62nd Edition. Cleveland, Ohio. CRC Press.

This document is a reference for air density values. 

Weast, R.C. 1986. Handbook of Chemistry and Physics. 66th Edition. Cleveland, Ohio. CRC Press.
TABLE B-3-8

FORAGE AND SILAGE CONCENTRATION DUE TO AIR-TO-PLANT TRANSFER

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 6 of 5)

B-133

This document is a reference for air density values, and is an update of Weast (1981).

Wipf, H.K., E. Hamberger, N. Neuner, U.B. Ranalder, W. Vetter, and J.P. Vuilleumier. 1982 “TCDD Levels in Soil and Plant Samples from the Seveso Area.” In: Chlorinated Dioxins and Related

Compounds: Impact on the Environment. Eds. Hutzinger, O. et al. Perganon. New York.
TABLE B-3-9

FORAGE/SILAGE/GRAIN CONCENTRATION DUE TO ROOT UPTAKE

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 1 of 3) 

B-134

Description

This equation calculates the COPC concentration in forage/silage/grain (aboveground produce), due to direct uptake of COPCs from soil through plant roots. Uncertainties associated with the use

of this equation include the following:

(1) The availability of site-specific information, such as meteorological data, will affect the accuracy of Cs estimates.

(2) Estimated COPC-specific soil-to-plant bioconcentration factors (Br) don’t reflect site-specific conditions. This may especially be true for inorganic COPCs for which Br would be more

accurately estimated by using site-specific bioconcentration factors rather than bioconcentration factors from Baes et al. (1984). We therefore recommend using plant uptake response

slope factors derived from U.S. EPA (1992) for arsenic, cadmium, selenium, nickel, and zinc.

Equation

For mercury modeling, forage/silage/grain concentration due to root uptake is calculated for divalent mercury (Hg2+) and methyl mercury (MHg) using their respective Cs and Br values. 

Variable Description Units Value

Pr Concentration of COPC in

forage/silage/grain due to root

uptake 

mgCOPC/kg DW

plant tissue

Cs Average soil concentration over

exposure duration 

mg/kg Varies

This value is COPC and site-specific, and calculated using the equation in Table B-3-1. Uncertainties associated with

this variable are site-specific.
TABLE B-3-9

FORAGE/SILAGE/GRAIN CONCENTRATION DUE TO ROOT UPTAKE

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 2 of 3) 

Variable Description Units Value

B-135

Brforage/

Brgrain

Plant-soil bioconcentration factor

for forage/silage, or grain

unitless

[(mg COPC/kg

plant DW)/

(mg COPC/kg

soil)]

Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in

the HHRAP companion database. 

Uncertainties associated with this variable include the following:

(1) Estimates of Br for some inorganic COPCs, based on plant uptake response slope factors, may be more

accurate than those based on BCFs from Baes et al. (1984).

(2) We recommend that you calculate uptake of organic COPCs from soil, and transport of the COPCs to

aboveground plant parts, by using a regression equation developed in a study of the uptake of 29 organic

compounds. This regression equation, developed by Travis and Arms (1988), may not accurately represent the

behavior of all classes of organic COPCs under site-specific conditions.

REFERENCES AND DISCUSSION

Baes, C.F. R.D. Sharp, A.L. Sjoreen, and R.W. Shor. 1984. Review and Analysis of Parameters and Assessing Transport of Environmentally Released Radionuclides Through Agriculture. 

ORNL-5786. Oak Ridge National Laboratory, Oak Ridge, Tennessee. September. 

This document presents inorganic-specific transfer factors (Br) for both vegetative (Bv) portions of food crops and nonvegetative (reproductive—fruits, seeds, and tubers) portions (Br) of

food crops. These bioconcentration factors were developed based on review and compilation of a wide variety of measured, empirical, and comparative data.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This is a source document for the equation in Table B-3-9.

Travis, C.C., and A.O. Arms. 1988. “Bioconcentration of Organics in Beef, Milk, and Vegetation.” Environmental Science and Technology. 22:271 to 274.

This document developed the following regression equation relating soil-to-plant bioconcentration factor (Br) to Kow, based on paired soil and plant concentration data:

log Br = 1.588 - 0.578 @ log Kow

U.S. EPA. 1992. Technical Support Document for Land Application of Sewage Sludge. Volumes I and II. Office of Water. Washington, D.C. EPA 822/R-93-001a.

Source of plant uptake response factors for arsenic, cadmium, nickel, selenium, and zinc. Plant uptake response factors can be converted to BCFs by multiplying the plant uptake response

factor by a factor of 2.
TABLE B-3-9

FORAGE/SILAGE/GRAIN CONCENTRATION DUE TO ROOT UPTAKE

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 3 of 3) 

B-136

U.S. EPA. 1995. Review Draft Development of Human Health Based and Ecologically Based Exit Criteria for the Hazardous Waste Identification Project. Volumes I and II. Office of Solid Waste. 

March 3.

This document recommends using the bioconcentration factors Bv and Br from Baes et al. (1984) for calculating the uptake of inorganics into vegetative and nonvegetative growth,

respectively.

Although most BCFs used in this document came from Baes et al. (1984), values for some inorganics were apparently obtained from plant uptake response slope factors. These uptake

response slope factors were calculated from field data, such as metal loading rates and soil metal concentrations. However, the methodologies and references used to calculate the uptake

response slope factors were not clearly identified.

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and 

Development. EPA 452/R-97-005. December.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This is one of the source documents for the equation in Table B-3-9.
TABLE B-3-10

BEEF CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 1 of 7)

B-137

Description

This equation first estimates the daily amount of COPCs cattle are exposed to through ingesting contaminated plant and soil material. The equation then recommends the use of biotransfer factors

to transform the daily animal intake of a COPC (mg COPC/day) into an animal COPC tissue concentration (mg COPC/kg FW tissue). 

The limitations and uncertainty introduced in calculating this variable include the following:

(1) Variables Pi and Cs are COPC- and site-specific. Uncertainties associated with these variables are site-specific.

(2) Uncertainties associated with the variables Fi, Qs, and Qpi are expected to be minimal.

(3) Using a single Babeef value for each COPC may not accurately reflect site-specific conditions. It is not clear whether the default values are likely to under - or overestimate Abeef.

Based on the information below, Abeef is dependent on the concentrations of COPCs estimated in plant feeds and soil, and the biotransfer factor estimated for each constituent.

Equation

For mercury modeling, beef concentration due to plant and soil ingestion is calculated for divalent mercury (Hg2+) and methyl mercury (MHg) using their respective Pi

, Cs, and Babeef values.

Variable Description Units Value

Abeef

Concentration of COPC in beef mg COPC/kg

FW tissue

Fi

Fraction of plant type (i) grown on

contaminated soil and ingested by

the animal 

unitless 1

This variable is site- and plant type-specific. Plant types for cattle are typically identified as grain, forage, and silage. We

recommend using a default value of 1.0 for all plant types when site-specific information is not available. This is

consistent with U.S. EPA (1998), U.S. EPA (1994a), U.S. EPA (1994b) and NC DEHNR (1997), which recommend

assuming that 100 percent of the plant materials ingested by cattle were grown on soil contaminated by emissions.

The following uncertainty is associated with this variable:

(1) Assuming 100 percent of the plant materials eaten by cattle were grown on soil contaminated by emissions may

overestimate Abeef.
TABLE B-3-10

BEEF CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 2 of 7)

Variable Description Units Value

B-138

Qpi

Quantity of plant type (i) ingested

by the animal per day

kg DW

plant/day

Forage: 8.8

Silage: 2.5

Grain: 0.47

This variable is site- and plant type-specific. Plant types for cattle are typically identified as grain, forage, and silage. We

recommend that you use the following Qp values when evaluating cattle raised by beef farmers: forage (8.8), silage

(2.5), and grain (0.47). These values are consistent with U.S. EPA (1994c), and NC DEHNR (1997).

The reference documents cite Boone et al. (1981), NAS (1987), McKone and Ryan (1989), and Rice (1994) as primary

references for plant ingestion rates.

Uncertainties introduced by this variable include the following:

(1) The recommended daily grain ingestion rate of 0.47 kg dry weight (DW)/day is calculated indirectly from (1) a

recommended total daily dry matter intake of 11.8 kg DW plant/day, based on NAS (1987) and McKone and

Ryan (1989), and (2) daily ingestion rates of forage (8.8 kg/day) and silage (2.5 kg DW/day), recommended by

Boone et al. (1981). However, Boone et al. (1981) recommended an alternative daily grain ingestion rate of 1.9

kg DW/day, about four times higher than the rate we recommend. As shown in Equations in Tables B-3-7

through B-3-9, the concentrations of COPCs in forage, silage, and grain are calculated similarly. Therefore, the

relative amounts of forage, silage, and grain ingested daily have a limited effect on the intake of COPCs, if the

total daily intake of dry matter is held constant. Therefore, limited uncertainty is introduced.

(2) The recommended daily ingestion rates (total and plant type-specific) may not accurately represent site-specific

or local conditions. Therefore, Abeef may be under- or overestimated, but to a limited degree.
TABLE B-3-10

BEEF CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 3 of 7)

Variable Description Units Value

B-139

Pi

Concentration of COPC in plant

type (i) ingested by the animal

mg/kg DW Varies

This variable is COPC-, site-, and plant type-specific; plant types for cattle are typically identified as grain, forage, and

silage. Values for Pd, Pv, and Pr are calculated by using the equations in Tables B-3-7, B-3-8, and B-3-9; and then

summed for each plant type to determine Pi

.

Uncertainties introduced by this variable include the following:

(1) Some of the variables in the equations in Tables B-3-7, B-3-8, and B-3-9—including Cs, Cyv, Q, Dydp, and

Dywp—are COPC- and site-specific. Uncertainties associated with these variables are site-specific.

(2) In the equation in Table B-3-7, uncertainties associated with other variables include the following: Fw (values

for organic compounds estimated on the basis of the behavior of polystyrene micro spheres), Rp (estimated on

the basis of a generalized empirical relationship), kp (estimation process does not consider chemical

degradation), and Yp (estimated on the basis of national harvest yield and area planted values). All of these

uncertainties contribute to the overall uncertainty associated with Pi

.

(3) In the equation in Table B-3-8, COPC-specific Bv values for nondioxin-like compounds may be overestimated

by up to one order of magnitude, based on experimental conditions used to develop the algorithm to estimate Bv

values.

(4) In the equation in Table B-3-9, COPC-specific plant-soil biotransfer factors (Br) may not reflect

site-specific conditions. This may be especially true for inorganic COPCs for which estimates of Br would be

more accurately estimated by using plant uptake response slope factors.

Qs Quantity of soil ingested by the

animal

kg/day 0.5

This variable is site-specific. We recommend using a soil ingestion rate of 0.5 kg/day. This is consistent with NC

DEHNR (1997) and U.S. EPA (1994c), which cite USDA (1994), Rice (1994), and NAS (1987). 

Uncertainties introduced by this variable include the following:

(1) The recommended soil ingestion rate may not accurately represent site-specific or local conditions. However,

we expect any differences between the recommended value and site-specific or local soil ingestion rates to be

small. Therefore, we likewise expect any uncertainty introduced to be limited.

Cs Average soil concentration over

exposure duration 

mg COPC/kg

soil

Varies

This variable is COPC- and site-specific, and calculated using the equation in Table B-3-1. Uncertainties are site-specific.
TABLE B-3-10

BEEF CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 4 of 7)

Variable Description Units Value

B-140

Bs Soil bioavailability factor unitless 1.0

The soil bioavailability factor, Bs, can be thought of as the ratio between bioconcentration (or biotransfer) factors for soil

and vegetation for a given contaminant. The efficiency of transfer from soil may differ from efficiency or transfer from

plant material for some COPCs. If the transfer efficiency is lower for soils, then this ratio would be less than 1.0. If it is

equal or greater than that of vegetation, the Bs would be equal to or greater than 1.0.

Since there is not enough data regarding bioavailability from soil, we recommend a default value of 1.0 for Bs, until more

COPC data becomes available for this parameter. There is a fair amount of uncertainty associated with the use of this

default value, because some COPCs may be much less bioavailable from soil than from plant tissues.

Babeef

Biotransfer factor for beef day/kg FW

tissue

Varies

This variable is COPC-specific. We discuss this variable and COPC-specific values in Appendix A-2. Babeef is defined as

the ratio of the COPC concentration in animal tissue (mg COPC/kg animal tissue) to the daily intake of the COPC (mg

COPC/day) by the animal. 

Uncertainties introduced by this variable include the following:

(1) We recommend using the regression equation developed by RTI (2005) to calculate Babeef values for organic

COPCs. Uncertainties listed in RTI (2005) in deriving the regression equation include: 1) the necesssity to

extrapolate data to steady state conditions, 2) metabolism may not be accounted for equally for all data points,

and 3) there is a +/- 0.5 variability in measured Log Kow values available in the literature. In addition, values

calculated by using this regression equation may not accurately represent the behavior of organic COPCs under

site-specific conditions. Babeef and subsequent Abeef values may therefore be under- or overestimated to some

degree.

(2) We recommend calculating Babeef values for metals be using single COPC-specific uptake factors developed by

Baes et al. (1984). These uptake factors may not accurately represent the behavior of inorganic COPCs under

site-specific conditions. Babeef and subsequent Abeef values may therefore be under- or overestimated to some

degree.

MF Metabolism factor unitless 0.01 and 1.0

This variable is COPC-specific. Based on a study by Ikeda et al. (1980), U.S. EPA (1995a) recommended using a

metabolism factor to account for metabolism in animals to offset the amount of bioaccumulation suggested by biotransfer

factors. MF applies only to beef, milk, and pork. It does not apply to direct exposures to air, soil, or water, or to ingestion

of produce, chicken, or fish. U.S. EPA (1995b) recommended an MF of 0.01 for bis(2-ethylhexyl)phthalate (BEHP) and

1.0 for all other contaminants.
TABLE B-3-10

BEEF CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 5 of 7)

B-141

REFERENCES AND DISCUSSION

Baes, C.F., R.D. Sharp, A.L. Sjoreen, and R.W. Shor. 1984. “Review and Analysis of Parameters and Assessing Transport of Environmentally Released Radionuclides Through Agriculture.” Oak

Ridge National Laboratory, Oak Ridge, Tennessee.

U.S. EPA (1994c) recommends Baes et al. (1984) as a source of Babeef values for inorganics.

Boone, F.W., Yook C. Ng, and John M. Palms. 1981. “Terrestrial Pathways of Radionuclide Particulates.” Health Physics, Vol. 41, No. 5, pp. 735-747. November.

This document is identified as a source of plant ingestion rates. Boone et al. (1981) reports forage, grain, and silage ingestion rates of 8.8, 1.9, and 2.5 kg DW/day, respectively, for beef

cattle.

Ikeda, G.J., P.P. Sapenza, and J.L. Couvillion. 1980. “Comparative distribution, excretion, and metabolism of di(2-ethylhexyl)phthalate in rats, dogs, and pigs.” Food Cosmet. Toxicology. 18:637-

642.

McKone, T.E., and P.B. Ryan. 1989. Human Exposures to Chemicals Through Food Chains: An Uncertainty Analysis. Livermore, California: Lawrence Livermore National Laboratory Report. 

UCRL-99290.

This document is cited as a source of plant ingestion rates. McKone and Ryan (1989) report an average total ingestion rate of 12 kg DW/day for the three plant feeds, which is consistent

with the total recommended by other guidance documents for cattle (that is, forage, grain, and silage total of 11.8 kg DW/day). 

National Academy of Sciences (NAS). 1987. Predicting Feed Intake of Food-Producing Animals. National Research Council, Committee on Animal Nutrition, Washington, D.C.

This document is identified as a source of food ingestion rates. NC DEHNR (1997) and U.S. EPA (1994c) note that NAS (1987) reports a daily dry matter intake that is 2 percent of an

average beef cattle body weight of 590 kilograms. This results in a daily total intake rate of 11.8 kg DW/day, and the daily soil ingestion rate of approximately 0.5 kg soil/day (based on

USDA [1994]). 

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is a reference source for the equation in Table B-3-10. 

NC DEHNR (1997) recommends forage, grain, and silage ingestion rates of 3.8, 3.8, and 1.0 kg dry weight/day, respectively, for typical farmer beef cattle. NC DEHNR (1997) reports

Rice (1994) as a references for these variable.

Research Triangle Institute (RTI). 2005. Methodology for Predicting Cattle Biotransfer Factors. Prepared for U.S. Environmental Protection Agency (EPA) Office fo Solid Waste. EPA Contract

No. 68-W-03-042. August.
TABLE B-3-10

BEEF CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 6 of 7)

B-142

U.S. Department of Agriculture (USDA). 1994. Personal Communication Between G.F. Fries, and Glenn Rice and Jennifer Windholtz, U.S. Environmental Protection Agency, Office of Research

and Development. Agricultural Research Service. March 22.

NC DEHNR (1997) and U.S. EPA (1994c) note that this reference reports soil ingestion for cattle to be 4 percent of the total daily dry matter intake.

U.S. EPA. 1993. Technical Support Document for Land Application of Sewage Sludge. Volumes I and II. EPA 822/R-93-001a. Office of Water. Washington, D.C.

U.S. EPA (1995) recommended that bioconcentration factors for the metals cadmium, mercury, selenium, and zinc presented in this document be used to derive Babeef values. Following the

method recommended by U.S. EPA (1992) for dioxins, the bioconcentration factors—with units of (kilograms feed DW/kilogram tissue DW—are divided by feed ingestion rates (kilogram

feed DW/day]) to calculate Babeef values (day/kilogram tissue DW). U.S. EPA (1993) recommended a feed ingestion rate of 20 kg DW/day.

U.S. EPA. 1994a. Estimating Exposures to Dioxin-like Compounds. Volume III: Site-specific Assessment Procedures. Office of Research and Development. EPA/600/6-88/005Cc. External

Review Draft. June.

This document recommends an Fi value of 1; this value assumes that 100 percent of the plant materials ingested by cattle have been grown on soil contaminated by emissions.

U.S. EPA. 1994b. Draft Exposure Assessment Guidance for RCRA Hazardous Waste Combustion Facilities. Office of Solid Waste and Emergency Response. EPA-530-R-94-021. April.

This document recommends an Fi

 value of 1; this value assumes that 100 percent of the plant materials ingested by cattle have been grown on soil contaminated by emissions.

U.S. EPA. 1994c. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document is one of the reference source documents for the equation in Table B-3-10. This document also recommends the following:

C An Fi

 value of 100 percent

C Qpi values for forage, silage, and grain of 8.8, 2.5 and 0.47 kg dry weight/day, respectively, based on Boone et al. (1981), NAS (1987), McKone and Ryan (1989), and Rice

(1994)

C A soil ingestion rate for cattle (2sw) of 0.5 kg/day, based on USDA (1994), Rice (1994), and NAS (1987)

U.S. EPA. 1995a. Further Issues for Modeling the Indirect Exposure Impacts from Combustor Emissions. Office of Research and Development. Washington, D.C. January.

This document recommends using BCF for the metals cadmium, mercury, selenium, and zinc, presented in U.S. EPA (1993), to calculate Babeef values for these metals. Specifically, the

BCFs from U.S. EPA (1993)—which are in units of kilogram feed DW/kilogram tissue DW are divided by a feed ingestion rate of 20 kilograms DW/day to arrive at Babeef values in units of

day/kilogram tissue DW, according to the methodology developed for dioxins (U.S. EPA 1992).

U.S. EPA. 1995b. “Waste Technologies Industries Screening Human Health Risk Assessment (SHHRA): Evaluation of Potential Risk from Exposure to Routine Operating Emissions.” Volume 

V. External Review Draft. U.S. EPA Region 5, Chicago, Illinois.

U.S. EPA. 1997a. Exposure Factors Handbook. “Food Ingestion Factors”. Volume II. SAB Review Draft. EPA/600/P-95/002F. August. 
TABLE B-3-10

BEEF CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 7 of 7)

B-143

U.S. EPA. 1997b. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research 

and Development. EPA 452/R-97-005. December.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document recommends an Fi value of 1; this value assumes that 100 percent of the plant materials ingested by cattle have been grown on soil contaminated by emissions.
TABLE B-3-11

MILK CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 1 of 7)

B-144

Description

This equation first estimates the daily amount of COPCs taken in by cattle through the ingestion of contaminated plant and soil material. The equation then recommends the use of biotransfer

factors to transform the daily animal intake of a COPC (mg COPC/day) into an animal (dairy cattle) milk COPC concentration (mg COPC/kg FW tissue).

The limitations and uncertainty introduced in calculating this variable include the following:

(1) Variables Pi and Cs are COPC- and site-specific. Uncertainties associated with these variables are site-specific.

(2) Uncertainties associated with the variables Fi, Qs, and Qpi are expected to be minimal.

(3) Bamilk values may not reflect site-specific conditions—Bamilk values for nondioxin-like organics are based on a generalized regression equation; Bamilk values for dioxins and furans are

estimated on the basis of experimental values from a single lactating cow; and Bamilk values for inorganics are based on integration of a wide variety of empirical and experimental result

which can mean that site-specific difference are ignored.

Based on the information below, Amilk is dependent on the concentrations of COPCs estimated in plant feeds and soil, and the biotransfer factor estimated for each compound. 

Equation

For mercury modeling, calculate milk concentrations due to plant and soil ingestion for divalent mercury (Hg2+) and methyl mercury (MHg) using their respective Pi

, Cs, and Bamilk values.

Variable Description Units Value

Amilk

Concentration of COPC in milk mg COPC/kg

FW tissue

Fi

Fraction of plant type (i) grown on

contaminated soil and ingested by

the animal

unitless 1.0

This variable is site- and plant type-specific. Plant types for cattle are identified as grain, forage, and silage. We

recommend using a default value of 1.0 for all plant types. This is consistent with U.S. EPA (1998), U.S. EPA (1994a),

U.S. EPA (1994b) and NC DEHNR (1997), which recommend assuming that 100 percent of the plant materials ingested

by cattle were grown on soil contaminated by emissions. 

The following uncertainty is associated with this variable:

(1) Assuming 100 percent of the plant materials eaten by cattle were grown on soil contaminated by facility

emissions may overestimate Amilk.
TABLE B-3-11

MILK CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 2 of 7)

Variable Description Units Value

B-145

Qpi

Quantity of plant type (i) ingested

by the animal per day

kg DW

plant/day

Forage: 13.2

Silage: 4.1

Grain: 3.0

This variable is site- and plant type-specific. Plant types for cattle are identified as grain, forage, and silage. We

recommend that you use the following Qp values when evaluating cattle raised by milk farmers: forage (13.2), silage

(4.1), and grain (3.0). 

The recommended plant type-specific Qpi values were calculated as follows. 

First, total dry matter intake (DMI) was estimated as 20 kg DW/day, based on information presented in NAS

(1987). 

Second, data from Boone et al. (1981) were used to separate the total DMI into plant type-specific fractions. 

Finally, the recommended plant type-specific Qpi values were calculated by multiplying the estimated total DMI

(20 kg DW/day) by the plant type-specific fractions. 

For example, the Qpi for forage was calculated as 20 kg DW/day @ 0.65 = 13.2 kg DW/day. These values are consistent

with U.S. EPA (1993; 1994b; 1995), and NC DEHNR (1997). These reference documents cite Boone et al. (1981),

NAS (1987), McKone and Ryan (1989), and Rice (1994) as primary references for plant ingestion rates.

Uncertainties introduced by this variable include the following:

(1) The plant type-specific Qpi values were calculated based on a total DMI of 20 kg DW/day (NAS 1987) rather

than the total DMI of 17 kg DW/day presented in Boone et al. (1981) and McKone and Ryan (1989). 

Site-specific total DMI values may vary.

(2) The plant type-specific fractions calculated from Boone et al. (1981) may not accurately represent site-specific

or local plant type-specific fractions. 
TABLE B-3-11

MILK CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 3 of 7)

Variable Description Units Value

B-146

Pi

Concentration of COPC in plant

type (i) ingested by the animal

mg/kg DW Varies

This variable is COPC-, site-, and plant type-specific; plant types for cattle are identified as grain, forage, and silage. 

Values for Pd, Pv, and Pr are calculated by using the equations in Tables B-3-7, B-3-8, and B-3-9, and then summed for

each plant type to determine Pi

.

Uncertainties introduced by this variable include the following:

(1) Some of the variables in the equations in Tables B-3-7, B-3-8, and B-3-9—including Cs, Cyv, Q, Dydp, and

Dywp—are COPC- and site-specific. Uncertainties associated with these variables are site-specific.

(2) In the equation in Table B-3-7, uncertainties associated with other variables include the following: Fw (values

for organic compounds estimated on the basis of the behavior of polystyrene micro spheres), Rp (estimated on

the basis of a generalized empirical relationship), kp (estimation process does not consider chemical

degradation), and Yp (estimated on the basis of national harvest yield and area planted values). All of these

uncertainties contribute to the overall uncertainty associated with Pi

.

(3) In the equation in Table B-3-8, COPC-specific Bv values for nondioxin-like compounds may be overestimated

by up to one order of magnitude, based on experimental conditions used to develop the algorithm to estimate Bv

values.

(4) In the equation in Table B-3-9, COPC-specific plant-soil biotransfer factors (Br) may not reflect

site-specific conditions. This may be especially true for inorganic COPCs for which estimates of Br would be

more accurately estimated by using plant uptake response slope factors.

Qs Quantity of soil ingested by the

animal 

kg/day 0.4

This variable is site-specific. We recommend using a soil ingestion rate of 0.4 kg/day. This is consistent with NC

DEHNR (1997) and U.S. EPA (1994b), which cite USDA (1994), Rice (1994), and NAS (1987). Briefly, the

recommended Qs value was calculated as follows. 

First, a total DMI was estimated as 20 kg DW/day based on information presented in NAS (1987). 

Second, USDA (1994) estimates that Qs equals 2 percent of the total DMI.

Finally, the recommended Qs value was calculated as 20 kg DW/day @ 0.02 = 0.4 kg DW /day.

Uncertainties introduced by this variable include:

(1) The recommended Qs value was based on a total DMI of 20 kg DW/day NAS (1987) rather than the total DMI

of 17 kg DW/day presented in Boone et al. (1981) and McKone and Ryan (1989). To the extent that

site-specific or local total DMI values may vary, Amilk may be under- or overestimated to a limited degree.

(2) USDA (1994) states that Qs equals 2 percent of the total DMI for dairy cattle on a farm. Although the basis of

the estimate of 2 percent is not known, it is apparent that to the extent that site-specific or local Qs values are

different than 2 percent, Amilk may be under- or overestimated to some degree.
TABLE B-3-11

MILK CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 4 of 7)

Variable Description Units Value

B-147

Cs Average soil concentration over

exposure duration

mg COPC/kg

soil

Varies

This variable is COPC- and site-specific, and calculated using the equation in Table B-3-1. Uncertainties are site-specific.

Bs Soil bioavailability factor unitless 1.0

The soil bioavailability factor, Bs, can be thought of as the ratio between bioconcentration (or biotransfer) factors for soil

and vegetation for a given COPC. The efficiency of transfer from soil may differ from efficiency or transfer from plant

material for some COPCs. If the transfer efficiency is lower for soils, then this ratio would be less than 1.0. If it is equal

or greater than that of vegetation, the Bs would be equal to or greater than 1.0.

Due to limited data regarding bioavailability from soil, we recommend a default value of 1.0 for Bs, until more COPCspecific data is available for this parameter. Some COPCs may be much less bioavailable from soil than from plant

tissues. This uncertainty may overestimate Bs.

Bamilk

Biotransfer factor for milk day/kg FW

tissue

Varies

This variable is COPC-specific. A detailed discussion of this variable and COPC-specific values are presented in

Appendix A-2. Bamilk is defined as the ratio of the COPC concentration in milk (mg COPC/kg tissue) to the daily intake of

the COPC (mg COPC/day) by the animal. 

Uncertainties introduced by this variable include the following:

(1) We recommend using the regression equation developed by RTI (2005) to calculate Bamilk values for organic

COPCs. Uncertainties listed in RTI (2005) in deriving the regression equation include: 1) the necesssity to

extrapolate data to steady state conditions, 2) metabolism may not be accounted for equally for all data points,

and 3) there is a +/- 0.5 variability in measured Log Kow values available in the literature. In addition, values

calculated by using this regression equation may not accurately represent the behavior of organic COPCs under

site-specific conditions. Bamilk and subsequent Amilk values may therefore be under- or overestimated to some

degree.

(2) We recommend calculating Bamilk values for metals be using single COPC-specific uptake factors developed by

Baes et al. (1984). These uptake factors may not accurately represent the behavior of inorganic COPCs under

site-specific conditions. Bamilk and subsequent Amilk values may therefore be under- or overestimated to some

degree.
TABLE B-3-11

MILK CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 5 of 7)

Variable Description Units Value

B-148

MF Metabolism factor unitless 0.01 and 1.0

This variable is COPC-specific. Based on a study by Ikeda et al. (1980), U.S. EPA (1995a) recommended using a

metabolism factor to account for metabolism in animals to offset the amount of bioaccumulation suggested by biotransfer

factors. MF applies only to beef, milk, and pork. It does not apply to direct exposures to air, soil, or water, or to ingestion

of produce, chicken, or fish. U.S. EPA (1995b) recommended an MF of 0.01 for bis(2-ethylhexyl)phthalate (BEHP) and

1.0 for all other COPCs.

REFERENCES AND DISCUSSION

Baes, C.F., R.D. Sharp, A.L. Sjoreen, and R.W. Shor. 1984. Review and Analysis of Parameters and Assessing Transport of Environmentally Released Radionuclides through Agriculture. Oak

Ridge National Laboratory, Oak Ridge, Tennessee.

U.S. EPA (1994c) recommends Baes et al. (1984) as a source of (1) Bamilk values for inorganics, and (2) water content of 0.9 for cow’s milk, which can be used to convert Bamilk values in

dry weight to wet weight.

Beecher, G.D., and C.C. Travis. 1989. Modeling Support for the RURA and Municipal Waste Combustion Project Final Report on Sensitivity and Uncertainty Analysis for the Terrestrial Food

Chain Model. Prepared under IAG-1824-A020-A1 by Oak Ridge National Laboratory for U.S. EPA Office of Health and Environmental Assessment, Environmental Criteria and

Assessment Office. Cincinnati, Ohio.

This document was cited by U.S. EPA (1990) as the source of Bamilk values for cadmium. 

Boone, F.W., Yook C. Ng, and John M. Palms. 1981. “Terrestrial Pathways of Radionuclide Particulates.” Health Physics. Vol. 41, No. 5, pages 735-747. November.

This document is identified as a source of plant ingestion rates. Boone et al. (1981) reports a total forage, grain, and silage ingestion rate of 17 kg DW/day for dairy cattle. Also, this

document states that this total DMI of 17 kg DW/day is made up of the following plant type-specific fractions: forage (65 percent), grain (15 percent), and silage (20 percent).

Ikeda, G.J., P.P. Sapenza, and J.L. Couvillion. 1980. “Comparative distribution, excretion, and metabolism of di(2-ethylhexyl)phthalate in rats, dogs, and pigs.” Food Cosmet. Toxicology. 

18:637-642.

McKone, T.E., and P.B. Ryan. 1989. Human Exposures to Chemicals Through Food Chains: An Uncertainty Analysis. Livermore, California: Lawrence Livermore National Laboratory Report. 

UCRL-99290.

This document is cited as a source of plant ingestion rates. It reports an average total ingestion rate of 17 kg dry weight/day for the three plant feeds, which is consistent with the total

recommended by Boone et al. (1981) for cattle.
TABLE B-3-11

MILK CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 6 of 7)

B-149

NAS. 1987. Predicting Feed Intake of Food-Producing Animals. National Research Council, Committee on Animal Nutrition. Washington, D.C.

NC DEHNR (1997) and U.S. EPA (1994c) note that this document reports a daily DMI equal to 3.2 percent of an average dairy cattle body weight of 630 kilograms; this results in a daily

DMI of 630 kg DW @ 0.032 = 20.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

Grains such as corn may be grown specifically as cattle feed. COPC uptake into these feed materials may occur through root uptake, wet and dry deposition of particulate-bound COPCs on

plants, and vapor-phase uptake of COPCs through plant foliage. Plants are classified as “protected” if they have an outer covering that acts as a barrier to direct deposition and vapor 

uptake of air contaminants. NC DEHNR (1997) classifies grains as protected, and recommends that only root uptake of COPCs be evaluated for grains. Because silage may consist of

forage materials that have been stored and fermented, it should be treated as forage (that is, as unprotected).

This document is a reference source for the equation in Table B-3-11. This document also recommends the following: 

(1) An Fi value of 1

(2) Forage, silage, and grain ingestion rates (Qpi) of 13.2, 4.1, and 3.0 kg DW/day for dairy farmer cattle, respectively, based on a total DMI of 20 kg DW/day calculated

from NAS (1987) and plant type-specific fractions from Boone et al. (1981)

(3) Forage, silage, and grain ingestion rates (Qpi) of 6.2, 1.9, and 12.2 kg DW/day, respectively for typical dairy farmer cattle based on USDA (1994)

(4) A Qs value of 0.4 kg/day, based on NAS (1987) and USDA (1994)

(5) Bamilk values ranging from 3.5 x 10-10 to 4.8, based on Baes et al. (1984).

Research Triangle Institute (RTI). 2005. Methodology for Predicting Cattle Biotransfer Factors. Prepared for U.S. Environmental Protection Agency (EPA) Office fo Solid Waste. EPA Contract

No. 68-W-03-042. August.

USDA. 1994. Personal Communication Regarding Soil Ingestion Rate for Dairy Cattle. Between G.F. Fries, Agricultural Research Service, and Glenn Rice and Jennifer Windholtz, U.S. EPA,

Office of Research and Development. March 22.

NC DEHNR (1997) and EPA (1994c) note that USDA (1994) reports soil ingestion to be 2 percent of the total DMI for dairy cattle on farms. 

U.S. EPA. 1994a. Draft Exposure Assessment Guidance for RCRA Hazardous Waste Combustion Facilities. Office of Solid Waste and Emergency Response. EPA-530-R-94-021. April.

This document recommends a Fi value of 1, assuming that 100 percent of the plant materials ingested by cattle have been grown on soil contaminated by combustion unit emissions.

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

This document is a reference source for the equation in Table B-3-11. This document also recommends the following:

(1) An Fi

 value of 1

(2) A forage ingestion rate (Qpi

) value of 13.2 kg DW/day, from NAS (1987) and Boone et al. (1981)

(3) A quantity of soil ingested (Qs) value of 0.4 kg/day, based on NAS (1987) and USDA (1994)

(4) Bamilk values ranging from 3.5 x 10-10 to 4.8, based on Baes et al. (1984)
TABLE B-3-11

MILK CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 7 of 7)

B-150

U.S. EPA. 1994c. Estimating Exposures to Dioxin-Like Compounds. Volume III: Site-specific Assessment Procedures. External Review Draft. Office of Research and Development. 

EPA/600/6-88/005Cc. June.

This document reported bioconcentration factors for dioxin-like compounds (dioxin and furan congeners) calculated on the basis of experimental data derived by McLachlan et al. (1990).

U.S. EPA. 1995a. Further Issues for Modeling the Indirect Exposure Impacts from Combustor Emissions. Office of Research and Development. Washington, D.C. January.

U.S. EPA. 1995b. “Waste Technologies Industries Screening Human Health Risk Assessment (SHHRA): Evaluation of Potential Risk from Exposure to Routine Operating Emissions.” Volume V. 

External Review Draft. U.S. EPA Region 5, Chicago, Illinois.

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and

Development. EPA 452/R-97-005. December.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document recommends an Fi value of 1; this value assumes that 100 percent of the plant materials ingested by cattle have been grown on soil contaminated by emissions.
TABLE B-3-12

PORK CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 1 of 7)

B-151

Description

This equation first estimates the daily intake of COPCs through the ingestion of contaminated plant and soil material. The equation uses biotransfer factors to transform the daily animal intake of

a COPC (mg COPC/day) into an animal COPC tissue concentration (mg COPC/kg tissue).

The limitations and uncertainty introduced in calculating this variable include the following:

(1) Uncertainties associated with the variables Pi and Cs are COPC- and site-specific.

(2) Uncertainties associated with the variables Fi, Q, and Qpi are expected to be minimal.

(3) Uncertainties associated with Bapork values may be significant for two primary reasons: (a) Bapork for dioxins are calculated from Bamilk values that are based on cattle metabolism of

dioxins rather than a sow metabolism, and (b) the source or methodology used to calculate the Bapork values for organics other than dioxins and inorganics other than cadmium, mercury,

selenium, and zinc as reported in NC DEHNR (1997) is not known. Therefore, the magnitude and direction of the associated uncertainties cannot be specified.

Based on the information below, Apork is dependent on the concentrations of COPCs estimated in plant feeds and soil, and the biotransfer factor estimated for each COPC. 

Equation

For mercury modeling, pork concentration due to plant and soil ingestion is calculated for divalent mercury (Hg2+) and methyl mercury (MHg) using their respective Pi

, Cs, and Bapork values.

Variable Description Units Value

Apork

Concentration of COPC in pork mg COPC/kg FW

tissue

Fi

Fraction of plant type (i) grown on

contaminated soil and ingested by

the animal 

unitless 1.0

This variable is site- and plant type-specific; plant types for swine are typically identified as grain and silage. We

recommend using a default value of 1.0 for all plant types. This is consistent with U.S. EPA (1998; 1994a; 1994c),

and NC DEHNR (1996), which recommend assuming that 100 percent of the plant materials ingested by swine were

grown on soil contaminated by emissions. 

The following uncertainty is associated with this variable:

Assuming 100 percent of the plant materials ingested by swine were grown on soil contaminated by

facility emissions may overestimate Apork.
TABLE B-3-12

PORK CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 2 of 7)

Variable Description Units Value

B-152

Qpi

Quantity of plant type (i) ingested

by the animal each day

kg DW plant/day Silage: 1.4

Grain: 3.3

This variable is site- and plant type-specific; plant types for swine are typically identified as grain and silage. We

recommend that you use the following Qp values when evaluating swine raised by farmers: silage (1.4) and grain

(3.3). These Qpi values are based on a total DMI value of 4.7 kg DW/day, and plant type-specific diet fractions

(70 percent grain and 30 percent silage) are based on U.S. EPA (1982).

NC DEHNR (1997) and U.S. EPA (1990) recommend silage and grain ingestion rates of 1.3 and 3.0 kg

dry/day, respectively, for swine. NC DEHNR (1997) references U.S. EPA (1990) as the source of these ingestion

rates. The difference between the default Qpi

 values and values recommended by NC DEHNR (1997) and U.S.

EPA (1990) is the total DMI upon which they are based. Specifically, we recommend the use of a total DMI for

swine of 4.7 kg DW/day, based on U.S. EPA (1995), whereas NC DEHNR (1997) and U.S. EPA (1990) recommend

a total DMI of 4.3 kg dry weight/day.

NC DEHNR (1997) and U.S. EPA (1990) don’t differentiate between subsistence and typical hog farmers as they do

for cattle, because it is assumed that forage is not a significant portion of a hog’s diet.

Uncertainties introduced by this variable include the following:

The recommended grain and silage ingestion rates may not accurately represent site-specific or

local conditions. Therefore, Qpi and Apork values may be under- or overestimated to some degree.
TABLE B-3-12

PORK CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 3 of 7)

Variable Description Units Value

B-153

Pi

Concentration of COPC in plant

type (i) ingested by the animal

mg/kg DW Varies

This variable is COPC-, site-, and plant type-specific; plant types for swine are identified as grain and silage. 

Values for Pd, Pv, and Pr are calculated by using the equations in Tables B-3-7, B-3-8, and B-3-9; and then

summed for each plant type to determine Pi

.

Uncertainties introduced by this variable include the following:

(1) Some of the variables in the equations in Tables B-3-7, B-3-8, and B-3-9—including Cs, Cyv, Q, Dydp,

and Dywp—are COPC- and site-specific. Uncertainties associated with these variables are site-specific.

(2) In the equation in Table B-3-7, uncertainties associated with other variables include: Fw (values for

organic compounds based on behavior of polystyrene micro spheres), Rp (estimated on the basis of a

generalized empirical relationship), kp (estimation process does not consider chemical degradation) and Yp

(estimated based on national harvest yield and area planted values). All of these uncertainties contribute

to the overall uncertainty associated with Pi

.

(3) In the equation in Table B-3-8, COPC-specific Bv values for nondioxin-like compounds may be

overestimated by up to one order of magnitude, based on experimental conditions used to develop the

algorithm to estimate Bv values.

(4) In the equation in Table B-3-9, COPC-specific soil-to-plant biotransfer factors (Br) may not reflect

site-specific conditions. This may be especially true for inorganic COPCs for which estimates of

Br would be accurately estimated by using plant uptake response slope factors.

Qs Quantity of soil ingested by the

animal

kg/day 0.37

This variable is site-specific. We recommend using the soil ingestion rate of 0.37 kg/day.

NC DEHNR (1997) recommended a soil ingestion rate for swine of 0.37 kg/day. This is estimated by assuming

a soil intake of 8 percent of the total DMI. NC DEHNR (1997) does not specify the total DMI used to estimate Qs. 

However, mathematically, Qs appears to be based on a total DMI of 4.7 kg DW/day (4.7@ 0.08 = 0.37), which is

consistent with U.S. EPA (1995).

The following uncertainty is associated with this variable:

The recommended soil ingestion rate may not accurately represent site-specific or local conditions. 

Therefore, Qs and Apork values, may be under- or overestimated to some degree.

Cs Average soil concentration over

exposure duration

mg COPC/kg soil Varies

This variable is COPC- and site-specific, and calculated using the equation in Table B-3-1. Uncertainties are sitespecific.
TABLE B-3-12

PORK CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 4 of 7)

Variable Description Units Value

B-154

Bs Soil bioavailability factor unitless 1.0

The soil bioavailability factor, Bs, can be thought of as the ratio between bioconcentration (or biotransfer) factors

for soil and vegetation for a given COPC. The efficiency of transfer from soil may differ from efficiency or transfer

from plant material for some COPCs. If the transfer efficiency is lower for soils, then this ratio would be less than

1.0. If it is equal or greater than that of vegetation, the Bs would be equal to or greater than 1.0.

Due to limited data regarding bioavailability from soil, we recommend a default value of 1.0 for Bs, until more

COPC-specific data is available for this parameter. Some COPCs may be much less bioavailable from soil than

from plant tissues. This uncertainty may overestimate Bs.

Bapork

Biotransfer factor for pork day/kg FW tissue Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values

in the HHRAP companion database. Bapork is defined as the ratio of the COPC concentration in animal tissue (mg

COPC/kg FW tissue) to the daily intake of the COPC (mg COPC/day) by the animal.

Uncertainties introduced by this variable include the following:

(1) We recommend calculating Bapork values for organic COPCs from Babeef values, assuming that pork is

23 percent fat and beef is 19 percent fat. Values derived this way might not accurately represent the

behavior of organic COPCs under site-specific conditions. Bapork and consequent Apork estimates may be

under- or overestimated to some degree.

(2) The sources or method used to support or estimate Bapork values presented in NC DEHNR (1997) are not

known. Therefore, the degree to which these values represent the behavior of COPCs under site-specific

conditions cannot be determined.

MF Metabolism factor unitless 0.01 and 1.0

This variable is COPC-specific. Based on a study by Ikeda et al. (1980), U.S. EPA (1995a) recommended using a

metabolism factor to account for metabolism in animals to offset the amount of bioaccumulation suggested by

biotransfer factors. MF applies only to beef, milk, and pork. It does not apply to direct exposures to air, soil, or

water, or to ingestion of produce, chicken, or fish. U.S. EPA (1995b) recommends an MF of 0.01 for bis(2-

ethylhexyl)phthalate (BEHP) and 1.0 for all other COPCs.
TABLE B-3-12

PORK CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 5 of 7)

B-155

REFERENCES AND DISCUSSION

Boone, F.W., Yook C. Ng, and John M. Palms. 1981. “Terrestrial Pathways of Radionuclide Particulates.” Health Physics, Vol. 41, No. 5, pp. 735-747. November.

This document is cited as the source of a total DMI for hogs of 3.4 kg DW/day.

Ikeda, G.J., P.P. Sapenza, and J.L. Couvillion. 1980. “Comparative distribution, excretion, and metabolism of di(2-ethylhexyl)phthalate in rats, dogs, and pigs.” Food Cosmet. Toxicology. 

18:637-642.

NAS. 1987. Predicting Feed Intake of Food-Producing Animals. National Research Council, Committee on Animal Nutrition, Washington, D.C.

This document presents a total DMI for lactating sows of 5.2 kg DW/day. This document is also cited by U.S. EPA (1995) as the source of a total DMI for swine of 4.7 kg DW/day. As

presented in this document, the value of 4.7 kg DW/day represents the average of specific total DMI values for gilts (young sows) and for lactating sows.

Ng, Y.C., C.S. Colsher, and S.E. Thomson. 1982. Transfer Coefficients for Assessing the Dose from Radionuclides in Meat and Eggs. U.S. Nuclear Regulatory Commission. Final Report. 

NUREG/CR-2976.

This document is cited as the source of biotransfer factors (Bapork) for several inorganic COPCs. However, U.S. EPA (1995) notes that “a large degree of uncertainty” exists in many of the

experiments used in this document to develop the biotransfer factors. The biotransfer factors developed by Ng, Colsher, and Thompson (1982) are not recommended for use by U.S. EPA .

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

Grains such as corn may be grown specifically as swine feed. COPC uptake into these feed materials may occur through root uptake, wet and dry deposition of particulate-bound

constituents on plants, and vapor-phase uptake of COPCs through plant foliage. Plants are classified as “protected” if they have an outer covering that acts as a barrier to direct deposition

and vapor uptake of air contaminants. NC DEHNR (1997) classifies grains as protected, and recommends that only root uptake of COPCs be evaluated for grains; because silage may

consist of forage materials that have been stored and fermented, it should be treated as forage (that is, as unprotected).

This document also recommends the following:

C An Fi value of 1, assuming that 100 percent of the plant material eaten by swine have been grown on soil contaminated by combustion unit emissions.

C Plant type-specific Qpi values for hogs of 3.0 and 1.3 kg DW/day for grain and silage, respectively. This document cites U.S. EPA (1990) as the source of these ingestion rates.

C A quantity of soil ingested (Qs) value of 0.37 kg DW/day. This value is calculated as 8 percent of the total DMI (U.S. EPA 1993a). The total DMI of 4.3 kg DW/day comes from

U.S. EPA (1990).

C A range of Bapork values (1.3 x 10-09 to 5.8 day/kg wet tissue); however, the sources of or methodology used to estimate, these values are not identified.

Pennington, J.A.T. 1989. Food Values of Portions Commonly Used. 15th ed. Harper and Row. New York.

Cited by NC DEHNR (1997)—actually NC DEHNR (1997) cities “Pennington (1993)” but presents only this document (Pennington 1989) in the reference section—for the estimated fat

content of pork, 23 percent.
TABLE B-3-12

PORK CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 6 of 7)

B-156

U.S. EPA. 1982. “Pesticides Assessment Guidelines Subdivision O.” Residue Chemistry. Office of Pesticides and Toxic Substances, Washington, D.C. EPA/540/9-82-023.

This document is cited by U.S. EPA (1990) as the source of the assumption that 70 percent of the total DMI for swine is grain and 30 percent is silage.

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. EPA-600-90-003. January.

This document represents total dry matter intake (DMI) rates for hogs and lactating sows of 3.4 and 5.2 kg DW/day, respectively, and recommends the average of these two rates (4.3 kg

DW/day) as the total DMI. U.S. EPA (1990) cites Boone et al. (1981) as the source of the hog ingestion rate and NAS (1987) as the source of the lactating sow ingestion rate.

This document then assumes that 70 percent of the total DMI for swine is grain and 30 percent is silage; fractions then are used to arrive at the recommended grain ingestion rate of 3.0 kg

DW/day (4.3 kg DW/day @ 0.70) and the recommended silage ingestion rate of 1.3 kg DW/day (4.3 kg DW/day @ 0.30). U.S. EPA (1990) cites U.S. EPA (1982) as the source of the grain

and silage fractions.

This document also recommends an Fi value of 1. This assumes that 100 percent of the plant material eaten by swine is grown on soil contaminated by combustion unit emissions.

U.S. EPA. 1992. Addendum to the Methodology for Assessing Health Risks Associated with Indirect Exposure to Combustor Emissions. External Review Draft. Office of Research and

Development. Washington, D.C. November.

This document recommends that the quantity of soil (Qs) eaten by swine be estimated as 8 percent of the total DMI. This document states “Fries of USDA notes pigs exhibit ‘rooting’

behavior and assumes a maximum soil ingestion intake of 8 percent of dry matter based on a 2 to 8 percent range noted in his earlier PCB work.” However, this document provides no

citations of work performed by Fries or personal communications with Fries.

U.S. EPA. 1994a. Draft Exposure Assessment Guidance for RCRA Hazardous Waste Combustion Facilities. Office of Solid Waste and Emergency Response. EPA-530-R-94-021. April.

This document recommends an Fi value of 1. This assumes that 100 percent of the plant material ingested by swine has been grown on soil contaminated by combustion unit emissions. 

U.S. EPA. 1994b. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-Specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This document states that milk is 3.5 percent fat. This document also uses experimental data derived by McLachlon, et al. (1990) to calculate biotransfer factors with units of (kg feed/kg

tissue).

U.S. EPA. 1994c. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document recommends an Fi

 value of 1. This assumes that 100 percent of the plant material eaten by swine has been grown on soil contaminated by combustion unit emissions.
TABLE B-3-12

PORK CONCENTRATION DUE TO PLANT AND SOIL INGESTION

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 7 of 7)

B-157

U.S. EPA. 1995a. Further Issues for Modeling the Indirect Exposure Impacts from Combustor Emissions. Office of Research and Development. Washington, D.C. January 20.

This document calculates Bapork values for cadmium, mercury, selenium, and zinc by dividing uptake slope factors ([mg COPC/kg tissue DW]/[mg COPC/kg feed DW]) from U.S. EPA

(1993b) - 0.003 (cadmium), 0.0234 (mercury), 2.94 (selenium), and 0.002 (zinc)—by a daily feed ingestion rate for pork of 4.7 kg DW/day (NAS 1987). This approach is similar to that

recommended by U.S. EPA (1994b) for dioxins. The calculated biotransfer factors are 6.0 x 10-04 (cadmium); 0.0051 (mercury); 6.255 x 10-01 (selenium); and 4.0 x 10-04 (zinc).

U.S. EPA. 1995b. “Waste Technologies Industries Screening Human Health Risk Assessment (SHHRA): Evaluation of Potential Risk from Exposure to Routine Operating Emissions.” Volume V. 

External Review Draft. U.S. EPA Region 5, Chicago, Illinois.

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and 

Development. EPA 452/R-97-005. December.
TABLE B-3-13

COPC CONCENTRATION IN EGGS

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 1 of 5)

B-158

Description

This equation calculates the COPC concentration in eggs due to ingestion of contaminated soil and grain by home grown chickens that have access to soil.

Uncertainties associated with this equation include the following:

(1) This pathway has typically been applied only to PCDDs and PCDFs. However, concentrations in chicken eggs for other organics and metals can be calculated using biotransfer factors

in an approach similar to that used to calculate concentrations in animal tissue.

(2) Assuming that 10 percent of a chicken’s diet is soil may not represent site-specific conditions. Stephens et al. (1995) suggested that the percentage of soil in the diet of chickens raised

under field conditions may be greater than 10 percent. Therefore, the concentration of COPCs in eggs, Aegg, may be underestimated.

(3) Estimated COPC-specific soil-to-plant biotransfer factors (Br) may not reflect site-specific or local conditions. Therefore, estimates of Pr and Aegg may be under- or overestimated to

some degree.

(4) The recommended BCFs used in calculating Baegg may not accurately represent the behavior of COPCs under site-specific and local conditions. For example, Stephens et al. (1995)

noted that chickens raised under field conditions showed larger apparent BCFs. Therefore, the recommended BCFs may underestimate the concentration of COPCs in eggs, Aegg.

(5) The recommended BCFs are based on incomplete experimental results. Stephens et al. (1995) presented complete experimental results. This study included results from a high-dose

group and a low-dose group; results were based on the full exposure period. A brief comparison of the results from Stephens et al. (1992) with those from Stephens et al. (1995)

indicates that BCFs from the high-dose group are generally higher than BCFs from the low-dose group. Therefore, using the currently recommended BCFs may underestimate the

COPC concentration in eggs, Aegg.

Equation

For mercury modeling, the concentration of COPC in eggs is calculated for divalent mercury (Hg2+) and methyl mercury (MHg) using their respective Pi

, Cs, and Baeggs values.

Variable Description Units Value

Aegg

Concentration of COPC in eggs mg

COPC/kg

FW tissue
TABLE B-3-13

COPC CONCENTRATION IN EGGS

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 2 of 5)

Variable Description Units Value

B-159

Fi

Fraction of plant type i (grain)

grown on contaminated soil and

ingested by the animal

unitless 1.0

This variable is site- and plant type-specific. Fi

 for chickens is estimated for grain feed only. We recommend using a default

value of 1.0. This is consistent with U.S. EPA (1998), U.S. EPA (1994a), U.S. EPA (1994b) and NC DEHNR (1997), which

recommend assuming that 100 percent of the plant materials ingested were grown on soil contaminated by facility emissions.

The following uncertainty is associated with this variable:

Assuming that 100 percent of the plant material eaten by chickens was grown on soil contaminated by emissions

may overestimate Aegg.

Qpi

Quantity of plant type i (grain)

ingested by the animal 

kg DW

plant/day

0.2

Qpi for chicken is estimated for grain feed only, as recommended by NC DEHNR (1997). 

Uncertainties associated with this variable include the following:

Actual grain ingestion rates can vary from site to site; this can over- or underestimate Qpi

.

Pi

Concentration of COPC in plant

type I (grain)

mg COPC/kg

DW

Varies

This variable is COPC-, site-, and plant type-specific. Calculate values for Pi for grain using the equation in Table B-3-9.

Uncertainties introduced by this variable include the following:

(1) Some of the variables in the equation in Table B-3-9—including Cs, Cyv, Q, Dydp, and Dywp—are COPC- and

site-specific. Uncertainties associated with these variables are site-specific.

(2) In the equation in Table B-3-9, COPC-specific plant-soil biotransfer factors (Br) may not reflect

site-specific conditions. This may be especially true for inorganic COPCs for which Br’s would be more accurately

estimated by using plant uptake response slope factors.

Qs Quantity of soil ingested by the

animal

kg/day 0.022

This variable is site-specific. We recommend that the soil ingestion rate of 0.022 kg/day be used. This is consistent with

Stephens et al. (1995).

Uncertainties introduced by this variable include the following:

(1) The recommended soil ingestion rate may not accurately represent site-specific or local conditions.

(2) Empirical data to support soil ingestion rates of chickens are limited.

Cs Average soil concentration over

exposure duration

mg COPC/kg

soil

Varies

This variable is COPC- and site-specific, and calculated using the equation in Table B-3-1. Uncertainties are site-specific.
TABLE B-3-13

COPC CONCENTRATION IN EGGS

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 3 of 5)

Variable Description Units Value

B-160

Bs Soil bioavailability factor unitless 1.0

The soil bioavailability factor, Bs, can be thought of as the ratio between bioconcentration (or biotransfer) factors for soil and

vegetation for a given COPC. The efficiency of transfer from soil may differ from efficiency or transfer from plant material

for some COPCs. 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 would be equal to or greater than 1.0.

Due to limited data regarding bioavailability from soil, we recommend a default value of 1.0 for Bs, until more COPCspecific data is available for this parameter. Some COPCs may be much less bioavailable from soil than from plant tissues. 

This uncertainty may overestimate Bs.

Baegg

Biotransfer factor for chicken eggs day/kg FW

tissue

Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in the

HHRAP companion database.

The following uncertainties are associated with this variable:

(1) We recommend calculating Baegg values for organic COPCs other than dioxins and furans by using the regression

equation developed on the basis of a study of 29 organic compounds. Values calculated by using this regression

equation may not accurately represent the behavior of organic COPCs under site-specific conditions. Therefore,

estimates of Baegg and, therefore, Aegg may be under- or overestimated to some degree.

(2) The recommended BCFs may not accurately represent the behavior of COPCs under site-specific or local

conditions. For example, Stephens et al. (1995) noted that chickens raised under field conditions, and which

probably had a more than 10 percent soil in their diet, showed larger apparent BCFs. Therefore, the recommended

BCFs may underestimate the concentration of COPCs in eggs, Aegg.

(3) The recommended BCFs are based on incomplete experimental results. Stephens et al. (1995) include results from

a high-dose group and as a low-dose group; results are based on the full exposure period. A brief comparison of

the results from Stephens et al. (1992) and those from Stephens et al. (1995) indicates that BCFs from the high-dose

group are generally higher than BCFs from the low-dose group. Therefore, using the currently recommended BCFs

may underestimate the COPC concentration in eggs, Aegg.
TABLE B-3-13

COPC CONCENTRATION IN EGGS

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 4 of 5)

B-161

REFERENCES AND DISCUSSION

California Environmental Protection Agency (CEPA). 1993. “ Parameter Values and Ranges for CALTOX.” Draft. Office of Scientific Affairs. California Department of Toxics Substances 

Control. Sacramento, CA. July. 

Chang, R.R., D. Hayward, L. Goldman, M. Harnly, J. Flattery, and R.D. Stephens. 1989. “Foraging Farm Animals as Biomonitors for Dioxin Contamination.” Chemosphere. Volume 19: 481-486. 

This document appears to be cited by Stephens et al. (1992) as support for the assumption that soil represents 10 percent of the diet of free-range chickens. 

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is a reference source for the equation in Table B-3-13. This document also cites Stephens et al. (1992) as the source of estimates of the fraction of diet that is soil (Fd), and

BCFegg for dioxins and furans.

Petreas, M.X., L.R. Goldman, D.G. Hayward, R. Chang, J. Flattery, T. Wiesmuller, R.D. Stephens, D.M. Fry, and C. Rappe. 1991. “Biotransfer and Bioaccumulation of PCDD/PCDFs from Soils:

Controlled Exposure Studies of Chickens.” Chemosphere. Volume 23: 1731-1741.

This document appears to be cited by Stephens et al. (1992) and Stephens et al. (1995) as support for the assumption that soil represents 10 percent of the diet of free-range chickens.

Stephens, R.D., M.X. Petreas, and D.G. Hayward. 1992. “Biotransfer and Bioaccumulation of Dioxins and Dibenzofurans from Soil.” Hazardous Materials Laboratory, California Department of

Health Services. Berkeley, California.

This document is cited as the source of the assumption that free- range chickens ingest soil as 10 percent of their diet and as the source of the dioxin and furan congener-specific BCFs. 

However, this document does not clearly reference or document the assumption that soil represents 10 percent of a free-range chicken diet. The document appears to cite two other

documents as supporting this assumption, Chang, Hayward, Goldman, Harnly, Flattery, and Stephens (1989) and Petreas, Goldman, Hayward, Chang, Flattery, Wiesmuller, Stephens, Fry,

and Rappe (1992). Also, this document presents dioxin and furan congener-specific BCFs (egg yolk) for the low-exposure group after 80 days of a 178-day exposure period. The chickens

in the low-dose group were fed a diet containing 10 percent soil with a PCDD/PCDF concentration of 42 parts per trillion (ppt) I-TEQ. Chickens in the high-dose group were fed a diet

containing 10 percent soil with a PCDD/PCDF concentration of 458 ppt I-TEQ; BCF results were not presented for this group. 

Stephens, R.D., M.X. Petreas, and D.G. Hayward. 1995. “Biotransfer and Bioaccumulation of Dioxins and furans from Soil: Chickens as a Model for Foraging Animals.” The Science of the Total

Environment. Volume 175: 253-273.

This document is an expansion of the results originally presented in Stephens et al. (1992). In particular, this document suggests that the percentage of soil in the diet of chickens raised

under field conditions is likely to be greater than 10 percent, the value that was used in the experimental study presented in this document.

This document also presents dioxin and furan congener-specific BCFs (egg yolk) under two exposure schemes: low exposure and high exposure. The white leghorn (Babcock D 300)

chickens in the low group were fed a diet containing 10 percent soil with a PCDD/PCDF concentration of 42 ppt I-TEQ. Chickens in the high group were fed a diet consisting of 10 percent

soil with a PCDD/PCDF concentration of 460 ppt I-TEQ (some congeners were fortified by spiking). The BCFs presented for low- and high-dose groups both represent averages of results

from Day-80, Day-160, and Day-178 (the end of the exposure duration).
TABLE B-3-13

COPC CONCENTRATION IN EGGS

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 5 of 5)

B-162

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. EPA/600/6-90/003. January. 

This document is a reference source for the equation in Table B-3-9; and an Fi value of 1.0.

U.S. EPA. 1992. Technical Support Document for Land Application of Sewage Sludge. Volumes I and II. EPA 822/R-93-001a. Office of Water. Washington, D.C.

U.S. EPA (1995) recommends that uptake slope factors for the metals cadmium, selenium, and zinc cited by this document be used to derive Baegg values.

U.S. EPA. 1995. Further Issues for Modeling the Indirect Exposure Impacts from Combustor Emissions. Office of Research and Development. Washington, D.C. January 20.

U.S. EPA. 1997a. Exposure Factors Handbook. “Food Ingestion Factors”. Volume II. EPA/600/P-95/002F. August.

U.S. EPA. 1997b. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research 

and Development. EPA 452/R-97-005. December.
TABLE B-3-14

CONCENTRATION IN CHICKEN

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 1 of 5)

B-163

Description

This equation calculates the COPC concentration ( Achicken) in chicken meat due to ingestion of contaminated soil and grain by home grown chickens that have access to soil.

Uncertainties associated with this equation include the following:

(1) This pathway has typically been applied only to PCDDs and PCDFs. However, concentrations in chickens for other organics and metals can be calculated using biotransfer factors

using a similar approach as was used to calculate concentrations in other animal tissue.

(2) The assumption that 10 percent of a chicken’s diet is soil may not represent site-specific or local conditions of chickens raised on farms. Stephens et al. (1995) suggests that the

percentage of soil in the diet of chickens raised under field conditions may be greater than 10 percent. Therefore, the concentration of COPCs in chicken, Achicken may be underestimated.

(3) The recommended BCFs are based on incomplete experimental results. Stephens et al. (1995) presents results for a high-dose group and low-dose group (results are based on the full

178-day exposure period). A comparison of the results from Stephens et al. (1992) with those from Stephens et al. (1995) shows that BCFs from the high dose group are generally

higher than BCFs from the low dose group. Therefore, use of the currently recommended BCFs may underestimate the COPC concentration in chicken, Achicken.

Equation

For mercury modeling, the concentration of COPC in chicken is calculated for divalent mercury (Hg2+) and methyl mercury (MHg) using their respective Pi

, Cs, and Bachicken values.

Variable Description Units Value

Achicken

Concentration of COPC in

chicken meat

 mg COPC/kg

FW tissue

Fi

Fraction of plant type i (grain)

grown on contaminated soil and

ingested by the animal

unitless 1.0

This variable is site- and plant type-specific. Fi

 for chickens is estimated for grain feed only. We recommend using a

default value of 1.0. This is consistent with U.S. EPA (1998), U.S. EPA (1994a), U.S. EPA (1994b) and NC DEHNR

(1997), which recommend assuming that 100 percent of the plant materials ingested were grown on soil contaminated by

facility emissions.

The following uncertainty is associated with this variable:

Assuming that 100 percent of the plant materials eaten by chickens were grown on soil contaminated by facility 

emissions may overestimate Achicken.
TABLE B-3-14

CONCENTRATION IN CHICKEN

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 2 of 5)

Variable Description Units Value

B-164

Qpi

Quantity of plant type i (grain)

ingested by the animal 

kg DW

plant/day

0.2

Qpi

 for chicken is estimated for grain feed only, as recommended by NC DEHNR (1997) and U.S. EPA (1990). 

Uncertainties associated with this variable include the following:

Actual grain ingestion rates can vary from site to site; this can over- or underestimate Qpi

.

Pi

Concentration of COPC in plant

type I (grain)

mg COPC/kg

DW

Varies

This variable is COPC-, site-, and plant type-specific. Values for Pi are calculated for grain using the equations in Table

B-3-9.

Uncertainties introduced by this variable include the following:

(1) Some of the variables in the equation in Table B-3-9—including Cs, Cyv, Q, Dydp, and Dywp—are COPC- and

site-specific. Uncertainties associated with these variables are site-specific.

(2) In the equation in Table B-3-9, COPC-specific plant-soil biotransfer factors (Br) may not reflect

site-specific conditions. This may be especially true for inorganic COPCs for which Br’s would be more

accurately estimated by using plant uptake response slope factors.

Qs Quantity of soil ingested by the

animal

kg/day 0.022

This variable is site-specific. We recommend using the soil ingestion rate of 0.022 kg/day. This is consistent with

Stephens et al. (1995).

Uncertainties introduced by this variable include the following:

(1) The recommended soil ingestion rate may not accurately represent site-specific or local conditions.

(2) Empirical data to support soil ingestion rates of chickens are limited.

Cs Average soil concentration over

exposure duration

mg COPC/kg

soil

Varies

This variable is COPC- and site-specific, and calculated using the equation in Table B-3-1. Uncertainties are site-specific.

Bs Soil bioavailability factor unitless 1.0

The soil bioavailability factor, Bs, can be thought of as the ratio between bioconcentration (or biotransfer) factors for soil

and vegetation for a given COPC. The efficiency of transfer from soil may differ from efficiency or transfer from plant

material for some COPCs. If the transfer efficiency is lower for soils, then this ratio would be less than 1.0. If it is equal

or greater than that of vegetation, the Bs would be equal to or greater than 1.0.

Due to limited data regarding bioavailability from soil, we recommend a default value of 1.0 for Bs, until more COPCspecific data is available for this parameter. Some COPCs may be much less bioavailable from soil than from plant

tissues. This uncertainty may overestimate Bs.
TABLE B-3-14

CONCENTRATION IN CHICKEN

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 3 of 5)

Variable Description Units Value

B-165

Bachicken

Biotransfer factor for chicken day/kg FW

tissue

Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in

the HHRAP companion database. Bachicken is defined as the ratio of the COPC concentration in fresh weight tissue (mg

COPC/kg FW tissue) to the daily intake of the COPC (mg COPC/day) from chicken feed. 

Uncertainties associated with this variable include the following:

(1) We recommend calculating Bachicken values for organic COPCs other than dioxins and furans by from Babeef

values by assuming that chicken is 15 percent fat and beef is 19 percent fat. Values calculated this way may not

accurately represent the behavior of organic COPCs under site-specific conditions. Therefore, estimates of

Bachicken and, therefore Achicken, may be under- or overestimated to some degree.

(2) The beef-to-chicken fat content ratio method which is used to estimate Bachicken values from Babeef values for

organics (except PCDDs and PCDFs) assumes that (1) COPCs bioconcentrate in the fat tissues, and (2) there are

no differences in metabolism or feeding characteristics between beef cattle and chicken. Due to uncertainties

associated with these assumptions, Bachicken, and Achicken values may be under- or overestimated to some degree.

(3) The recommended BCFs may not accurately represent the behavior of COPCs under site-specific or local

conditions. For example, Stephens et al. (1995) noted that chickens raised under field conditions, and which

probably had more than 10 percent soil in their diet, showed larger apparent BCFs. Therefore, using the

recommended BCFs may underestimate Achicken , to some extent.

(4) The recommended BCFs are based on incomplete experimental results. Stephens et al. (1995) presented results

that are based on the full 178-day exposure period. A comparison of the results from Stephens et al. (1992) to

those from Stephens et al. (1995) shows that BCFs from the high-dose group are generally higher than BCFs

from the low-dose group. Therefore, using the currently recommended BCFs may underestimate the COPC

concentration in chicken, Achicken.
TABLE B-3-14

CONCENTRATION IN CHICKEN

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 4 of 5)

B-166

REFERENCES AND DISCUSSION

Chang, R.R., D. Hayward, L. Goldman, M. Harnly, J. Flattery, and R.D. Stephens. 1989. “Foraging Farm Animals as Biomonitors for Dioxin Contamination.” Chemosphere. Volume 19; 481-486.

This document appears to be cited by Stephens et al. (1992) as support for the assumption that soil represents 10 percent of the diet of free-range chickens.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is the reference source for the equation in Table B-3-14. This document also cites Stephens et al. (1992) as the source for the recommended fraction of diet that is soil (Fd)

and BCFChicken for dioxins and furan congeners.

Petreas, M.X., L. R. Goldman, D. G. Hayward, R. Chang, J. Flattery, T. Wiesmuller, R.D. Stephens, D.M. Fry, and C. Rappe. 1991. “Biotransfer and Bioaccumulation of PCDD/PCDFs from Soils:

Controlled Exposure Studies of Chickens.” Chemosphere. Volume 23: 1731-1741.

This document appears to be cited by Stephens et al. (1992) and Stephens et al. (1995) as support for the assumption that soil represents 10 percent of the diet of free-range chickens. 

Stephens, R.D., M.X. Petreas, and D.G. Hayward. 1992. “Biotransfer and Bioaccumulation of Dioxins and Dibenzofurans from Soil.” Hazardous Materials Laboratory, California Department of

Health Services. Berkeley, California. Presented at the 12th International Symposium on Dioxins and Related Compounds. August 24 through 28. University of Tampere, Tampere,

Finland.

This document is cited as the source of the assumption that free-range chickens ingest soil as 10 percent of their diet and as the source of the dioxin and furan congeners-specific BCFs

recommended by NC DEHNR (1997). However this document does not clearly reference or document the assumption that soil represents 10 percent of a free-range chicken’s diet. The

document appears to cite two other documents as supporting its assumption, (1) Change, Hayward, Goldman, Harnly, Flattery and Stephens (1989) and (2) Petreas, Goldman, Hayward,

Chang, Flattery, Wiesmuller, Stephens, Fry, and Rappe (1992). 

This document also presents dioxin and furan congener-specific BCFs (thigh) for the low- exposure group after 80 days of a 178-day total exposure period. The chickens in the low-dose

group were fed a diet containing 10 percent soil with a PCDD/PCDF concentration of 42 ppt I-TEQ. Chickens in the high-dose group were fed a diet containing 10 percent soil with a

PCDD/PCDF concentration of 458 ppt I-TEQ; BCF results were not presented from the high-dose group.

Stephens, R.D., M.X. Petreas, and D.G. Hayward. 1995. “Biotransfer and Bioaccumulation of Dioxins and Furans from Soil: Chickens as a Model for Foraging Animals.” The Science of the Total

Environment. Volume 175: 253-273.

This document is an expansion of the results originally presented in Stephens et al. (1992). In particular, this document suggests that the percentage of soil in the diet of chickens raised

under field conditions is likely to be greater than 10 percent, the value that was used in the experimental study presented in this document.

This document also presents dioxin and furan congener-specific BCFs (thigh) under two exposure schemes—low exposure and high exposure. The white leghorn (Babcock D 300)

chickens in the low group were fed a diet containing 10 percent soil with a PCDD/PCDF concentrations of 42 ppt I-TEQ. Chickens in the high group were fed a diet containing 10 percent

soil with a PCDD/PCDF concentration of 460 ppt I-TEQ (some congeners were fortified by spiking).

The BCFs presented for low- and high-dose groups both represent averages of results from Day-80 and Day-164 of a total 178-day exposure period.
TABLE B-3-14

CONCENTRATION IN CHICKEN

(CONSUMPTION OF ANIMAL PRODUCTS EQUATIONS)

(Page 5 of 5)

B-167

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. EPA/600/6-90/003. January. 

This document is a reference source for the equation in Table B-3-9; and an Fi value of 1.0.

U.S. EPA. 1992. Technical Support Document for Land Application of Sewage Sludge. Volumes I and II. EPA 822/R-93-001a. Office of Water. Washington, D.C.

U.S. EPA (1995) recommends that uptake slope factors for the metals cadmium, selenium, and zinc cited by this document be used to derive Bachicken values.

U.S. EPA. 1995. Further Issues for Modeling the Indirect Exposure Impacts from Combustor Emissions. Office of Research and Development. Washington, D.C. January 20.

U.S. EPA. 1997a. Exposure Factors Handbook. “Food Ingestion Factors”. Volume II. EPA/600/P-95/002F. August.

U.S. EPA. 1997b. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research 

and Development. EPA 452/R-97-005. December.
TABLE B-4-1

WATERSHED SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 8)

B-168

Description

Use the equations in this table to calculate an average COPC soil concentration resulting from wet and dry deposition of particles and vapors to soil over the exposure duration. We recommend

assuming that COPCs are incorporated only to a finite depth (the soil mixing zone depth, Zs). Use the COPC soil concentration averaged over the exposure duration, represented by Cs, for

carcinogenic COPCs, where risk is averaged over the lifetime of an individual. Because the hazard quotient associated with noncarcinogenic COPCs is based on a reference dose rather than a

lifetime exposure, we recommend using the highest annual average COPC soil concentration occurring during the exposure duration period for noncarcinogenic COPCs. The highest annual

average COPC soil concentration would most likely occur at the end of the time period of combustion and is represented by CstD. 

The following uncertainties are associated with this variable:

(1) We assume that the time period for deposition of COPCs resulting from hazardous waste combustion is a conservative, long-term value. This assumption may overestimate Cs and CstD.

(2) Exposure duration values (T2) are based on historical mobility studies and won’t necessarily remain constant. Specifically, mobility studies indicate that most receptors that move

remain in the vicinity of the combustion unit; however, it is impossible to accurately predict the probability that these short-distance moves will influence exposure, based on factors

such as atmospheric transport of pollutants.

(3) Using a value of zero for T1

 doesn’t account for exposure that may have occurred from historic operations and emissions from hazardous waste combustion. This may underestimate Cs

and CstD.

(4) For soluble COPCs, leaching might lead to movement to below the mixing depth, resulting in lower concentrations within the mixing depth. This uncertainty may overestimate Cs and

CstD. 

(5) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in situ materials) compared to other residues. This may

underestimate Cs and CstD. 

Equation for Carcinogens

Soil Concentration Averaged Over Exposure Duration
TABLE B-4-1

WATERSHED SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 8)

B-169

Equation for Noncarcinogens

Highest Annual Average Soil Concentration

where

For mercury modeling

Use 0.48Q for total mercury and Fv = 0.85 in the mercury modeling equation to calculate Ds. Apportion the calculated Ds value into the divalent mercury (Hg2+) and methyl mercury (MHg)

forms based on the assumed 98% Hg2+ and 2% MHg speciation split in soils (see Chapter 2). Elemental mercury (Hg0) occurs in very small amounts in the vapor phase and does not exist in the

particle or particle-bound phase. Therefore, assume elemental mercury deposition onto soils is negligible or zero. Evaluate elemental mercury for the direct inhalation pathway only (Table

B-5-1).

Ds (Hg2+) = 0.98 Ds (Mercu ry)

Ds (Mhg) = 0.02 Ds (Mercu ry)

Ds (Hg0) = 0.0

Evaluate divalent and methyl mercury as individual COPCs. Calculate Cs for divalent and methyl mercury using the corresponding (1) fate and transport parameters for mercuric chloride

(divalent mercury, Hg2+) and methyl mercury provided in Appendix A-2, and (2) Ds (Hg2+) and Ds (MHg) as calculated above.
TABLE B-4-1

WATERSHED SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 8)

B-170

Variable Description Units Value

Cs Average soil concentration over

exposure duration 

mg COPC/kg

soil

CstD

Soil concentration at time tD mg COPC/kg

soil

Ds Deposition term mg COPC/kg

soil-yr

Varies

U.S. EPA (1994a) and NC DEHNR (1991) recommended incorporating a deposition term into the Cs equation. 

Uncertainties associated with this variable include the following:

(1) Five of the variables in the equation for Ds (Q, Cyv, Dywv, Dywp, and Dydp) are COPC- and site-specific. 

Values of these variables are estimated through modeling. The direction and magnitude of any uncertainties

shouldn’t be generalized.

(2) Based on the narrow recommended ranges, we expect uncertainties associated with Vdv, Fv, and BD to be low.

(3) Values for Zs vary by about one order of magnitude. Uncertainty is greatly reduced if you know whether soils

are tilled or untilled.

tD Time period over which deposition

occurs (time period of combustion)

yr 30

U.S. EPA (1998) suggests that this period of time can be $30 years. We recommend using 30 years unless site-specific

information is available indicating that this assumption is unreasonable (see Chapter 6 of the HHRAP). 

ks COPC soil loss constant due to all

processes

yr-1 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-2. The COPC soil loss constant

is the sum of all COPC removal processes. 

Uncertainty associated with this variable includes the following:

COPC-specific values for ksg (one of the variables in the equation in Table B-4-2) are empirically determined

from field studies. No information is available regarding the application of these values to the site-specific

conditions associated with affected facilities.
TABLE B-4-1

WATERSHED SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 4 of 8)

Variable Description Units Value

B-171

T2

Length of exposure duration yr 6, 30, or 40

We recommend reasonable maximum exposure (RME) values for T2

:

Exposure Duration RME Reference

Child Resident 6 years U.S. EPA (1997b)

Farmer Child

Fisher Child

Adult Resident and 30 years U.S. EPA (1997b)

Fisher

Farmer 40 years U.S. EPA (1994b)

U.S. EPA (1994c) recommended the following unreferenced values:

Exposure Duration Years 

Subsistence Farmer 40

Adult Resident 30

Subsistence Fisher 30

Child Resident 9

Uncertainties associated with this variable include the following:

(1) Exposure duration rates are based on historical mobility rates and may not remain constant. This assumption

may overestimate or underestimate Cs and CstD.

(2) Mobility studies indicate that most receptors that move remain in the vicinity of the emission sources. However,

it is impossible to accurately predict the likelihood that these short-distance moves will influence exposure, based

on factors such as atmospheric transport of pollutants. This assumption may overestimate or underestimate Cs

and CstD.

T1

Time period at the beginning of

combustion

yr 0

Consistent with U.S. EPA (1994c), we recommend a value of 0 for T1.

The following uncertainty is associated with this variable:

A T1

 of zero doesn’t account for exposure that may have occurred from historical operation or emissions from

the combustion of hazardous waste. This may underestimate Cs and CstD.

100 Units conversion factor mg-cm2

/kg-cm2
TABLE B-4-1

WATERSHED SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 5 of 8)

Variable Description Units Value

B-172

Q COPC emission rate g/s Varies

This variable is COPC- and site-specific. See Chapters 2 and 3 of the HHRAP for guidance calculating this variable. 

Uncertainties associated with this variable are site-specific.

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs

:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with

U.S. EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A

default value of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil

(Brzuzy et al. 1995). A default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below Zs, resulting in lower concentrations within the

Zs

. This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution compared to other residues. 

This uncertainty may underestimate Cs and CstD. 

BD Soil bulk density g soil/cm3

 soil 1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value

of 1.5 g soil/cm3

 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that

a value of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended BD value may not accurately represent site-specific soil conditions; and may under- or

overestimate site-specific soil conditions to an unknown degree.
TABLE B-4-1

WATERSHED SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 6 of 8)

Variable Description Units Value

B-173

Fv

Fraction of COPC air concentration

in vapor phase 

unitless 0 to 1

This variable is COPC-specific. We discuss Fv

in detail in Appendix A-2, and offer COPC-specific values in the HHRAP

companion database. The range is based on values presented in Appendix A-2. Values are also presented in U.S. EPA

(1994b) and NC DEHNR (1997). 

Fv was calculated using an equation presented in Junge (1977) for all organic COPCs, including PCDDs and PCDFs. U.S.

EPA (1994c) states that Fv = 0 for all metals (except mercury).

The following uncertainties are associated with this variable:

(1) Fv calculations assume a default ST value for background plus local sources, rather than an ST value for urban

sources. If a specific site is located in an urban area, using the latter ST value may be more appropriate. 

Specifically, the ST

 value for urban sources is about one order of magnitude greater than that for background plus

local sources, and it would result in a lower calculated Fv

 value; however, the Fv

 value is likely to be only a few

percent lower.

(2) According to Bidleman (1988), the equation used to calculate Fv assumes that the variable c (Junge constant) is

constant for all chemicals; however, the value of c depends on the chemical (sorbate) molecular weight, the

surface concentration for monolayer coverage, and the difference between the heat of desorption from

the particle surface and the heat of vaporization of the liquid-phase sorbate. To the extent that site- or

COPC-specific conditions may cause the value of c to vary, uncertainty is introduced if a constant value

of c is used to calculate Fv.

Dytwv Unitized yearly (water body or

watershed) average total deposition

from vapor phase 

s/m2-yr Varies

This variable is COPC- and site-specific, and is determined by air modeling (see Chapter 3). Uncertainties associated with

this variable are site-specific.

Dytwp Unitized yearly (water body or

watershed) average total (wet and

dry) deposition from particle phase

s/m2

-yr Varies

This variable is COPC- and site-specific, and is determined by air modeling (see Chapter 3). Uncertainties associated with

this variable are site-specific.
TABLE B-4-1

WATERSHED SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 7 of 8)

B-174

REFERENCES AND DISCUSSION

Bidleman, T.F. 1988. “Atmospheric Processes.” Environmental Science and Technology. Volume 22. Number 4. Pages 361-367.

For discussion, see References and Discussion, Table B-1-1.

Brzuzy, L.P. and R.A. Hites. 1995. “Estimating the Atmospheric Deposition of Polychlorinated Dibenzo-p-dioxins and Dibenzofurans from Soils.” Environmental Science and Technology. 

Volume 29. Pages 2090-2098.

This reference presents soil profiles for dioxin measurements.

Carsel, R.F., R.S. Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2.

Pages 11-24.

This reference is cited by U.S. EPA (1994b) as the source for a mean soil bulk density value, BD, of 1.5 g soil/cm3 soil for loam soil.

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York, New York.

Cited by U.S. EPA (1998) for the statement that BD is affected by the soil structure, such as looseness or compaction of the soil, depending on the water and clay content of the soil.

Junge, C.E. 1977. Fate of Pollutants in Air and Water Environments, Part I. Suffet, I.H., Ed. Wiley. New York. Pages 7-26.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This is one of the source documents for the equation in Table B-4-1. This document also recommends using (1) a deposition term, Ds, and (2) COPC-specific Fv

 values.

Research Triangle Institute (RTI). 1992. Preliminary Soil Action Level for Superfund Sites. Draft Interim Report. Prepared for U.S. EPA Hazardous Site Control Division, Remedial Operations

Guidance Branch. Arlington, Virginia. EPA Contract 68-W1-0021. Work Assignment No. B-03, Work Assignment Manager Loren Henning. December.

This document is a reference source for COPC-specific Fv values.

U.S. EPA. 1992. Estimating Exposure to Dioxin-Like Compounds. Draft Report. Office of Research and Development. Washington, D.C. EPA/600/6-88/005b.

The External Review Draft of the MPE document (the final is U.S. EPA 1998) cites this document as the source of values for soil mixing zone depth, Zs

, for tilled and untilled soils.

U.S. EPA. 1993. Addendum to the Methodology for Assessing Health Risks Associated with Indirect Exposure to Combustor Emissions. Working Group Recommendations. Office of Solid Waste. 

Office of Research and Development. Washington, D.C. September.

This document is a reference for the equation in Table B-4-1. It recommends using a deposition term, Ds, and COPC-specific Fv

 values in the Cs equation.
TABLE B-4-1

WATERSHED SOIL CONCENTRATION DUE TO DEPOSITION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 8 of 8)

B-175

U.S. EPA 1994a. Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for RCRA

Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. April.

This document is a reference for the equation in Table B-4-1; it recommends using the following in the Cs equation: (1) a deposition term, Ds, and (2) a default soil bulk density value of

1.5 (g soil/cm3

 soil), based on a mean value for loam soil from Carsel et al. (1988).

U.S. EPA. 1994b. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-Specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. June. EPA/600/6-88/005Cc.

This document recommends T2

 values for the farmer.

U.S. EPA. 1994c. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Office of Emergency and Remedial Response. Office

of Solid Waste. December.

This document recommends the following:

C Values for the length of exposure duration, T2

C Value of 0 for the time period of the beginning of combustion, T1

C Fv

 values that range from 0.27 to 1 for organic COPCs

C Default soil bulk density value of 1.5 (g soil/cm3 soil), based on a mean for loam soil from Carsel et al. (1988)

U.S. EPA. 1997a. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and

Development. EPA 452/R-97-005. December.

U.S. EPA. 1997b. Exposure Factors Handbook. Office of Research and Development. EPA/600/P-95/002Fc. August.

This document is a reference source for values for length of exposure duration, T2.

U.S. EPA. 1998. Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions (MPE). Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document is a reference for recommended values for soil mixing zone depth, Zs, for tilled and untilled soils.
TABLE B-4-2

COPC SOIL LOSS CONSTANT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 4)

B-176

Description

This equation calculates the COPC soil loss constant, which accounts for the loss of COPCs from soil by several mechanisms.

Uncertainties associated with this equation include the following:

(1) COPC-specific values for ksg are empirically determined from field studies. No information is available regarding the application of these values to the site-specific conditions associated

with affected facilities.

(2) The source of the equations in Tables B-4-3 through B-4-5 have not been identified.

Equation

Variable Description Units Value

ks COPC soil loss constant due to all

processes

yr-1

ksg COPC loss constant due to biotic

and abiotic degradation

yr-1 Varies

This variable is COPC-specific. Values are available in the COPC tables in Appendix A-2. 

“Degradation rate” values are also presented in NC DEHNR (1997), however, no reference or source is provided for the values. U.S.

EPA (1994a) and U.S. EPA (1994b) state that ksg values are COPC-specific; however, all ksg values are presented as zero (U.S. EPA

1994a) or as “NA” (U.S. EPA 1994b); the basis of these assumptions is not addressed. 

The following uncertainty is associated with this variable:

COPC-specific values for ksg are empirically determined from field studies; no information is available regarding the

application of these values to the site-specific conditions associated with affected facilities.
TABLE B-4-2

COPC SOIL LOSS CONSTANT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 4)

Variable Description Units Value

B-177

kse COPC loss constant due to soil

erosion

yr-1 0

This variable is COPC- and site-specific, and is further discussed in Table B-4-3. Consistent with U.S. EPA (1994a), U.S. EPA

(1994b) and NC DEHNR (1997), we recommend a default value of 0 for kse because contaminated soil erodes both onto the site and

away from the site.

Uncertainties associated with this variable include the following:

(1) The source of the equation in Table B-4-3 has not been identified.

(2) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in lower

concentrations within the Zs. This uncertainty may overestimate kse.

(3) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in

situ materials) compared to other residues. This uncertainty may underestimate kse.

ksr COPC loss constant due to surface

runoff

yr-1 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-4. No reference document is cited for this

equation; using this equation is consistent with U.S. EPA (1994b) and NC DEHNR (1997). U.S. EPA (1994a) assumes that all ksr

values are zero but does not explain the basis of this assumption. 

Uncertainties associated with this variable (calculated using Table B-4-4) include the following:

(1) The source of Table B-4-4 has not been identified.

(2) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in lower

concentrations within the Zs

. This uncertainty may overestimate ksr.

(3) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in

situ materials) compared to other residues. This uncertainty may underestimate ksr.

ksl COPC loss constant due to leaching yr-1 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-5. Using this equation is consistent with

U.S. EPA (1998), U.S. EPA(1994b), and NC DEHNR (1997). U.S. EPA (1994a) assumes that all ksl values are zero but does not

explain the basis of this assumption.

Uncertainties associated with this variable (calculated using Table B-4-5) include the following:

(1) The source of the equation in Table B-4-5 has not been identified.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing

with in-situ materials) compared to other residues. This uncertainty may underestimate ksl.
TABLE B-4-2

COPC SOIL LOSS CONSTANT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 4)

Variable Description Units Value

B-178

ksv COPC loss constant due to

volatilization

yr-1 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-6. This equation calculates the COPC loss

constant from soil due to volatilization, and was obtained from U.S. EPA (1998). The soil loss constant due to volatilization (ksv) is

based on gas equilibrium coefficients and gas phase mass transfer. The first order decay constant, ksv, is obtained by adapting the

Hwang and Falco equation for soil vapor phase diffusion (Hwang and Falco 1986).

Uncertainties associated with this equation include the following:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in lower

concentrations within the Zs. This uncertainty may overestimate ksv.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in

situ materials) compared to other residues. This uncertainty may underestimate ksv.

REFERENCES AND DISCUSSION

Hwang S. T. and Falco, J. W. 1986. “Estimation of multimedia exposures related to hazardous waste facilities”, In: Pollutants in a Multimedia Environment. Yoram Cohen, Ed. Plenum Publishing

Corp. New York.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the reference documents for Tables B-4-4 and B-4-5. This document is also cited as (1) the source for a range of COPC-specific degradation rates (ksg), and (2) one

of the sources that recommend assuming that the loss resulting from erosion (kse) is zero because of contaminated soil eroding both onto the site and away from the site.

U.S. EPA. 1994a. Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. April.

This document is cited as a source for the assumptions that losses resulting from erosion (kse), surface runoff (ksr), degradation (ksg), leaching (ksl), and volatilization (ksv) are all zero.

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

This document is one of the reference documents for Tables B-4-4 and B-4-5. This document is also cited as one of the sources that recommend assuming that the loss resulting from erosion

(kse) is zero and the loss resulting from degradation (ksg) is “NA” or zero for all compounds.
TABLE B-4-2

COPC SOIL LOSS CONSTANT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 4 of 4)

B-179

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document is one of the reference documents for the equations for ksr, ksl, and ksv.
TABLE B-4-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 5)

B-180

Description

This equation calculates the constant for COPC loss resulting from erosion of soil. Consistent with U.S. EPA (1994), U.S. EPA (1994b), and NC DEHNR (1997), we recommend a default value of

zero for kse is zero because of contaminated soil eroding both onto the site and away from the site. In site-specific cases where the permitting authority considers it appropriate to calculate a kse,

we recommend using the equation presented in this table along with associated uncertainties. You can find additional discussion on determining kse in U.S. EPA (1998). Uncertainties associated

with this equation include:

(1) For soluble COPCs, leaching might lead to movement below 1 centimeter in untilled soils, resulting in a greater mixing depth. This uncertainty may overestimate kse.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in situ materials) compared to other residues. This uncertainty

may underestimate kse.

Equation

Variable Description Units Value

kse COPC loss constant due to soil

erosion

yr-1 0

Consistent with U.S. EPA (1994), U.S. EPA (1994b), and NC DEHNR (1997), we recommend assuming a default value of zero

for kse because contaminated soil erodes both onto the site and away from the site. Uncertainty may overestimate kse.

0.1 Units conversion factor g-kg/cm2

-

m2

Xe

Unit soil loss kg/m2-yr Varies

This variable is site-specific and is calculated by using the equation in Table B-4-13.

The following uncertainty is associated with this variable:

All of the equation variables are site-specific. Using default values rather than site-specific values for any or all of

these variables will result in unit soil loss (Xe) estimates that are under- or overestimated to some degree. Based on

default values, Xe

 estimates can vary over a range of less than two orders of magnitude.
TABLE B-4-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 5)

Variable Description Units Value

B-181

SD Sediment delivery ratio unitless Varies

This value is site-specific and is calculated using the equation in Table B-4-14.

Uncertainties associated with this variable include the following: 

(1) The recommended default values for the empirical intercept coefficient, a, are average values that are based on studies

of sediment yields from various watersheds. Therefore, those default values may not accurately represent site-specific

watershed conditions. As a result, using these default values may under- or overestimate SD.

(2) The recommended default value for the empirical slope coefficient, b, is based on a review of sediment yields from

various watersheds. This single default value may not accurately represent site-specific watershed conditions. As a

result, using the default value may under- or overestimate SD.

ER Soil enrichment ratio unitless Inorganics: 1

Organics: 3

COPC enrichment occurs because (1) lighter soil particles erode more quickly than heavier soil particles, and (2) concentration

of organic COPCs—which is a function of organic carbon content of sorbing media—is expected to be higher in eroded

material than in in situ soil (U.S. EPA 1998). In the absence of site-specific data, we recommend a default value of 3 for

organic COPCs and 1 for inorganic COPCs. This is consistent with other Agency guidance (U.S. EPA 1998), which

recommends a range of 1 to 5 and a value of 3 as a “reasonable first estimate.” This range has been used for organic matter,

phosphorus, and other soil-bound COPCs (U.S. EPA 1998); however, no sources or references were provided for this range. 

ER is generally higher in sandy soils than in silty or loamy soils (U.S. EPA 1998).

The following uncertainty is associated with this variable:

The default ER value may not accurately reflect site-specific conditions; therefore, kse may be over- or

underestimated to an unknown extent. Using county-specific ER values will reduce the extent of any uncertainties.

BD Soil bulk density g soil/cm3

soil

1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value of

1.5 g soil/cm3

 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that a value

of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended soil bulk density value may not accurately represent site-specific soil conditions.
TABLE B-4-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 5)

Variable Description Units Value

B-182

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs

:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with U.S.

EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A default

value of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil (Brzuzy et al.

1995). A default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting a greater

mixing depth. This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution compared to of other residues. 

This uncertainty may underestimate Cs and CstD. 

Kds

Soil-water partition coefficient mL water/g

soil 

(or cm3

water/g soil)

Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in Appendix A-2.

2sw

Soil volumetric water content mL

water/cm3

soil

0.2

This variable is site-specific, and depends on the available water and on soil structure; 2sw can be estimated as the midpoint

between a soil’s field capacity and wilting point, if a representative watershed soil can be identified. However, we recommend

the use of 0.2 mL/cm3

 as a default value. This value is the midpoint of the range 0.1 (very sandy soils) to 0.3 (heavy loam/clay

soils) recommended by U.S. EPA (1993) (no source or reference is provided for this range) and is consistent with U.S. EPA

(1994b).

The following uncertainty is associated with this variable:

The default 2sw value may not accurately reflect site-specific or local conditions; therefore, kse may be under- or

overestimated to a small extent, based on the limited range of values.
TABLE B-4-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 4 of 5)

B-183

REFERENCES AND DISCUSSION

Carsel, R.F., R.S. Parish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2. 

Pages 11-24.

This document is cited by U.S. EPA (1994b) as the source for a mean soil bulk density, BD, value of 1.5 (g soil/cm3 soil) for loam soil. 

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York.

This document is cited by U.S. EPA (1998) for the statement that soil bulk density, BD, is affected by the soil structure, such as looseness or compaction of the soil, depending on the water

and clay content of the soil.

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the sources that recommend assuming that the loss resulting from erosion (kse) is zero because contaminated soil erodes both onto the site and away from the site.

U.S. EPA. 1994. Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for RCRA

Hazardous Waste Combustion Facilities. April.

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This document is the source of values for soil mixing zone depth, Zs, for tilled and untilled soil.

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

This document recommends (1) a default BD value of 1.5 (g soil/cm3

 soil), based on a mean value for loam soil that is taken from Carsel et al. (1988), and (2) a default 2sw, value of 0.2 (mL

water/cm3 soil).
TABLE B-4-3

COPC LOSS CONSTANT DUE TO SOIL EROSION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 5 of 5)

B-184

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document is the source of a range of COPC enrichment ratio, ER, values. The recommended range, 1 to 5, was used for organic matter, phosphorous, and other soul-bound COPCs. 

This document recommends a value of 3 as a “reasonable first estimate,” and states that COPC enrichment occurs because lighter soil particles erode more quickly than heavier soil particles. 

Lighter soil particles have higher ratios of surface area to volume and are higher in organic matter content. Therefore, concentration of organic COPCs, which is a function of the organic

carbon content of sorbing media, is expected to be higher in eroded material than in in situ soil.

This document is also a source of the following:

C A range of 2sw values of 0.1 ml water/cm3

 soil (very sandy soils) to 0.3 ml water/cm3 soil (heavy loam/clay soils). However, no source or reference is provided for this range.

C A range of values for Zs

, for tilled and untilled soil

C The equations in Tables B-1-3 and B-1-5.
TABLE B-4-4

COPC LOSS CONSTANT DUE TO RUNOFF

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 4)

B-185

Description

This equation calculates the COPC loss constant due to runoff of soil. Uncertainties associated with this equation include the following:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in a greater mixing depth. This uncertainty may overestimate ksr.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution compared to other residues. This uncertainty may underestimate ksr.

Equation

Variable Description Units Value

ksr COPC loss constant due to runoff yr-1

RO Average annual surface runoff from

pervious areas

cm/yr Varies

This variable is site-specific. According to U.S. EPA (1998), U.S. EPA (1994b), and NC DEHNR (1997), you can estimate RO

by using the Water Atlas of the United States (Geraghty et al. 1973). According to NC DEHNR (1997), you can also use more

detailed, site-specific procedures for estimating the amount of surface runoff, such as those based on the U.S. Soil Conservation

Service curve number equation (CNE). U.S. EPA (1985) is cited as an example of such a procedure. 

The following uncertainty is associated with this variable:

To the extent that site-specific or local average annual surface runoff information is not available, default or estimated

values may not accurately represent site-specific or local conditions. As a result, ksr may be under- or overestimated

to an unknown degree.
TABLE B-4-4

COPC LOSS CONSTANT DUE TO RUNOFF

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 4)

Variable Description Units Value

B-186

2sw

Soil volumetric water content mL

water/cm3

soil

0.2

This variable is site-specific, and depends on the available water and on soil structure; you can estimate 2sw as the midpoint

between a soil’s field capacity and wilting point, if you can identify a representative watershed soil. We recommend using 0.2

ml/cm3 as a default value. This value is the midpoint of the range 0.1 (very sandy soils) to 0.3 (heavy loam/clay soils),

recommended by U.S. EPA (1998) (no source or reference is provided for this range), and is consistent with U.S. EPA (1994b)

and NC DEHNR (1997).

The following uncertainty is associated with this variable:

The default 2sw value may not accurately reflect site-specific or local conditions; therefore, ksr may be under- or

overestimated to a small extent, based on the limited range of values.

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with U.S.

EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A default value

of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil (Brzuzy et al. 1995). A

default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting lower

concentrations within the Zs

. This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution compared to other residues. This

uncertainty may underestimate Cs and CstD. 

Kds

Soil-water partition coefficient mL water/g

soil 

(or cm3

water/g

soil)

Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in Appendix A-2.
TABLE B-4-4

COPC LOSS CONSTANT DUE TO RUNOFF

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 4)

Variable Description Units Value

B-187

BD Soil bulk density g soil/cm3

soil

1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value of 1.5

g soil/cm3 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that a value of

1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended soil bulk density value may not accurately represent site-specific soil conditions.

REFERENCES AND DISCUSSION

Carsel, R.F., R.S. Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2. 

Pages 11-24.

This document is cited by U.S. EPA (1994b) as the source of a mean soil bulk density, BD, value of 1.5 (g soil/cm3 soil) for loam soil. 

Geraghty, J.J., D.W. Miller, F. Van der Leeden, and F.L. Troise. 1973. Water Atlas of the United States. Water Information Center, Port Washington, New York.

This document is cited by U.S. EPA (1998), U.S. EPA (1994), and NC DEHNR (1997) as a reference to calculate average annual runoff, RO. This reference provides maps with isolines of

annual average surface water runoff, which is defined as all flow contributions to surface water bodies, including direct runoff, shallow interflow, and ground water recharge. Because these

values are total contributions and not only surface runoff, U.S. EPA (1994) recommends that the volumes be reduced by 50 percent in order to estimate surface runoff.

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York.

This document is cited by U.S. EPA (1998) for the statement that dry soil bulk density, BD, is affected by the soil structure, such as looseness or compaction of the soil, depending on the

water and clay content of the soil.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the source documents that cites the use of Table B-4-4; however, this document is not the original source of this equation (this source is unknown). This document

also recommends the following:

C Estimating annual current runoff, RO (cm/yr), by using the Water Atlas of the United States (Geraghty et al. 1973) or site-specific procedures, such as using the U.S. Soil

Conservation Service curve number equation (CNE); U.S. EPA (1985) is cited as an example of such a procedure.

C Default value of 0.2 (mL water/cm3 soil) for soil volumetric water content (2sw)
TABLE B-4-4

COPC LOSS CONSTANT DUE TO RUNOFF

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 4 of 4)

B-188

U.S. EPA. 1985. Water Quality Assessment: A Screening Procedure for Toxic and Conventional Pollutants in Surface and Ground Water—Part I (Revised. 1985). Environmental Research

Laboratory. Athens, Georgia. EPA/600/6-85/002a. September.

This document is cited by NC DEHNR (1997) as an example of the use of the U.S. Soil Conservation Service CNE to estimate site-specific surface runoff. 

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This document presents a range of values for soil mixing zone depth, Zs

, for tilled and untilled soil.

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Offices of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document recommends the following:

C Estimation of average annual runoff, RO, by using the Water Atlas of the United States (Geraghty et al. 1973)

C Default soil dry bulk density, BD, value of 1.5 (g soil/cm3 soil), based on the mean for loam soil that is taken from Carsel et al. (1988)

C Default soil volumetric water content, 2sw, value of 0.2 (mL water/cm3 soil)

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document recommends the following:

C A range of soil volumetric water content, 2sw, values of 0.1 (very sandy soils) to 0.3 (heavy loam/clay soils) (the original source of, or reference for, these values is not identified)

C A range of values for soil mixing depth, Zs, for tilled and untilled soil (the original source of, or reference for, these values is not identified)

C Using the Water Atlas of the United States (Geraghty, Miller, Van der Leeden, and Troise 1973) to calculate average annual runoff, RO
TABLE B-4-5

COPC LOSS CONSTANT DUE TO LEACHING

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 5)

B-189

Description

This equation calculates the COPC loss constant resulting from leaching of soil. Uncertainties associated with this equation include the following:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in a greater mixing depth. This uncertainty may overestimate ksl.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in situ materials) compared to other residues. This uncertainty

may underestimate ksl.

(3) The original source of this equation has not been identified. U.S. EPA (1998) presents the equation as shown here. U.S. EPA (1994a) and NC DEHNR (1997) replaced the numerator as

shown with “q”, defined as average annual recharge (cm/yr).

Equation

Variable Description Units Value

ksl COPC loss constant due to leaching yr-1

P Average annual precipitation cm/yr 18.06 to 164.19

This variable is site-specific. This range is based on information presented in U.S. EPA (1998), representing data for 69

selected cities (U.S. Bureau of Census 1987; Baes et al. 1984). The 69 selected cities are not identified; however, they appear to

be located throughout the continental United States. We recommend using site-specific data.

The following uncertainty is associated with this variable:

To the extent that a site is not located near an established meteorological data station, and site-specific data are not

available, default average annual precipitation data may not accurately reflect site-specific conditions. As a result, ksl

may be under- or overestimated. However, average annual precipitation data are reasonably available; therefore, we

expect uncertainty introduced by this variable to be minimal.
TABLE B-4-5

COPC LOSS CONSTANT DUE TO LEACHING

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 5)

Variable Description Units Value

B-190

I Average annual irrigation cm/yr 0 to 100

This variable is site-specific. This range is based on information presented in U.S. EPA (1998), representing data for 69 selected

cities (Baes et al. 1984). The 69 selected cities are not identified; however, they appear to be located throughout the continental

United States.

The following uncertainty is associated with this variable:

To the extent that site-specific or local average annual irrigation information is not available, default values (generally

based on the closest comparable location) may not accurately reflect site-specific conditions. As a result, ksl may be

under- or overestimated to an unknown degree.

RO Average annual surface runoff from

pervious areas

cm/yr Varies

This variable is site-specific. According to U.S. EPA (1998), U.S. EPA (1994a), and NC DEHNR (1997), you can estimate RO

by using the Water Atlas of the United States (Geraghty et al. 1973). According to NC DEHNR (1997), you can also use more

detailed, site-specific procedures, such as those based on the U.S. Soil Conservation Service CNE. U.S. EPA (1985) is cited as

an example of such a procedure.

The following uncertainty is associated with this variable:

To the extent that site-specific or local average annual surface runoff information is not available, default or estimated

values may not accurately represent site-specific or local conditions. As a result, ksl may be under- or overestimated

to an unknown degree.

Ev

Average annual evapotranspiration cm/yr 35 to 100

This variable is site-specific. This range is based on information presented in U. S. EPA (1998), representing data from 69

selected cities. The 69 selected cities are not identified; however, they appear to be located throughout the continental United

States.

The following uncertainty is associated with this variable:

To the extent that site-specific or local average annual evapotranspiration information is not available, default values

may not accurately reflect site-specific conditions. As a result, ksl may be under- or overestimated to an unknown

degree.
TABLE B-4-5

COPC LOSS CONSTANT DUE TO LEACHING

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 5)

Variable Description Units Value

B-191

2sw

Soil volumetric water content mL

water/cm3

soil

 0.2

This variable is site-specific, and depends on the available water and on soil structure. You can estimate 2sw as the midpoint

between a soil’s field capacity and wilting point, if you can identify a representative watershed soil. We recommend using 0.2

ml/cm3 as a default value. This value is the midpoint of the range of 0.1 (very sandy soils) to 0.3 (heavy loam/clay soils)

recommended by U.S. EPA (1998) (no source or reference is provided for this range) and is consistent with U.S. EPA (1994b)

and NC DEHNR (1997).

The following uncertainty is associated with this variable:

The default 2sw value may not accurately reflect site-specific or local conditions; therefore, ksl may be under- or

overestimated to a small extent, based on the limited range of values.

Zs

Soil depth mixing zone cm 2 to 20

We recommend the following values for Zs:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with U.S.

EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A default

value of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil (Brzuzy et al.

1995). A default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in lower

concentrations within the Zs. This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution compared to other residues. This

uncertainty may underestimate Cs and CstD. 

BD Soil bulk density g soil/cm3

soil

1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value of 1.5

g soil/cm3 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that a value of

1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended soil bulk density value may not accurately represent site-specific soil conditions.
TABLE B-4-5

COPC LOSS CONSTANT DUE TO LEACHING

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 4 of 5)

Variable Description Units Value

B-192

Kds

Soil-water partition coefficient cm3

 water/g

soil

Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in Appendix A-2.

REFERENCES AND DISCUSSION

Baes, C.F., R.D. Sharp, A.L. Sjoreen and R.W. Shor. 1984. “A Review and Analysis of Parameters for Assessing Transport of Environmentally Released Radionuclides through Agriculture.” 

Prepared for the U.S. Department of Energy under Contract No. DEAC05-840R21400.

For the continental United States, as cited in U.S. EPA (1998), this document is the source of a series of maps showing: (1) average annual precipitation (P), (2) average annual irrigation (I),

and (3) average annual evapotranspiration isolines.

Carsel, R.F., R.S. Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2. 

Pages 11-24.

This document is cited by U.S. EPA (1994a) as the source for a mean soil bulk density value, BD, of 1.5 (g soil/cm3 soil) for loam soil. 

Geraghty, J.J., D.W. Miller, F. Van der Leeden, and F.L. Troise. 1973. Water Atlas of the United States. Water Information Center, Port Washington, New York.

This document is cited by U.S. EPA (1998), U.S. EPA (1994a), and NC DEHNR (1997) as a reference for calculating RO. This document provides maps with isolines of annual average

surface runoff, which is defined as all flow contributions to surface water bodies, including direct runoff, shallow interflow, and ground water recharge. Because these volumes are total

contributions and not only surface runoff, U.S. EPA (1994a) recommends that the volumes be reduced by 50 percent in order to estimate average annual surface runoff.

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York, New York.

This document is cited by U.S. EPA (1998) for the statement that BD is affected by the soil structure, such as looseness or compaction of the soil, depending on the water and clay content of

the soil.
TABLE B-4-5

COPC LOSS CONSTANT DUE TO LEACHING

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 5 of 5)

B-193

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the source documents that cites the use of the equation in Table B-4-5. However, the document is not the original source of this equation. This document also

recommends the following:

C Estimation of average annual surface runoff, RO (cm/yr), by using either the Water Atlas of the United States (Geraghty et al. 1973) or site-specific procedures, such as the U.S.

Soil Conservation Service CNE; U.S. EPA 1985 is cited as an example of such a procedure.

C A default value of 0.2 (mL water/cm3 soil) for soil volumetric water content, 2sw

U.S. Bureau of the Census. 1987. Statistical Abstract of the United States: 1987. 107th edition. Washington, D.C.

This document is a source of average annual precipitation (P) information for 69 selected cities, as cited in U.S. EPA (1998); these 69 cities are not identified.

U.S. EPA. 1985. Water Quality Assessment: A Screening Procedure for Toxic and Conventional Pollutants in Surface and Groundwater. Part I (Revised 1985). Environmental Research

Laboratory. Athens, Georgia. EPA/600/6-85/002a. September.

This document is cited by NC DEHNR (1997) as an example of the use of the U.S. Soil Conservation Service CNE to estimate RO. 

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. EPA 600-90-003. January.

This document presents ranges of (1) average annual precipitation, (2) average annual irrigation, and (3) average annual evapotranspiration. This document cites Baes et al. (1984) and U.S.

Bureau of the Census (1987) as the original sources of this information.

U.S. EPA. 1994a. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

U.S. EPA. 1994b. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This document presents values for soil mixing depth, Zs, for tilled and untilled soil, as cited in U.S. EPA (1993). 

This document recommends (1) a default soil volumetric water content, 2sw, value of 0.2 (mL water/cm3

 soil), based on U.S. EPA (1993), and (2) a default soil bulk density, BD, value of 1.5

(g soil/cm3 soil), based on a mean value for loam soil from Carsel et al. (1988).

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document is one of the reference source documents for the equation in Table B-1-5. The original source of this equation is not identified. This document also presents a range of values

for soil mixing depth, Z, for tilled and untilled soil; the original source of these values is not identified.
TABLE B-4-6

COPC LOSS CONSTANT DUE TO VOLATILIZATION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 5)

B-194

Description

This equation calculates the COPC loss constant from soil due to volatilization, and was obtained from Methodology for Assessing Health Risks Associated with Multiple Exposure Pathways to

Combustor Emissions (U.S. EPA 1998). The soil loss constant due to volatilization (ksv) is based on gas equilibrium coefficients and gas phase mass transfer. The first order decay constant, ksv, is

obtained by adapting the Hwang and Falco equation for soil vapor phase diffusion (Hwang and Falco 1986).

Uncertainties associated with this equation include the following:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting in a greater mixing depth. This uncertainty may overestimate ksv.

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in situ materials) compared to other residues. This uncertainty

may underestimate ksv.

Equation

Variable Definition Units Value

ksv Constant for COPC loss due to 

volatilization 

yr1

3.1536 x 10+07 Units conversion factor s/yr

H Henry’s Law constant atm-m3

/mol Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in

the HHRAP companion database. 

The following uncertainty is associated with this variable:

Values for this variable, estimated by using the parameters and algorithms in Appendix A-2, may under- or

overestimate the actual COPC-specific values. As a result, ksv may be under- or overestimated.
TABLE B-4-6

COPC LOSS CONSTANT DUE TO VOLATILIZATION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 5)

Variable Definition Units Value

B-195

Zs

Soil mixing zone depth cm 2 to 20

We recommend the following values for Zs

:

Soil Depth (cm) Reference

Untilled 2 Brzuzy et al. (1995)

Tilled 20 U.S. EPA (1998)

U.S. EPA (1992) recommended values of 1 cm (for untilled) and 20cm (for tilled soil). These values are consistent with

U.S. EPA (1998), which further states that leaching soluble compounds might lead to movement below a 1-cm depth. A

default value of 2 cm for untilled soil mixing depth is based on a study that profiled dioxin measurements within soil

(Brzuzy et al. 1995). A default value of 20 cm for tilled soil mixing depth is based on U.S. EPA (1998). 

The following uncertainties are associated with this variable:

(1) For soluble COPCs, leaching might lead to movement to below 2 centimeters in untilled soils, resulting a

greater mixing depth. This uncertainty may overestimate Cs and CstD. 

(2) Deposition to hard surfaces may result in dust residues that have negligible dilution compared to other residues. 

This uncertainty may underestimate Cs and CstD. 

Kds

Soil-water partition coefficient cm3 water/g

soil

Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in

Appendix A-2.

R Universal gas constant atmm3

/mol-K

8.205 x 10-5

There are no uncertainties associated with this parameter.
TABLE B-4-6

COPC LOSS CONSTANT DUE TO VOLATILIZATION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 5)

Variable Definition Units Value

B-196

Ta

Ambient air temperature K 298

This variable is site-specific. U.S. EPA (1998) also recommends an ambient air temperature of 298 K.

The following uncertainty is associated with this variable:

To the extent that site-specific or local values for the variable are not available, default values may not

accurately represent site-specific conditions. We expect the uncertainty associated with the selection of a single

value from within the temperature range at a single location to be more significant than the uncertainty

associated with choosing a single ambient temperature to represent all localities. In other words, the range of

average ambient temperatures across the country is generally less than the temperature range at an individual

site.

BD Soil bulk density g soil/cm3

soil

1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD

value of 1.5 g soil/cm3 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998)

stated that a value of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended soil bulk density value may not accurately represent site-specific soil conditions.

Dsoil

Solids particle density g/cm3

2.7

We recommend the use of this value, based on Blake and Hartage (1996) and Hillel (1980). 

The solids particle density will vary with location and soil type.

Da

Diffusivity of COPC in air cm2

/s Varies

This value is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in the

HHRAP companion database. 

The following uncertainty is associated with this variable:

The default Da

 values may not accurately represent the behavior of COPCs under site-specific conditions. 

However, we expect the degree of uncertainty to be minimal.
TABLE B-4-6

COPC LOSS CONSTANT DUE TO VOLATILIZATION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 4 of 5)

Variable Definition Units Value

B-197

2sw

Soil volumetric water content mL/cm3

 soil 0.2

This variable depends on the available water and on soil structure. You can estimate 2sw as the midpoint between a soil’s

field capacity and wilting point, if you can identify a representative watershed soil. However, we recommend using 0.2

ml/cm3 as a default value. This value is the midpoint of the range 0.1 (very sandy soils) to 0.3 (heavy loam/clay soils)

recommended by U.S. EPA (1998) (no source or reference is provided for this range) and is consistent with U.S. EPA

(1994b).

The following uncertainty is associated with this variable:

The default 2sw values may not accurately reflect site-specific or local conditions; therefore, ksv may be underor overestimated to a small extent, based on the limited range of values.

REFERENCES AND DISCUSSION

Blake, GR. and K.H. Hartge. 1996. Particle Density. Methods of Soil Analysis, Part 1: Physical and Mineralogical Methods. Second Edition. Arnold Klute, Ed. American Society of Agronomy,

Inc. Madison, WI., p. 381. 

Carsel, R.F., R.S, Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. Vol. 2. 

Pages 11-24.

This document is cited by U.S. EPA (1994b) as the source of a mean soil bulk density value, BD, of 1.5 (g soil/cm3 soil) for loam soil.

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York, New York.

Hwang S. T. and Falco, J. W. 1986. “Estimation of multimedia exposures related to hazardous waste facilities”, In: Pollutants in a Multimedia Environment. Yoram Cohen, Ed. Plenum Publishing

Corp. New York.

Miller, R.W. and D.T. Gardiner. 1998. In: Soils in Our Environment. J.U. Miller, Ed. Prentice Hall. Upper Saddle River, NJ. pp. 80-123. 

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington,

D.C. EPA/600/6-88/005Cc. June.

This document presents value for soil, mixing depth, Zs, for tilled and untilled soil.

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Waste. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.
TABLE B-4-6

COPC LOSS CONSTANT DUE TO VOLATILIZATION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 5 of 5)

B-198

This document recommends a default soil density, BD, value of 1.5 (g soil/cm3 soil), based on a mean value for loam soil that is taken from Carsel et al. (1988).

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document recommends the following:

C A range of values for soil mixing zone depth, Zs, for tilled and untilled soil; however, the source or basis for these values is not identified

C A default ambient air temperature of 298 K

C A range of soil volumetric water content, 2sw
TABLE B-4-7

TOTAL WATER BODY LOAD

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 2)

B-199

Description

This equation calculates the total average water body load from wet and dry vapor and particle deposition, runoff, and erosion loads. The limitations and uncertainties associated with this equation

include the following:

(1) Uncertainties associated with variables in equations presented in Tables B-4-8, B-4-9, B-4-10, B-4-11, and B-4-12 that are site-specific. These variables include Q, Dytwv, Dytwp, Aw,

Cywv, AI, AL, Cs, and Xe. Values for many of these variables are estimated through the use of mathematical models and the uncertainties associated with values for these variables may be

significant in some cases (Bidleman 1988).

(2) We expect the uncertainties associated with the remaining variables in equations presented in Tables B-4-8, B-4-9, B-4-10, B-4-11, and B-4-12 to be less significant, primarily because of

the narrow ranges of probable values for these variables or because values for these variables (such as Kds) were estimated using well-established methods.

Equation

Variable Description Units Value

LT

Total COPC load to the water body g/yr

LDEP

Total (wet and dry) particle phase

and vapor phase COPC direct

deposition load to water body

g/yr Varies

This variable is COPC- and site-specific, and calculated using the equation presented in Table B-4-8.

Uncertainty associated with this variable include the following:

Most of the uncertainty associated with the variables in the equation in Table B-4-8, specifically those associated with

Q, Dytwv, Dytwp, and Aw, are site-specific and may be significant in some cases. 

Ldif

Vapor phase COPC diffusion load

to water body 

g/yr Varies

This variable is calculated using equation presented in Table B-4-12.

Uncertainty associated with this variable include the following:

Most of the uncertainty associated with the variables in the equation in Table B-4-12, specifically those associated with

Q, Cywv, and Aw, are site-specific.
TABLE B-4-7

TOTAL WATER BODY LOAD

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 2)

Variable Description Units Value

B-200

LRI

Runoff load from impervious

surfaces

g/yr Varies

This variable is calculated using the equation presented in Table B-4-9.

Uncertainty associated with this variable include the following:

Most of the uncertainty associated with the variables in this equation, specifically those associated with Q,

Dytwv, Dytwp, and AI, are site-specific.

LR

Runoff load from pervious surfaces g/yr Varies

This variable is calculated using equation presented in Table B-4-10.

Uncertainties associated with this variable include the following:

(1) Most of the uncertainties associated with the variables in the equation in Table B-4-10, specifically those for AL, AI, and

Cs, are site-specific.

(2) Uncertainties associated with the remaining variable in the equation in Table B-4-10 are not expected to be significant,

primarily because of the narrow ranges of probable values for these variables or the use of well-established

estimation procedures (Kds

).

LE

Soil erosion load g/yr Varies

This variable is calculated using equation presented in Table B-4-11.

Uncertainties associated with this variable include the following:

(1) Most of the uncertainties associated with the variables in the equation in Table B-4-11, specifically those for Xe,, AL, AI,

and Cs, are site-specific.

(2) Uncertainties associated with the remaining variables in the equation in Table B-4-11 are not expected to be significant,

primarily because of the narrow range of probable values for these variables or the use of well-established

estimation procedures (Kds).

REFERENCES AND DISCUSSION

Bidleman, T.F. 1988. “Atmospheric Processes.” Environmental Science and Technology. Volume 22. Number 4. Pages 361-367.

For discussion, see References and Discussion in Table B-1-1.
TABLE B-4-8

DEPOSITION TO WATER BODY

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 3)

B-201

Description

This equation calculates the average load to the water body from direct deposition of wet and dry particles and wet vapors onto the surface of the water body. Uncertainties associated with this

equation include the following:

(1) Most of the uncertainties associated with the variables in this equation, specifically those associated with Q, Dytwv, Dytwp , and Aw, are site-specific.

(2) It is calculated assuming a default ST value for background plus local sources, rather than an ST value for urban sources. If a specific site is located in an urban area, using the latter ST

value may be more appropriate. Specifically, the ST value for urban sources is about one order of magnitude greater than that for background plus local sources and would result in a

lower calculated Fv value. However, Fv would likely to be only a few percent lower.

Equation

For mercury modeling

Use 0.48Q for total mercury (to account for loss to the global cycle) and Fv = 0.85 in the mercury modeling equation.

Variable Description Units Value

LDEP

Total (wet and dry) particle phase

and vapor phase direct deposition

load to water body

g/yr

Q COPC-specific emission rate g/s Varies

This variable is COPC- and site-specific. See Chapters 2 and 3 for guidance on calculating this variable. 

Uncertainties associated with this variable are site-specific.
TABLE B-4-8

DEPOSITION TO WATER BODY

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 3)

Variable Description Units Value

B-202

Fv

Fraction of COPC air concentration

in vapor phase

unitless 0 to 1

This variable is COPC-specific. We discuss Fv

in detail in Appendix A-2, and offer COPC-specific values in the

HHRAP companion database. This range is based on values presented in Appendix A-2. Values are also presented

in U.S. EPA (1994b) and NC DEHNR (1997). 

Fv was calculated using an equation presented in Junge (1977) for all organic COPCs, including PCDDs and PCDFs. 

U.S. EPA (1994c) states that Fv = 0 for all metals (except mercury).

The following uncertainties are associated with this variable:

(1) It assumes a default ST value for background plus local sources, rather than an ST value for urban sources. If

a specific site is located in an urban area, using the latter ST value may be more appropriate. Specifically,

the ST

 value for urban sources is about one order of magnitude greater than that for background plus local

sources. It would result in a lower calculated Fv

 value; however, the Fv

 value is likely to be only a few

percent lower.

(2) According to Bidleman (1988), the equation used to calculate Fv assumes that the variable c (Junge

constant) is constant for all chemicals; however, the value of c depends on the chemical (sorbate) molecular

weight, the surface concentration for monolayer coverage, and the difference between the heat of desorption

from the particle surface and the heat of vaporization of the liquid-phase sorbate. To the extent that site- or

COPC-specific conditions may cause the value of c to vary, uncertainty is introduced if a constant value

of c is used to calculate Fv.

Dytwv Unitized yearly (water body or

watershed) average total (wet and

dry) deposition from vapor phase

s/m2-yr Varies

This variable is COPC- and site-specific, and is determined by air dispersion modeling (see Chapter 3). Uncertainties

associated with this variable are site-specific.

Dytwp Unitized yearly (water body or

watershed) average total (wet and

dry) deposition from vapor phase

s/m2

-yr Varies

This variable is COPC- and site-specific, and is determined by air dispersion modeling (see Chapter 3). Uncertainties

associated with this variable are site-specific.

Aw

Water body surface area m2 Varies

This variable is COPC- and site-specific, and is determined by air dispersion modeling (see Chapter 3). Uncertainties

associated with this variable are site-specific.
TABLE B-4-8

DEPOSITION TO WATER BODY

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 3)

B-203

REFERENCES AND DISCUSSION

Bidleman, T.F. 1988. “Atmospheric Processes.” Environmental Science and Technology. Volume 22. Number 4. Pages 361-367.

For discussion, see References and Discussion in Table B-1-1.

Junge, C.E. 1977. Fate of Pollutants in Air and Water Environments, Part I. Suffet, I.H., Ed. Wiley. New York. Pages 7-26.

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is a reference source for the equation in Table B-4-8. This document also recommends by using the equations in Bidleman (1988) to calculate Fv

 values for all organics other

than dioxins (PCDD/PCDFs). However, the document does not present a recommendation for dioxins. Finally, this document states that metals are generally entirely in the particulate phase

(Fv= 0) except for mercury, which is assumed to be entirely in the vapor phase. The document does not state whether Fv for mercury should be calculated by using the equations in Bidleman

(1988).

U.S. EPA. 1994. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document is a reference source for Equation B-4-8. This document also presents values for organic COPCs that range from 0.27 to 1. Fv

 values for organics other than PCDD/PCDFs

are calculated by using the equations presented in Bidleman (1988). The Fv value for PCDD/PCDFs is assumed to be 0.27, based on U.S. EPA (no date). Finally, this document presents Fv

values for inorganic COPCs equal to 0, based on the assumption that these COPCs are nonvolatile and assumed to be 100 percent in the particulate phase and 0 percent in the vapor phase.

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and

Development. EPA 452/R-97-005. December.
TABLE B-4-9

IMPERVIOUS RUNOFF LOAD TO WATER BODY

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 3)

B-204

Description

This equation calculates the average runoff load to the water body from impervious surfaces in the watershed from which runoff is conveyed directly to the water body.

Uncertainties associated with this equation include the following:

(1) Most of the uncertainties associated with the variables in this equation, specifically those associated with Q, Dytwv, Dytwp, and AI, are site-specific.

(2) The equation assumes a default ST value for background plus local sources, rather than an ST value for urban sources. If a specific site is located in an urban area, using the latter ST value

may be more appropriate. Specifically, the ST value for urban sources is about one order of magnitude greater than that for background plus local sources and would result in a lower

calculated Fv value; however, the Fv value is likely to be only a few percent lower.

Equation

For Mercury modeling

Use 0.48Q for total mercury (to account for loss to the global cycle) and Fv = 0.85 in the mercury modeling equation.

Variable Description Units Value

LRI

Runoff load from impervious

surfaces

g/yr

Q COPC-specific emission rate g/s Varies

This variable is COPC- and site-specific (see Chapters 2 and 3). Uncertainties associated with this variable are site-specific.
TABLE B-4-9

IMPERVIOUS RUNOFF LOAD TO WATER BODY

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 3)

Variable Description Units Value

B-205

Fv

Fraction of COPC air

concentration in vapor phase

unitless 0 to 1

This variable is COPC-specific. We discuss Fv

in detail in Appendix A-2, and offer COPC-specific values in the HHRAP

companion database. This range is based on values presented in Appendix A-2. Values are also presented in U.S. EPA (1994b)

and NC DEHNR (1997). 

Fv was calculated using an equation presented in Junge (1977) for all organic COPCs, including PCDDs and PCDFs. U.S. EPA

(1994c) states that Fv = 0 for all metals (except mercury).

The following uncertainties are associated with this variable:

(1) Calculations assume a default ST value for background plus local sources, rather than an ST value for urban sources. If a

specific site is located in an urban area, using the latter ST value may be more appropriate. Specifically, the ST value for

urban sources is about one order of magnitude greater than that for background plus local sources, and it would result in

a lower calculated Fv

 value; however, the Fv

 value is likely to be only a few percent lower.

(2) According to Bidleman (1988), the equation used to calculate Fv assumes that the variable c (Junge constant) is constant

for all chemicals; however, the value of c depends on the chemical (sorbate) molecular weight, the surface concentration

for monolayer coverage, and the difference between the heat of desorption from the particle surface and the heat of

vaporization of the liquid-phase sorbate. To the extent that site- or COPC-specific conditions may cause the value of c

to vary, uncertainty is introduced if a constant value of c is used to calculate Fv.

Dytwv Unitized yearly (water body or

watershed) average total (wet and

dry) deposition from vapor phase

s/m2-yr Varies

This variable is COPC- and site-specific, and is determined by air dispersion modeling (see Chapter 3). Uncertainties associated

with this variable are site-specific.

Dytwp Unitized yearly (water body or

watershed) average total (wet and

dry) deposition from particle

phase

s/m2-yr Varies

This variable is COPC- and site-specific, and is determined by air dispersion modeling (see Chapter 3). Uncertainties associated

with this variable are site-specific.

AI

Impervious watershed area

receiving COPC deposition

m2 Varies

This variable is site-specific. Uncertainties associated with this variable are site-specific.
TABLE B-4-9

IMPERVIOUS RUNOFF LOAD TO WATER BODY

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 3)

B-206

REFERENCES AND DISCUSSION

Bidleman, T.F. 1988. “Atmospheric Processes.” Environmental Science and Technology. Volume 22. Number 4. Pages 361-367.

For discussion see References and Discussion in Table B-1-1.

Junge, C.E. 1977. Fate of Pollutants in Air and Water Environments, Part I. Suffet, I.H., Ed. Wiley. New York. Pages 7-26.

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is a reference source for the equation in Table B-4-9. This document also recommends using the equations in Bidleman (1988) to calculate Fv values for all organics other

than dioxins (PCDD/PCDFs). However, the document does not present a recommendation for dioxins. Finally, this document states that generally metals are entirely in the particulate phase

(Fv= 0) except for mercury, which is assumed to be entirely in the vapor phase. The document does not state whether Fv for mercury should be calculated using the equations in Bidleman

(1988).

U.S. EPA. 1994. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

This document is a reference source for the equation in Table B-4-9. This document also presents Fv values for organic COPCs that range form 0.27 to 1. Fv values for organics other than

PCDD/PCDFs are calculated using the equations presented in Bidleman (1988). The Fv value for PCDD/PCDFs is assumed to be 0.27, based on Lorber (no date). Finally, this document

presents Fv values for inorganic COPCs equal to 0, based on the assumption that these COPCs are nonvolatile and 100 percent in the particle phase (and 0 percent in the vapor phase).

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and 

Development. EPA 452/R-97-005. December.
TABLE B-4-10

PERVIOUS RUNOFF LOAD TO WATER BODY

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 4)

B-207

Description

This equation calculates the average runoff load to the water body from pervious soil surfaces in the watershed. Uncertainty associated with this equation includes the following:

To the extent that site-specific or local average annual surface runoff information is not available, default or estimated values may not accurately represent site-specific or local conditions. 

As a result, LR may be under- or overestimated to an unknown degree.

Equation

Variable Description Units Value

LR

Runoff load from pervious surfaces g COPC/yr

RO Average annual surface runoff from

pervious areas

cm water/yr Varies

This variable is site-specific. According to U.S. EPA (1998), U.S. EPA (1994), and NC DEHNR (1997), average

annual surface runoff, RO, can be estimated by using the Water Atlas of the United States (Geraghty et al. 1973). 

According to NC DEHNR (1997), more detailed, site-specific procedures for estimating the amount of surface runoff,

such as those based on the U.S. Soil Conservation Service CNE may also be used. U.S. EPA (1985) is cited as an

example of such a procedure.

The following uncertainty is associated with this variable:

To the extent that site-specific or local average annual surface runoff information is not available, default or

estimated values may not accurately represent site-specific or local conditions. As a result, RO may be

under- or overestimated to an unknown degree.

AL

Total watershed area receiving

COPC deposition

m2 Varies 

This variable is site-specific. See Chapter 4 for procedures to calculate this variable. Uncertainties associated with this

variable are site-specific.

AI

Impervious watershed area

receiving COPC deposition

m2 Varies

This variable is site-specific. See Chapter 4 for procedures to calculate this variable. Uncertainties associated with this

variable are site-specific.
TABLE B-4-10

PERVIOUS RUNOFF LOAD TO WATER BODY

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 4)

Variable Description Units Value

B-208

Cs Average soil concentration over

exposure duration

mg COPC/kg soil Varies 

This variable is COPC- and site-specific, and is calculated using the equation presented in Table B-4-1. Uncertainties

associated with this variable are site-specific.

BD Soil bulk density g soil/cm3

 soil 1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default

BD value of 1.5 g soil/cm3

 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA

(1998) stated that a value of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended range of soil bulk density values may not accurately represent site-specific soil

conditions.

2sw

Soil volumetric water content mL water/cm3

 soil 0.2

This variable depends on the available water and on soil structure; you can estimate 2sw as the midpoint between a

soil’s field capacity and wilting point, if a representative watershed soil can be identified. However, we recommend 

using a default value of 0.2 mL/cm3; this value is the midpoint of the range 0.1 (very sandy soils) to 0.3 (heavy

loam/clay soils) recommended by U.S. EPA (1998) (no source or reference is provided for this range) and is consistent

with other U.S. EPA (1994b) and NC DEHNR (1997) guidance.

The following uncertainty is associated with this variable:

The default 2sw value may not accurately reflect site-specific or local conditions; therefore, KR may be underor overestimated to a limited extent.

Kds

Soil-water partition coefficient cm3

 water/g soil Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in

Appendix A-2.

0.01 Units conversion factor cm2

 water-kg soil-g

COPC/m2-gsoilmgCOPC
TABLE B-4-10

PERVIOUS RUNOFF LOAD TO WATER BODY

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 4)

B-209

REFERENCES AND DISCUSSION

Carsel, R.F., R.S. Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology.

Volume 2: pages 11-24.

Geraghty, J.J., D.W Miller, F. Van der Leeden, and F.L. Troise. 1973. Water Atlas of the United States. Water Information Center. Port Washington, New York.

This document is cited by U.S. EPA (1993), U.S. EPA (1994c), and NC DEHNR (1997) as a reference for calculating average annual runoff, RO. Specifically, this reference provides maps

with isolines of annual average surface water runoff, which is defined as all flow contributions to surface water bodies, including direct runoff, shallow interflow, and ground water recharge. 

Because these volumes are total contributions and not only surface runoff, U.S. EPA (1994c) notes that they need to be reduced to estimate surface runoff. U.S. EPA (1994c) recommends a

reduction of 50 percent.

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Pres, Inc. New York.

This document is cited by U.S. EPA (1990) for the statement that soil bulk density, BD, is affected by soil structure, such as looseness or compaction of the soil, depending on the water and

clay content of the soil.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the source documented that cites the use of the equation in Table B-4-10; however, the document is not the original source of this equation. This document also

recommends the following:

C Estimation of average annual runoff, RO (cm/yr), by using the Water Atlas of the United States (Geraghty et al. 1973) or site-specific procedures, such as the U.S. Soil

Conservation Service CNE; U.S. EPA (1985) is cited as an example of the use of the CNE

C A default value of 0.2 (mL water/cm3

 soil) for soil volumetric content (2sw)

U.S. EPA. 1985. Water Quality Assessment: A Screening Procedures for Toxic and Conventional Pollutants in Surface and Ground Water - Part I (Revised - 1985). Environmental Research

Laboratory. Athens, Georgia. EPA/600/6-85/002a. September.

U.S. EPA. 1994. Revised Draft Guidance of Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document recommends (1) a default soil bulk density value of 1.5 (g soil/cm3 soil), based on a mean value for loam soil from Carsel et al. (1988), and (2) a default soil volumetric water

content, 2sw, value of 0.2 (mL water/cm3

 soil), based on U.S. EPA (1993).

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and

Development. EPA 452/R-97-005. December.
TABLE B-4-10

PERVIOUS RUNOFF LOAD TO WATER BODY

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 4 of 4)

B-210

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document cites Hillel (1980) for the statement that only soil bulk density, BD, is affected by the soil structure, such as loosened or compaction of the soil, depending on the water and

clay content of the soil.

This document is also a source of the following:

C A range of soil volumetric water content (2sw) values of 0.1 ml water/cm3

 soil (very sandy soils) to 0.3 ml water/cm3 soil (heavy loam/clay soils). However, no source or reference is

provided for this range.

C A range of values for soil mixing zone depth, Zs

, for tilled and untilled soil
TABLE B-4-11

EROSION LOAD TO WATER BODY

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 4)

B-211

Description

This equation calculates the load to the water body from soil erosion. Uncertainties associated with this equation include the following:

(1) Uncertainties associated with the variables Xe, AS, AI, and Cs, are site-specific and may be significant in some cases. 

(2) Uncertainties associated with the remaining variables aren’t expected to be significant, primarily because of the narrow ranges of probable values for these variables or the use of

well-established estimation procedures (Kds).

Equation

For mercury modeling, the erosion load to water body is calculated for divalent mercury (Hg2+) and methyl mercury (MHg) using their respective Cs values and Kds

 values.

Variable Description Units Value

LE

Soil erosion load g COPC/yr

Xe

Unit soil loss kg soil/m2-yr Varies

This variable is site-specific, and calculated using the equation presented in Table B-4-13. 

The following uncertainty is associated with this variable:

All of the equation variables are site-specific. Using default values rather than site-specific values, for any or all

or these variables, will result in estimates of unit soil loss, Xe

, that are under- or overestimated to some degree. 

The range of Xe calculated on the basis of default values spans slightly more than one order of magnitude (0.6 to

36.3 kg/m2-yr).

AL

Total watershed area receiving

deposition

m2 Varies

This variable is site-specific (see Chapter 4). Uncertainties associated with this variable are site-specific.

AI

Area of impervious watershed

receiving deposition

m2 Varies

This variable is site-specific (see Chapter 4). Uncertainties associated with this variable are site-specific.
TABLE B-4-11

EROSION LOAD TO WATER BODY

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 4)

Variable Description Units Value

B-212

SD Watershed sediment delivery ratio unitless Varies

This value is site-specific and calculated using equation in Table B-4-14.

The following uncertainty is associated with this variable:

The recommended default values for the variables a and b (empirical intercept coefficient and empirical slope

coefficient, respectively) are average values, based on a review of sediment yields from various watersheds. These

default values may not accurately represent site-specific watershed conditions and, therefore, may contribute to

under- or over estimating LE.

ER Soil enrichment ratio unitless 1 or 3

COPC enrichment occurs because (1) lighter soil particles erode more quickly than heavier soil particles and (2)

concentrations of organic COPCs—a function of organic carbon content of sorbing media—are expected to be higher in

eroded material than in situ soil (U.S. EPA 1998). In the absence of site-specific data, we recommend a default value of 3 for

organic COPCs and 1 for inorganic COPCs. This is consistent with other Agency guidance (U.S. EPA 1998), which

recommends a range of 1 to 5 and a value of 3 as a “reasonable first estimate”. This range has been used for organic matter,

phosphorus, and other soil-bound COPCs (U.S. EPA 1998); however, no sources or references were provided for this range. 

ER is generally higher in sandy soils than in silty or loamy soils (U.S. EPA 1998).

The following uncertainty is associated with this variable:

The default ER value may not accurately reflect site-specific conditions; therefore, LE may be over- or

underestimated to an unknown, but relatively small, extent. Using county-specific ER values will reduce the extent

of any uncertainties.

Cs Average soil concentration over

exposure duration

mg COPC/kg

soil

Varies

This variable is COPC- and site-specific, and calculated using the equation in Table B-4-1. Uncertainties are site-specific.

Kds

Soil-water partition coefficient mL water/g

soil

 (or cm3

water/g soil)

Varies

This variable is COPC-specific. We discuss this variable in detail and offer COPC-specific values in Appendix A-2.

The following uncertainty is associated with this variable:

Uncertainties associated with this parameter will be limited if Kds values are calculated as described in

Appendix A-2.
TABLE B-4-11

EROSION LOAD TO WATER BODY

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 4)

Variable Description Units Value

B-213

BD Soil bulk density g soil/cm3

 soil 1.5

This variable 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), as summarized in U.S. EPA (1998). U.S. EPA (1994c) recommended a default BD value of

1.5 g soil/cm3 soil, based on a mean value for loam soil obtained from Carsel et al. (1988). U.S. EPA (1998) stated that a

value of 1.5 would suffice for most uses, if site-specific information was unavailable. 

The following uncertainty is associated with this variable:

The recommended BD value may not accurately represent site-specific soil conditions; and may under- or

overestimate site-specific soil conditions to an unknown degree.

2sw

Soil volumetric water content mL water/cm3

soil

0.2

This variable is site-specific, and depends on the available water and on soil structure; you can estimate 2sw as the midpoint

between a soil’s field capacity and wilting point, if you can identify a representative watershed soil. However, we

recommend using 0.2 ml/cm3 as a default value. This value is the midpoint of the range 0.1 (very sandy soils) to 0.3 (heavy

loam/clay soils) recommended by U.S. EPA (1998) (no source or reference is provided for this range) and is consistent with

U.S. EPA (1994b).

The following uncertainty is associated with this variable:

The default 2sw value may not accurately reflect site-specific or local conditions; therefore, LE

 may be under- or

overestimated to a small extent, based on the limited range of values.

0.001 Units conversion factor mgCOPC/

g COPC
TABLE B-4-11

EROSION LOAD TO WATER BODY

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 4 of 4)

B-214

REFERENCES AND DISCUSSION

Carsel, R.F., R.S. Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988. “Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.” Journal of Contaminant Hydrology. 

Volume 2. Pages 11-24.

This document is the source for a mean soil bulk density, BD, of 1.5 (g soil/cm3 soil) for loam soil.

Hillel, D. 1980. Fundamentals of Soil Physics. Academic Press, Inc. New York.

This document is cited by U.S. EPA (1998) for the statement that soil bulk density, BD, is affected by the soil structure, such as looseness or compaction of the soil, depending on the water

and clay content of the soil.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is cited as one of the sources for the range of BD values, and the default value for the volumetric soil water content. 

U.S. EPA. 1994. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

This document recommends (1) a default soil bulk density value of 1.5 (g soil/cm3 soil), based on a mean value for loam soil from Carsel et al. (1988), and (2) a default soil volumetric water

content, 2sw, value of 0.2 (mL water/cm3 soil).

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and

Development. EPA 452/R-97-005. December.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document is the source of a range of COPC enrichment ratio, ER, values. The recommended range, 1 to 5, was used for organic matter, phosphorous, and other soul-bound COPCs. 

This document recommends a value of 3 as a “reasonable first estimate,” and states that COPC enrichment occurs because lighter soil particles erode more quickly than heavier soil particles. 

Lighter soil particles have higher ratios of surface area to volume and are higher in organic matter content. Therefore, concentration of organic COPCs, which is a function of the organic

carbon content of sorbing media, is expected to be higher in eroded material than in in situ soil.

This document is also a source of the following:

C A range of soil volumetric water content (2sw) values of 0.1 ml water/cm3 soil (very sandy soils) to 0.3 ml water/cm3 soil (heavy loam/clay soils). However, no source or reference is

provided for this range.

C A range of values for soil mixing zone depth, Zs

, for tilled and untilled soil
TABLE B-4-12

DIFFUSION LOAD TO WATER BODY

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 4)

B-215

Description

This equation calculates the load to the water body due to vapor phase diffusion. Uncertainties associated with this equation include the following:

(1) Most of the uncertainties associated with the variables Kv, Q, Cywv, and Aw, are site-specific.

(2) This equation assumes a default ST value for background plus local sources, rather than an ST value for urban sources. If a specific site is located in an urban area, using the latter ST value

may be more appropriate. Specifically, the ST value for urban sources is about one order of magnitude greater than that for background plus local sources and would result in a lower

calculated Fv value; however, the Fv value is likely to be only a few percent lower.

Equation

For Mercury modeling

Use 0.48Q for total mercury (to account for loss to the global cycle) and Fv = 0.85 in the mercury modeling equation.

Variable Description Units Value

Ldif

Vapor phase diffusion load to water

body 

g COPC/yr

Kv

Overall transfer rate coefficient m/yr Varies

This variable is COPC- and site-specific, and calculated using the equation in Table B-4-19. Uncertainties associated with

this variable are site-specific.
TABLE B-4-12

DIFFUSION LOAD TO WATER BODY

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 4)

Variable Description Units Value

B-216

Q COPC-specific emission rate g COPC/s Varies

This variable is COPC- and site-specific. See Chapters 2 and 3 for guidance on calculating this variable. Uncertainties

associated with this variable are site-specific.

Fv

Fraction of COPC air concentration

in vapor phase

unitless 0 to 1

This variable is COPC-specific. We discuss Fv

in detail in Appendix A-2, and offer COPC-specific values in the HHRAP

companion database. Values are also presented in U.S. EPA (1994), RTI (1992), and NC DEHNR (1997). Values are based

on the work of Bidleman (1988), as cited in U.S. EPA (1994) and NC DEHNR (1997). U.S. EPA (1994) presents values for

organic COPCs that range from 0.27 to 1. All values presented by U.S. EPA (1994) for inorganic COPCs are given as 0.

Uncertainties associated with this variable include the following:

(1) This equation assumes a default ST value for background plus local sources, rather than an ST value for urban

sources. If a specific site is located in an urban area, using the latter ST value may be more appropriate. 

Specifically, the ST

 value for urban sources is about one order of magnitude greater than that for background plus

local sources and would result in a lower calculated Fv

 value; however, the Fv

 value is likely to be only a few

percent lower.

(2) According to Bidleman (1988), the equation used to calculate Fv

 assumes that the variable c is

constant for all chemicals; however, the value of c depends on the chemical (sorbate) molecular weight, the surface

concentration for monolayer coverage, and the difference between the heat of desorption from the particle surface

and the heat of vaporization of the liquid phase sorbate. To the extent that site- or COPC-specific conditions may

cause the value of c to vary, uncertainty is introduced if a constant value of c issued to calculate Fv

.

Cywv Unitized yearly average air

concentration from vapor phase

:g-s/g-m3 Varies

This variable is COPC- and site-specific, and is determined by air dispersion modeling (see Chapter 3). Uncertainties

associated with this variable are site-specific.

Aw

Water body surface area m2 Varies

This variable is site-specific (see Chapter 4). Uncertainties associated with this variable are site-specific. However, we

expect that the uncertainty associated with this variable will be limited, because maps, aerial photographs, and other

resources from which water body surface areas can be measured, are readily available.

10-6 Units conversion factor g/μg
TABLE B-4-12

DIFFUSION LOAD TO WATER BODY

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 4)

Variable Description Units Value

B-217

H Henry’s Law constant atm-m3

/mol Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in the

HHRAP companion database. 

The following uncertainty is associated with this variable:

Values for this variable, estimated by using the parameters and algorithms in Appendix A-2, may under- or

overestimate the actual COPC-specific values. As a result, LDif may be under- or overestimated to a limited degree.

R Universal gas constant atm-m3

/mol-K 8.205 x 10-5

Twk

Water body temperature K 298

This variable is site-specific. We recommend using this default value in the absence of site-specific information, consistent

with U.S. EPA (1998) and U.S. EPA (1994).

The following uncertainty is associated with this variable:

To the extent that the default water body temperature value does not accurately represent site-specific or local

conditions, Ldif will be under- or overestimated.

REFERENCES AND DISCUSSION

Bidleman, T.F. 1988. “Atmospheric Processes.” Environmental Science and Technology. Volume 22. Number 4. Pages 361-367.

For discussion, see References and Discussion in Table B-1-1.

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is a reference source for the equation in Table B-4-12. This document also recommends using the equations in Bidleman (1988) to calculate Fv

 values for all organics other

than dioxins (PCDD/PCDFs). However, the document does not present a recommendation for dioxins. This document also states that metals are generally entirely in the particulate phase

(Fv = 0), except for mercury, which is assumed to be entirely in the vapor phase. The document does not state whether Fv for mercury should be calculated by using the equations in

Bidleman (1988); We assume that this is the case.

U.S. EPA 1994. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

This document is cited as the reference source for Twk, water body temperature (298 K); however, no references or sources are identified for this value. This document is a reference source

for the equation in Table B-4-8. This document also presents values for organic COPCs that range from 0.27 to 1. Fv values for organics other than PCDD/PCDFs are calculated by using
TABLE B-4-12

DIFFUSION LOAD TO WATER BODY

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 4 of 4)

B-218

the equations presented in Bidleman (1988). The Fv

 value for PCDD/PCDFs is assumed to be 0.27, based on Lorber (no date). Finally, this document presents Fv values for inorganic

COPCs equal to 0, based on the assumption that these COPCs are nonvolatile and 100 percent in the particulate phase and 0 percent in the vapor phase.

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and

Development. EPA 452/R-97-005. December.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document recommends a range (10°C to 20°C;

 283 K to 303 K) for water body temperature, Twk. No source was identified for this range. 
TABLE B-4-13

UNIVERSAL SOIL LOSS EQUATION (USLE)

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 4)

B-219

Description

This equation calculates the soil loss rate from the watershed by using the Universal Soil Loss Equation (USLE); the result is used in the soil erosion load equation in Table B-4-11. Estimates of 

unit soil loss, Xe, should be determined specific to each watershed evaluated. Information on determining site- and watershed-specific values for variables used in calculating Xe is provided in U.S.

Department of Agriculture (U.S. Department of Agriculture 1997) and U.S. EPA guidance (U.S. EPA 1985). Uncertainties associated with this equation include the following:

(1) All of the equation variables are site-specific. Use of default values will result in estimates of unit soil loss, Xe, that are under- or overestimated to some unknown degree. 

Equation

Variable Description Units Value

Xe

Unit soil loss kg/m2-yr

RF USLE rainfall (or erosivity) factor yr-1 50 to 300

This value is site-specific and is derived on a storm-by-storm basis. As cited in U.S. EPA (1998), average annual values

were compiled regionally by Wischmeier and Smith (1978); the recommended range reflects these compiled values.

The following uncertainty is associated with this variable:

The range of average annual rainfall factors (50 to 300) from Wischmeier and Smith (1978) may not accurately

reflect site-specific conditions. Therefore, unit soil loss, Xe

, may be under- or overestimated.

K USLE erodibility factor ton/acre Varies

This value is site-specific. We recommend using current guidance (U.S. Department of Agriculture 1997; U.S. EPA 1985) in

determining watershed-specific values for this variable based on site-specific information. A default value of 0.39, as cited in

NC DEHNR (1997) and U.S. EPA (1994), was based on a soil organic matter content of 1 percent (Droppo et al. 1989), and

chosen to be representative of a whole watershed, not just an agricultural field.

The following uncertainty is associated with this variable:

Using a site-specific USLE soil erodibility factor, K, may cause unit soil loss, Xe, to be under- or overestimated to

some unknown degree.
TABLE B-4-13

UNIVERSAL SOIL LOSS EQUATION (USLE)

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 4)

Variable Description Units Value

B-220

LS USLE length-slope factor unitless Varies

This value is site-specific. We recommend using current guidance (U.S. Department of Agriculture 1997; U.S. EPA 1985) in

determining watershed-specific values for this variable based on site-specific information. A value of 1.5 as cited in NC

DEHNR (1997) and U.S. EPA (1994), reflects a variety of possible distance and slope conditions (U.S. EPA 1988), and was

chosen to be representative of a whole watershed, not just an agricultural field. 

The following uncertainty is associated with this variable:

A site-specific USLE length-slope factor, LS, may not accurately represent site-specific conditions. Therefore, unit

soil loss, Xe, may be under- or overestimated to some unknown degree.

C USLE cover management factor unitless Varies

This value is site-specific. We recommend using current guidance (U.S. Department of Agriculture 1997; U.S. EPA 1985) in

determining watershed-specific values for this variable based on site-specific information. The range of values up to 0.1

reflect dense vegetative cover, such as pasture grass; values from 0.1 to 0.7 reflect agricultural row crops; and a value of 1.0

reflects bare soil (U.S. EPA 1998). U.S. EPA (1993) recommended a value of 0.1 for both grass and agricultural crops. This

range of values was also cited in NC DEHNR (1997). However, U.S. EPA (1994) and NC DEHNR (1997) both

recommended a default value of 0.1 to be representative of a whole watershed, not just an agricultural field.

The following uncertainty is associated with this variable:

The USLE cover management factor, C, value determined may not accurately represent site-specific conditions. 

Therefore, the value for C may result in the under- or overestimation of unit soil loss, Xe

.

PF USLE supporting practice factor unitless Varies

This value is site-specific. We recommend using current guidance (U.S. Department of Agriculture 1997; U.S. EPA 1985) in

determining watershed-specific values for this variable based on site-specific information. A default value of 1.0, which

conservatively represents the absence of any erosion or runoff control measures, was cited in NC DEHNR (1997) and U.S.

EPA (1998; 1994).

The following uncertainty is associated with this variable:

Using a site-specific USLE supporting practice factor, PF, may result in under- or overestimating Xe depending on

the actual extent that there are erosion or runoff control measures in the vicinity of the watershed evaluated.

907.18 Units conversion factor kg/ton

4047 Units conversion factor m2

/acre
TABLE B-4-13

UNIVERSAL SOIL LOSS EQUATION (USLE)

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 4)

B-221

REFERENCES AND DISCUSSION

Droppo, J.G. Jr., D.L. Strenge, J.W. Buck, B.L. Hoopes, R.D. Brockhaus, M.B. Walter, and G. Whelan. 1989. Multimedia Environmental Pollutant Assessment System (MEPAS) Application

Guidance: Volume 2-Guidelines for Evaluating MEPAS Input Parameters. Pacific Northwest Laboratory. Richland, Washington. December.

This document is cited by U.S. EPA 1994 and NC DEHNR 1997 as the reference source for a USLE erodibility factor value of 0.36, based on a soil organic matter content of 1 percent. 

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document recommended the following:

C A USLE erodibility factor, K, value of 0.36 ton/acre

C A USLE length-slope factor, LS, value of 1.5 (unitless)

C A range of USLE cover management factor, C, values of 0.1 to 1.0; it also recommended a value of 0.1 to be representative of a whole watershed, not just an agricultural field.

C A USLE supporting practice factor, PF, value of 1.0

U.S. Department of Agriculture. 1997. Predicting Soil Erosion by Water: A Guide to Conservation Planning With the Revised Universal Soil Loss Equation (RUSLE). Agricultural Research Service,

Agriculture Handbook Number 703. January.

U.S. EPA. 1985. Water Quality Assessment: A Screening Procedure for Toxic and Conventional Pollutants in Surface and Ground Water—Part I (Revised). ORD. Athens, Georgia. 

EPA/600/6-85/002a.

U.S. EPA. 1988. Superfund Exposure Assessment Manual. Office of Solid Waste. Washington, D.C. April.

This document is cited by U.S. EPA 1994 and NC DEHNR 1997 as the reference source for the USLE length-slope factor, LS, value of 1.5. This value reflects a variety of possible distance

and slope conditions and was chosen to be representative of a whole watershed, not just an agricultural field.

U.S. EPA. 1993. Addendum: Methodology for Assessing Health Risks Associated with Indirect Exposure to Combustor Emissions. Working Group Recommendations. Office of Solid Waste and

Office of Research and Development. Washington, D.C. September.

This document recommends the following:

C A USLE cover management factor, C, of 0.1 for both grass and agricultural crops

C A USLE supporting practice factor, PF, of 1.0, based on the assumed absence of any erosion or runoff control measures
TABLE B-4-13

UNIVERSAL SOIL LOSS EQUATION (USLE)

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 4 of 4)

B-222

U.S. EPA. 1994. Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Office of Emergency and Remedial Response. Office of Solid Waste. 

December.

This document recommends the following:

C A USLE erodibility factor, K, value of 0.36 ton/acre

C A USLE length-slope factor, LS, value of 1.5 (unitless)

C A range of USLE cover management factor, C, values of 0.1 to 1.0; it recommends a default value of 0.1 to be representative of a whole watershed, not just an agricultural field.

C A USLE supporting practice factor, PF, value of 1.0

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and 

Development. EPA 452/R-97-005. December.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document cites Wischmeier and Smith (1978) as the source of average annual USLE rainfall factors, RF, and states that annual values range from less than 50 for the arid western

United States to greater than 300 for the southeast.

This document discusses the USLE cover management factor. This factor, C, primarily reflects how erosion is influenced by vegetative cover and cropping practices, such as planting across

slope rather than up and down slope. This document discusses a range of C values for 0.1 to 1.0; values greater than 0.1 but less than 0.2 are appropriate for agricultural row crops, and a

value of 1.0 is appropriate for sites mostly devoid of vegetation.

Wischmeier, W.H., and D.D. Smith. 1978. Predicting Rainfall Erosion Losses—A Guide to Conservation Planning. Agricultural Handbook No. 537. U.S. Department of Agriculture Washington,

D.C.

This document is cited by U.S. EPA (1998) as the source of average annual USLE rainfall factors, RF, compiled regionally. According to U.S. EPA (1998), annual values range from less

than 50 for the arid western United States to greater than 300 for the southeast. 
TABLE B-4-14

SEDIMENT DELIVERY RATIO

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 3)

B-223

Description

This equation calculates the sediment delivery ratio for the watershed; the result is used in the soil erosion load equation in Table B-4-11.

Uncertainties associated with this equation include the following:

(1) The recommended default empirical intercept coefficient (a) values are average values based on various studies of sediment yields from various watersheds. Therefore, these default

values may not accurately represent site-specific watershed conditions. As a result, using these default values may under- or overestimate the watershed sediment delivery ratio, SD.

(2) The recommended default empirical slope coefficient (b) value is based on a review of sediment yields from various watersheds. This single default value may not accurately represent

site-specific watershed conditions. As a result, using this default value may under- or overestimate the watershed sediment delivery ratio, SD.

Equation

Variable Description Units Value

SD Watershed sediment delivery ratio unitless

a Empirical intercept coefficient unitless 0.6 to 2.1

This variable is site-specific and is determined on the basis of the watershed area (Vanoni 1975), as cited in U.S. EPA (1998):

Watershed “a” Coefficient

Area (sq. miles) (unitless)

#0.1 2.1

1 (>0.1 but #1.0) 1.9 

10 (>1.0 but #10) 1.4 

100 (>10 but #100) 1.2

1,000 (>100) 0.6 

Note: 1 sq. mile = 2.59 x 106 m2

Using these values is consistent with U.S. EPA (1994a), U.S. EPA (1994b), and NC DEHNR (1997).

The following uncertainty is associated with this variable:

The recommended default empirical intercept coefficient, a, values are average values based on various studies of

sediment yields from various watersheds. Therefore, these default values may not accurately represent site-specific

watershed conditions. As a result, using these default values may under- or overestimate the watershed sediment

delivery ratio, SD.
TABLE B-4-14

SEDIMENT DELIVERY RATIO

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 3)

Variable Description Units Value

B-224

AL

Total watershed area receiving

deposition

m2 Varies

This variable is site-specific (see Chapter 4). Uncertainties associated with this variable are site-specific.

b Empirical slope coefficient unitless 0.125

As cited in U.S. EPA (1998), this variable is an empirical constant based on the research of Vanoni (1975), which concludes

that sediment delivery ratios vary approximately with negative one-eighth (G1/8) power of the drainage area. The use of this

value is consistent with U.S. EPA (1994a), U.S. EPA (1994b), and NC DEHNR (1997).

The following uncertainty is associated with this variable:

The recommended default empirical slope coefficient, b, value is based on a review of sediment yields from various

watersheds. This single default value may not accurately represent site-specific watershed conditions. As a result,

use of this default value may under- or overestimate the watershed sediment delivery ratio, SD.

REFERENCES AND DISCUSSION

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is cited as one of the reference source documents for the empirical intercept coefficient, a, and empirical slope coefficient, b, values. This document cites U.S. EPA (1993) as

the source of its information.

U.S. EPA. 1994a. Draft Guidance for Performing Screening Level Risk Analysis at Combustor Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for RCRA

Hazardous Waste Combustion Facilities. April.

This document is cited as one of the reference source documents for the empirical intercept coefficient, a, and empirical slope coefficient, b, values. This document does not identify Vanoni

(1975) as the source of its information.

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

This document is cited as one of the reference source documents for the empirical intercept coefficient, a, and the empirical slope coefficient, b, values. This document cites U.S. EPA

(1993) as the source of its information.
TABLE B-4-14

SEDIMENT DELIVERY RATIO

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 3)

B-225

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document is cited as one of the reference source documents for the empirical intercept coefficient, a, and empirical slope coefficient, b, values. This document cites Vanoni (1975) as its

source of information.

Vanoni, V.A. 1975. Sedimentation Engineering. American Society of Civil Engineers. New York, New York. Pages 460-463. 

This document is cited by U.S. EPA (1998) as the source of the equation in Table B-4-14 and the empirical intercept coefficient, a, and empirical slope coefficient, b, values. Based on

various studies of sediment yields from watersheds, this document concludes that the sediment delivery ratios vary approximately with negative one-eighth (G1/8) power of the drainage

ratio. U.S. EPA has not completed a review of this document.
TABLE B-4-15

TOTAL WATER BODY CONCENTRATION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 4)

B-226

Description

This equation calculates the total water body concentration, including the water column and the bed sediment. 

Uncertainties associated with this equation include the following:

(1) The default variable values recommended for use in the equation in Table B-4-15 may not accurately represent site-specific water body conditions. The degree of uncertainty associated

with the variables Vfx, Aw, dwc, and dbs is expected to be limited either because the probable ranges for these variables are narrow or information allowing accurate estimates is generally

available.

(2) Uncertainty associated with fwc is largely the result of uncertainty associated with default organic carbon (OC) content values and may be significant in specific instances. Uncertainties

associated with the total core load into water body (LT) and overall total water body core dissipation rate constant (kwt) may also be significant in some instances because of the summation

of many variable-specific uncertainties.

Equation

Variable Description Units Value

Cwtot

Total water body COPC

concentration, including water

column and bed sediment 

g COPC/m3 

water body

(equivalent

to mg

COPC/L

water body)

LT

Total COPC load to the water body,

including deposition, runoff, and

erosion

g/yr Varies

This variable is COPC- and site-specific, and calculated using the equation in Table B-4-7. Uncertainties associated with LDEP,

LDif, LRI, LR, and LE, as presented in the equation in Table B-4-7, are also associated with LT. 
TABLE B-4-15

TOTAL WATER BODY CONCENTRATION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 4)

Variable Description Units Value

B-227

Vfx

Average volumetric flow rate

through water body

m3

/yr Varies

This variable is site-specific. The following uncertainty is associated with this variable:

Default average volumetric flow rate (Vfx

) information may not accurately represent site-specific conditions,

especially for those water bodies for which flow rate information is not readily available. Therefore, using default Vfx

values may contribute to under- or overestimating total water body COPC concentration, Cwtot.

fwc

Fraction of total water body COPC

concentration in the water column

unitless 0 to 1

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-16.

The following uncertainty is associated with this variable:

The default values for the variables in the equation in Table B-4-16 may not accurately represent site- and water

body - specific conditions. However, the range of several variables—including dbs, CBS, and 2bs—is relatively

narrow. Other variables, such as dwc and dz

, can be reasonably estimated on the basis of generally available

information. The largest degree of uncertainty may be introduced by the default medium-specific organic carbon

(OC) content values. Because OC content values may vary widely in different locations in the same medium,

using default values may result in insignificant uncertainty in specific cases.

kwt

Overall total water body dissipation

rate constant

yr-1 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-17.

The following uncertainty is associated with this variable:

All of the variables in the equation in Table B-4-17 are site-specific; therefore, using default values for any or all of

these variables will contribute to under- or overestimating Cwtot. The degree of uncertainty associated with the

variable Kb is expected to be under one order of magnitude and is associated largely with the estimation of the unit

soil loss, Xe, values for the variables fwc, Kv, and fbs are dependent on medium-specific estimates of OC content. 

Because OC content can vary widely for different locations in the same medium, uncertainty associated with these

three may be significant in specific instances.

Aw

Water body surface area m2 Varies

This variable is site-specific. The value you select represents an average value for the entire year. See Chapter 4 for

procedures to determine this variable.

Uncertainties associated with this variable are site-specific. However, we expect that the uncertainty associated with this

variable will be limited because maps, aerial photographs, and other resources from which water body surface areas can be

measured, are readily available.
TABLE B-4-15

TOTAL WATER BODY CONCENTRATION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 4)

Variable Description Units Value

B-228

dwc

Depth of water column m Varies

This variable is site-specific. The value you select represents an average value for the entire year.

The following uncertainty is associated with this variable:

Depth of water column, dwc, values may not accurately reflect site-specific conditions, especially for those water

bodies for which depth of water column information is unavailable or outdated. Therefore, using dwc values may

contribute to under-or overestimating total water body COPC concentration, Cwtot.

dbs

Depth of upper benthic sediment

layer

m 0.03

This variable is site-specific. The value you select represents an average value for the entire year. We recommend a default

upper benthic sediment depth of 0.03 meter, which is consistent with U.S. EPA (1994) and NC DEHNR (1997) guidance. 

This value was cited by U.S. EPA (1993); however, no reference was presented. U.S. EPA (1998) suggests a range of values,

from 0.01 to 0.05 meters.

The following uncertainty is associated with this variable:

Default dbs values may not accurately represent site-specific water body conditions. However, based on the narrow

recommended range, we expect any uncertainty introduced to be limited.

REFERENCES AND DISCUSSION

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is also cited as one of the reference source documents for the default depth of upper benthic layer value. The default value is the midpoint of an acceptable range. This

document cites U.S. EPA (1993) as its source of information for the range of values for the depth of the upper benthic layer.

U.S. EPA. 1993. Addendum: Methodology for Assessing Health Risks Associated with Indirect Exposure to Combustor Emissions. Working Group Recommendations. Office of Solid Waste and

Office of Research and Development. Washington, D.C. September 24.

This document is cited by NC DEHNR (1997) and U.S. EPA (1994) as the source of the range and default value for the depth of the upper benthic layer (dbs).

U.S. EPA. 1994. Draft Guidance for Performing Screening Level Risk Analysis at Combustor Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for RCRA

Hazardous Waste Combustion Facilities. April 15.

This document is cited as one of the reference source documents for the default depth of the upper benthic layer value. The default value is the midpoint of an acceptable range. This

document cites U.S. EPA (1993) as its source of information for the range of values for the depth of the upper benthic layer.
TABLE B-4-15

TOTAL WATER BODY CONCENTRATION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 4 of 4)

B-229

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and

Development. EPA 452/R-97-005. December.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document is cited as the source of a range of values for the depth of the upper benthic layer (dbs).
TABLE B-4-16

FRACTION IN WATER COLUMN AND BENTHIC SEDIMENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 5) 

B-230

Description

This equation calculates the fraction of total water body concentration occurring in the water column and the bed sediments. 

Uncertainties associated with this equation include the following:

The default variable values may not accurately represent site-specific water body conditions. However, the range of several variables—including dbs, CBS, and 2bs—is relatively narrow. 

Other variables, such as dwc and dz, can be reasonably estimated on the basis of generally available information. The largest degree of uncertainty may be introduced by the default

medium-specific OC content values. OC content values can vary widely for different locations in the same medium. Therefore, the use of default values may introduce

significant uncertainty in some cases.

Equations

Variable Description Units Value

fwc

Fraction of total water body COPC

concentration in the water column

unitless

fbs

Fraction of total water body COPC

concentration in benthic sediment 

unitless
TABLE B-4-16

FRACTION IN WATER COLUMN AND BENTHIC SEDIMENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 5) 

Variable Description Units Value

B-231

Kdsw

Suspended sediments/surface water

partition coefficient

L water/kg

suspended

sediment

(or cm3

water/kg

suspended

sediment)

Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in the

HHRAP companion database. 

The following uncertainty is associated with this variable:

Kdsw values in the HHRAP companion database are based on default OC contents for surface water and soil. Kdsw

values based on default values may not accurately reflect site- and water body-specific conditions and may underor overestimate actual Kdsw values. You can reduce uncertainty associated with Kdsw by using site-specific and

medium-specific OC estimates to calculate Kdsw.

TSS Total suspended solids

concentration

mg/L 2 to 300

This variable is site-specific. We recommend using site- and waterbody specific measured values, representative of long-term

average annual values for the water body of concern (see Chapter 5). A value of 10 mg/L was cited by NC DEHNR (1997)

and U.S. EPA (1993) in the absence of site-specific measured data.

The following uncertainty is associated with this variable:

Limitation on measured data used for determining a water body specific total suspended solids (TSS) value may not

accurately reflect site- and water body-specific conditions long term. Therefore, the TSS value may contribute to 

under- or overestimating fwc.

1 × 10-

6

Units conversion factor kg/mg

dwc

Depth of water column m Varies

This variable is site-specific. The value you select represents an average value for the entire year.

The following uncertainty is associated with this variable:

Depth of water column, dwc, values may not accurately reflect site-specific conditions, especially for those water

bodies for which depth of water column information is unavailable or outdated. Therefore, using dwc values may

contribute to under- or overestimating total water body COPC concentration, Cwtot.
TABLE B-4-16

FRACTION IN WATER COLUMN AND BENTHIC SEDIMENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 5) 

Variable Description Units Value

B-232

dbs

Depth of upper benthic sediment

layer

m 0.03

This variable is site-specific. The value you select represents an average value for the entire year. We recommend a default

upper benthic sediment depth of 0.03 meter, which is consistent with U.S. EPA (1994) and NC DEHNR (1997) guidance. 

This value was cited by U.S. EPA (1993); however, no reference was presented. U.S. EPA (1998) suggests a range of values,

from 0.01 to 0.05 meter.

The following uncertainty is associated with this variable:

A default dbs value may not accurately represent site-specific water body conditions. However, we expect any

uncertainty introduced to be limited on the basis of the narrow recommended range.

dz

Total water body depth m Varies

This variable is site-specific. We recommend using the following equation to calculate total water body depth, consistent

with NC DEHNR (1997):

dz

 = dwc + dbs

The following uncertainty is associated with this variable:

Calculating this variable sums the concentrations associated with the two variables dwc and dbs. Because most of the

total water body depth (dz

) is made up of the depth of the water column (dwc), and we don’t expect the uncertainties

associated with dwc to be significant, we likewise don’t expect the total uncertainties associated with dz to be

significant.

CBS

Bed sediment concentration (or bed

sediment bulk density)

g/cm3

(equivalent to

kg/L)

1.0

This variable is site-specific. We recommend a default value of 1.0, consistent with U.S. EPA (1998), which states that this

value should be reasonable for most applications. The recommended default value is also consistent with other U.S. EPA

(1994), and NC DEHNR (1997) guidance.

The following uncertainty is associated with this variable:

The recommended default value may not accurately represent site- and water body-specific conditions. Therefore,

the variable fwc may be under- or overestimated. Based on th narrow recommended range, we expect the under- or

overestimation will be limited.
TABLE B-4-16

FRACTION IN WATER COLUMN AND BENTHIC SEDIMENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 4 of 5) 

Variable Description Units Value

B-233

2bs

Bed sediment porosity Lwater/Lsediment 0.6

This variable is site-specific. We recommend a default bed sediment porosity of 0.6 (by using a CBS value of 1 g/cm3

 and a

solid density (Ds

) value of 2.65 kg/L) calculated by using the following equation (U.S. EPA 1998):

2bs = 1 - CBS /Ds

This is consistent with other U.S. EPA (1994), and NC DEHNR (1997) guidance.

The following uncertainty is associated with this variable:

Calculation of this variable combines the uncertainties associated with the two variables, CBS and Ds, used in the

calculation. To the extent that the recommended default values of CBS and Ds don’t accurately represent site- and

water body-specific conditions, 2bs will be under- or overestimated.

Kdbs

Bed sediment/sediment pore water

partition coefficient

L water/kg

bottom

sediment 

(or

cm3water/g

bottom

sediment)

Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in the

HHRAP companion database. 

The following uncertainty is associated with this variable:

The Kdbs values in the HHRAP companion database are based on default OC contents for sediment and soil. Kdbs

values based on default OC values may not accurately represent site- and water body-specific conditions and may

under- or overestimate actual Kdbs values. Uncertainty associated with this variable will be reduced if site- and

water body-specific OC estimates are used to calculate Kdbs.

REFERENCES AND DISCUSSION

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is cited as one of the sources of 

the range of Kds values 

TSS values. This document cites U.S. EPA (1993b) as its source of information. 

the equation for calculating total water body depth. No source of this equation was identified. 

the default value for bed sediment porosity. This document cites U.S. EPA (1993b) as its source of information. 

the default value for depth of the upper benthic layer. The default value is the midpoint of an acceptable range. This document cites U.S. EPA (1993b) as its source of information

for the range of values for the depth of the upper benthic layer. 

the default bed sediment concentration. This document cites U.S. EPA (1993b) as its source of information.
TABLE B-4-16

FRACTION IN WATER COLUMN AND BENTHIC SEDIMENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 5 of 5) 

B-234

U.S. EPA. 1993. Addendum: Methodology for Assessing Health Risks Associated with Indirect Exposure to Combustor Emissions. Working Group Recommendations. Office of Solid Waste and

Office of Research and Development. Washington, D.C. September.

This document is cited by NC DEHNR (1997) as the source of the TSS value. This document is also cited by NC DEHNR (1997) and U.S. EPA (1994) as the source of the default bed

sediment porosity value and the equation used to calculate CBS, and the range for the depth of the upper benthic layer values. 

U.S. EPA. 1994. Draft Guidance for Performing Screening Level Risk Analysis at Combustor Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for RCRA

Hazardous Waste Combustion Facilities. April.

This document is cited as one of the reference source documents for 

the default value for bed sediment porosity. This document cites U.S. EPA (1993b) as its source of information. 

the default value for depth of the upper benthic layer. The default value is the midpoint of an acceptable range. This document cites U.S. EPA (1993b) as its source of information

for the range of values for the depth of the upper benthic layer. 

the default bed sediment concentration. This document cites U.S. EPA (1993b) as its source of information. 

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and

Development. EPA 452/R-97-005. December.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document is cited as one of the sources of 

the equation for calculating bed sediment porosity (2bs); no source of this equation was identified. 

the range of the bed sediment concentration (CBS); no original source of this range was identified. 
TABLE B-4-17

OVERALL TOTAL WATER BODY DISSIPATION RATE CONSTANT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 2)

B-235

Description

This equation calculates the overall COPC dissipation rate in surface water due to volatilization and benthic burial. 

Uncertainties associated with this equation include the following:

(1) All of the variables in the equation in Table B-4-17 are site-specific. Therefore, using default values for any or all of these variables will contribute to under- or overestimating kwt. We

expect the uncertainty associated with the variable kb to be one order of magnitude at most. This uncertainty is associated with the estimation of the unit soil loss, Xe (a component of kb). 

Values for the variables fwc, kv, and fbs are dependent on medium-specific estimates of medium-specific OC content. Because OC content can vary widely for different locations in the

same medium, uncertainty associated with these three variables may be significant in specific instances.

Equation

Variable Description Units Value

kwt

Overall total water body dissipation

rate constant

yr-1

fwc

Fraction of total water body COPC

concentration in the water column

unitless Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-16.

Uncertainties associated with this variable include the following: 

(1) The default variable values we recommend you use in the equation in Table B-4-16 may not accurately represent

site-specific water body conditions. However, the ranges of several component variables—including dbs, CBS, and

2sw—are moderate (factors of 5, 3, and 2, respectively). We therefore expect the degree of uncertainty associated

with these variables to be moderate. You can reasonably estimate other variables, such as dwc and dz, using

generally available information. We therefore expect the degree of uncertainty associated with these variables to

be relatively small.

(2) The largest degree of uncertainty may be introduced by the default medium-specific OC content values. OC

content values are often not readily available and can vary widely for different locations in the same medium. 

Therefore, the degree of uncertainty may be significant in specific instances.
TABLE B-4-17

OVERALL TOTAL WATER BODY DISSIPATION RATE CONSTANT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 2)

Variable Description Units Value

B-236

kv

Water column volatilization rate

constant

yr-1 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-18.

Uncertainties associated with this variable include the following: 

(1) All of the variables in the equation in Table B-4-18 are site-specific. Therefore, using default values for any or all

of these variables could contribute to under- or overestimating kv

.

(2) We expect the degree of uncertainty associated with kv

 components dz

 and TSS to be minimal, either because

information needed to estimate these variables is generally available or because the range of likely values is

narrow.

(3) Values for the variable kv and Kdsw are dependent on medium-specific estimates of OC content. Because OC

content can vary widely for different locations in the same medium, uncertainty associated with these two variables

may be significant in specific instances.

fbs

Fraction of total water body COPC

concentration in benthic sediment 

unitless Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-16.

Uncertainties associated with this variable include the following: 

(1) The default variable values we recommend you use in the equation in Table B-4-16 may not accurately represent

site-specific water body conditions. However, the ranges of several components—including dbs, CBS, and 2sw—are

relatively narrow. We therefore expect the degree of uncertainty associated with these variables to be relatively

small. You can reasonably estimate other components, such as dwc and dz

, using generally available information.

(2) The largest degree of uncertainty may be introduced by the default medium-specific OC contact values. OC

content values are often not readily available and can vary widely for different locations in the same medium. 

Therefore, the degree of uncertainty may be significant in specific instances.

kb

Benthic burial rate constant yr-1 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-22.

Uncertainties associated with this variable include the following: 

(1) All of the variables in the equation in Table B-4-22 are site-specific. Therefore, using default values rather than

site-specific values, for any or all of these variables, will contribute to under- or overestimating Kb.

(2) The degree of uncertainty associated with each of these variables is as follows: (1) Xe—about one order of

magnitude at most, (2) CBS, dbs, Vfx, TSS, and Aw—limited because of the narrow recommended ranges for these

variables or because resources to estimate variable values are generally available, and (3) AL and SD—very

site-specific, degree of uncertainty unknown.
TABLE B-4-18

WATER COLUMN VOLATILIZATION LOSS RATE CONSTANT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 4)

B-237

Description

This equation calculates the water column COPC loss rate constant due to volatilization. Uncertainty associated with this equation includes the following:

All of the variables in the equation in Table B-4-18 are site-specific. Therefore, using default values for any or all of these variables will contribute to under- or over estimating kv. We

expect the uncertainty associated with the variables dwc, dbs, and dz to be minimal, either because information necessary to estimate these variables is generally available or because the

range of probable values is narrow. Values for the variables Kv and Kdsw are dependent on medium-specific estimates of OC content. Because OC content can vary widely for different

locations in the same medium, uncertainty associated with these two variables may be significant in specific instances.

Equation

Variable Description Units Value

kv

Water column volatilization rate

constant

yr-1

Kv

Overall COPC transfer rate

coefficient

m/yr Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-19.

Uncertainties associated with this variable include the following: 

(1) All of the variables in the equation in Table B-4-19—except R, the universal gas constant, which is

well-established—are site-specific. Therefore, using default values, for any or all these variables, could contribute to

under- or overestimating Kv

.

(2) We expect the degree of uncertainty associated with the variables H and Twk to be minimal. Values for H are

well-established, and Twk will likely vary less than 10 percent of the default value. 

(3) The uncertainty associated with the variables KL and KG is attributable largely to medium-specific estimates of organic

carbon, OC, content. Because OC content values can vary widely for different locations in the same medium, using

default values may generate significant uncertainty in specific instances. Finally, the origin of the

recommended temperature correction factor, 2, value is unknown. The degree of associated uncertainty is therefore

also unknown.
TABLE B-4-18

WATER COLUMN VOLATILIZATION LOSS RATE CONSTANT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 4)

Variable Description Units Value

B-238

dz

Total water body depth m Varies

This variable is site-specific. We recommend using the following equation to calculate dz

, consistent with NC DEHNR (1997):

dz

 = dwc + dbs

The following uncertainty is associated with this variable:

Calculating this variable sums the concentrations associated with the two variables dwc and dbs. Because most of the

total water body depth (dz) is made up of the depth of the water column (dwc), and we don’t expect the uncertainties

associated with dwc to be significant, we likewise don’t expect the total uncertainties associated with dz, to be

significant.

dwc

Depth of water column m Varies

This variable is site-specific.

The following uncertainty is associated with this variable:

Default values for depth of water column, dwc, may not accurately reflect site-specific conditions, especially for water

bodies for which depth of water column information is unavailable or outdated. Therefore, using default dwc values

may contribute to under- or overestimating total water body COPC concentration, Cwtot. However, we don’t expect the

degree of under- or overestimating to be significant.

dbs

Depth of upper benthic sediment

layer

m 0.03

This variable is site-specific. The value you select represents an average value for the entire year. We recommend a default

upper benthic sediment depth of 0.03 meter, which is consistent with U.S. EPA (1994) and NC DEHNR (1997) guidance. This

value was cited by U.S. EPA (1993); however, no reference was presented. U.S. EPA (1998) suggests a range of values, from

0.01 to 0.05 meter.

The following uncertainty is associated with this variable:

A default dbs value may not accurately represent site-specific water body conditions. However, we expect any

uncertainty introduced to be limited on the basis of the narrow recommended range.
TABLE B-4-18

WATER COLUMN VOLATILIZATION LOSS RATE CONSTANT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 4)

Variable Description Units Value

B-239

Kdsw

Suspended sediments/surface water

partition coefficient

L water/kg

suspended

sediments

Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in the

HHRAP companion database. 

The following uncertainty is associated with this variable:

The Kdsw values presented in the HHRAP companion database were calculated on the basis of default OC contents for

surface water and soil. Kdsw values based on default values may not accurately reflect site-and water body-specific

conditions and may under- or overestimate actual Kdsw values. You can reduce uncertainty associated with this

variable by using site-specific and medium-specific OC estimates to calculate Kdsw.

TSS Total suspended solids

concentration

mg/L 2 to 300

This variable is site-specific. We recommend using site- and waterbody specific measured values, representative of long-term

average annual values for the water body of concern (see Chapter 5). A value of 10 mg/L was cited by NC DEHNR (1997) and

U.S. EPA (1993) in the absence of site-specific measured data. 

The following uncertainty is associated with this variable:

Limitation on measured data used to determine a water body specific total suspended solids (TSS) value may not

accurately reflect site- and water body-specific conditions long term. Therefore, the TSS value may contribute to

under-or overestimating fwc.

1 × 10-6 Units conversion factor kg/mg

REFERENCES AND DISCUSSION

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is cited as the source of the equation for calculating total water body depth. No source of this equation was identified. This document is also cited as one of the sources of the

range of Kds

 values and an assumed OC value of 0.075 for surface water. This document is also cited as one of the sources of TSS. This document cites U.S. EPA (1993b) as its source of

information.

U.S. EPA. 1993. Addendum: Methodology for Assessing Health Risks Associated with Indirect Exposure to Combustor Emissions. Working Group Recommendations. Office of Solid Waste and

Office of Research and Development. Washington, D.C. September.

This document is cited by U.S. EPA (1994) and NC DEHNR (1997) as the source of the range and default value for the depth of the upper benthic layer (dbs). This document is also cited by

NC DEHNR (1997) as the source of the TSS value. 
TABLE B-4-18

WATER COLUMN VOLATILIZATION LOSS RATE CONSTANT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 4 of 4)

B-240

U.S. EPA. 1994. Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facility Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for RCRA

Hazardous Waste Combustion Facility. April 15.

This document is cited as one of the reference source documents for the default value of the depth of the upper benthic layer. The default value is the midpoint of an acceptable range. This

document cites U.S. EPA (1993b) as its source of information.

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and

Development. EPA 452/R-97-005. December.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.
TABLE B-4-19

OVERALL COPC TRANSFER RATE COEFFICIENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 3)

B-241

Description

This equation calculates the overall transfer rate of contaminants from the liquid and gas phases in surface water. 

Uncertainties associated with this equation include the following:

(1) All of the variables in the equation in Table B-4-19—except R, the universal gas constant, which is well-established—are site-specific. Therefore, using default values for any or all of

these variables will contribute to under- or overestimating Kv. 

(2) We believe the degree of uncertainty associated with the variables H and Twk to be minimal. Values for H are well-established, and Twk will likely vary less than 10 percent of the default

value. 

(3) The uncertainty associated with the variables Kv and KG is attributable largely to medium-specific estimates of OC content. Because OC content values can vary widely for different

locations in the same medium, using default values may generate significant uncertainty in specific instances. Finally, the origin of the recommended value is unknown; therefore, the

degree of associated uncertainty is also unknown.

Equation

Variable Description Units Value

Kv

Overall COPC transfer rate

coefficient

m/yr
TABLE B-4-19

OVERALL COPC TRANSFER RATE COEFFICIENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 3)

Variable Description Units Value

B-242

KL

Liquid phase transfer coefficient m/yr Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-20.

Uncertainties associated with this variable include the following:

All of the variables in the equation in Table B-4-20 are site-specific. Therefore, using default values rather than

site-specific values, for any or all of these variables, will contribute to under- or overestimating Kv. The degree of

uncertainty associated with these variables is as follows:

a) We assume the uncertainty associated with six variables—Dw, u, dz, Da, Dw, and μw—is minimal or

insignificant, either because of narrow recommended ranges for these variables or because information to

estimate variable values is generally available.

b) No original sources were identified for the equations used to derive recommended values or specific

recommended values for variables Cd

, k, and 8z

. Therefore, the degree and direction of any uncertainties

associated with these variables are unknown.

c) Uncertainties associated with the variable W are site-specific. 

KG

Gas phase transfer coefficient m/yr Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-21.

Uncertainties associated with this variable include the following:

All of the variables in the equation in Table B-4-21, with the exception of k, are site-specific. Therefore, using

default values rather than site-specific values, for any or all of these variables, will contribute to under- or

overestimating KG

. The degree of uncertainty associated with each of these variables is as follows:

a) We assume the uncertainty associated with the variables Da

, μa

, and Da

, is minimal or insignificant, because

these variables have been extensively studied, and equation procedures are well-established.

b) No original sources were identified for equations used to derive recommended values or specific

recommended values for variables Cd

, k, and dz

. Therefore, the degree and direction of any uncertainties

are unknown.

c) Uncertainties associated with the variable W are site-specific and cannot be readily estimated.

H Henry’s Law constant atm-m3

/mol Varies

This variable is COPC-specific. We discuss this variable in detail in detail in Appendix A-2, and offer COPC-specific values

in the HHRAP companion database.

The following uncertainty is associated with this variable:

Values for this variable, estimated using the parameters and algorithms in Appendix A-2, may under- or overestimate

the actual COPC-specific values. As a result, Kv may be under- or overestimated to a limited degree.
TABLE B-4-19

OVERALL COPC TRANSFER RATE COEFFICIENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 3)

Variable Description Units Value

B-243

R Universal gas constant atm-m3

/mol-K 8.205 x 10G5

There are no uncertainties associated with this constant.

Twk

Water body temperature K 298

This variable is site-specific. We recommend using this default value when site-specific information is not available; this is

consistent with U.S. EPA (1994) and U.S. EPA (1998).

The following uncertainty is associated with this variable:

To the extent that the default water body temperature value does not accurately represent site- and water

body-specific conditions, Kv, will be under- or overestimated.

2 Temperature correction factor unitless 1.026

This variable is site-specific. We recommend using this default value when site-specific information is not available. This is

consistent with U.S. EPA (1994) and U.S. EPA (1998). 

The following uncertainty is associated with this variable:

The purpose and sources of this variable and the recommended value are unknown.

REFERENCES AND DISCUSSION

U.S. EPA. 1994. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document is cited as the reference source for water body temperature (Twk ) and temperature correction factor (2). This document apparently cites U.S. EPA (1993a) as its source of

information.

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and

Development. EPA 452/R-97-005. December.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document is the reference source for the equation in Table B-4-19. This document also recommends the Twk value of 298 K (298 K = 25°C) and the 2 value of 1.026. No

source was identified for these values.
TABLE B-4-20

LIQUID PHASE TRANSFER COEFFICIENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 5)

B-244

Description

This equation calculates the rate of COPC transfer from the liquid phase for a flowing or quiescent water body. 

Uncertainties associated with this equation include the following:

(1) We assume uncertainly associated with the following six variables is minimal or insignificant: Dw, u, dz, Da, Dw, and μw.

(2) No original sources were identified for equations used to derive recommended values or specific recommended values for the following three variables: Cd, k, and dz. Therefore, the

degree and duration of any uncertainties associated with these variables is unknown.

(3) Uncertainties associated with the variable W are site-specific.

Equation

For flowing streams or rivers

For quiescent lakes or ponds

Variable Description Units Value

KL

Liquid phase transfer

coefficient

m/yr
TABLE B-4-20

LIQUID PHASE TRANSFER COEFFICIENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 5)

Variable Description Units Value

B-245

Dw

Diffusivity of COPC in water cm2

/s Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in the

HHRAP companion database. 

The following uncertainty is associated with this variable:

The default Dw values may not accurately represent the behavior of COPCs under water body-specific conditions.

However, we expect the degree of uncertainty to be minimal.

u Current velocity m/s Varies

This variable is site-specific, and relates to the volumetric flow rate of the waterbody evaluated.

The following uncertainty is associated with this variable:

Sources of values for this variable are reasonably available for most large surface water bodies. Estimated values

for this variable may be necessary for smaller water bodies; uncertainty will be associated with these estimates. We

don’t expect the degree of uncertainty associated with this variable to be significant.

dz

Total water body depth m Varies

This variable is site-specific, and, in most cases, represents the average mean across the waterbody evaluated. We recommend

that you calculate this value using the following equation, consistent with U.S. EPA (1994) and NC DEHNR (1997):

dz = dwc + dbs

No reference was cited for this recommendation.

The following uncertainty is associated with this variable:

Calculating this variable sums the concentrations associated with the two variables dwc and dbs. Because most of the

total water body depth (dz) is made up of the depth of the water column (dwc), and the uncertainties associated with

dwc are not expected to be significant, we likewise don’t expect the total uncertainties associated with dz

 to be

significant.

3.1536 x

107

Units conversion factor s/yr
TABLE B-4-20

LIQUID PHASE TRANSFER COEFFICIENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 5)

Variable Description Units Value

B-246

Cd

Drag coefficient unitless 0.0011

This variable is site-specific. We recommend a default value of 0.0011, consistent with U.S. EPA (1994), NC DEHNR (1997),

and U.S. EPA (1998).

The following uncertainty is associated with this variable:

The original source of this variable value is unknown. Therefore, any uncertainties associated with its use are also

unknown.

W Average annual wind speed m/s 3.9

Consistent with U.S. EPA (1998), we recommend a default value of 3.9 m/s. See Chapter 3 for guidance regarding the

references and methods used to determine a site-specific value that is consistent with air dispersion modeling.

The following uncertainty is associated with this variable:

To the extent that site-specific or local values for this variable are not available, default values may not accurately

represent site-specific conditions. The uncertainty associated with the selection of a single value from within the

range of windspeeds at a single location may be more significant than the uncertainty associated with choosing a

single windspeed to represent all locations.

Da

Density of air g/cm3

0.0012

We recommend this default value when site-specific information is not available. This is consistent with U.S. EPA (1994) and

NC DEHNR (1997), both of which cite Weast (1979) as the source of this value. This value applies at standard conditions

(25°C or 298 K and 1 atm or 750 mm Hg). 

The density of air will vary with temperature.

Dw

Density of water g/cm3

1

We recommend this default value, consistent with U.S. EPA (1994) and NC DEHNR (1997), both of which cite Weast (1979)

as the source of this value. This value applies at standard conditions (25°C or 298 K and 1 atm or 750 mm Hg). There is no

significant uncertainty associated with this variable.

k von Karman’s constant unitless 0.4

This value is a constant. We recommend using this value, consistent with U.S. EPA (1994) and NC DEHNR (1997).

The following uncertainty is associated with this variable:

The original source of this variable value is unknown. Therefore, any uncertainties associated with its use are also

unknown.
TABLE B-4-20

LIQUID PHASE TRANSFER COEFFICIENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 4 of 5)

Variable Description Units Value

B-247

8z

Dimensionless viscous sublayer

thickness

unitless 4

This value is site-specific. We recommend using this default value when site-specific information is not available; consistent

with U.S. EPA (1994) and NC DEHNR (1997).

The following uncertainty is associated with this variable:

The source of the value for this variable is unknown. Therefore, any uncertainties associated with its use cannot be

quantified.

:w

Viscosity of water

corresponding to water

temperature

g/cm-s 1.69 x 10G02

We recommend this default value, consistent with U.S. EPA (1994) and NC DEHNR (1997), which both cite Weast (1979) as

the source of this value. This value applies at standard conditions (25°C or 298 K and 1 atm or 760 mm Hg). There is no

significant uncertainty associated with this variable.

REFERENCES AND DISCUSSION

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is cited as one of the sources of the range of Dw values and assumed Cd, Da, Dw, k, "8, and :w values of 0.0011, 1.2 x 10-3, 1, 0.4, 4, and 1.69 x 10-2, respectively. This

document cites (1) Weast (1979) as its source of information regarding Da, Dw, and μw; and (2) U.S. EPA (1993a) as its source of information regarding Cd, k, and dz.

U.S. EPA. 1993a. Addendum: Methodology for Assessing Health Risks Associated with Indirect Exposure to Combustor Emissions. Working Group Recommendations. Office of Solid Waste and

Office of Research and Development. Washington, D.C. September 24.

This document is cited by U.S. EPA (1994) and NC DEHNR (1997) as the source of the recommended drag coefficient (Cd) value of 0.0011 and the recommended von Karman’s constant (k)

value of 0.4. The original sources of variable values are not identified.

U.S. EPA. 1994. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document is cited as one of the sources of the range of Dw values and assumed Cd, Da, Dw, k, 8z, and :w values of 0.0011, 1.2 x 10-3, 1, 0.4, 4, and 1.69 x 10-2, respectively. This

document cites (1) Weast (1979) as its source of information regarding Da

, Dw

, and μw

; and (2) U.S. EPA (1993a) as its source of information regarding Cd, k, and dz

.

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and

Development. EPA 452/R-97-005. December.
TABLE B-4-20

LIQUID PHASE TRANSFER COEFFICIENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 5 of 5)

B-248

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document recommends a value of 0.0011 for the drag coefficient (Cd) variable and a value of 0.4 for von Karman’s constant (k). No sources are cited for these values.

Weast, R. C. 1979. CRC Handbook of Chemistry and Physics. 60th ed. CRC Press, Inc. Cleveland, Ohio.

This document is cited as the source of Da

, Dw

, and μw

 variables of 1.2 x 10-3, 1, and 1.69 x 10-2, respectively.
TABLE B-4-21

GAS PHASE TRANSFER COEFFICIENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 4)

B-249

Description

This equation calculates the rate of COPC transfer from the gas phase for a flowing or quiescent water body. Uncertainties associated with this equation include the following:

(1) Minimal or insignificant uncertainty is assumed to be associated with the variables Da, μa, and Da.

(2) No original sources were identified for equations used to derive recommended values or specific recommended values for variables Cd, k, and 8z. Therefore, the degree and direction of

any uncertainties associated with these variables are unknown.

(3) Uncertainties associated with the remaining variables are site-specific.

Equation

Flowing streams or rivers

Quiescent lakes or ponds

Variable Description Units Value

KG

Gas phase transfer coefficient m/yr

Cd

Drag coefficient unitless 0.0011

This variable is site-specific. We recommend using this default value when site-specific information is not available, consistent

with U.S. EPA (1994), NC DEHNR (1997), and U.S. EPA (1998).

The following uncertainty is associated with this variable:

The original source of this variable is unknown. Therefore, any uncertainties associated with its use are also

unknown.
TABLE B-4-21

GAS PHASE TRANSFER COEFFICIENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 4)

Variable Description Units Value

B-250

W Average annual wind speed m/s 3.9

Consistent with U.S. EPA (1998), we recommend a default value of 3.9 m/s. See Chapter 3 of the HHRAP for guidance

regarding the references and methods used to determine a site-specific value that is consistent with air dispersion modeling.

The following uncertainty is associated with this variable:

To the extent that site-specific or local values for this variable are not available, default values may not accurately

represent site-specific conditions. The uncertainty associated with the selection of a single value from within the

range of windspeeds at a single location may be more significant than the uncertainty associated with choosing a

single windspeed to represent all locations.

k von Karman’s constant unitless 0.4

This value is a constant. We recommend using this value, consistent with U.S. EPA (1994) and NC DEHNR (1997).

The following uncertainty is associated with this variable:

The original source of this variable is unknown. Therefore, any uncertainties associated with its use are also

unknown.

8z

Dimensionless viscous

sublayer thickness

unitless 4

This value is site-specific. We recommend using this default value when site-specific information is not available, consistent

with U.S. EPA (1994) and NC DEHNR (1997).

The following uncertainty is associated with this variable:

The original source of this variable is unknown. Therefore, any uncertainties associated with its use are also

unknown.

:a

Viscosity of air g/cm-s 1.81 x 10G04

We recommend using this default value when site-specific information is not available, consistent with U.S. EPA (1994) and

NC DEHNR (1997), both of which cite Weast (1979) as the source of their information. There is no significant uncertainty

associated with this variable.

Da

Density of air g/cm3

0.0012

We recommend using this default value when site-specific information is not available, consistent with U.S. EPA (1994) and

NC DEHNR (1997), both of which cite Weast (1979) as the source of this value. This value applies at standard conditions

(25°C or 298 K and 1 atm or 760 mm Hg) .

The density of air will vary with temperature.
TABLE B-4-21

GAS PHASE TRANSFER COEFFICIENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 4)

Variable Description Units Value

B-251

Da

Diffusivity of COPC in air cm2

/s Varies

This variable is COPC-specific. We discuss this variable in detail in detail in Appendix A-2, and offer COPC-specific values in

the HHRAP companion database. 

The following uncertainty is associated with this variable:

The recommended Da values may not accurately represent the behavior of COPCs under water body-specific

conditions. However, we expect the degree of uncertainty to be minimal.

3.1536 x 107 Units conversion factor s/yr

REFERENCES AND DISCUSSION

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is cited as one of the sources of the variables Da, k, 8z, and μa values of 1.2 x 10-3, 0.4, 4, and 1.81 x 10G04, respectively. This document cites (1) Weast (1979) as its source of

information for Da and μa, and (2) U.S. EPA (1993a) as its source of information for k and 8z.

U.S. EPA. 1993a. Addendum: Methodology for Assessing Health Risks Associated with Indirect Exposure to Combustion Emissions. Working Group Recommendations. Office of Solid Waste, and

Office of Research and Development. Washington, D.C. September.

This document is cited by U.S. EPA (1994) and NC DEHNR (1997) as the source of (1) the recommended drag coefficient (Cd) value of 0.0011, (2) the recommended von Karman’s

constant (k) value of 0.4, and (3) the recommended dimensionless viscous sublayer thickness (8z) value of 4. The original sources of these variable values are not identified.

U.S. EPA. 1994. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document is cited as one of the sources of the variables Da, k, 8z, and μa values of 1.2 x 10-3, 0.4, 4, and 1.81 x 10G04, respectively. This document cites (1) Weast (1979) as its source of

information for Da

 and μa

, and (2) U.S. EPA (1993a) as its source of information for k and 8z

.

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and

Development. EPA 452/R-97-005. December.
TABLE B-4-21

GAS PHASE TRANSFER COEFFICIENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 4 of 4)

B-252

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document recommends (1) a value of 0.0011 for the drag coefficient (Cd) variable, (2) a value of 0.4 for von Karman’s constant (K), and (3) a value of 4 for the dimensionless viscous

sublayer thickness (8z) variable. The original sources of the variable values are not identified.

Weast, R.C. 1979. CRC Handbook of Chemistry and Physics. 60th ed. CRC Pres, Inc. Cleveland, Ohio. 

This document is cited as the source of Da

, Dw

, and :a

 variables of 1.2 x 10-3, 1, and 1.69 x 10-2, respectively.
TABLE B-4-22

BENTHIC BURIAL RATE CONSTANT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 4)

B-253

Description

This equation calculates the water column loss constant due to burial in benthic sediment. 

Uncertainties associated with this equation include the following:

(1) All of the variables in the equation in Table B-4-22 are site-specific. Therefore, using default values rather than site-specific values, for any or all of these variables, will contribute to

under- or overestimating kb. The degree of uncertainty associated with each of these variables is as follows: (a) Xe—about one order of magnitude at the most, (b) CBS, dbs, Vfx, TSS, and

Aw—limited because of the narrow recommended ranges for these variables or because resources to estimate variable values are generally available, (c) AL and SD—very site-specific,

degree of uncertainty unknown.

Based on the possible ranges for the input variables to this equation, values of kb can range over about one order of magnitude.

Equation

Variable Description Units Value

kb

Benthic burial rate constant yr-1

Xe

Unit soil loss kg/m2

-yr Varies

This variable is site-specific and is calculated using the equation in Table B-4-13.

The following uncertainty is associated with this variable:

All of the variables in the equation used to calculate unit soil loss, Xe, are site-specific. Using default values rather

than site-specific values, for any or all of the equation variables, will result in estimates of Xe

 that under- or

overestimate the actual value. We expect the degree or magnitude of any under- or overestimation to be about one

order of magnitude or less.

AL

Total watershed area receiving

deposition

m2 Varies

This variable is site-specific (see Chapter 4). Uncertainties associated with this variable are site-specific.
TABLE B-4-22

BENTHIC BURIAL RATE CONSTANT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 4)

Variable Description Units Value

B-254

SD Watershed sediment delivery ratio unitless Varies

This value is site-specific and is calculated using the equation in Table B-4-14.

Uncertainties associated with this variable include the following:

(1) The default values for empirical intercept coefficient (a) that we recommend for use in the equation in Table B-4-14,

are average values based on various studies of sediment yields from various watersheds. Therefore, these default

values may not accurately represent site-specific watershed conditions. As a result, using these default values may

contribute to under- or overestimating the benthic burial rate constant, kb.

(2) The default value for empirical slope coefficient (b) that we recommend for use in the equation in Table B-4-14 is

based on a review of sediment yields from various watersheds. This single default value may not accurately

represent site-specific watershed conditions. As a result, using this default value may contribute to under-or

overestimating kb

. 

1 x 10 3 Units conversion factor g/kg

Vfx

Average volumetric flow rate

through water body

m3/yr Varies

This variable is site-specific. We recommend using site- and waterbody-specific measured values, representative of long-term

average annual values for the water body of concern.

The following uncertainty is associated with this variable:

Default average volumetric flow rate (Vfx) values may not accurately represent site-specific water body conditions. 

Therefore, using such default values may contribute to under- or overestimating kb. However, we expect that the

uncertainty associated with this variable to be limited, because resources such as maps, aerial photographs, and

gauging station measurements—from which Vfx

 can be estimated—are generally available.

TSS Total suspended solids

concentration

mg/L 2 to 300

This variable is site-specific. We recommend using site- and waterbody specific measured values, representative of long-term

average annual values for the water body of concern (see Chapter 5). A value of 10 mg/L was cited by NC DEHNR (1997),

and U.S. EPA (1993) in the absence of site-specific measured data. 

The following uncertainty is associated with this variable:

Limitation on measured data used for determining a water body specific total suspended solids (TSS) value may not

accurately reflect site- and water body-specific conditions long term. Therefore, the TSS value may contribute to

under-or overestimating fwc.
TABLE B-4-22

BENTHIC BURIAL RATE CONSTANT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 4)

Variable Description Units Value

B-255

Aw

Water body surface area m2 Varies

This variable is site-specific. The value selected represents an average value for the entire year. See Chapter 4 for guidance

regarding the references and methods used to determine this value. Uncertainties associated with this variable are site-specific. 

However, we expect that the uncertainty associated with this variable will be limited, because maps, aerial photographs—and

other resources from which water body surface area, Aw

, can be measured—are readily available.

1 x 10 G6 Units conversion factor kg/mg

CBS

Bed sediment concentration g/cm3

1.0

This variable is site-specific. We recommend a default value of 1.0, consistent with U.S. EPA (1998), which states that this

value should be reasonable for most applications. No reference is cited for this recommendation. The recommended default

value is also consistent with U.S. EPA (1994), and NC DEHNR (1997). 

The following uncertainty is associated with this variable:

The recommended value may not accurately represent site-specific water body conditions. 

dbs

Depth of upper benthic sediment

layer

m 0.03

This variable is site-specific. The value selected represents an average value for the entire year. We recommend a default

upper-benthic sediment depth of 0.03 meters, which is based on the center of the range cited by U.S. EPA (1993). This value

is also consistent with U.S. EPA (1994) and NC DEHNR (1997).

The following uncertainty is associated with this variable:

The recommended default value for depth of upper benthic sediment layer, dbs, may not accurately represent

site-specific water body conditions. Therefore, use of this default value may contribute to the under- or

overestimation of kb

. However, the degree of uncertainty associated with this variable is expected to be limited

because of the narrow recommended range.

REFERENCES AND DISCUSSION

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is cited as one of the sources of the range of all recommended specific CBS and dbs values. This document cites U.S. EPA (1993a) as its source.
TABLE B-4-22

BENTHIC BURIAL RATE CONSTANT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 4 of 4)

B-256

U.S. EPA. 1993. Addendum: Methodology for Assessing Health Risks Associated with Indirect Exposure to Combustion Emissions. Working Group Recommendations. Office of Solid Waste, and

Office of Research and Development. Washington, D.C. September.

This document is cited by U.S. EPA (1994) and NC DEHNR (1997) as the source of (1) the recommended drag coefficient (Cd) value of 0.0011, (2) the recommended von Karman’s

constant (k) value of 0.4, and (3) the recommended dimensionless viscous sublayer thickness (8z) value of 4. The original sources of these variable values are not identified.

U.S. EPA 1994. Draft Guidance for Performing Screening Level Risk Analysis at Combustor Facilities Burning Hazardous Waste. Attachment C, Draft Exposure Assessment Guidance for RCRA

Hazardous Waste Combustion Facilities. April 15.

This document is cited as one of the reference sources for the dbs value. The recommended value is the midpoint of an acceptable range. This document is also cited as one of the reference

source documents for the default CBS value. This document cites U.S. EPA (1993a) as its source.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.
TABLE B-4-23

TOTAL WATER COLUMN CONCENTRATION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 3)

B-257

Description

This equation calculates the total water column concentration of COPCs including (1) both dissolved COPCs and (2) COPCs sorbed to suspended solids. Uncertainties associated with this

equation include the following:

(1) All of the variables in the equation in Table B-4-23 are COPC- and site-specific. Therefore, using default values rather than site-specific values, for any or all of these variables, will

contribute to under- or overestimating Cwctot.

We expect the degree of uncertainty associated with the variables dwc and dbs to be minimal either because information for estimating a variable (dwc) is generally available or because the probable

range for a variable (dbs) is narrow. The uncertainty associated with the variables fwc and Cwtot is associated with estimates of OC content. Because OC content values can vary widely for different

locations in the same medium, the uncertainty associated with using default OC values may be significant in specific cases.

Equation

Variable Description Units Value

Cwctot

Total COPC concentration in water

column

mg

COPC/L

water

column

fwc

Fraction of total water body COPC

concentration in the water column 

unitless 0 to 1

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-16.

The following uncertainty is associated with this variable:

The default variable values we recommend you use in the equation in Table B-4-16 may not accurately represent

site-specific water body conditions. However, the ranges of several variables—including dbs, CBS, and 2sw—are

relatively narrow. Therefore, we expect the uncertainty to be relatively small. You can reasonably estimate other

variables, such as dwc and dz, using generally available information. The largest degree of uncertainty may be

introduced by the default medium-specific OC content values. OC content values are often not readily available and

can vary widely for different locations in the same medium. Therefore, default values may not adequately represent

site-specific conditions.
TABLE B-4-23

TOTAL WATER COLUMN CONCENTRATION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 3)

Variable Description Units Value

B-258

Cwtot

Total waterbody COPC

concentration including water

column and bed sediment

mg

COPC/L

water body

(or g

COPC/m3

water body)

Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-15.

The following uncertainty is associated with this variable:

The default variable values we recommend you use in the equation in Table B-4-15 may not accurately represent site-

-specific water body conditions. We expect the degree of uncertainty associated with variables Vfx, Aw, dw, and dbs to

be limited either because the probable ranges for variables are narrow or information allowing accurate estimates is

generally available. Uncertainty associated with fwc is largely the result of water body-associated default OC content

values, and may be significant in specific instances. Uncertainties associated with the total COPC load into water

body (Lt) and overall total water body COPC dissipation rate constant (kwt) may also be significant in some instances

because of the combination of many variable-specific uncertainties.

dwc

Depth of water column m Varies

This variable is site-specific. The following uncertainty is associated with this variable:

Default values for depth of water column, dwc, may not accurately reflect site-specific water body conditions. 

Therefore, using default values may contribute to under- or overestimating Cwctot. However, we expect the degree of

uncertainty associated with this variable to be limited, because information regarding this variable is generally

available.

dbs

Depth of upper benthic sediment

layer

m 0.03

This variable is site-specific. We recommend a default upper-benthic sediment depth of 0.03 meters, which is based on the

center of a range cited by U.S. EPA (1993) This value is consistent with U.S. EPA (1994) and NC DEHNR (1997).

The following uncertainty is associated with this variable:

The recommended default value for depth of upper benthic sediment layer, dbs, may not accurately represent

site-specific water body conditions. Therefore, using this default value may contribute to under- or overestimating

Cwctot. However, we expect the degree of uncertainty associated with this variable to be limited because of the narrow

recommended range.
TABLE B-4-23

TOTAL WATER COLUMN CONCENTRATION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 3)

B-259

REFERENCES AND DISCUSSION

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is cited as one of the sources of the range of dbs values. This document cites U.S. EPA (1993a) as its source.

U.S. EPA. 1993. Addendum: Methodology for Assessing Health Risks Associated with Indirect Exposure to Combustor Emissions. Working Group Recommendations. Office of Solid Waste and

Office of Research and Development. Washington, D.C. September.

This document is cited by U.S. EPA (1994) and NC DEHNR (1997) as one of the sources of the ranges of dbs values. No original source of this range was identified.

U.S. EPA. 1994. Draft Guidance for Performing Screening Level Risk Analysis at Combustor Facilities Burning Hazardous Waste. Attachment C, Draft Exposure Assessment Guidance for RCRA

Hazardous Waste Combustion Facility. April.

This document is cited as one of the reference sources for the default value for depth of upper benthic layer (dbs). The recommended value is the midpoint of an acceptable range. This

document cites U.S. EPA (1993) as the source of its information. The degree of uncertainty associated with the variables dwc and dbs is expected to be minimal either because information for

estimating these variables is generally available (dwc) or the probable range for a variable (dbs) is narrow. Uncertainty associated with the variables fwc and Cwtot is largely associated with the

use of default OC content values. Because OC content is known to vary widely in different locations in the same medium, use of default medium-specific values can result in significant

uncertainty in some instances.
TABLE B-4-24

DISSOLVED PHASE WATER CONCENTRATION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 3)

B-260

Description

This equation calculates the concentration of COPC dissolved in the water column. Uncertainties associated with this equation include the following:

(1) The variables in the equation in Table B-4-24 are site-specific. Therefore, using default values rather than site-specific values, for any or all of these variables, will contribute to under- or

overestimating Cdw. We expect the degree of uncertainty associated with TSS to be relatively small, because information regarding reasonable site-specific values for this variable are

generally available or it can be easily measured. On the other hand, the uncertainty associated with the variables Cwctot and Kdsw is associated with estimates of OC content. Because OC

content values can vary widely for different locations in the same medium, using default OC values may result in significant uncertainty in specific cases.

Equation

For mercury modeling,

Use the equation above to calculate the Cdw mercury value. Apportion into the divalent mercury (Hg2+) and methyl mercury (MHg) forms based on the assumed 85% Hg2+ and 15% MHg speciation

split in the water body (see Chapter 2) using the correlations below. Elemental mercury (Hg0) occurs in very small amounts in the vapor phase and does not exist in the particle or particle-bound

phase. Therefore, assume elemental mercury in the water body is negligible or zero, and evaluate it for the direct inhalation pathway only (Table B-5-1).

Cdw (Hg2+) = 0.85 C dw (Mercu ry)

Cdw (Mhg) = 0.15 C dw (Mercu ry)

Cdw (Hg0) = 0.0

Evaluate divalent and methyl mercury as individual COPCs to determine Cfish (Tables B-4-26 and B-4-27) for calculating COPC intake from fish in Table C-1-4, and in evaluating COPC intake

from drinking water (Table C-1-5). Calculate Cdw (Mercury) as above using the corresponding fate and transport parameters for mercuric chloride (Hg2+) provided in Appendix A-2, and determine 

Cdw (Hg2+) and Cdw (Mhg) as calculated above.
TABLE B-4-24

DISSOLVED PHASE WATER CONCENTRATION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 3)

B-261

Variable Description Units Value

Cdw

Dissolved phase water

concentration 

mg

COPC/L

water

Cwctot

Total COPC concentration in water

column

mg

COPC/L

water

column

Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-23.

The following uncertainty is associated with this variable:

All of the variables in the equation in Table B-4-23 are COPC- and site-specific. Therefore, using default values rather

than site-specific values, for any or all of these variables, will contribute to under- or overestimating Cwctot.

We expect the degree of uncertainty associated with the variables dwc and dbs to be minimal either because information

for estimating a variable (dwc) is generally available or because the probable range for a variable (dbs) is narrow. The

uncertainty associated with the variables fwc and Cwtot is associated with estimates of Organic Carbon, OC, content. 

Because OC content values can vary widely for different locations in the same medium, using default OC values may

result in significant uncertainty in specific cases.

Kdsw

Suspended sediments/surface water

partition coefficient

L water/kg

suspended

sediment

Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in the

HHRAP companion database. 

The following uncertainty is associated with this variable:

Values contained in Appendix A-2 for Kdsw are based on default OC content values for surface water and soil. Because

OC content can vary widely for different locations in the same medium, the uncertainty associated with estimated Kdsw

values based on default OC content values may be significant in specific cases.

TSS Total suspended solids

concentration

mg/L 2 to 300

This variable is site-specific. We recommend using site- and waterbody specific measured values, representative of long-term

average annual values for the water body of concern (see Chapter 5). A value of 10 mg/L was cited by NC DEHNR (1997) and

U.S. EPA (1993b) in the absence of site-specific measured data. 

The following uncertainty is associated with this variable:

Limitation on measured data used for determining a water body specific total suspended solids (TSS) value may not

accurately reflect site- and water body-specific conditions long term. Therefore, the TSS value may contribute to

under-or overestimating fwc.

1 x 10-6 Units conversion factor kg/mg
TABLE B-4-24

DISSOLVED PHASE WATER CONCENTRATION

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 3)

B-262

REFERENCES AND DISCUSSION

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is cited as one of the sources of the range of Kds values and the TSS value of 10. This document cites U.S. EPA (1993) as its sources of information regarding TSS, and (2)

RTI (1992) as its source regarding Kds.

U.S. EPA. 1993. Addendum to the Methodology for Assessing Health Risks Associated with Indirect Exposure to Combustor Emissions. Working Group Recommendations. Office of Solid Waste

and Office of Research and Development. Washington, D.C. September.

This document is cited by U.S. EPA (1994) and NC DEHNR (1997) as one of the sources of the range of Kds value and the assumed OC value of 0.075 for surface water. The generic

equation for calculating partition coefficients (soil, surface water, and bed sediments) is as follows: Kdij = Kocj * OCi. Koc is a chemical-specific value; however, OC is medium-specific. 

The range of Kds values was based on an assumed OC value of 0.01 for soil. Therefore, the Kdsw values were estimated by multiplying the Kds values by 7.5, because the OC value for

surface water is 7.5 times greater than the OC value for soil. This document is also cited by U.S. EPA (1994) and NC DEHNR (1997) as the source of the recommended TSS value. 

U.S. EPA. 1994. Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Waste. Attachment C, Draft Exposure Assessment Guidance for RCRA

Hazardous Waste Combustion Facilities. April 15.

This document is cited as one of the sources of the range of Kds values, citing RTI (1992) as its source of information.
TABLE B-4-25

COPC CONCENTRATION SORBED TO BED SEDIMENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 1 of 4)

B-263

Description

This equation calculates the concentration of COPCs sorbed to bed sediments.

 Uncertainties associated with this equation include the following:

(1) The default variable values recommended for use in the equation in Table B-4-25 may not accurately represent site-specific water body conditions. We expect the degree of uncertainty

associated with variables 2bs, CBS, dwc, and dbs to be limited either because the probable ranges for these variables are narrow or because information allowing reasonable estimates is

generally available.

(2) Uncertainties associated with variables fbs, Cwtot and Kdbs are largely associated with the use of default OC content values in their calculation. The uncertainty may be significant in

specific instances, because OC content is known to vary widely in different locations in the same medium.

Equation

Variable Description Units Value

Csb

Concentration sorbed to bed

sediment

mg

COPC/kg

sediment

fbs

Fraction of total water body COPC

concentration that occurs in the

benthic sediment

unitless Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-16.

The following uncertainty is associated with this variable:

The default values for the variables in the equation in Table B-4-16 may not accurately represent site- and water

body-specific conditions. However, the range of several variables—including dbs, CBS, and 2bs—is relatively narrow. 

You can reasonably estimate other variables, such as dwc and dz

, using generally available information. The largest

degree of uncertainty may be introduced by the default medium-specific OC content values. Because OC content

values may vary widely in different locations in the same medium, using default values may result in significant

uncertainty in specific cases.
TABLE B-4-25

COPC CONCENTRATION SORBED TO BED SEDIMENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 2 of 4)

Variable Description Units Value

B-264

Cwtot

Total water body concentration

including water column and bed

sediment

mg COPC/L

water body

(or g

COPC/cm3

water body)

Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-15.

The following uncertainty is associated with this variable:

(1) The default variable values may not accurately represent site-specific water body conditions. We expect the degree

of uncertainty associated with variables Vfx, Aw, dwc, and dbs to be limited either because the probable ranges for these

variables are narrow or information allowing reasonable estimates is generally available.

(2) Uncertainty associated with fwc is largely the result of uncertainty associated with default OC content values and may

be significant in specific instances. Uncertainties associated with the variable LT and Kwt may also be significant

because of the combination of many variable-specific uncertainties.

Kdbs

Bed sediment/sediment pore water

partition coefficient

L water/kg

bed sediment

(or cm3

water/g bed

sediment)

Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in the

HHRAP companion database. 

The following uncertainty is associated with this variable:

The default Kdbs values in Appendix A-2 are based on default OC content values for sediment and soil. Because

medium-specific OC content may vary widely at different locations in the same medium, the uncertainty associated

with Kdbs values calculated by using default OC content values may be significant in specific instances.

2bs

Bed sediment porosity unitless

(L pore

volume/Lsediment)

0.6

This variable is site-specific. We recommend a default bed sediment porosity of 0.6 (using a CBS value of 1 g/cm3

 and a solids

density (Ds) value of 2.65 kg/L), calculated using the following equation (U.S. EPA 1998):

2bs = 1 - CBS /Ds

This also is consistent with U.S. EPA (1993), U.S. EPA (1994), and NC DEHNR (1997).

The following uncertainty is associated with this variable:

To the extent that the recommended default values of CBS and Ds don’t accurately represent site- and water

body-specific conditions, 2bs will be under- or overestimated to some degree. However, we expect the degree of

uncertainty to be minimal, based on the narrow range of recommended values.
TABLE B-4-25

COPC CONCENTRATION SORBED TO BED SEDIMENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 3 of 4)

Variable Description Units Value

B-265

CBS

Bed sediment concentration (or bed

sediment bulk density)

g/cm3

1.0

This variable is site-specific. We recommend a default value of 1.0, consistent with U.S. EPA (1998), which states that this

value should be reasonable for most applications. No reference is cited for this recommendation. This is also consistent with

U.S. EPA (1993), U.S. EPA (1994), and NC DEHNR (1997).

The following uncertainty is associated with this variable:

The recommended default value for 2bs may not accurately represent site- and water body-specific conditions.

Therefore, the variable Csb may be under- or overestimated to a limited degree, as indicated by the narrow range of

recommended values.

dwc

Depth of water column m Varies

This variable is site-specific. 

The following uncertainty is associated with this variable:

Default dwc values may not accurately reflect site-specific conditions. Therefore, using these values may contribute

to under- or overestimating the variable Csb. However, we expect the degree of uncertainty to be minimal, because

resources allowing reasonable water body-specific estimates of dwc are generally available.

dbs

Depth of upper benthic sediment

layer

m 0.03

This variable is site-specific. We recommend a default upper-benthic sediment depth of 0.03 meters, which is based on the

center of a range cited by U.S. EPA (1998). This value is consistent with U.S. EPA (1994) and NC DEHNR (1997). 

The following uncertainty is associated with this variable:

Default dbs values may not accurately reflect site-specific conditions. Therefore, using these values may contribute to

under- or overestimating Csb. However, we expect the degree of uncertainty to be small, based on the narrow

recommended range of default values.

REFERENCES AND DISCUSSION

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is cited as one of the sources of the range of Kds

 values and an assumed OC value of 0.04 for sediment. This document cites RTI (1992) as its source of information

regarding Kds values. This document is also cited as one of the reference source documents for the default value for bed sediment porosity(2sw). This document cites U.S. EPA (1993a;

1993b) as its source of information. This document is also cited as one of the reference source documents for the default value for depth of the upper benthic layer. The default value is the
TABLE B-4-25

COPC CONCENTRATION SORBED TO BED SEDIMENT

(CONSUMPTION OF DRINKING WATER AND FISH EQUATIONS)

(Page 4 of 4)

B-266

midpoint of an acceptable range. This document cites U.S. EPA (1993a) and U.S. EPA (1993b) as its source of information for the range of values for the depth of the upper benthic layer. 

This document is also cited as one of the reference source documents for the default bed sediment concentration (CBS). This document cites U.S. EPA (1993a; 1993b) as its source.

U.S. EPA. 1993b. Addendum: Methodology for Assessing Health Risks Associated with Indirect Exposure to Combustor Emissions. Working Group Recommendations. Office of Solid Waste and

Office of Research and Development. Washington, D.C. September.

This document is cited by NC DEHNR (1997) and U.S. EPA (1994) as the source of the default bed sediment porosity value (2sw), the default bed sediment concentration value (CBS), and the

range for depth of upper benthic layer (dbs) values. 

U.S. EPA. 1994. Draft Guidance for Performing Screening Level Risk Analysis at Combustor Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for RCRA

Hazardous Waste Combustion Facilities. April.

This document is cited as one of the sources of the range of Kds values and an assumed OC value of 0.04 for sediment. This document cites RTI (1992) as its source of information

regarding Kds values. This document is cited as one of the reference source documents for the default value for bed sediment porosity (2sw). This document cites U.S. EPA (1993a; 1993b)

as its source. This document is also cited as one of the reference source documents for the default value for depth of upper benthic layer (dbs). The default value is the midpoint of an

acceptable range. This document cites U.S. EPA (1993a) and U.S. EPA (1993b) as its source of information for the range of values for the depth of the upper benthic layer. This document

is also cited as one of the reference source documents for the default bed sediment concentration (CBS). This document cites U.S. EPA (1993b) as its source. 

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and

Development. EPA 452/R-97-005. December.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

This document is also cited as the source of the equation for calculating bed sediment porosity (2sw). No source of this equation was identified. This document was also cited as the source

for the range of the bed sediment concentration (CBS). No source of this range was identified. 
TABLE B-4-26

FISH CONCENTRATION FROM BIOCONCENTRATION FACTORS USING DISSOLVED PHASE WATER CONCENTRATION

(CONSUMPTION OF FISH EQUATIONS)

(Page 1 of 3)

B-267

Description

This equation calculates fish concentration, from dissolved COPCs, by using a bioconcentration factor. Uncertainty associated with this equation include the following:

Calculating Cdw is dependent on default values for two variables Cwctot and Kdsw. Values for these two variables are, in turn, dependent on default medium-specific OC content values. 

Because OC content can vary widely at different locations in the same medium, significant uncertainty may be associated with Cwctot and Kdsw and, in turn, Cdw in specific instances.

Equation

Variable Description Units Value

Cfish

Concentration of COPC in fish mg

COPC/kg

FW tissue

Cdw

Dissolved phase water

concentration 

mg

COPC/L

Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-24.

Uncertainties associated with this variable include the following: 

(1) The variables in the equation in Table B-4-24 are site-specific. Therefore, using default values rather than site-specific

values, for any or all of these variables, will contribute to the under- or overestimating Cdw. We expect the degree of

uncertainty associated with TSS to be relatively small, because information regarding reasonable site-specific values

for this variable is generally available or can be easily measured.

(2) The uncertainty associated with the variables Cwctot and Kdsw is dependent on estimates of OC content. Because OC

content values can vary widely for different locations in the same medium, the uncertainty associated with using

different OC content values may be significant in specific cases.
TABLE B-4-26

FISH CONCENTRATION FROM BIOCONCENTRATION FACTORS USING DISSOLVED PHASE WATER CONCENTRATION

(CONSUMPTION OF FISH EQUATIONS)

(Page 2 of 3)

Variable Description Units Value

B-268

BCFfish

Bioconcentration factor for COPC

in fish

unitless

([mg

COPC/kg

FW

tissue]/[mg

COPC/kg

feed])

Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in the

HHRAP companion database.

As explained in Appendix A-2, we recommend using BCFs for organic COPCs with log Kow less than 4.0 and BAFs (rather than

BCFs) for organic COPCs with log Kow of 4.0 or greater. For organics with a log Kow value of less than 4.0 and all metals

(except lead and mercury), we obtained values from U.S. EPA (1998) or, when measured values were not available, derived

from the correlation equation presented by Lyman et al. (1982). 

The following uncertainty is associated with this variable:

The COPC-specific BCF values may not accurately represent site-specific water body conditions, because estimates of

BCFs and BAFs can vary, based on experimental conditions.

REFERENCES AND DISCUSSION

Ellgenhausen, H. J., A. Guth, and H.O. Esser. 1980. “Factors Determining the Bioaccumulation Potential of Pesticides in the Individual Compartments of Aquatic Food Chains.” Ecotoxicology

Environmental Safety. Vol. 4. P. 134.

BCFs for pesticides and polycyclic aromatic hydrocarbons (PAHs) with log Kow less than 5.5 were apparently calculated by using the following equation derived for pesticides from this

document:

log BCF = 0.83 A log Kow - 1.71

where

BCF = Bioconcentration factor for COPC in fish(unitless)

Kow = Octanol-water partition coefficient (unitless)

Lyman, W.J., W.F. Reehl, and D.H. Rosenblatt. 1982. Handbook of Chemical Property Estimation Methods: Environmental Behavior of Organic Compounds. McGraw-Hill Book Company. New

York, New York.

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document cites Ogata et al. (1984), U.S. EPA (1994, 1995) as its sources of the equations used to calculate BCFs fish:
TABLE B-4-26

FISH CONCENTRATION FROM BIOCONCENTRATION FACTORS USING DISSOLVED PHASE WATER CONCENTRATION

(CONSUMPTION OF FISH EQUATIONS)

(Page 3 of 3)

B-269

Ogata, M.K., Y. Ogino Fijusaw, and E. Mano. 1984. “Partition Coefficients as a Measure of Bioconcentration Potential of Crude Oil Compounds in Fish and Shellfish.” Bulletin of Environmental

Contaminant Toxicology. Vol. 33. P. 561.

BCFs for compounds with log Kow less than 5.5 were calculated by using the following equation derived for aromatic compounds from this document:

log BCF = 0.71 A log Kow - 0.92

where

BCF = Bioconcentration factor for COPC in fish (unitless)

Kow = Octanol-water partition coefficient (unitless)

U.S. EPA. 1994. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

U.S. EPA. 1995. Review Draft Development of Human-Health Based and Ecologically - Based Exit Criteria for the Hazardous Waste Identification Project. Volumes I and II. Office of Solid

Waste. March.

This document recommends that the following references be used:

C BCFs for organic COPCs with log Kow less than 4.0 should be based on equations presented in Thomann, R.V. 1989. “Bioaccumulation Model of Organic Chemical Distribution

in Aquatic Food Chains.” Environmental Science and Technology-23(b): 699-707.

C BAFs for organic COPCs with log Kow greater than or equal to 4.0 and less than 6.5 are estimated on the basis of models presented in Thomann (1989) - see above - for the limnetic

ecosystem, or for the littoral ecosystem, based on the following document:

- Thomann, R.V., J.P. Connolly, and T.F. Parkerton. 1992. “An Equilibrium Model of Organic Chemical Accumulation in Aquatic Food Webs with Sediment

Interaction.” Environmental Toxicology and Chemistry. 11:615-629.

C For organics with log Kow greater than or equal to 6.5, a default BAF of 1,000 was assumed on the basis of an analysis of available data on polycyclic aromatic hydrocarbons

(PAH), and the following document:

- Stephan, C.E. et al. 1993. “Derivation of Proposed Human Health and Wildlife Bioaccumulation Factors for the Great Lake Initiative.” Office of Research and

Development. U.S. EPA Research Laboratory. PB93-154672. Springfield, Virginia.

C BCFs for inorganics were obtained from various literature sources and the AQUIRE electronic database.

All BCFs and BAFs were corrected to 5 percent lipid, reflecting a typical value for a fish fillet.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December. Environmental Criteria and Assessment Office. ORD. Cincinnati, Ohio.

U.S. EPA. 1999. Screening Level Ecological Risk Assessment Protocol for Hazardous Waste Combustion Facilities. Peer Review Draft. Office of Solid Waste. August.
TABLE B-4-27

FISH CONCENTRATION FROM BIOACCUMULATION FACTORS USING DISSOLVED PHASE WATER CONCENTRATION

(CONSUMPTION OF FISH EQUATIONS)

(Page 1 of 3)

B-270

Description

This equation calculates fish concentration from dissolved COPC concentration by using a bioaccumulation factor. Uncertainty associated with this equation include the following:

Calculating Cdw uses on default values for variables Fwater and Cwtot. Values for these two variables, in turn, depend on default medium-specific OC content values. Because OC content

can vary widely at different locations in the same medium, significant uncertainty may be associated with Fwater and Cwtot, and, in turn, Cwt in specific instances.

Equation

For mercury modeling, the concentration of COPC in fish is calculated for divalent mercury (Hg 2+) and methyl mercury (MHg) as shown in the following equations: 

Variable Description Units Value

Cfish

Concentration of COPC in fish mg

COPC/kg

FW tissue
TABLE B-4-27

FISH CONCENTRATION FROM BIOACCUMULATION FACTORS USING DISSOLVED PHASE WATER CONCENTRATION

(CONSUMPTION OF FISH EQUATIONS)

(Page 2 of 3)

Variable Description Units Value

B-271

Cdw

Dissolved phase water

concentration 

mg

COPC/L

Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-24.

Uncertainties associated with this variable include the following: 

(1) The variables in the equation in Table B-4-24 are site-specific. Therefore, using default values rather than site-specific

values, for any or all of these variables, will contribute to under- or overestimating Cdw. We expect the degree of

uncertainty associated with TSS to be relatively small, because information regarding reasonable site-specific values

for this variable is generally available or can be easily measured.

(2) The uncertainty associated with the variables Cwctot and Kdsw depends on estimates of OC content. Because OC content

values can vary widely for different locations in the same medium, the uncertainty associated with using different OC

content values may be significant in specific cases.

BAFfish

Bioaccumulation factor for COPC

in fish

L/kg FW

tissue

Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in the

HHRAP companion database. As discussed in Appendix A-2, BAFfish values were adjusted for dissolved water concentrations.

We obtained BAFs for all organics with a log Kow greater than or equal to 4.0 from U.S. EPA (1998), which cites U.S. EPA

(1995a), U.S. EPA (1995b), and U.S. EPA (1994b). We calculated the BAFfish value for lead as a geometric mean of data from

various literature sources described in U.S. EPA (1998). We don’t expect Elemental mercury to deposit significantly onto soils

and surface water; therefore, assume no transfer of elemental mercury to fish. Assume that all mercury in fish exists or is

converted to the methyl mercury (organic) form after uptake into the fish tissue. For this HHRAP, we use the BAFfish value for

methyl mercury listed in U.S. EPA (1997) for a trophic level 4 fish.

The following uncertainty is associated with this variable:

The COPC-specific BAF values may not accurately represent site-specific water body conditions, because estimates of

BAFs can vary, based on experimental conditions. 

REFERENCES AND DISCUSSION

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document cites the following documents as its sources of information regarding BAFs:
TABLE B-4-27

FISH CONCENTRATION FROM BIOACCUMULATION FACTORS USING DISSOLVED PHASE WATER CONCENTRATION

(CONSUMPTION OF FISH EQUATIONS)

(Page 3 of 3)

B-272

U.S. EPA. 1993. “Derivation of Proposed Human Health and Wildlife Bioaccumulation Factors for the Great Lakes Initiative.” Office of Research and Development, U.S. Environmental Research

Laboratory. Duluth, Minnesota. March.

This study presents three methods for estimating BAFs, in the following order of preference (first to last): (1) measured BAF; (2) measured BCF multiplied by a food-chain multiplier

estimated from log Kow; and (3) BAF estimated from log Kow.

U.S. EPA 57 Federal Register 20802. 1993. “Proposed Water Quality Guidance for the Great Lakes System.” April.

This document recommends using BAFs for compounds with a log Kow greater than 5.5.

U.S. EPA. 1994. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes Attachment C, Draft Exposure 

Assessment Guidance for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December.

U.S. EPA. 1995a. Review Draft Development of Human Health-Based and Ecologically-Based Exit Criteria for the Hazardous Waste Identification Project. Volumes I and II. Office of Solid Waste. 

March 3.

This document recommends that the following references be used.

C BAFs for organic COPCs with log Kow greater than 4.0 but less than 6.5 should be calculated from the following references for the limetic ecosystem and the literal ecosystem,

respectively.

- Thomann, R.V. 1989. “Bioaccumulation Model of Organic Chemical Distribution in Aquatic Food Chains.” Environmental Science and Technology. 

23(6):699-707.

- Thomann, R.V., J.P. Connolly, and T.F. Parkerton. 1992. “An Equilibrium Model of Organic Chemical Accumulation in Aquatic Food Webs with Sediment

Interaction.” Environmental Toxicology and Chemistry. 11:6115-629.

C BAFs for compounds with logKow greater than 6.5 were allowed to equal 1,000, based on an analysis of available data on PAHs and the following document:

- Stephan, C.E. et al. 1993. “Derivation of Proposed Human Health and Wildlife Bioaccumulation Factors for the Great Lakes Initiative.” Office of Research and

Development, U.S. Environmental Research Laboratory. PB93-154672. Springfield, Virigina.

All BAFs were corrected to 5 percent lipid, reflecting a typical value for a fish fillet.

U.S. EPA. 1995b. Great Lakes Water Quality Initiative. Technical Support Document for the Procedure to Determine Bioaccumulation Factors. Office of Water. EPA-820-B-95-005. March.

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and

Development. EPA 452/R-97-005. December.

U.S. EPA. 1998. “Methodology for Assessing Health Risks Associated with Multiple Pathways of Exposure to Combustor Emissions.” Update to EPA/600/6-90/003. Office of Research and

Development, National Center for Environmental Assessment, U.S. EPA. EPA/600/R-98/137. December.

U.S. EPA. 1999. Screening Level Ecological Risk Assessment Protocol for Hazardous Waste Combustion Facilities. Peer Review Draft. Office of Solid Waste. August.
TABLE B-4-28

FISH CONCENTRATION FROM BIOTA-TO-SEDIMENT ACCUMULATION FACTORS USING COPC SORBED TO BED SEDIMENT

(CONSUMPTION OF FISH EQUATIONS)

(Page 1 of 3)

B-273

Description

This equation calculates fish concentration from bed sediment concentration, by using a biota-to-sediment accumulation factor (BSAF). Uncertainties associated with this equation include the

following:

(1) Calculation of Csb is largely dependent on default medium-specific OC content values. Because OC content can vary widely within a medium, significant uncertainty may be associated

with estimates of Csb in specific instances.

(2) Lipid content varies between different species of fish. Therefore, use of a default flipid value results in a moderate degree of uncertainty.

(3) Some species of fish have limited, if any, contact with water body sediments. Therefore, use of BSAFs to estimate the accumulation of COPCs in these species may be significantly

uncertain.

Equation

Variable Description Units Value

Cfish

Concentration of COPC in fish mg

COPC/kg

FW tissue

Csb

Concentration of COPC sorbed to

bed sediment

mg

COPC/kg

bed

sediment

Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-25.

Uncertainties associated with this variable include the following: 

(1) The default variable values recommended for use in the equation in Table B-4-25 may not accurately represent sitespecific water body conditions. We expect the degree of uncertainty associated with variables 2bs, TSS, dwc, and dbs to

be limited either because the probable ranges for these variables are narrow or information allowing reasonable

estimates is generally available.

(2) Uncertainty associated with variables fbs, Cwtot, and Kdbs is largely associated with the use of default OC content values. 

Because OC content is known to vary widely in different locations in the same medium, use of default medium-specific

values can result in significant uncertainty in some instances.
TABLE B-4-28

FISH CONCENTRATION FROM BIOTA-TO-SEDIMENT ACCUMULATION FACTORS USING COPC SORBED TO BED SEDIMENT

(CONSUMPTION OF FISH EQUATIONS)

(Page 2 of 3)

Variable Description Units Value

B-274

flipid

Fish lipid content unitless 0.03 to 0.07

We recommend this default range of values to be representative of warm water non-salmonoid fish (3 percent lipid content) at the

low end and cold water salmonoid game fish at the high end (7 percent lipid content). Examples of non-salmonoid fish that may

have lipid percentages in the edible portion at the lower end of the range would be catfish, northern pike, and walleye. U.S. EPA

(1994a) and U.S. EPA (1994b) recommended values of 7 percent, which was originally cited by Cook et al. (1991). A value of

3 percent lipid content for the edible portion is provided by U.S. EPA (2000). 

The following uncertainty is associated with this variable:

(1) Lipid content may vary between different species of fish. Therefore, using a default flis value may result in under- or

overestimating Cfish.

BSAF Biota-to-sediment accumulation

factor

unitless

([mg

COPC/kg

lipid

tissue]/[m

g

COPC/kg

sediment])

Varies

This variable is COPC-specific. We discuss this variable in detail in Appendix A-2, and offer COPC-specific values in the

HHRAP companion database. 

These factors are applied only to PCDDs, PCDFs, and polychlorinated biphenyls (PCBs), consistent with NC DEHNR (1997),

U.S. EPA (1992), U.S. EPA (1994), and U.S. EPA (1995). 

Uncertainty is associated with this variable: 

The greatest uncertainty associated with using BSAFs is that some species of fish have limited, if any, contact with

water body sediments. Any accumulation of compounds into the tissue of these fishes is almost entirely the result of

contact with surface water. Therefore, using BSAFs to estimate COPC accumulation in these species may be uncertain.

OCsed

Fraction of organic carbon in

bottom sediment

unitless 0.04

This variable is site-specific. We recommend a default value of 0.04, the midpoint of the range (0.03 to 0.05), if site-specific

information is not available. This is consistent with other U.S. EPA (1994b) and NC DEHNR (1997) guidance. 

The following uncertainty is associated with this variable:: 

The recommended OCsed value may not accurately represent site-specific water body conditions. However, as indicated

by the probable range of values for this parameter, we expect any uncertainty to be limited in most cases.
TABLE B-4-28

FISH CONCENTRATION FROM BIOTA-TO-SEDIMENT ACCUMULATION FACTORS USING COPC SORBED TO BED SEDIMENT

(CONSUMPTION OF FISH EQUATIONS)

(Page 3 of 3)

B-275

REFERENCES AND DISCUSSION

Cook, P.M., D.W. Duehl, M.K. Walker, and R.E. Peterson. 1991. Bioaccumulation and Toxicity of TCDD and Related Compounds in Aquatic Ecosystems. In Gallo, M.A., R.J. Scheuplein, and K.A.

Van Der Heijden (eds). Banbury Report 35: Biological Basis for Risk Assessment of Dioxins and Related Compounds. Cold Spring Harbor Laboratory Press. 0-87969-235-9/91.

This document is cited by U.S. EPA (1992) and U.S. EPA (1994) as the source of the fish lipid content value. 

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is cited as one of the reference source documents for biota-to-sediment factors for PCBs and dioxins. This document cites U.S. EPA (1992) as its source. This document is

also cited as one of the reference documents for the default value for fraction OC in bottom sediment. The default value is the midpoint of the range obtained from U.S. EPA (1993). No

source of this recommendation was identified. 

This document is cited as one of the reference source documents for the fish lipid content value. The document cites Cook, Duehl, Walker, and Peterson (1991) as its original source of

information. This document is also cited by U.S. EPA (1994) and NC DEHNR (1997) as the source of the BSAFs. BSAF values from this document were either measured values or

estimates based on a whole fish lipid content of 7 percent. Specifically, BSAF values from this document must be evaluated because of the difficult experimental methods used to derive

them.

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume III: Site-specific Assessment Procedures. External Review Draft. Office of Research and Development. Washington.

D.C. EPA/600/6-88/005Cc. June.

U.S. EPA. 1994b. Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. April.

This document is cited as one of the reference source documents for the fish lipid content value. The document cites Cook, Duehl, Walker, and Peterson (1991) as its original source of

information. This document is also cited as one of the reference source documents for biota-to-sediment factors for PCBs and dioxins. This document cites U.S. EPA (1992) as its source of

information. This document is also cited as one of the reference documents for the default fraction OC in bottom sediment value. The default value is the midpoint of the range obtained

from U.S. EPA (1993). No source of this recommendation was identified.

U.S. EPA. 1995. Review Draft Development of Human Health-Based and Ecologically-Based Exit Criteria for the Hazardous Waste Identification Project. Volumes I and II. Office of Solid Waste. 

March.

U.S. EPA. 2000. Draft Methodology for Deriving Ambient Water Quality Criteria for Protection of Human Health. Technical Support Document Volume III: Bioaccumulation Part 1 - Development

of National Bioaccumulation Factors. Office of Science and Technology in the Office of Water.

This document is cited as one of the reference source documents for the fish lipid content value.
TABLE B-5-1

AIR CONCENTRATION

(DIRECT INHALATION EQUATION)

(Page 1 of 3)

B-276

Description

This equation calculates the air concentration of a COPC based on the fraction in vapor phase and the fraction in particle phase.

Uncertainties associated with this equation include the following:

(1) Most of the uncertainties associated with the variables in this equation—specifically, those associated with variables Q, Cyv, and Cyp—are site-specific.

(2) In calculation of Fv, the equation assumes a default ST value for background plus local sources, rather than an ST value for urban sources. If a specific site is located in an urban area, the

use of the latter ST value may be more appropriate. Specifically, the ST value for urban sources is about one order of magnitude greater than the ST value for background plus local sources

and would result in a lower calculated Fv value; however, the Fv value is likely to be only a few percent lower.

Equation

For all COPCs (except mercury)

Air concentration is calculated using (1) 0.002Q and Fv = 1.0 for elemental mercury (Hg0) and (2) 0.48Q and Fv = 0.85 for divalent mercury (Hg2+). Elemental mercury is evaluated only for the

inhalation exposure pathway (see discussion in Chapter 2).

Variable Description Units Value

Ca

Air concentration :g/m3

Q COPC-specific emission rate g/s Varies

This variable is COPC- and site-specific. See Chapters 2 and 3 for guidance on calculating this variable. Uncertainties

associated with this variable are COPC- and site-specific. 
TABLE B-5-1

AIR CONCENTRATION

(DIRECT INHALATION EQUATION)

(Page 2 of 3)

Variable Description Units Value

B-277

Fv

Fraction of COPC air concentration

in vapor phase 

unitless 0 to 1

This variable is COPC-specific. We discuss Fv

in detail in Appendix A-2, and offer COPC-specific values in the HHRAP

companion database. This range is based on values presented in Appendix A-2. Values are also presented in U.S. EPA (1994b)

and NC DEHNR (1997). 

Fv was calculated using an equation presented in Junge (1977) for all organic COPCs, including PCDDs and PCDFs. U.S. EPA

(1994c) states that Fv = 0 for all metals (except mercury).

The following uncertainties are associated with this variable:

(1) It uses a default ST value for background plus local sources, rather than an ST value for urban sources. If a specific site

is located in an urban area, using the latter ST value may be more appropriate. Specifically, the ST value for urban

sources is about one order of magnitude greater than that for background plus local sources, and it would result in a

lower calculated Fv

 value; however, the Fv

 value is likely to be only a few percent lower.

(2) According to Bidleman (1988), the equation used to calculate Fv assumes that the variable c (Junge constant) is

constant for all chemicals; however, the value of c depends on the chemical (sorbate) molecular weight, the

surface concentration for monolayer coverage, and the difference between the heat of desorption from the particle

surface and the heat of vaporization of the liquid-phase sorbate. To the extent that site- or COPC-specific conditions

may cause the value of c to vary, uncertainty is introduced if a constant value of c is used to calculate Fv.

Cyv Unitized yearly air concentration

from vapor phase

:g-s/g-m3 Varies

This variable is COPC- and site-specific and is determined by air dispersion modeling (see Chapter 3). Uncertainties associated

with this variable are COPC- and site-specific. 

Cyp Unitized yearly air concentration

from particle phase

:g-s/g-m3 Varies

This variable is COPC- and site-specific and is determined by air dispersion modeling (see Chapter 3). Uncertainties associated

with this variable are COPC- and site-specific. 
TABLE B-5-1

AIR CONCENTRATION

(DIRECT INHALATION EQUATION)

(Page 3 of 3)

B-278

REFERENCES AND DISCUSSION

Bidleman, T.F. 1988. “Atmospheric Processes.” Environmental Science and Technology. Volume 22. Number 4. Pages 361-367.

For discussion, see References and Discussion, Table B-1-1.

Junge, C.E. 1977. Fate of Pollutants in Air and Water Environments, Part I. Suffet, I.H., Ed. Wiley. New York. Pages 7-26.

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document recommends using the equations in Bidleman (1988) to calculate Fv

 values for all organics other than dioxins (PCDD/PCDFs). However, this document does not present a

recommendation for dioxins. This document also states that metals are generally entirely in the particulate phase (Fv = 0), except for mercury, which is assumed to be entirely in the vapor

phase. The document does not state whether Fv for mercury should be calculated by using the equations in Bidleman (1988).

U.S. EPA. 1994. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document presents Fv

 values for organic COPCs that range from 0.27 to 1. Fv

 values for organics other than PCDD/PCDFs are calculated by using the equations presented in Bidleman

(1988). The Fv

 value for PCDD/PCDFs is assumed to be 0.27. This value represents dioxin TEQs by weighting data for all dioxin and furan congeners with nonzero TEFs. This document

presents Fv values for most inorganic COPCs equal to 0, based on the assumption that these COPCs are nonvolatile and assumed to be 100 percent in the particulate phase and 0 percent in the

vapor phase.

U.S. EPA. 1997. Mercury Study Report to Congress. Volume III: Fate and Transport of Mercury in the Environment. Office of Air Quality and Planning and Standards and Office of Research and 

Development. EPA 452/R-97-005. December.
TABLE B-6-1

ACUTE AIR CONCENTRATION EQUATION

(ACUTE EQUATION)

(Page 1 of 3)

B-279

Description

This equation calculates the total air concentration of a COPC (hourly) based on the fraction in vapor phase and the fraction in particle phase.

Uncertainties associated with this equation include the following:

(1) Most of the uncertainties associated with the variables in this equation—specifically, those associated with variables Q, Chv, and Chp—are site-specific.

(2) In calculating Fv, the equation assumes a default ST value for background plus local sources, rather than an ST value for urban sources. If a specific site is located in an urban area, using the

latter ST value may be more appropriate. Specifically, the ST value for urban sources is about one order of magnitude greater than the ST value for background plus local sources and would

result in a lower calculated Fv value; however, the Fv value is likely to be only a few percent lower.

Equation

For all COPCs (except mercury)

Consistent with Table B-5-1, air concentration is calculated using (1) 0.002Q and Fv

 = 1.0 for elemental mercury (Hg0) and (2) 0.48Q and Fv

 = 0.85 for divalent mercury (Hg2+). Although calculated

as separate species, acute toxicity benchmarks are not available for mercury and therefore, acute air concentration for each species should be summed for comparison to the acute toxicity benchmark

for mercury.

Variable Description Units Value

Cacute

Acute air concentration :g/m3

Q COPC-specific emission rate g/s Varies

This variable is COPC- and site-specific. See Chapters 2 and 3 for guidance regarding the calculation of this variable. 

Uncertainties associated with this variable are COPC- and site-specific. 
TABLE B-6-1

ACUTE AIR CONCENTRATION EQUATION

(ACUTE EQUATION)

(Page 2 of 3)

Variable Description Units Value

B-280

Fv

Fraction of COPC air concentration

in vapor phase 

unitless 0 to 1

This variable is COPC-specific. We discuss Fv

in detail in Appendix A-2, and offer COPC-specific values in the HHRAP

companion database. This range is based on values presented in Appendix A-2. Values are also presented in U.S. EPA (1994b)

and NC DEHNR (1997). 

Fv was calculated using an equation presented in Junge (1977) for all organic COPCs, including PCDDs and PCDFs. U.S. EPA

(1994c) states that Fv = 0 for all metals (except mercury).

The following uncertainties are associated with this variable:

(1) It assumes a default ST value for background plus local sources, rather than an ST value for urban sources. If a specific

site is located in an urban area, using the latter ST value may be more appropriate. Specifically, the ST value for urban

sources is about one order of magnitude greater than that for background plus local sources, and it would result in a

lower calculated Fv

 value; however, the Fv

 value is likely to be only a few percent lower.

(2) According to Bidleman (1988), the equation used to calculate Fv assumes that the variable c (Junge constant) is

constant for all chemicals; however, the value of c depends on the chemical (sorbate) molecular weight, the

surface concentration for monolayer coverage, and the difference between the heat of desorption from the particle

surface and the heat of vaporization of the liquid-phase sorbate. To the extent that site- or COPC-specific conditions

may cause the value of c to vary, uncertainty is introduced if a constant value of c is used to calculate Fv.

Chv Unitized hourly air concentration

from vapor phase

:g-s/g-m3 Varies

This variable is COPC- and site-specific and is determined by air dispersion modeling (see Chapter 3). Uncertainties associated

with this variable are COPC- and site-specific. 

Chp Unitized hourly air concentration

from particle phase

:g-s/g-m3 Varies

This variable is COPC- and site-specific and is determined by air dispersion modeling (see Chapter 3). Uncertainties associated

with this variable are COPC- and site-specific. 

REFERENCES AND DISCUSSION

Bidleman, T.F. 1988. “Atmospheric Processes.” Environmental Science and Technology. Volume 22. Number 4. Pages 361-367.

For discussion, see References and Discussion, Table B-1-1.

Junge, C.E. 1977. Fate of Pollutants in Air and Water Environments, Part I. Suffet, I.H., Ed. Wiley. New York. Pages 7-26.
TABLE B-6-1

ACUTE AIR CONCENTRATION EQUATION

(ACUTE EQUATION)

(Page 3 of 3)

B-281

NC DEHNR. 1997. Final NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document recommends using the equations in Bidleman (1988) to calculate Fv values for all organics other than dioxins (PCDD/PCDFs). However, this document does not present a

recommendation for dioxins. This document also states that metals are generally entirely in the particulate phase (Fv = 0), except for mercury, which is assumed to be entirely in the vapor

phase. The document does not state whether Fv for mercury should be calculated by using the equations in Bidleman (1988).

U.S. EPA. 1994. Revised Draft Guidance for Performing Screening Level Risk Analysis at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document presents Fv

 values for organic COPCs that range from 0.27 to 1. Fv

 values for organics other than PCDD/PCDFs are calculated by using the equations presented in Bidleman

(1988). The Fv

 value for PCDD/PCDFs is assumed to be 0.27. This value represents dioxin TEQs by weighting data for all dioxin and furan congeners with nonzero TEFs. This document

presents Fv values for most inorganic COPCs equal to 0, based on the assumption that these COPCs are nonvolatile and assumed to be 100 percent in the particulate phase and 0 percent in the

vapor phase.

U.S. EPA. 1997. “Mercury Study Report to Congress.” Volume III. Draft. Office of Air Quality and Planning and Standards and Office of Research and Development. December.
APPENDIX C

RISK CHARACTERIZATION EQUATIONS

Table Equation

C-1-1 COPC INTAKE FROM SOIL

C-1-2 COPC INTAKE FROM PRODUCE

C-1-3 COPC INTAKE FROM BEEF, MILK, PORK, POULTRY, AND EGGS

C-1-4 COPC INTAKE FROM FISH

C-1-5 COPC INTAKE FROM DRINKING WATER

C-1-6 TOTAL DAILY INTAKE

C-1-7 INDIVIDUAL CANCER RISK

C-1-8 HAZARD QUOTIENT

C-1-9 TOTAL CANCER RISK

C-1-10 TOTAL HAZARD INDEX

C-1-11 SEGREGATED HAZARD INDEX FOR SPECIFIC ORGAN EFFECTS

C-2-1 INHALATION CANCER RISK FOR INDIVIDUAL CHEMICALS

C-2-2 INHALATION HAZARD QUOTIENT FOR COPCS

C-2-3 TOTAL INHALATION CANCER RISK

C-2-4 HAZARD INDEX FOR INHALATION

C-3-1 CONCENTRATION OF DIOXINS AND DIOXIN-LIKE PCBs IN BREAST MILK

C-3-2 AVERAGE DAILY DOSE TO THE EXPOSED INFANT

C-4-1 ACUTE HAZARD QUOTIENT
TABLE C-1-1

COPC INTAKE FROM SOIL

(Page 1 of 4)

C-1

Description

This equation calculates the daily intake of COPC from soil consumption. The soil concentration will vary with each scenario location, and the soil consumption rate varies for children and

adults. Uncertainties associated with this equation include:

(1) Assume that the amount of soil intake is constant and representative of the exposed population. This assumption may under- or overestimate Isoil

.

(2) The standard assumptions regarding period exposed might not be representative of an actual exposure situation. This assumption may under- or overestimate Isoil. 

Equation

Variable Description Units Value

Isoil

Daily intake of COPC from soil mg/kgday

Cs Average soil concentration over

exposure duration 

mg/kg Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-1-1. Cs varies based on whether the

COPC is carcinogenic or noncarcinogenic.

For carcinogenic COPCs, this value is equal to the soil concentration averaged over the exposure duration (Table B-1-1) (U.S.

EPA 1994 and NC DEHNR 1997). For noncarcinogenic COPCs, this value is equal to the highest annual soil concentration

occurring within the exposure duration. The highest annual soil concentration would most likely occur at the end of the time

period of combustion (Table B-1-1) (U.S. EPA 1994 and NC DEHNR 1997).

The following uncertainties are associated with this variable:

(1) We assume that the time period for deposition of COPCs resulting from hazardous waste combustion is a conservative,

long-term value. This assumption may overestimate Cs and CstD.

(2) Exposure duration values (T2) are based on historical mobility studies and won’t necessarily remain constant. Specifically,

mobility studies indicate that most receptors that move remain in the vicinity of the combustion unit; however, it is

impossible to accurately predict the probability that these short-distance moves will influence exposure, based on factors

such as atmospheric transport of pollutants.

(3) Using a value of zero for T1 doesn’t account for exposure that may have occurred from historic operations and emissions

from hazardous waste combustion. This may underestimate Cs and CstD.

(4) For soluble COPCs, leaching might lead to movement to below the mixing depth, resulting in lower concentrations within

the mixing depth. This uncertainty may overestimate Cs and CstD. 

(5) Deposition to hard surfaces may result in dust residues that have negligible dilution (as a result of potential mixing with in

situ materials) compared to other residues. This may underestimate Cs and CstD. 
TABLE C-1-1

COPC INTAKE FROM SOIL

(Page 2 of 4)

Variable Description Units Value

C-2

CRsoil

Consumption rate of soil kg/day 0.0001 to 0.0002

The soil consumption rate varies for the adult and child receptors (U.S. EPA 1997). 

Receptor Intake Rate (kg/day)

Adult 0.0001

Child 0.0002

U.S. EPA (1997) recommends using a child intake rate of 0.0002 kg/day for a child receptor as a conservative estimate of

exposure. These values are consistent with U.S. EPA (1991). U.S. EPA (1997) references studies done by Hawley (1985) and

Calabrese (1990) as the sources used to derive soil consumption rates. 

Uncertainties associated with this variable include:

(1) Tracer studies have resulted in wide ranging estimates of the amount of soil and dust ingested by young children, making

it difficult to identify a single value to use. It is also extremely difficult to separate the contribution of exposure resulting

from exterior soil vs. interior dust. As a result, the intake rate is reported as the combined rate for soils and dusts. This

uncertainty may under- or overestimate CR soil.

(2) Our recommended intake rates may not accurately represent behavioral characteristics since they are upper estimates. This

uncertainty may overestimate CRsoil.

(3) The intake rates represent normal mouthing tendencies. Some children exhibit abnormal mouthing (i.e. “pica” ) behavior

and would have much higher intake rates. This uncertainty may considerably underestimate CRsoil.

Fsoil

Fraction of soil that is contaminated unitless 1.0

We recommend assuming that all consumed soil is contaminated. This is consistent with NC DEHNR (1997) and U.S. EPA

(1994), which assume the fraction of consumed soil contaminated is 1.0 for all exposure scenarios. 

Uncertainty associated with this variable include:

U.S. EPA guidance recommends the fraction of consumed soil contaminated is equal to 1.0. However, due to variations

in the proximity of the receptor to the contaminated source, size of the contaminated source, receptors of concern,

mobility of receptors, and nature of exposure, this assumption may underestimate or overestimate Fsoil.
TABLE C-1-1

COPC INTAKE FROM SOIL

(Page 3 of 4)

Variable Description Units Value

C-3

BW Body weight kg 15 or 70

We recommend using default values of 70 (adults) and 15 (children). These default values are consistent with U.S. EPA (1991;

1994). 

Uncertainty associated with this variable include:

These body weights represent the average weight of an adult and child. However, depending on the actual receptor, body

weights may be higher or lower. These default values may overestimate or underestimate actual body weights. However,

the degree of under- or overestimation is not expected to be significant. 

REFERENCES AND DISCUSSION

Calabrese, E.J., Stanek, E.J., Gilbert, C.E., and Barnes, R.M. 1990. Preliminary adult soil ingestion estimates; results of a pilot study. Regul. Toxicol. Pharmacol. 12:88-95.

This document is cited by U.S. EPA (1997) as a source of information used to derive soil consumption rates.

Hawley, J.K. 1985. Assessment of health risk from exposure to contaminated soil. Risk Analysis 5:289-302.

This document is cited by U.S. EPA (1997) as a source of information used to derive soil consumption rates.

NC DEHNR. 1997. North Carolina Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the sources for the equation in Table C-1-1. This document also states that (1) for carcinogenic COPCs, Cs is equal to the soil concentration averaged over the

exposure duration; however, no reference document is cited and (2) for noncarcinogenic COPCs, Cs is equal to the highest annual soil concentration occurring within the exposure duration; the

highest annual soil concentration would occur at the end of the time period of emissions.

U.S. EPA. 1991. Human Health Evaluation Manual, Supplemental Guidance: Standard Default Exposure Factors. Office of Solid Waste and Emergency Response. OSWER Directive

9285.6-03. Washington, D.C. March 21.

This document is cited as the reference source document of soil ingestion rates, and the exposure frequency and body weight variables. 

U.S. EPA. 1994. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document is one of the sources for the equation in Table C-1-1. This document also states that (1) for carcinogenic COPCs, Cs is equal to the soil concentration averaged over the

exposure duration; however, no reference document is cited and (2) for noncarcinogenic COPCs, Cs is equal to the highest annual soil concentration occurring within the exposure duration; the

highest annual soil concentration would occur at the end of the time period of emissions.
TABLE C-1-1

COPC INTAKE FROM SOIL

(Page 4 of 4)

C-4

U.S. EPA. 1997. Exposure Factors Handbook. Office of Research and Development. EPA/600/P-95/002F. August.

This document is the source for soil consumption rates.
TABLE C-1-2

COPC INTAKE FROM PRODUCE

(Page 1 of 4 )

C-6

Description

This equation calculates the daily intake of COPC from ingestion of exposed aboveground, protected aboveground, and belowground produce. The consumption rate varies for children and

adults, and for the type of produce. The concentration in exposed aboveground, protected aboveground, and belowground produce will also vary with each scenario location.

Consumption rates were derived from the Exposure Factors Handbook (U.S. EPA 1997). U.S. EPA (1997) presents consumption rates based on body weight; therefore, body weight is not

included as a variable in the calculation of Iag.

Uncertainties associated with this equation include the following:

(1) The amount of produce intake is assumed to be constant and representative of the exposed population. This assumption may under- or overestimate Iag.

(2) The standard assumptions regarding period exposed may not be representative of any actual exposure situation. This assumption may under- or overestimate Iag. 

Equation

Variable Description Units Value

Iag

Daily intake of COPC from

produce

mg/kg-day

DW

Pd Aboveground exposed

produce concentration due

to direct (wet and dry)

deposition onto plant

surfaces

mg/kg Varies

This variable is COPC- and site-specific, and is calculated by using the equation in Table B-2-7.

Uncertainties associated with this variable include the following:

(1) The recommended equation for calculating kp does not consider chemical degradation processes. Adding chemical degradation

processes would decrease half-lifes and thereby increase kp values; plant concentration decreases as kp increases. Using a kp

value that does not consider chemical degradation processes is protective.

(2) Estimating other parameter values (for example, Fw and Rp) is based directly or indirectly on studies of vegetation other than

aboveground produce (primarily grasses). Uncertainty is introduced to the extent that the calculated parameter values do not

accurately represent aboveground produce-specific values.
TABLE C-1-2

COPC INTAKE FROM PRODUCE

(Page 2 of 4 )

Variable Description Units Value

C-7

Pv Aboveground exposed

produce concentration due

to air-to-plant transfer

mg/kg Varies

This variable is COPC- and site-specific, and is calculated by using the equation in Table B-2-8.

Uncertainties associated with this variable include the following:

(1) The range of values for the variable Bv (air-to-plant biotransfer factor) is about 19 orders of magnitude for organic COPCs. 

(2) The algorithm used to calculate values for the variable Fv assumes a default value for the parameter ST (Whitby’s average surface

area of particulates [aerosols]) of background plus local sources rather than an ST value for urban sources. If a specific site is

located in an urban area, the use of the latter ST value may be more appropriate. The ST value for urban sources is about one order

of magnitude greater than that for background plus local sources and would result in a lower Fv value; however, the Fv value is

likely to be only a few percent lower.

Pr Aboveground exposed and

protected produce

concentration due to root

uptake

mg/kg Varies

This variable is COPC- and site-specific, and is calculated by using the equation in Table B-2-9.

Uncertainty associated with this variable include the following:

Estimated COPC-specific soil-to-plant bioconcentration factors (Br) may not be representative of site-specific conditions.

Prbg

Belowground produce

concentration due to root

uptake

mg/kg Varies

This variable is COPC- and site-specific, and is calculated by using the equation in Table B-2-10.

Uncertainty associated with this variable include the following:

Estimated COPC-specific soil-to-plant bioconcentration factors (Br) may not be representative of site-specific conditions.
TABLE C-1-2

COPC INTAKE FROM PRODUCE

(Page 3 of 4 )

Variable Description Units Value

C-8

CRag;

CRpp;

CRbg

Consumption rate of

aboveground, protected

aboveground, and

belowground produce,

respectively

kg/kg-day

DW

This variable is site-specific. The recommended default values represent the total of the following produce-specific ingestion rates:

Ingestion Rate (kg/kg-day DW)

Plant Type Farmer Farmer Child Resident Res. Child Fisher Fisher Child

Exposed Aboveground Produce (Crag) 0.00047 0.00113 0.00032 0.00077 0.00032 0.00077

Protected Aboveground Produce (Crpp) 0.00064 0.00157 0.00061 0.00150 0.00061 0.00150

Belowground Produce (Crbg) 0.00017 0.00028 0.00014 0.00023 0.00014 0.00023

We derived ingestion rates from U.S. EPA (1997), Tables 13-61, 13-62, 13-63, 13-64, and 13-65. The ingestion rates listed in U.S.

EPA (1997) are derived from the 1987-1988 USDA National Food Consumption Survey and may be used to assess exposure to

contaminants in foods grown at a specific site. The ingestion rates were adjusted for cooking and preparation loss as recommended by

U.S. EPA (1997). The amount of preparation and cooking loss varied depending on type of food consumed. We assumed that no

preparation and cooking loss occurs with exposed fruits because we further assumed this type of fruit is eaten in the raw form. In

addition, ingestion rates for the child receptor represent a time-weighted mean from the respective tables.

Uncertainty associated with this variable include the following:

The recommended ingestion rates are based on national average home produced consumption rates. Site-specific ingestion rates

may be higher or lower than those recommended. Therefore, using the recommended ingestion rates may under- or overestimate

Iag.

Fag

Fraction of produce that is

contaminated

unitless 1.0

This variable is site-specific. We recommend using the default value in the absence of site-specific information, consistent with U.S.

EPA (1997). 

Only that portion of the diet produced at home (and therefore exposed to facility emissions) is of consequence in the risk assessment. 

As detailed above (in Section 6.2.2.2), the consumption rates we recommend represent only the home-produced portion of the diet.

Therefore, by using consumption rates specific to home produced foods, it is reasonable to assume that 100% of those home produced

foods are contaminated. 

The following uncertainty is associated with this variable:

Using default values may overestimate Fag.
TABLE C-1-2

COPC INTAKE FROM PRODUCE

(Page 4 of 4 )

C-9

REFERENCES AND DISCUSSION

Baes, C.F., R.D. Sharp, A.L. Sjoreen, and R.W. Shor. 1984. Review and Analysis of Parameters and Assessing Transport of Environmentally Released Radionuclides through Agriculture. Oak

Ridge National Laboratory. Oak Ridge, Tennessee.

This document is cited as a source for Br values.

U.S. EPA 1990. Exposure Factors Handbook. Office of Health and Environmental Assessment, Exposure Assessment Group. Washington, D.C. March.

This is the document cited as the source of the fraction of produce that is contaminated (Fag) the adult resident, child resident, and fisher. U.S. EPA assumes that Fag for the fisher child is the

same as for the fisher.

U.S. EPA 1992. Technical Support Document for Land Application of Sewage Sludge. Volumes I and II. Office of Water. Washington, D.C. EPA 822/R-93-001a.

This document is cited as a source for plant uptake response slope factors.

U.S. EPA. 1994. Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Waste. Office of Emergency and Remedial Response. Office of Solid Waste.

This document is cited as the source of the fraction of produce that is contaminated (Fag) for the farmer (U.S. EPA assumes that Fag for the farmer child is the same as for the farmer). 

U.S. EPA. 1997. Exposure Factors Handbook. Office of Research and Development. EPA/600/P-95/002F. August.

This document is the source for produce consumption rates.
TABLE C-1-3

COPC INTAKE FROM BEEF, MILK, PORK, POULTRY, AND EGGS

(Page 1 of 4) 

C-10

Description

This equation calculates the daily intake of COPCs from the ingestion of animal tissue (where the i in the equation refers to beef, milk, pork, poultry, or eggs). The consumption rate varies for

children and adults and for the type of animal tissue (j). The concentration in the animal tissue will also vary with each scenario location. 

Consumption rates were derived from the Exposure Factors Handbook (U.S. EPA 1997). U.S. EPA (1997) presents consumption rates based on body weight; therefore, body weight is not

included as a variable in the calculation of Ii

.

Uncertainties associated with this equation include the following:

(1) The amount of animal tissue intake is assumed to be constant and representative of the exposed population. This assumption may under- or overestimate Ii.

(2) The standard assumptions regarding period exposed may not be representative of an actual exposure situation. This assumption may under- or overestimate Ii

. 

Equation

Variable Description Units Value

Ii

Daily intake of COPC i

from animal j tissue

mg/kg-day

Aj

Concentration of COPC i

in animal tissue j

mg/kg FW Varies

This variable is COPC- and site-specific, and is calculated using output from the equations in Tables B-3-10, B-3-11, B-3-12, B-3-13,

and B-3-14.

Uncertainties associated with this variable include the following:

(1) Based on the information provided, Abeef and Apork depend on estimated concentrations of COPCs in plant feeds and soil, and the

biotransfer factors estimated for each constituent. To the extent the estimated concentrations and biotransfer factors do not

reflect site-specific or local conditions, Abeef may be under- or overestimated. 

(2) Uptake of COPCs into chicken and eggs has typically been applied only to PCDDs and PCDFs but could possibly be used to

calculate Achick and Aegg resulting from other COPCs. 

(3) The assumption that 10 percent of a chicken’s diet is soil may not represent site-specific or local conditions of chickens raised

on farms. Stephens, Petreas, and Hayward (1992) and Stephens, Petreas, and Hayward (1995) suggest the percentage of soil in

the diet of chickens raised under field conditions may be greater than 10 percent. Therefore, the concentration of COPCs in

eggs, Aegg, and the concentration of COPCs in chicken, Achick, may be underestimated.
TABLE C-1-3

COPC INTAKE FROM BEEF, MILK, PORK, POULTRY, AND EGGS

(Page 2 of 4) 

Variable Description Units Value

C-11

CRj

Consumption rate of

animal tissue j

kg/kg-day 

FW

Varies

This variable is site-specific. We derived our recommended ingestion rates of animal tissues (see the equation in Table C-1-4 for fish

ingestion) from U.S. EPA (1997):

Animal Tissue Ingestion Rates (kg/kg-day FW)

 Farmer Farmer Child

Homegrown Beef 0.00122 0.00075

Homegrown Milk 0.01367 0.02268

Homegrown Poultry 0.00066 0.00045

Homegrown Eggs 0.00075 0.00054

Homegrown Pork 0.00055 0.00042

Ingestion rates were based on data from U.S. EPA (1997) Tables 13-28, 13-36, 13-43, 43-54, and 13-55. The ingestion rates listed in

U.S. EPA (1997) were derived from the 1987-1988 USDA National Food Consumption Survey and may be used to assess exposure to

contaminants in foods raised at a specific site. Prior to the adjustment for cooking and preparation loss, the mean individual meat

consumption rates were weighted by age group. The ingestion rates were then adjusted for cooking and preparation loss as

recommended in U.S. EPA (1997). The total preparation and cooking loss was in the range of 45 to 54 percent for beef, pork, and

poultry.

In addition, ingestion rates for the child receptor represent a time-weighted mean from the respective tables. Where data for a specific

age group was incomplete, the intake was extrapolated using data from the general population (Tables 11-11 and 11-13 of U.S. EPA

1997). See HHRAP Section 6.2.2.2 for a more detailed explanation of our recommended method for estimating age-appropriate

consumption rates.

U.S. EPA (1997) provides information for total home produced dairy (Table 13-28 of U.S. EPA 1997), but does not specify intake for

fluid milk.

For the metals mercury, selenium, and cadmium, the concentration in beef, milk, and pork, and the consumption rate are in kilograms

dry weight per day. Wet-weight to dry-weight conversion information for beef, milk, and pork is presented in U.S. EPA (1997)

The following uncertainty is associated with this variable:

The recommended tissue-specific consumption rates may not accurately reflect site-specific local conditions. As a result, tissuespecific intakes may be under- or overestimated. 
TABLE C-1-3

COPC INTAKE FROM BEEF, MILK, PORK, POULTRY, AND EGGS

(Page 3 of 4) 

Variable Description Units Value

C-12

Fj

Fraction of animal tissue j

that is contaminated 

unitless 1.0

This variable is site-specific. We recommend an Fj of 1.0 for all animal tissues consumed. This recommendation is consistent with

NC DEHNR (1997).

The following uncertainty is associated with this variable:

The fraction of animal tissue that is contaminated is site-specific; therefore, any of the following may be under- or

overestimated: variations in the proximity of the receptor to the contaminated source, size of the contaminated source, receptors

of concern, mobility of receptors, and nature of exposure.

REFERENCE AND DISCUSSIONS

Stephens, R.D., M.X. Petreas, and D.G. Hayward. 1992. “Biotransfer and Bioaccumulation of Dioxins and Dibenzofurans from Soil.” Hazardous Materials Laboratory, California Department of

Health Services. Berkeley, California. Presented at the 12th International Symposium on Dioxins and Related Compounds. August 24 through 28. University of Tampere, Tampere, Finland.

This document is cited as the source of the assumption that free-range chickens ingest soil as 10 percent of their diet and as the source of the dioxin and furan congeners-specific BCFs

recommended by NC DEHNR (1997). However this document does not clearly reference or document the assumption that soil represents 10 percent of a free-range chicken’s diet. The

document appears to cite two other documents as supporting its assumption: (1) Chang, Hayward, Goldman, Harnly, Flattery and Stephens (1989) and (2) Petreas, Goldman, Hayward, Chang,

Flattery, Wiesmuller, Stephens, Fry, and Rappe (1992). 

Also, this document presents dioxin and furan congener-specific BCFs (thigh) for the low- exposure group after 80 days of a 178-day total exposure period. The chickens in the low-dose group

were fed a diet containing 10 percent soil with a PCDD/PCDF concentration of 42 ppt I-TEQ. Chickens in the high-dose group were fed a diet containing 10 percent soil with a PCDD/PCDF

concentration of 458 ppt I-TEQ; BCF results were not presented from the high-dose group.

Stephens, R.D., M.X. Petreas, and D.G. Hayward. 1995. “Biotransfer and Bioaccumulation of Dioxins and Furans from Soil: Chickens as a Model for Foraging Animals.” The Science of the Total

Environment. Volume 175: 253-273.

This document is an expansion of the results originally presented in Stephens, Petreas, and Hayward (1992). In particular, this document suggests that the percentage of soil in the diet of

chickens raised under field conditions is likely to be greater than 10 percent, the value that was used in the experimental study presented in this document.

Also, this document presents dioxin and furan congener-specific BCFs (thigh) under two exposure schemes; low exposure and high exposure. The white leghorn (Babcock D 300) chickens in

the low group were fed a diet containing 10 percent soil with a PCDD/PCDF concentrations of 42 ppt I-TEQ. Chickens in the high group were fed a diet containing 10 percent soil with a

PCDD/PCDF concentration of 460 ppt I-TEQ (some congeners were fortified by spiking).

The BCFs presented for low- and high-dose groups both represent averages of results from Day-80 and Day-164 of a total 178-day exposure period.
TABLE C-1-3

COPC INTAKE FROM BEEF, MILK, PORK, POULTRY, AND EGGS

(Page 4 of 4) 

C-13

U.S. EPA. 1997. Exposure Factors Handbook. Office of Research and Development. EPA/600/P-95/002F. August.

This document is the source for home produced beef, milk, pork, poultry, and egg consumption rates.
TABLE C-1-4

COPC INTAKE FROM FISH

(Page 1 of 4)

C-14

Description

This equation calculates the daily intake of COPCs from the ingestion of fish. Consumption rates were derived from the Exposure Factors Handbook (U.S. EPA 1997). U.S. EPA (1997) presents

consumption rates based on body weight; therefore, body weight is not included as a variable in the calculation of I

fish.

The limitations and uncertainty introduced in calculating this value include the following:

(1) The amount of fish intake is assumed to be constant and representative of the exposed population. This assumption may under- or overestimate Ifish.

(2) The standard assumptions regarding period exposed may not be representative of any actual exposure situation. This assumption may under- or overestimate Ifish. 

Equation

Variable Description Units Value

I

fish Daily intake of COPC from

fish

mg/kg-day

Cfish Concentration in fish mg/kg Varies

This variable is COPC- and site-specific, and is calculated using output from the equations in Tables B-4-26 through B-4-28; the fish

concentration will vary for each water body.

The following uncertainty is associated with this variable:

The methodology does not account for concentration variations across fish species. Different species may accumulate

COPCs to different extents depending, for example, on their feeding habits and fat content. This may cause Cfish to be underor overestimated.
TABLE C-1-4

COPC INTAKE FROM FISH

(Page 2 of 4)

Variable Description Units Value

C-15

CRfish Consumption rate of fish kg/kg-day

FW

Varies

The consumption rate varies for the receptor considered. The following home produced or caught ingestion rates for fish were derived

from U.S. EPA (1997):

Receptor Ingestion Rate (kg/kg-day FW)

Fisher 0.00125

Fisher Child 0.00088

We derived ingestion rates using data from U.S. EPA (1997) Table 13-23. The ingestion rates listed in U.S. EPA (1997) were derived

from the 1987-1988 USDA National Food Consumption Survey and may be used to assess exposure to contaminants in foods grown,

raised, or caught at a specific site. Prior to the adjustment for cooking and preparation loss, the mean individual fish consumption rates

were weighted by age group. The ingestion rates were then adjusted for cooking and preparation loss as recommended in U.S. EPA

(1997). The total preparation and cooking loss for fish was 41 percent.

In addition, the ingestion rates for the child receptor represents a time-weighted mean. Where data for a specific age group was

incomplete, the intake was extrapolated using data from the general population (Table 10-46 of U.S. EPA 1997). See HHRAP Section

6.2.2.2 for a more detailed explanation of our recommended method for estimating age-appropriate consumption rates.

Uncertainties introduced by assumptions made to calculate this value include the following:

(1) Our recommended intake rates don’t necessarily take into account the types of fish that will be present in the water body. 

Separate intake rates are needed for freshwater and estuarine fish and shellfish, depending on the nature of the local surface

water body. This assumption can overestimate or underestimate CRfish.

(2) These intake rates do not represent long behavior patterns, which is the focus of the exposure assessments used to support

chronic health effects. This introduces uncertainty into the estimates of medians and other percentiles. This assumption can

overestimate or underestimate CRfish.

(3) The intake rates represent total intake rates of home-caught fish. Where use of site-specific information would reveal the

amount of fish consumed from waters within the study area, this information should be used. This assumption can overestimate

or underestimate CRfish.

Ffish Fraction of fish that is

contaminated

unitless 1.0

We recommend using this default value if site-specific information is not available. The contaminated fraction will vary with each

exposure scenario; however, NC DEHNR (1997) and U.S. EPA (1994) assume that this value equals 1.0 for the fisher. 

The following uncertainty is associated with this variable:

Using 1.0 as a default value for fraction of fish that is contaminated assumes that receptors consume only contaminated fish;

this assumption may overestimate Ffish.
TABLE C-1-4

COPC INTAKE FROM FISH

(Page 3 of 4)

C-16

REFERENCES AND DISCUSSION

NC DEHNR. 1997. NC DEHNR Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Combustion Units. January.

This document is one of the reference source documents for the equation in Table C-1-4.

U.S. EPA. 1994. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document is one of the reference source documents for the equation in Table C-1-4.

U.S. EPA. 1997. Exposure Factors Handbook. Office of Research and Development. EPA/600/P-95/002F. August.

This document is the source for home-caught fish consumption rates.
TABLE C-1-5

COPC INTAKE FROM DRINKING WATER

(Page 1 of 3) 

C-17

Description

This equation calculates the daily intake of COPC from drinking water. COPC intake from drinking water is calculated from the concentration of COPC dissolved in the water column of each

surface water body or watershed identified as a drinking water source. The dissolved concentration is used to estimate COPC intake from drinking water because it is assumed the water is filtered

prior to human consumption. The COPC concentration will vary for each water body. The consumption rate varies for children and adults. 

Uncertainties associated with this equation include the following:

(1) The amount of drinking water intake is assumed to be constant and representative of the exposed population. This assumption may under- or overestimate Idw.

(2) The standard assumptions regarding period exposed may not be representative of any actual exposure situation. This assumption may under- or overestimate Idw. 

Equation

Variable Description Units Value

Idw

Daily intake of COPC from

drinking water 

mg/kg-day

Cdw

Dissolved phase water

concentration 

mg/L Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-4-24.

Uncertainties associated with this variable include the following:

All of the variables in the equation in Table B-4-24 are COPC- and site-specific. Therefore, using default values rather than

site-specific values, for any or all of these variables, will contribute to the under- or overestimating Cwt.

We expect the degree of uncertainty associated with the variables dw and db to be minimal because information for estimating dw

is generally available and the probable range for db is narrow. The uncertainty associated with the variables Fwater and Cwtot is

associated with estimates of OC content. Because OC content values can vary widely for different locations in the same

medium, using default OC values may result in significant uncertainty in specific cases.
TABLE C-1-5

COPC INTAKE FROM DRINKING WATER

(Page 2 of 3) 

Variable Description Units Value

C-18

CRdw

Rate of consumption of

drinking water 

L/day 0.67 or 1.4

This variable is site-specific. We recommend using default values of 0.67 (child) and 1.4 (adult) in the absence of site-specific data.

Our recommended average adult consumption rate of drinking water is based on information cited in U.S. EPA (1997). For the child

receptor, U.S. EPA (1997) provides recommended drinking water intake rates for various age groups in Table 3-30. The child default

drinking water intake was derived using a time-weighted average for the age groups 0 to 6 years of age.

The following uncertainty is associated with this variable:

The average consumption rate of drinking water is based on the average intake observed from five studies. The number of

studies conduct may underestimate or underestimate CRdw.

Fdw

Fraction of drinking water

that is contaminated 

unitless 1.0

This variable is site-specific. Consistent with U.S. EPA (1994), we recommend assuming 1.0 for the fraction of drinking water that is

contaminated.

The following uncertainty is associated with this variable:

Some receptors may consume a fraction of their drinking water from sources unimpacted by facility emissions. Therefore, this

assumption will likely overestimate Fdw.

BW Body weight kg 15 or 70

This variable is site-specific. We recommend using default values of 15 (children) or 70 (adults) in the absence of site-specific

information. These default values are consistent with U.S. EPA (1991; 1994). 

Uncertainties associated with this variable include:

These body weights represent the average weight of an adult and child. However, depending on the receptor, the body weights

may be higher or lower. These default values may overestimate or underestimate actual body weights. However, the degree of

under- or overestimation is not expected to be significant. 
TABLE C-1-5

COPC INTAKE FROM DRINKING WATER

(Page 3 of 3) 

C-19

REFERENCES AND DISCUSSION

U.S. EPA. 1991. Human Health Evaluation Manual, Supplemental Guidance: Standard Default Exposure Factors. Office of Solid Waste and Emergency Response. OSWER Directive 9285.6-03. 

Washington, D.C. March 21.

This document is cited as the reference source document of the exposure frequency and body weight variables. 

U.S. EPA. 1994. Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Office of Emergency and Remedial Response. Office of Solid

Waste.

This document was cited as the source of the fraction of drinking water that is contaminated.

U.S. EPA. 1997. Exposure Factors Handbook. Office of Research and Development. EPA/600/P-95/002F. August.

This document is the source for the drinking water consumption rates.
TABLE C-1-6

TOTAL DAILY INTAKE

(Page 1 of 3)

C-20

Description

This equation calculates the daily intake of COPC via all indirect exposure pathways. As discussed in Chapter 4 and Table 4-1, the indirect exposure pathways considered in the calculation of the

total daily intake of COPCs are specific to the recommended exposure scenario evaluated and the representative exposure setting. Daily intake values from exposure pathways which are not

evaluated in a respective exposure scenario may be assumed to be zero when calculating the total daily intake of COPC (I).

Uncertainties associated with this equation include the following:

(1) The uncertainties associated with estimates of total intake are those associated with each of the medium- or tissue-specific intakes. 

(2) To the extent that medium- or tissue-specific intakes do not accurately represent site-specific local conditions, I may be under- or overestimated.

Equation

Variable Description Units Value

I Total daily intake of COPC mg/kg-day

Isoil

Daily intake of COPC from

soil

mg/kg-day Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table C-1-1. The value for this variable will vary for

each receptor and each exposure scenario location.

Uncertainties associated with this variable include the following:

(1) We assume the amount of soil intake is constant and representative of the exposed population. This assumption may under- or

overestimate Isoil.

(2) The standard assumptions regarding period exposed may not be representative of an actual exposure situation. This assumption

may under- or overestimate Isoil. 
TABLE C-1-6

TOTAL DAILY INTAKE

(Page 2 of 3)

Variable Description Units Value

C-21

Iag

Daily intake of COPC from

aboveground produce

mg/kg-day

DW

Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table C-1-2. The value for this variable will vary for

each receptor and each exposure scenario location. 

Uncertainties associated with this variable include the following:

(1) We assume the amount of produce intake is constant and representative of the exposed population. This assumption may

under- or overestimate Iag.

(2) The standard assumptions regarding period exposed may not be representative of an actual exposure situation. This assumption

may under- or overestimate Iag. 

Ibeef;

Imilk; 

Ipork;

Ipoultry;

Ieggs

Daily intake of COPC from

beef, milk, pork, poultry,

and eggs 

mg/kg-day

FW

Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table C-1-3. The value for this variable will vary for

each receptor and each exposure scenario location. 

Uncertainties associated with this variable include the following:

(1) We assume the amount of animal tissue intake is constant and representative of the exposed population. This assumption may

under- or overestimate Ibeef, Imilk, Ipork, Ipoultry, and Ieggs.

(2) The standard assumptions regarding period exposed may not be representative of an actual exposure situation. This assumption

may under- or overestimate Ibeef, Imilk, Ipork, Ipoultry, and Ieggs.

Ifish

Daily intake of COPC from

fish

mg/kg-day

FW

Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table C-1-4. The value for this variable will vary for

each water body evaluated.

Uncertainties associated with this variable include the following:

(1) We assume the amount of fish intake is constant and representative of the exposed population. This assumption may under- or

overestimate Ifish.

(2) The standard assumptions regarding period exposed may not be representative of an actual exposure situation. This assumption

may under- or overestimate Ifish.
TABLE C-1-6

TOTAL DAILY INTAKE

(Page 3 of 3)

Variable Description Units Value

C-22

Idw

Daily intake of COPC from

drinking water

mg/kg-day Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table C-1-5. The value for this variable will vary for

each water body evaluated. 

Uncertainties associated with this variable include the following:

(1) We assume the amount of drinking water intake is constant and representative of the exposed population. This assumption may

under- or overestimate Idw.

(2) The standard assumptions regarding period exposed may not be representative of an actual exposure situation. This assumption

may under- or overestimate Idw. 
TABLE C-1-7

INDIVIDUAL CANCER RISK: CARCINOGENS

(Page 1 of 3) 

C-23

Description

This equation calculates the individual cancer risk from indirect exposure to carcinogenic COPCs. The exposure duration varies for different scenarios. Uncertainties associated with this

equation include the following:

(1) Default factors for exposure frequency and exposure duration are assumed to represent the highest exposure that is reasonably expected to occur at a site and, in practice, is estimated by

combining upper-bound (90th to 95th percentile) values for these exposure parameters, but not all parameters. This assumption may over- or underestimate the Cancer Riski

.

(2) Slope factors are used to estimate an upper-bound lifetime probability of an individual developing cancer as a result of exposure to a particular level of a COPC, and are accompanied by

the weight of evidence classification to indicate the strength of the evidence that the agent is a human carcinogen. This classification potentially over- or underestimates Cancer Riski

.

(3) Risk at low exposure levels is difficult to measure directly, either by animal experiments or by epidemiological studies. The development of a cancer slope factor generally entails

applying a model to the available data set and using the model to extrapolate from the relatively high doses administered to experimental animals (or the exposures noted in

epidemiological studies) to lower exposure levels expected for human contact in the environment. This approach may under- or overestimate Oral CSF. 

Equation

Variable Description Units Value

Cancer

Riski

Individual lifetime cancer

risk through indirect

exposure to COPC

carcinogen i

unitless

Ii

Daily intake of COPC i from

animal tissue j

mg COPC/kg

BW-day

Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table C-1-6. The value for this variable will vary

for each exposure pathway and each exposure scenario location.

The following uncertainty is associated with this variable:

This variable is COPC- and site-specific. See the equation in Table C-1-6 regarding the calculation of and uncertainties

associated with this variable.
TABLE C-1-7

INDIVIDUAL CANCER RISK: CARCINOGENS

(Page 2 of 3) 

Variable Description Units Value

C-24

ED Exposure duration yr 6, 30, or 40

This variable is exposure scenario-specific:

Exposure Scenario ED 

Farmer 40 (U.S. EPA 1994)

Farmer Child 6 (U.S. EPA 1989)

Adult Resident 30 (U.S. EPA 1989)

Child Resident 6 (U.S. EPA 1989)

Fisher 30 (U.S. EPA 1994)

Fisher Child 6 (U.S. EPA 1989) 

The following uncertainty is associated with this variable:

This exposure duration is a single value that represents the highest exposure that is reasonably expected to occur at a site. 

This assumption may overestimate ED.

EF Exposure frequency days/yr 350

This variable is site-specific. We recommend using this default value in the absence of site-specific information, consistent with

U.S. EPA (1991). 

The following uncertainty is associated with this variable:

This exposure frequency is a single value that represents the most frequent exposure that is reasonably expected to occur at a

site, assuming 2 weeks of vacation or travel. This assumption may overestimate EF.

AT Averaging time yr 70

This variable is site-specific. We recommend using this default value in the absence of site-specific information, consistent with

U.S. EPA (1989). 

The following uncertainty is associated with this variable:

The recommendation for averaging time may not accurately represent site-specific time; specifically, this single value may

under- or overestimate the length of time of exposure.

365 Units conversion factor day/yr
TABLE C-1-7

INDIVIDUAL CANCER RISK: CARCINOGENS

(Page 3 of 3) 

Variable Description Units Value

C-25

Oral

CSF

Oral Cancer Slope Factor (mg/kg-day)-1 Varies

This variable is COPC-specific. We recommend using the companion database to the HHRAP as an initial source for this

parameter. We also recommend checking the recommended hierarchy of sources of health benchmark values (discussed in

Appendix A-2) to make sure the database values are still valid, especially if using database values result in risk estimates of

concern. 

Uncertainties associated with this variable include the following:

(1) Slope factors are used to estimate an upper-bound lifetime probability of an individual developing cancer as a result of

exposure to a particular level of a COPC; and are accompanied by the weight of evidence classification to indicate the

strength of the evidence that the agent is a human carcinogen.

(2) Risk at low exposure levels is difficult to measure directly either by animal experiments or by epidemiological studies. 

Developing a cancer slope factor generally entails applying a model to the available data set and using the model to

extrapolate from the relatively high doses administered to experimental animals (or the exposures noted in epidemiological

studies) to the lower exposure levels expected for human contact in the environment. This approach may under- or

overestimate Oral CSF. 

REFERENCES AND DISCUSSION

U.S. EPA. 1989. Risk Assessment Guidance for Superfund, Volume I, Human Health Evaluation Manual (Part A). Interim Final. Office of Emergency and Remedial Response. EPA/540/1-89/002. 

December.

This document is cited as the reference source document of the exposure duration for adult and child residents. This document is also cited as the reference source document for the averaging

time for carcinogens. 

U.S. EPA. 1991. Human Health Evaluation Manual, Supplemental Guidance: Standard Default Exposure Factors. Office of Solid Waste and Emergency Response. OSWER Directive 9285.6-03. 

Washington, D.C.

This document is cited as the reference source document of the exposure frequency. 

U.S. EPA. 1994. Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance for

RCRA Hazardous Waste Combustion Facilities. April 15.

This document is cited as the reference source document of the exposure duration for the fisher and farmer. 
TABLE C-1-8

HAZARD QUOTIENT: NONCARCINOGENS

(Page 1 of 3) 

C-26

Description

This equation calculates the hazard quotient for indirect exposure to noncarcinogenic COPCs. The following uncertainty is associated with this equation.

A chronic RfD is an estimate of a daily exposure level for the human population, including sensitive subpopulations, that is likely to be without an appreciable risk of deleterious effects

during a lifetime. Chronic RfDs are specifically developed to be protective for long-term exposure (from 7 years to a lifetime) to a compound. COPC-specific reference doses (RfD) are

unlikely to underestimate a chemical potential for causing adverse effects.

Equation

Variable Description Units Value

HQ Hazard quotient unitless

Ii

Daily intake of COPC i

from animal tissue j

mg COPC/

kg-day

Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table C-1-6. The value for this variable will vary for

each exposure pathway and each exposure scenario location. Uncertainties associated with this variable are site-specific.

ED Exposure duration yr 6, 30, or 40

Consistent with U.S. EPA (1994b) and NC DEHNR (1997), we recommend using the following default values:

Exposure Scenario ED

Farmer 40 (U.S. EPA 1994a)

Farmer Child 6 (U.S. EPA 1989)

Adult Resident 30 (U.S. EPA 1989)

Child Resident 6 (U.S. EPA 1989)

Fisher 30 (U.S. EPA 1994a)

Fisher Child 6 (U.S. EPA 1989)

Uncertainty associated with this variable includes:

These exposure durations are single values that represent the highest exposure that is reasonably expected to occur at a site. 

These values may overestimate ED for some individuals.
TABLE C-1-8

HAZARD QUOTIENT: NONCARCINOGENS

(Page 2 of 3) 

Variable Description Units Value

C-27

EF Exposure frequency days/yr 350

This variable is site-specific. We recommend using this default value in the absence of site-specific data. This value is based on U.S.

EPA (1991) and is consistent with U.S. EPA (1994b). 

Uncertainty associated with this variable includes:

This exposure frequency is a single value that represents the most frequent exposure that is reasonably expected to occur at a site

with two weeks of vacation or travel. This recommended value may overestimate EF for individuals who are away from their

home for more than two weeks each year. On the other hand, some individuals (such as farmers) may remain at their home (or

farm) for more than 350 days per year. In either case, the degree of over- or underestimation is not expected to be significant in

most cases. 

RfD Reference Dose mg/kg-day Varies

This variable is COPC-specific. We recommend using the companion database to the HHRAP as an initial source for this parameter. 

We also recommend checking the recommended hierarchy of sources of health benchmark values (discussed in Appendix A-2) to

make sure the database values are still valid, especially if using database values result in risk estimates of concern. 

The following uncertainty is associated with this variable:

A chronic RfD is an estimate of a daily exposure level for the human population, including sensitive subpopulations, that is

likely to be without an appreciable risk of deleterious effects during a lifetime. Chronic RfDs are specifically developed to be

protective for long-term exposure (from 7 years to a lifetime) to a compound. COPC-specific RfDs are unlikely to underestimate

a COPC’s potential for causing adverse health effects. 

365 Units conversion factor day/yr

AT Averaging time yr 6, 30, or 40

This variable is site-specific and related to ED. Specifically, the AT for noncarcinogens is numerically the same as ED. This default

value is consistent with U.S. EPA (1989), U.S. EPA (1991), and U.S. EPA (1994a).

Uncertainty associated with this variable includes:

Our recommended averaging time may not accurately represent site-specific time; specifically this single value may under- or

overestimate the length of an average adult lifetime. 
TABLE C-1-8

HAZARD QUOTIENT: NONCARCINOGENS

(Page 3 of 3) 

C-28

REFERENCES AND DISCUSSION

NC DEHNR (1997). Draft North Carolina Protocol for Performing Indirect Exposure Risk Assessments for Hazardous Waste Exposure Risk Assessments for Hazardous Waste Combustion 

Units. January.

U.S. EPA. 1989. Risk Assessment Guidance for Superfund, Volume I, Human Health Evaluation Manual (Part A).

Interim Final. Office of Emergency and Remedial Response. EPA/540/1-89/002. December.

This document is cited as the reference source document of the exposure duration for adult and child residents. U.S. EPA OSW assumes that the recommended exposure duration for the child

resident may also reasonably be applied to the farmer child and to the fisher child. 

U.S. EPA. 1991. Human Health Evaluation Manual, Supplemental Guidance: Standard Default Exposure Factors. Office of Solid Waste and Emergency Response. OSWER Directive 9285.6-03. 

Washington, D.C.

This document is cited as a source document for exposure frequency and averaging time.

U.S. EPA. 1994a. Estimating Exposure to Dioxin-like Components - Volume III: Site-Specific Assessment Procedure. Review Draft. Office of Research and Development. Washington D.C. 

EPA/600/6-88/005Cc. June.

This document is cited by U.S. EPA (1994b) as the same document for the recommended default exposure duration (ED) values for the farmer and fisher. The ED value of 40 years

recommended for both the farmer and the fisher is based on the assumption that “farmers live in one location longer than the general population”.

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.

This document recommends the following:

C An exposure frequency of 350 days per year

C Receptor-specific exposure duration values as presented in U.S. EPA (1994a)— fisher (40 years) and farmer (40 years) and U.S. EPA (1989)—adult resident (30 years) and child

resident (6 years)

C Adult and child body weights of 70 kg and 15 kg, respectively
TABLE C-1-9

TOTAL CANCER RISK: CARCINOGENS

(Page 1 of 1)

C-29

Description

For carcinogens, cancer risks are added across all carcinogenic COPCs. See Appendix A for identification of carcinogens. Uncertainty associated with this equation includes the following:

Total Cancer Risk assumes that different carcinogens affect the same target organ to produce a cancer response, ignoring potential antagonistic or synergistic effects or disparate effects on

different target organs. 

Equation

Variable Description Units Value

Total

Cancer

Risk

Individual lifetime cancer

risk through indirect

exposure to all COPC

carcinogens

unitless

Cancer

Riski

Individual lifetime cancer

risk through indirect

exposure to COPC

carcinogen i

unitless Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table C-1-7. The value for this variable will vary for

each exposure pathway.

Uncertainties associated with this variable include the following:

(1) We assume that the default values for exposure frequency and exposure duration represent the highest exposure that is reasonably

expected to occur at a site. In practice, intakes are estimated by combining upper-bound (90th to 95th percentile) values for these

exposure variables, but not for other parameters. This assumption is likely to overestimate intakes and the Cancer Riski.

(2) Slope factors are used to estimate an upper-bound lifetime probability of an individual developing cancer as a result of exposure

to a particular level of a potential carcinogen; and are accompanied by the weight of evidence classification to indicate the

strength of the evidence that the agent is a human carcinogen. This classification potentially over- or underestimates risk.

(3) Risk at low exposure levels is difficult to measure directly either by animal experiments or by epidemiological studies. 

Developing a cancer slope factor generally entails applying a model to the available data set and using the model to extrapolate

from the relatively high doses administered to experimental animals (or the exposures noted in epidemiological studies) to lower

exposure levels expected for human contact in the environment. This approach is likely to overestimate CSF. 
TABLE C-1-10

TOTAL HAZARD INDEX: NONCARCINOGENS

(Page 1 of 1) 

C-30

Description

For non-cancer health effects, hazard quotient for all COPCs, regardless of target organs, are summed to calculate a total hazard index. Uncertainties associated with this equation include the

following:

(1) Assuming that different COPCs affect the same target organ to produce an adverse health effect, while ignoring potential antagonistic or synergistic effects or disparate effects on different

target organs, may overestimate the total hazard index.

(2) Total hazard index assumes that a single individual in the exposure scenario is exposed to site-related contaminants at estimated exposure concentrations by all pathways that make up the

scenario. It is unlikely, however, that a single individual will be exposed by each pathway in the exposure media. This assumption may overestimate the total hazard index.

Equation

Variable Description Units Value

Total

Hazard

Index

Total individual hazard index for all

COPCs across all exposure

pathways

unitless

HIj

Hazard Index for exposure

 pathway j

unitless Varies

This variable is COPC- and site-specific. The value for this variable will vary for each exposure pathway. Uncertainties

associated with this variable are site-specific.

HQi

Hazard Quotient for COPC i unitless Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table C-1-8. The value for this variable will

vary for each exposure pathway. Uncertainties associated with this variable are site-specific.
TABLE C-1-11

SEGREGATED HAZARD INDEX FOR SPECIFIC ORGAN EFFECTS: NONCARCINOGENS

(Page 1 of 1) 

C-31

Description

For non-cancer health effects, hazard quotients are added across COPCs when they target the same organ to calculate a segregated hazard index. See Appendix A-2 for identification of

noncarcinogens and their associated target organ. Since segregation by critical effect requires the identification of all major effects, information in Appendix A-2 may not always represent the

most current and complete information on COPC-specific major effects. Therefore, Appendix A-2 may require supplemental information about COPC-specific major effects. Uncertainties

associated with this equation include the following:

(1) Target organ segregation is dependent upon the critical effect. Segregation by critical effect requires the identification of all major effects, not just those seen at higher doses. The

segregation process may over- or underestimate the hazard index.

Equation

Variable Description Units Value

HIj Hazard index for exposure

pathway j

unitless

HQi Hazard quotient for COPC i unitless Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table C-1-8. The value for this variable will vary

for each exposure pathway.

The following uncertainty is associated with this variable:

(1) We assume that the default values for exposure frequency and exposure duration represent the highest exposure that is

reasonably expected to occur as a site. In practice, intakes are estimated by combining upper-bound (90th to 95th percentile)

values for these exposure variables, but not for other parameters. This equation is likely to overestimate intakes and HI j.

(2) Adverse health effects at low exposure levels are difficult to either directly either by animal experiments or by epidemiological

studies. The development of RfDs generally entails applying uncertainty factors to extrapolate from the results of studies using

high exposure doses to lower exposure doses expected for human contact in the environment. This approach is unlikely to

underestimate and likely overestimate HIj.

The uncertainties associated with this variable are COPC- and site-specific and will vary for each exposure pathway.
TABLE C-2-1

INHALATION CANCER RISK FOR INDIVIDUAL CHEMICALS: CARCINOGENS

(Page 1 of 4)

C-32

Description

This equation calculates the excess lifetime individual cancer risk from the average daily intake via inhalation of a COPC carcinogen. Uncertainties associated with this equation include:

(1) COPC-specific URF values are unlikely to underestimate, and may overestimate, the carcinogenic potential of a COPC because of the choice of mathematical models and the use of

uncertainty factors in the estimation of these values.

(2) The uncertainty associated with the variable Ca

 are largely site-specific.

Equation

Variable Description Units Value

Cancer

Riskinh(i)

Individual lifetime cancer risk

through direct inhalation of

COPC carcinogen i

unitless

EC Exposure concentration :g/m3
TABLE C-2-1

INHALATION CANCER RISK FOR INDIVIDUAL CHEMICALS: CARCINOGENS

(Page 2 of 4)

Variable Description Units Value

C-33

URF Inhalation Unit Risk Factor (μg/m3

)

-1 Varies

This variable is COPC-specific. We recommend using the companion database to the HHRAP as an initial source for this

parameter. We also recommend checking the recommended hierarchy of sources of health benchmark values (discussed in

Appendix A-2) if using database values results in risk estimates of concern. 

The following general uncertainty is associated with this variable:

COPC-specific inhalation unit risk factors (URFs) are generally estimated by fitting the results of studies conducted on

laboratory animals with a mathematical model. The model generally recommended by U.S. EPA is the linearized multistage

(LMS) model. U.S. EPA’s position on assessing carcinogenic potential was updated (U.S. EPA 1996b) and should be

considered along with recommended toxicological benchmarks and information (U.S. EPA 1995; 1996a). The LMS model

assumes that there is no “safe dose” or threshold below which a COPC causing cancer at higher doses will no longer cause

cancer in expected individuals. In other words, any exposure to a carcinogen may, through a series of stages, cause cancer in

an exposed individual.

Also, a series of uncertainty factors are applied to the results before the results are fitted with the LMS model. Applying

uncertainty factors follows the underlying assumption that humans are, or may be, as sensitive or more sensitive to the

carcinogenic effects of COPCs than the laboratory animals that were tested. As a result of the choice of models and the use of

uncertainty factors, COPC-specific URFs are unlikely to underestimate a COPC’s potential for causing cancer.

Ca

Total COPC air concentration :g/m3 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-5-1. 

Uncertainty associated with this variable includes:

Calculated assuming a default ST value for background plus local sources, rather than a ST value for urban sources. If a

specific site is located in an urban area, using the latter ST value may be more appropriate. Specifically, the ST value for urban

sources is about one order of magnitude greater than the ST value for background plus local sources and would result in a

lower calculated Fv value; however, the Fv value is likely to be only a few percent lower.
TABLE C-2-1

INHALATION CANCER RISK FOR INDIVIDUAL CHEMICALS: CARCINOGENS

(Page 3 of 4)

Variable Description Units Value

C-34

EF Exposure frequency days/yr 350

This variable is site-specific. We recommend using this default value in the absence of site-specific data. This value is based on

U.S. EPA (1991) and is consistent with U.S. EPA (1994b).

Uncertainties associated with this variable include:

This exposure frequency is a single value that represents the most frequent exposure that is reasonably expected to occur at a

site, with two weeks of vacation. This recommended value may overestimate EF for individuals who are away from their

home for more than two weeks each year. On the other hand, individuals such as subsistence farmers may remain at their

home (or farm) for more than 350 days per year. In either case, we don’t expect a significant degree of over- or

underestimation in most cases.

ED Exposure duration yr 6, 30, or 40

We recommend reasonable maximum exposure (RME) values for T2

:

Exposure Duration RME Reference

Child Resident 6 years U.S. EPA (1997b)

Farmer Child

Fisher Child

Adult Resident and 30 years U.S. EPA (1997b)

Fisher

Farmer 40 years U.S. EPA (1994b)

U.S. EPA (1994c) recommended the following unreferenced values:

Exposure Duration Years 

Subsistence Farmer 40

Adult Resident 30

Subsistence Fisher 30

Child Resident 9

Uncertainties associated with this variable include the following:

(1) Exposure duration rates are based on historical mobility rates and may not remain constant. This assumption may

overestimate or underestimate Cs and CstD.

(2) Mobility studies indicate that most receptors that move remain in the vicinity of the emission sources. However, it is

impossible to accurately predict the likelihood that these short-distance moves will influence exposure, based on factors such

as atmospheric transport of pollutants. This assumption may overestimate or underestimate Cs and CstD.
TABLE C-2-1

INHALATION CANCER RISK FOR INDIVIDUAL CHEMICALS: CARCINOGENS

(Page 4 of 4)

Variable Description Units Value

C-35

AT Averaging time yr 70

This variable is site-specific. We recommend using this default value in the absence of site-specific data.

This default value is consistent with U.S. EPA (1989), U.S. EPA (1991), and U.S. EPA (1994b).

Uncertainties associated with this variable include:

The recommendation for averaging time may not accurately represent site-specific time; specifically this single value may

under- or overestimate the length of an average adult lifetime.

REFERENCES AND DISCUSSION

U.S. EPA. 1995. Health Effects Assessment Summary Tables. Annual Update. OHEA-ECAO-CIN-909. Environmental Criteria and Assessment Office, Office of Research and Development

Cincinnati, Ohio.

This document represent U.S. EPA’s secondary source of Inhalation CSF values. 

 

U.S. EPA. 1996a. “Integrated Risk Information System (IRIS)”. Database on Toxicity Information Network (TOXNET).

This reference represents U.S. EPA’s primary source of Inhalation CSF values and other toxicity factors. This reference is updated periodically and should be reviewed prior to preparing a risk

assessment.

U.S. EPA. 1996b. “Proposed Guidelines for Carcinogenic Risk Assessment.” Federal Register. 61 FR 31667. Volume 61. Number 120. June 20.

This document proposes new guidelines for assessing the carcinogenicity of COPCs.
TABLE C-2-2

INHALATION HAZARD QUOTIENT FOR COPCS: NONCARCINOGENS

(Page 1 of 3)

C-36

Description

This equation calculates the HQ for inhalation exposures to COPCs that have noncancer health effects. Uncertainties associated with this equation include the following:

(1) COPC-specific reference concentrations (RfC) are unlikely to underestimate a COPC’s potential for causing adverse health effects.

(2) Most of the uncertainties associated with the variables in the equation in Table B-5-1 (used to calculate Ca

), specifically those associated with the variables Q, Cyv, and Cyp, are sitespecific.

Equation

Variable Description Units Value

HQinh(i)

Hazard quotient for direct

inhalation of COPC

noncarcinogen i

unitless

EC Exposure concentration :g/m3

0.001 Units conversion factor mg/:g
TABLE C-2-2

INHALATION HAZARD QUOTIENT FOR COPCS: NONCARCINOGENS

(Page 2 of 3)

Variable Description Units Value

C-37

RfC Reference concentration mg/m3 Varies

This variable is COPC-specific, and values can be found in the HHRAP companion database. 

The following uncertainty is associated with this variable:

COPC RfCs are generally estimated by applying a series of uncertainty factors to the results of studies conducted on laboratory

animals. The application of uncertainty factors follows the underlying assumption that humans are, or may be, as sensitive or

more sensitive to the harmful effects of COPCs than the laboratory animals that were tested. RfCs are designed to ensure that

the general public, including sensitive subpopulations, will not experience adverse health effects as a result of exposure to a

COPC at its RfC. As a result, COPC-specific RfCs are unlikely to underestimate a COPC’s potential for causing adverse health

effects.

Ca

Total COPC air

concentration

:g/m3 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-5-1.

EF Exposure frequency days/yr 350

This variable is site-specific. We recommend using this default value in the absence of site-specific data. This value is based on U.S.

EPA (1991) and is consistent with U.S. EPA (1994b).

Uncertainties associated with this variable include:

This exposure frequency is a single value that represents the most frequent exposure that is reasonably expected to occur at a

site, with two weeks of vacation. This recommended value may overestimate EF for individuals who are away from their home

for more than two weeks each year. On the other had, individuals such as subsistence farmers may remain at their home (or

farm) for more than 350 days per year. In either case, we don’t expect a significant degree of over- or underestimation in most

cases.
TABLE C-2-2

INHALATION HAZARD QUOTIENT FOR COPCS: NONCARCINOGENS

(Page 3 of 3)

Variable Description Units Value

C-38

ED Exposure duration yr 6, 30, or 40

We recommend reasonable maximum exposure (RME) values for T2:

Exposure Duration RME Reference

Child Resident 6 years U.S. EPA (1997b)

Farmer Child

Fisher Child

Adult Resident and 30 years U.S. EPA (1997b)

Fisher

Farmer 40 years U.S. EPA (1994b)

U.S. EPA (1994c) recommended the following unreferenced values:

Exposure Duration Years 

Subsistence Farmer 40

Adult Resident 30

Subsistence Fisher 30

Child Resident 9

Uncertainties associated with this variable include the following:

(1) Exposure duration rates are based on historical mobility rates and may not remain constant. This assumption may overestimate

or underestimate Cs and CstD.

(2) Mobility studies indicate that most receptors that move remain in the vicinity of the emission sources. However, it is impossible

to accurately predict the likelihood that these short-distance moves will influence exposure, based on factors such as

atmospheric transport of pollutants. This assumption may overestimate or underestimate Cs and CstD.

AT Averaging time yr 6, 30, or 40

This variable is site-specific and related to ED. Specifically, the AT for noncarcinogens is numerically the same as ED. This default

value is consistent with U.S. EPA (1989; 1991; 1994a).

Uncertainty associated with this variable includes:

Our recommended averaging time may not accurately represent site-specific time; specifically this single value may under- or

overestimate the length of an average adult lifetime. 
TABLE C-2-3

TOTAL INHALATION CANCER RISK: CARCINOGENS

(Page 1 of 1) 

C-39

Description

Cancer risk to the individual via inhalation are added across all COPCs that are carcinogenic via the direct inhalation route of exposure.

 Uncertainties associated with this equation include the following:

(1) Total Cancer Risk assumes that different carcinogens affect the same target organ to produce a cancer response, ignoring potential antagonistic or synergistic effects or disparate

effects on different target organs. This assumption may overestimate Total Cancer Risk.

(2) The summation of cancer risks across multiple COPCs means that the uncertainties associated with estimating cancer risk for each COPC are also summed. This means Total Cancer

Risk, as defined below, is unlikely to be overestimated.

Equation

Variable Description Units Value

Total 

Cancer

Riskinh

Total individual lifetime cancer risk

through direct inhalation of all

COPC carcinogens

unitless

Cancer

Riskinh(i)

Individual lifetime cancer risk

through direct inhalation for COPC

carcinogen i

unitless Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table C-2-1.

Uncertainties associated with this variable include the following:

(1) COPC-specific URF values are unlikely to underestimate, and may overestimate, the carcinogenic potential of COPCs

because of the mathematical models and the use of uncertainty factors in the estimation of these values.

(2) Most of the uncertainties associated with the variables used to calculate Ca

, specifically Q, Cyv, and Cyp, are

site-specific.
TABLE C-2-4

HAZARD INDEX FOR INHALATION: NONCARCINOGENS

(Page 1 of 1) 

C-40

Description

For non-cancer health effects, HQs for inhalation exposures are added across COPCs when they target the same organ to obtain an HI for the target organ. See Appendix A-2 for target organs and

Appendix A-3 for COPC-specific inhalation RfCs and for identification of COPCs that cause noncarcinogenic effects via the inhalation route of exposure and their associated target organs. 

Uncertainties associated with this equation include the following:

(1) The summation of noncarcinogenic hazards across multiple COPCs means that the uncertainties associated with estimating hazards for each COPC (see HQ below) are also summed. This

means that the total noncarcinogenic hazard, as defined below, is unlikely to be overestimated.

(2) As defined below, the HI sums the HQs for all COPCs to which a receptor is potentially exposed. Ideally, HQs should be summed only for COPCs that affect the same target organs and

systems. To the extent that COPCs affect different target organs, summing their associated HQs will overestimate the actual HI. 

Equation

Variable Description Units Value

HIinh(j)

Hazard index for target organ effect

j through direct inhalation of all

COPCs

unitless

HQinh(i)

Hazard quotient for direct

inhalation of COPC i

unitless Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table C-2-2.

Uncertainties associated with this variable include the following:

(1) COPC-specific RfCs are unlikely to underestimate a COPC’s potential for causing adverse health effects.

(2) Most of the uncertainties associated with the variables used to calculate Ca

, specifically Q, Cyv, and Cyp, are site-specific.
TABLE C-3-1

CONCENTRATION OF DIOXINS AND DIOXIN-LIKE PCBs IN BREAST MILK

(Page 1 of 7)

C-41

Description

This equation calculates the concentration of dioxins and dioxin-like PCBs in milkfat of breast milk. Uncertainties associated with this equation include the following:

(1) The most significant uncertainties associated with this equation are those associated with the variable m. Because m is calculated as the sum of numerous potential intakes, estimates of m

incorporate uncertainties associated with each exposure pathway. Therefore, m may be under- or overestimated. Every effort should be made to limit and characterize the uncertainties

associated with this variable.

(2) This equation assumes that the concentration of dioxinand dioxin-like PCBs in breast milkfat is the same as in maternal fat. To the extent that this is not the case, uncertainty is introduced.

Equation

The average maternal intake of dioxin for each adult exposure scenario (m) is equal to the total daily intake of dioxin and dioxin-like PCBs (I) from inhalation [calculated as the average daily

COPC intake via inhalation (ADI) using the equation provided below] and all indirect pathways [which is calculated using the equation in Table C-1-6 and based on the highest annual average

soil concentration (Cstd)] for each adult exposure scenario concentration.

Variable Description Units Value

Cmilkfat

Concentration of dioxin and dioxinlike PCBs in milk fat of breast milk

for a specific exposure scenario

pg COPC/kg

milk fat
TABLE C-3-1

CONCENTRATION OF DIOXINS AND DIOXIN-LIKE PCBs IN BREAST MILK

(Page 2 of 7)

Variable Description Units Value

C-42

m Average maternal intake of dioxin

and dioxin-like PCBs for each adult

exposure scenario

mg COPC/kg

BW-day

Varies

This variable is COPC- and site-specific and is equal to the total daily intake of dioxin and dioxin-like PCBs (I) from

inhalation [calculated as the average daily COPC intake via inhalation (ADI) using the equation provided above] and all

indirect pathways [which is calculated using the equation in Table C-1-6 and based on the highest annual average soil

concentration (Cstd)] for each adult exposure scenario concentration.

The following uncertainty is associated with this variable:

(1) The uncertainty associated with this variable may be significant, because this uncertainty represents the sum of all

uncertainties associated with each of the potential exposure pathways. To gauge the potential magnitude of the

uncertainty associated with this variable, compare estimated m values to values reported in the literature.

1 × 109 Units conversion factor pg/mg

h Half-life of dioxin in adults days 2,555

This variable is COPC- and site-specific. We recommend using this default value, consistent with U.S. EPA (1994a) and

U.S. EPA (1994b).

The following uncertainty is associated with this variable:

As discussed in U.S. EPA (1994a), the half-life may vary from about 5 to 7 years for 2,3,7,8-TCDD. Using the upper

end of the range is conservative. Based on the work of Schecter (1991), and Schlatter (1991), as discussed in U.S. EPA

(1994a), the value of h may vary by almost one order of magnitude (1.1 to 50) for different dioxin and furan congeners

around the value of 7 proposed for 2,3,7,8-TCDD. The differences are largely the result of differences in absorption. 

However, if the average material intake of dioxin is calculated in terms of TEQs, we assume using a single h value

based on 2,3,7,8-TCDD is reasonable.

f1

Fraction of ingested dioxin and

dioxin-like PCBs that is stored in

fat

unitless 0.9

This variable is COPC- and site-specific. We recommend using this default value, consistent with U.S. EPA (1994b). The

source of this value is U.S. EPA (1994a).

f2

Fraction of mother’s weight that is

fat

unitless 0.3

This variable is COPC-specific. We recommend using this default value, consistent with U.S. EPA (1994a) and U.S. EPA

(1994b). The source of this value is U.S. EPA (1994a).

The following uncertainty is associated with this variable:

Although this single value clearly does not adequately represent all potentially exposed women of childbearing age, we

assume the average uncertainty associated with this value to be minimal.
TABLE C-3-1

CONCENTRATION OF DIOXINS AND DIOXIN-LIKE PCBs IN BREAST MILK

(Page 3 of 7)

Variable Description Units Value

C-43

ADI Average daily COPC intake via

inhalation

mg COPC/

kg-day

Ca

Total COPC air concentration :g/m3 Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table B-5-1. 

Uncertainty associated with this variable includes:

Calculated assuming a default ST value for background plus local sources, rather than a ST value for urban sources. If a

specific site is located in an urban area, using the latter ST value may be more appropriate. Specifically, the ST value for

urban sources is about one order of magnitude greater than the ST value for background plus local sources and would

result in a lower calculated Fv value; however, the Fv value is likely to be only a few percent lower.

IR Inhalation rate m3

/hr adult: 0.83

We recommend using default values of 0.83 in the absence of site-specific information. The recommended adult value is

consistent with values used in U.S. EPA (1991; 1994b; 1996a), and consistent with average of values provided in U.S. EPA

(1997) when considering adult age brackets for both male and female inhalation rates for indoor and outdoor activities in a

residential setting.

Uncertainty associated with this variable includes:

The recommended inhalation rates do not consider individual respiratory or activity differences. Therefore, based on

the individual and the activities that individual is engaged in, the recommended inhalation rates may under-or

overestimate the actual rates. However, we don’t expect the degree of under-or overestimation to be significant. 

ET Exposure time hrs/day 24

This variable is site-specific. We recommend using this default value in the absence of site-specific data. 

Uncertainty associated with this variable includes:

The recommended ET value assumes that an individual remains at a specific location 24 hours per day. In reality this is

likely to be true only for a minority of the population including young children, their caregivers, and elderly or

individuals who are sick. Therefore, the recommended value contributes to a degree of overestimation for much of the

population. However, it must be noted that though an individual may not always be at a single location, that individual

may continue to be exposed to emissions at an alternate location.
TABLE C-3-1

CONCENTRATION OF DIOXINS AND DIOXIN-LIKE PCBs IN BREAST MILK

(Page 4 of 7)

Variable Description Units Value

C-44

EF Exposure frequency days/yr 350

This variable is site-specific. We recommend using this default value in the absence of site-specific data. This value is based

on U.S. EPA (1991) and is consistent with U.S. EPA (1994b). 

Uncertainties associated with this variable include:

This exposure frequency is a single value that represents the most frequent exposure that is reasonably expected to

occur at a site with two weeks of vacation. This recommended value may overestimate EF for individuals who are

away from their home for more than two weeks each year. On the other hand, some individuals (such as farmers) may

remain at their home (or farm) for more than 350 days per year. In either case, we don’t expect the degree of over- or

underestimation to be significant in most cases. 

ED Exposure duration yr 30, or 40

This variable is site-specific. Consistent with U.S. EPA (1994b), we recommend using the following default values:

Exposure Scenario ED

Farmer 40 (U.S. EPA 1994a)

Adult Resident 30 (U.S. EPA 1989)

Fisher 30 (U.S. EPA 1994a)

Uncertainties associated with this variable include:

These exposure durations are single values that represent the highest exposure that is reasonably expected to occur at a

site. These values may overestimate ED for some individuals.

BW Body weight kg 70

This variable is site-specific. We recommend using default value of 70 (adults) in the absence of site-specific information. 

These default values are consistent with U.S. EPA (1991; 1994b). 

Uncertainties associated with this variable include:

This body weight represents the average weight of an adult. However, depending on the site, the body weights may be

higher or lower. This default value may overestimate or underestimate actual body weights. However, we don’t expect

the degree of under- or overestimation to be significant. 
TABLE C-3-1

CONCENTRATION OF DIOXINS AND DIOXIN-LIKE PCBs IN BREAST MILK

(Page 5 of 7)

Variable Description Units Value

C-45

AT Averaging time yr 70

This variable is site-specific. We recommend using this default value in the absence of site-specific data. This default value

is consistent with U.S. EPA (1989), U.S. EPA (1991), and U.S. EPA (1994b).

Uncertainties associated with this variable include:

The recommended averaging time may not accurately represent site-specific time; specifically this single value may

under- or overestimate the length of an average adult lifetime. 

0.001 Units conversion factor mg/:g

365 Units conversion factor days/yr

REFERENCES AND DISCUSSION

Schecter, A. 1991. “Dioxins and Related Chemicals in Humans and in the Environment.” In: Biological Basis for Risk Assessment of Dioxins and Related Compounds: Gallo, M.; Schenplein, R;

Van Der Heijden, K. Eds; Banbury Report 35, Cold Spring Harbor Laboratory Press.

This document is cited by U.S. EPA (1994a) as the source of information related to the metabolism of dioxin and related compounds, in addition to concentrations of various congeners in

adipose tissue.

Schlatter, C., 1991. “Data on Kinetics of PCDDs and PCDFs as a Prerequisite for Human Risk Assessment.” In: Biological Basis for Risk Assessment of Dioxins and Related Compounds; Gallo, M;

Schenplein, R; Van Der Heijder, K., eds. Banbury Report 35, Cold Spring Harbor Laboratory press.

This document is cited by U.S. EPA (1994a) as a source of a method of estimating the half-life of dioxin-related compounds, based on uptake data relative to 2,3,7,8-TCDD. U.S. EPA (1994a)

proposed the following equation, based on this document:
TABLE C-3-1

CONCENTRATION OF DIOXINS AND DIOXIN-LIKE PCBs IN BREAST MILK

(Page 6 of 7)

C-46

where

CTCDD

= Concentration of TCDD in body

DTCDD = Daily intake of TCDD

t1/2, TCDD = Half-life of TCDD in body

V = Volume of body compartment

Smith, A.H. 1987. “Infant Exposure Assessment for Breast Milk Dioxins and Furans Derived from Waste Incineration Emissions.” Risk Analysis. 7(3) 347-353.

This document is cited by U.S. EPA (1994a) as the source of the equation in Table C-3-1 and the recommended values for h (2,555 days), f1

 (0.9), and f2

(0.3). This document assumes that the

concentration of dioxins in breast milkfat is the same as in maternal fat.

U.S. EPA. 1989. Risk Assessment Guidance for Superfund, Volume I, Human Health Evaluation Manual (Part A). Interim Final. Office of Emergency and Remedial Response. EPA/540/1-89/002. 

December.

This document is cited as the reference source document of the exposure duration for adult residents. This document is also cited as reference source document for the averaging time for

carcinogens.

U.S. EPA. 1991. Human Health Evaluation Manual, Supplemental Guidance: Standard Default Exposure Factors. Office of Solid Waste and Emergency Response. OSWER Directive 9285.6-03. 

Washington, D.C. March 21.

This document is cited as the reference source document of the exposure frequency, body weight, and adult inhalation rate variables. 

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Volume II: Properties, Sources, Occurrence, and Background Exposures. Review Draft. Office of Research and Development. 

EPA/600/6-88/0055Cb. Washington, D.C. June.

This document cites Smith (1987) as the source for half of the recommended values for the life of dioxin for adults (h), proportion of ingested dioxin that is stored in fat (f1

), and proportion of

mother’s milk that is fat (f2).

This document is cited by U.S. EPA (1994b) as the same document for the recommended default exposure duration (ED) values for the farmer and fisher. The ED value of 40 years

recommended for both the farmer and the fisher is based on the assumption that “farmers live in one location longer than the general population”.
TABLE C-3-1

CONCENTRATION OF DIOXINS AND DIOXIN-LIKE PCBs IN BREAST MILK

(Page 7 of 7)

C-47

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Waste. Attachment C, Draft Exposure Assessment Guidance

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14. 

This document recommends using the equation in Table C-3-1 and values for the variables in this equation: h (2,555 days), f1 (0.9), and f2 (0.3).

This document also recommends the following:

C An adult inhalation rate of 20 m3/day (0.83 m3/hr)

C An exposure frequency of 350 days per year

C Receptor-specific exposure duration values as presented in U.S. EPA (1994a)—fisher (40 years) and farmer (40 years) and U.S. EPA (1989)—adult resident (30 years)

C Adult body weight of 70 kg

C An averaging time, AT, of 70 years

U.S. EPA. 1997. Exposure Factors Handbook. Office of Research and Development. EPA/600/P-95/002F. August.

This document recommends an adult inhalation rate value of 20.5 m3/day (0.85 m3/hr) if considering indoor and outdoor activities.
TABLE C-3-2

AVERAGE DAILY DOSE TO THE EXPOSED INFANT

(Page 1 of 3) 

C-48

Description

This equation calculates the average daily dose for an infant exposed to contaminated breast milk. Uncertainty associated with this equation includes the following:

The most significant uncertainty associated with this equation is the selection of a value for averaging time (AT). As stated in U.S. EPA (1994a), “Little agreement exists regarding the

appropriate choice of an averaging time for less than lifetime exposures. This is especially true for cases where exposure is occurring in a particularly sensitive developmental period.”

An averaging time (AT) of 1 year is appropriate for assessing noncarcinogenic effects. However, using this value may overestimate a lifetime average appropriate for assessing carcinogenic

risk by almost two orders of magnitude (70/1).

Equation

Variable Description Units Value

ADDinfant

Average daily dose for infant

exposed to contaminated breast

milk

pg

COPC/kg

BW-day

Cmilkfat

Concentration of COPC in

milk fat of breast milk for a

specific exposure scenario

pg

COPC/kg

milkfat

Varies

This variable is COPC- and site-specific, and is calculated using the equation in Table C-3-1.

The following uncertainty is associated with this variable:

The most significant uncertainties associated with the calculation of this variable are those associated with the variable m and

the estimate of Cmilkfat. Uncertainties associated with m represent a sum of the various uncertainties associated with each of

the potential exposure pathways (see the equation in Table C-1-6).

f3

Fraction of mother’s breast

milk that is fat

unitless 0.04

This variable is COPC- and site-specific. We recommend using this default value, consistent with U.S. EPA (1994a; 1994b; 

2002). As cited in U.S. EPA (1994a), the source of this variable value is Smith (1987).

We assume the uncertainty associated with this value is minimal.
TABLE C-3-2

AVERAGE DAILY DOSE TO THE EXPOSED INFANT

(Page 2 of 3) 

Variable Description Units Value

C-49

f4 Fraction of ingested COPC that

is absorbed

unitless 0.9

This variable is COPC- and site-specific. We recommend using this default value, as do U.S

U.S. EPA (1994a), the source of this variable value is Smith (1987).We assume the uncertainty associated with this value is minimal.

IRmilk Ingestion rate of breast milk by

the infant

kg/day 0.688

This variable is COPC- and site-specific. We recommend using this default value, from Tabl

The following uncertainty is associated with this variable:

U.S. EPA (2002) reports a 12-month time weighted average of 688 mL/day. Assuming 

more than 1.0, the recommended value is converted from milliliters per day to kilogramsignificant site-specific variation from this value. 

ED Exposure duration yr 1.0

This variable is COPC- and site-specific. We recommend using this default value, as do U.S. The following uncertainty is associated with this variable:

Some infants may nurse for more or less than the recommended 1 year. However, we d

associated with this variable value to be large.

BWinfant Body weight of infant kg 9.4

As cited in U.S. EPA (2002), this value is estimated using using data from NHANES III, whi

The following uncertainty is associated with this variable:

As reported in U.S. EPA (2002), NHANES III collected body weight data for approximages of 2 months and 17 years. U.S. EPA (2002) reported a range of body weights for 7kilograms, with a mean body weight of 9.4 kilograms. Based on this information and a

uncertainty associated with this variable value to be minimal.
TABLE C-3-2

AVERAGE DAILY DOSE TO THE EXPOSED INFANT

(Page 3 of 3) 

Variable Description Units Value

C-50

AT Averaging time yr 1

This variable is COPC- and site-specific. We recommend using this default value, as do U.S. The following uncertainty is associated with this variable:

The uncertainty associated with this variable value is significant, as stated in U.S. EPA regarding the appropriate choice of an averaging time for less than lifetime exposures. 

where exposure is occurring in a particularly sensitive developmental period.” An aver

assessing noncarcinogenic effects. However, using this value may overestimate a lifetimcarcinogenic risk, by almost two orders of magnitude (70/1).

REFERENCES AND DISCUSSION

National Center for Health Statistics. 1987.

Cited in U.S. EPA (1994a) as the source of the recommended BWinfant value of 10 kilograms. However, that document does not provide a complete referen

Smith., A.H. 1987. “Infant Exposure Assessment for Breast Milk Dioxins and Furans Derived from Waste Incineration Emissions.” Risk Analysis. 7(3) 347-3

This document is cited by U.S. EPA (1994a) as the source of the recommended values for the variables in the equation in Table C-3-2.

U.S. EPA. 1994a. Estimating Exposure to Dioxin-Like Compounds. Review Draft. Office of Research and Development. EPA/600/6-88/0055Cc. Washingto

This document is cited as the original source of the fraction of fat in breast milk, fraction of ingested COPC that is absorbed, and exposure duration.

U.S. EPA. 1994b. Revised Draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes. Attachment C, 

for RCRA Hazardous Waste Combustion Facilities. Office of Emergency and Remedial Response. Office of Solid Waste. December 14.This document recommends using the equation in Table C-3-2 and values for the variables in this equation: f3 (0.04), f4 (0.9), ED (1 year), and AT (1 yea

U.S. EPA. 2002. Child-Specific Exposure Factors Handbook. EPA-600-P-00-002B. National Center for Environmental Assessment (Washington Office) and U

This document recommends values for the variables f3 (0.04), IRmilk (0.688 kg/day), and BWinfant (9.4 kg).
TABLE C-4-1

ACUTE HAZARD QUOTIENT

(Page 1 of 1) 

C-51

Description

This equation calculates the acute hazard quotient AHQ for short term inhalation exposures to COPCs. Uncertainties associated with this equation include the following:

(1) Uncertainties may be associated with development components of COPC-specific acute inhalation exposure criteria (AIECs), including exposure group protected, exposure duration, and

toxicity endpoint. Uncertainties are specific to each COPC’s AIEC, and may under or overestimate the potential for causing adverse health effects.

(2) Most of the uncertainties associated with the variables in the equation in Table B-6-1 (used to calculate Cacute), specifically those associated with the variables Q, Chv, and Chp, are

site-specific.

Equation

Variable Description Units Value

AHQinh(i)

Acute hazard quotient for

inhalation of COPCs

unitless

Cacute

Acute air concentration :g/m3 Varies

This variable is COPC- and site-specific, and is calculated by using the equation in Table B-6-1.

AIEC COPC acute inhalation exposure

criteria

mg/m3 Varies

This variable is COPC-specific (see the companion database to the HHRAP) and determined following a hierarchal approach

as discussed in Chapter 7 of the HHRAP. 

The following uncertainty is associated with this variable:

Uncertainties may be associated with development components of COPC-specific acute inhalation exposure criteria

(AIECs), including exposure group protected, exposure duration, and toxicity endpoint. Uncertainties are specific to

each COPC’s AIEC, and may under or overestimate the potential for causing adverse health effects.

0.001 Conversion factor mg/:g