United States
ptoMak>n 600R03036
Example Exposure Scenarios
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EPA/600/R-03/036
August 2004
EXAMPLE EXPOSURE SCENARIOS
National Center for Environmental Assessment
U.S. Environmental Protection Agency
Washington, DC 20460
Recycled/Recyclable
VA«. Printed with vegetable-based ink on
T~V \ \ paper that contains a minimum of
\^1/~7 50% post-consumer fiber content
>1\-' processed chlorine free.
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DISCLAIMER
This final document has been reviewed in accordance with U.S. Environmental
Protection Agency policy and approved for publication. Mention of trade names or commercial
products does not constitute endorsement or recommendation for use.
ABSTRACT
Exposure scenarios are a tool to help the assessor develop estimates of exposure,
dose, and risk. An exposure scenario generally includes facts, data, assumptions, inferences, and
sometimes professional judgment about how the exposure takes place. The human physiological
and behavioral data necessary to construct exposure scenarios can be obtained from the Exposure
Factors Handbook (U.S. EPA, 1997a). The handbook provides data on drinking water
consumption, soil ingestion, inhalation rates, dermal factors including skin area and soil
adherence factors, consumption of fruits and vegetables, fish, meats, dairy products, homegrown
foods, breast milk, activity patterns, body weight, consumer products, and life expectancy.
The purpose of the Example Exposure Scenarios is to outline scenarios for various
exposure pathways and to demonstrate how data from the Exposure Factors Handbook (U.S.
EPA, 1997a) may be applied for estimating exposures. The example scenarios presented here
have been selected to best demonstrate the use of the various key data sets in the Exposure
Factors Handbook (U.S. EPA, 1997a), and represent commonly encountered exposure pathways.
An exhaustive review of every possible exposure scenario for every possible receptor population
would not be feasible and is not provided. Instead, readers may use the representative examples
provided here to formulate scenarios that are appropriate to the assessment of interest, and apply
the same or similar data sets and approaches as shown in the examples.
Preferred Citation:
U.S. Environmental Protection Agency (EPA). (2003) Example Exposure Scenarios. National
Center for Environmental Assessment, Washington, DC; EPA/600/R-03/036. Available from:
NationalMormation Service, Springfield, VA; PB2003-103280 and at http://www.epa.gov/ncea
11
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TABLE OF CONTENTS
1.0 INTRODUCTION AND PURPOSE OF THIS DOCUMENT 1
1.1 CONDUCTING AN EXPOSURE ASSESSMENT .1
1.1.1 General Principles 1
1.1.2 Important Considerations in Calculating Dose 5
1.1.3 Other Sources of Information on Exposure Assessment 7
1.2 CHOICEOFEXPOSURESCENARIOS 8
1.3 CONVERSION FACTORS 10
1.4 DEFINITIONS 13
2.0 EXAMPLE BSfGESTION EXPOSURE SCENARIOS 18
2.1 PER CAPITA INGESTION OF CONTAMINATED HOMEGROWN
VEGETABLES: GENERAL POPULATION (ADULTS), CENTRAL
TENDENCY, LIFETIME AVERAGE EXPOSURE 18
2.1.1 Introduction 18
2.1.2 Exposure Algorithm 18
2.1.3 Exposure Factor Inputs 19
2.1.4 Calculations 21
2.1.5 Exposure Characterization and Uncertainties 21
2.2 CONSUMER ONLY INGESTION OF CONTAMINATED HOMEGROWN
TOMATOES: CHILDREN, HIGH-END, CHRONIC DAILY EXPOSURE .. 24
2.2.1 Introduction 24
2.2.2 Exposure Algorithm 24
2.2.3 Exposure Factor Inputs 25
2.2.4 Calculations 26
2.2.5 Exposure Characterization and Uncertainties 27
2.3 PER CAPITA INGESTION OF CONTAMINATED BEEF: ADULTS,
CENTRAL TENDENCY, LIFETIME AVERAGE EXPOSURE 29
2.3.1 Introduction 29
2.3.2 Exposure Algorithm 29
2.3.3 Exposure Factor Inputs 30
2.3.4 Calculations 32
2.3.5 Exposure Characterization and Uncertainties 32
2.4 CONSUMER ONLY INGESTION OF CONTAMINATED DAIRY
PRODUCTS: GENERAL POPULATION (ALL AGES COMBINED),
BOUNDING, ACUTE EXPOSURE 34
2.4.1 Introduction 34
2.4.2 Exposure Algorithm 34
2.4.3 Exposure Factor Inputs 34
2.4.4 Calculations 36
2.4.5 Exposure Characterization and Uncertainties 37
HI
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2.5 INGESTION OF CONTAMINATED DRINKING WATER: OCCUPATIONAL
ADULTS, BASED ON OCCUPATIONAL TENURE, HIGH-END, LIFETIME
AVERAGE EXPOSURE 38
2.5.1 Introduction 38
2.5.2 Exposure Algorithm 38
2.5.3 Exposure Factor Inputs 38
2.5.4 Calculations 40
2.5.5 Exposure Characterization and Uncertainties 40
2.6 INGESTION OF CONTAMINATED DRINKING WATER: SCHOOL
CHILDREN, CENTRAL TENDENCY, SUBCHRONIC EXPOSURE 42
2.6.1 Introduction 42
2.6.2 Exposure Algorithm 42
2.6.3 Exposure Factor Inputs 43
2.6.4 Calculations 44
2.6.5 Exposure Characterization and Uncertainties 44
2.7 INGESTION OF CONTAMINATED DRINKING WATER: ADULT MALES IN
HIGH PHYSICAL ACTIVITY OCCUPATIONS, BOUNDING, AVERAGE
LIFETIME EXPOSURE 46
2.7.1 Introduction 46
2.7.2 Exposure Algorithm 46
2.7.3 Exposure Factor Inputs 47
2.7.4 Calculations 48
2.7.5 Exposure Characterization and Uncertainties 48
2.8 INCIDENTAL INGESTION OF POOL WATER: CHILDREN, BOUNDING,
ACUTE EXPOSURE 50
2.8.1 Introduction 50
2.8.2 Exposure Algorithm 50
2.8.3 Exposure Factor Inputs 51
2.8.4 Calculations 52
2.8.5 Exposure Characterization and Uncertainties 52
2.9 INGESTION OF CONTAMINATED FRESHWATER AND MARINE FISH:
CHILDREN, CENTRAL TENDENCY, CHRONIC EXPOSURE 54
2.9.1 Introduction 54
2.9.2 Exposure Algorithm 54
2.9.3 Exposure Factor Inputs 55
2.9.4 Calculations 57
2.9.5 Exposure Characterization and Uncertainties 58
2.10 INGESTION OF CONTAMINATED FISH: SUBSISTENCE FISHING NATIVE
AMERICAN ADULTS, BOUNDING, AVERAGE LIFETIME EXPOSURE .. 60
2.10.1 Introduction 60
2.10.2 Exposure Algorithm 60
2.10.3 Exposure Factor Inputs 61
2.10.4 Calculations 62
IV
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2.10.5 Exposure Characterization and Uncertainties 62
2.11 CONSUMER ONLY INGESTION OF CONTAMINATED FISH: GENERAL
POPULATION ADULTS, HIGH-END, ACUTE EXPOSURE 64
2.11.1 Introduction 64
2.11.2 Exposure Algorithm 64
2.11.3 Exposure Factor Inputs 65
2.11.4 Calculations 66
2.11.5 Exposure Characterization and Uncertainties 66
2.12 INGESTION OF CONTAMINATED BREAST MILK: INFANTS, CENTRAL
TENDENCY SUBCHRONIC EXPOSURE 68
2.12.1 Introduction 68
2.12.2 Exposure Algorithm 68
2.12.3 Exposure Factor Inputs 69
2.12.4 Calculations 70
2.12.5 Exposure Characterization and Uncertainties 71
2.13 INGESTION OF CONTAMINATED INDOOR DUST: YOUNG CHILDREN,
HIGH-END, AVERAGE LIFETIME EXPOSURE 73
2.13.1 Introduction 73
2.13.2 Exposure Algorithm 73
2.13.3 Exposure Factor Inputs 74
2.13.4 Calculations 75
2.13.5 Exposure Characterization and Uncertainties 75
2.14 INGESTION OF INDOOR DUST ORIGINATING FROM OUTDOOR SOIL:
OCCUPATIONAL ADULTS, CENTRAL TENDENCY, AVERAGE LIFETIME
EXPOSURE 77
2.14.1 Introduction 77
2.14.2 Exposure Algorithm 77
2.14.3 Exposure Factor Inputs 78
2.14.4 Calculations 79
2.14.5 Exposure Characterization and Uncertainties 79
3.0 EXAMPLE INHALATION EXPOSURE SCENARIOS 81
3.1 INHALATION OF CONTAMINATED INDOOR AIR: OCCUPATIONAL
FEMALE ADULTS, CENTRAL TENDENCY, AVERAGE LIFETIME
EXPOSURE 82
3.1.1 Introduction 82
3.1.2 Exposure Algorithm 82
3.1.4 Calculations 83
3.1.5 Exposure Characterization and Uncertainties 84
3.2 INHALATION OF CONTAMINATED INDOOR AIR: RESIDENTIAL CHILD,
CENTRAL TENDENCY, AVERAGE LIFETIME EXPOSURE 85
3.2.1 Introduction 85
3.2.2 Exposure Algorithm 85
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3.2.3 Exposure Factor Inputs 85
3.2.4 Calculations 86
3.2.5 Exposure Characterization and Uncertainties 87
3.3 INHALATION OF CONTAMINATED INDOOR AIR: SCHOOL CHILDREN,
CENTRAL TENDENCY, SUBCHRONIC EXPOSURE 88
3.3.1 Introduction 88
3.3.2 Exposure Algorithm 88
3.3.3 Exposure Factor Inputs 88
3.3.4 Calculations 89
3.3.5 Exposure Characterization and Uncertainties 90
4.0 EXAMPLE DERMAL EXPOSURE SCENARIOS 91
4.1 DERMAL CONTACT WITH CONTAMINATED SOIL: RESIDENTIAL
ADULT GARDENERS, CENTRAL TENDENCY, AVERAGE LIFETIME EXPOSURE
91
4.1.1 Introduction 91
4.1.2 Exposure Algorithm 91
4.1.3 Exposure Factor Inputs 92
4.1.4 Calculations 96
4.1.5 Exposure Characterization and Uncertainties 98
4.2 DERMAL CONTACT WITH SOIL: TEEN ATHLETE: CENTRAL
TENDENCY, SUBCHRONIC EXPOSURE 100
4.2.1 Introduction 100
4.2.2 Exposure Algorithm 100
4.2.3 Exposure Factor Inputs 101
4.2.4 Calculations 105
4.2.5 Exposure Characterization and Uncertainties 106
4.3 DERMAL CONTACT WITH CONSUMER PRODUCTS: GENERAL
POPULATION ADULTS, CENTRAL TENDENCY, AVERAGE LIFETIME
EXPOSURE 108
4.3.1 Introduction 108
4.3.2 Exposure Algorithm 108
4.3.3 Exposure Factor Inputs 109
4.3.4 Calculations Ill
4.3.5 Exposure Characterization and Uncertainties 112
4.4 DERMAL CONTACT WITH SURFACE WATER: RECREATIONAL
CHILDREN, CENTRAL TENDENCY, AVERAGE LIFETIME EXPOSURE
113
4.4.1 Introduction 113
4.4.2 Exposure Algorithm 113
4.4.3 Exposure Factor Inputs 114
4.4.4 Calculations 119
4.4.5 Exposure Characterization and Uncertainties 120
VI
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5.0 REFERENCES 121
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LIST OF TABLES
Table 1. Roadmap of Example Exposure Scenarios Conversion Factors 11
Table 2. Conversion Factors 12
Table 3. Homegrown Vegetable Intake Rates 20
Table 4. Homegrown Tomato Intake Rate 25
Table 5. Percentage Lipid Content of Beef 30
Table 6. Adult Beef Intake Rates 31
Table 7. Weighted Average Body Weight (Ages 1-75) 36
Table 8. Drinking Water Intake Rate for School Children (Ages 4-10) 43
Table 9. Marine and Freshwater Intake Rates 56
Table 10. Average Body Weight For Children, Age 2-9 57
Table 11. Male and Female Intake Rates for Fish 65
Table 12. Breast Milk Intake Rates 70
Table 13. Body Surface Areas for Residential Gardeners 94
Table 14. Soil Adherence For Residential Gardeners 95
Table 15. Surface Area For Teen Athletes 102
Table 16. Soil Adherence For Teen Athletes 103
Table 17. Body Part Percentages 110
Table 18. Surface Area for Children, Age 7-12 Years 117
Table 19. Body Surface Area Exposed During Wading 118
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PREFACE
The National Center for Environmental Assessment (NCEA) of EPA's Office of
Research and Development prepared the Example Exposure Scenarios to outline scenarios for
various exposure pathways and to demonstrate how data from the Exposure Factors Handbook
(U.S. EPA, 1997a) may be applied for estimating exposures. The Example Exposure Scenarios
is intended to be a companion document to the Exposure Factors Handbook. The example
scenarios presented were compiled from questions and inquiries received from users of the
Exposure Factors Handbook during the past few years on how to select data from the Handbook.
Although a few children scenarios are included in this report, a separate and more comprehensive
document specifically focusing on children scenarios is planned as soon as the Child-Specific
Exposure Factors Handbook is finalized.
The scenarios examined in this report refer to a single chemical and exposure route.
However, EPA promotes and supports the use of new and innovative approaches and tools to
improve the quality of public health and environmental protection. For example, characterizing
the exposures to an individual throughout the different life stages is an area of growing interest.
In addition, in the past few years there has been an increased emphasis in cumulative risk
assessments1, aggregate exposures2, and chemical mixtures. Detailed and comprehensive
guidance for evaluating cumulative risk is not currently available. The Agency has, however,
developed a framework that lays out a broad outline of the assessment process and provides a
basic structure for evaluating cumulative risks. This basic structure is presented in the
Framework for Cumulative Risk Assessment published in May 2003 (U.S. EPA 2003).
The Example Exposure Scenarios does not include an example of a probabilistic
assessment. However, the use of probabilistic methods to characterize the degree of variability
and/or uncertainty in risk estimates is a tool of growing demand. In contrast to the point-estimate
approach, probabilistic methods allow for a better characterization of variability and/or
uncertainty in risk estimates. These techniques are increasingly being used to quantify the range
and likelihood of possible exposure outcomes. Various Program Offices in EPA are directing
efforts to develop guidance on the use of probabilistic techniques. Some of these efforts include:
Summary Report for the Workshop on the Monte Carlo Analysis. U.S. EPA 1996
Guiding Principles for Monte Carlo Analysis. U.S. EPA 1997b
http://www.epa.gov/ncea/raf/montecar.pdf
Policy for Use of Probabilistic Analysis in Risk Assessment, U.S. 1997c
1 Cumulative risk assessment - An analysis, characterization, and possible quantification
of the combined risks to health or the environment from multiple agents or stressors.
2 Aggregate exposures - The combined exposure of an individual (or defined population)
to a specific agent or stressor via relevant routes, pathways, and sources.
ix
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Guidance for Submission of Probabilistic Exposure Assessments to the Office of
Pesticide Programs'Health Effects Division -Draft, U.S.EPA 1998a
http://www.epa.gov/oscpmont/sap/1998/niarch/backgrd.pdf
Report of the Workshop on Selecting Input Distributions for Probabilistic Assessments.
U.S. EPA 1999
Options for Development of Parametric Probability Distributions for Exposure Factors.
U.S. EPA 2000a
Risk Assessment Guidance for Superfund: Volume HI - Part A, Process for Conducting
Probabilistic Assessment, U.S. EPA 2001a
http://www.epa.gov/superfund/programs/risk/rags3a/index.htm
In general, the Agency advocates a tiered approach, which begins with a point estimate
risk assessment. Further refinements to the assessment may be conducted after studying several
important considerations, such as resources, quality and quantity of exposure data available, and
value added by conducting a probabilistic assessment (U.S. EPA 200la). Great attention needs
to be placed in the development of distributions and how they influence the results. A more
extensive discussion of these techniques can be found in EPA 2001a.
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AUTHORS, CONTRIBUTORS, AND REVIEWERS
The National Center for Environmental Assessment (NCEA), Office of Research and
Development was responsible for the preparation of this document. This document has been
prepared by the Exposure Assessment Division of Versar Inc. in Springfield, Virginia, under
EPA Contract No. 68-W-99-041. Jacqueline Moya served as Work Assignment Manager,
providing overall direction, technical assistance, and serving as contributing author.
AUTHORS WORD PROCESSING
Versar. Inc. Versar, Inc.
Linda Phillips Valerie Schwartz
Wendy Powell
CONTRIBUTORS TECHNICAL EDITING
Versar U.S. EPA
Nathan Mottl Laurie Schuda
Kelly McAloon
C. William Smith
U.S. EPA
Jacqueline Moya
Laurie Schuda
The following EPA individuals reviewed an earlier draft of this document and provided
valuable comments:
Marcia Bailey, U.S. EPA, Region X
Denis R. Borum, U.S. EPA, Office of Water, Health and Ecological Criteria Division
Pat Kennedy, U.S. EPA, Office of Prevention, Pesticides, and Toxic Substances
Youngmoo Kim, U.S. EPA, Region VI
Lon Kissinger, U.S. EPA, Region X
Roseanne Lorenzana, U.S. EPA, Region X
Tom McCurdy, U.S. EPA, Office of Research and Development, National Exposure Research
Laboratory
Debdas Mukerjee, U.S. EPA, Office of Research and Development, National Center for
Environmental Assessment-Cincinnatti
Marian Olsen, U.S. EPA, Region H
Marc Stifelman, U.S. EPA, Region X
XI
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This document was reviewed by an external panel of experts. The panel was composed of the
following individuals:
Dr. Robert Blaisdell
Dr. Amy Arcus Arth
Dr. Annette Guiseppi-Elie
Dr. Steven D. Colome
Dr. Annette Bunge
Dr. Mary Kay O'Rourke
California Environmental Protection Agency
1515 Clay St., 16th Floor
Oakland, California 94612
California Environmental Protection Agency
1515 Clay St., 16* Floor
Oakland, California 94612
DuPont Spruance Plant
5401 Jefferson Davis Highway
P.O. Box 126
Richmond, Virginia 23234
University of South Carolina School of Medicine
6311 Garners Ferry Road
Columbia, South Carolina 29209
Colorado School of Mines
1500 Dlinois St
Golden, Colorado 80401
The University of Arizona
Tucson, Arizona 85721
XII
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1.0 INTRODUCTION AND PURPOSE OF THIS DOCUMENT
The Exposure Factors Handbook was published in 1997 (U.S. EPA, 1997a;
http://www.epa.gov/ncea/exposfac.htm). Its purpose is to provide exposure assessors with
information on physiological and behavioral factors that may be used to assess human exposure.
Exposure parameters include factors such as drinking water, food, and soil intake rates,
inhalation rates, skin surface area, body weight, and exposure duration. Behavioral information
(e.g., activity pattern data) is included for estimating exposure frequency and duration. The
Exposure Factors Handbook (U.S. EPA, 1997a) provides recommended values for use in
exposure assessment, as well as confidence ratings for the various factors. However, specific
examples of how the data may be used to assess exposure are not provided.
The purpose of this document is to outline scenarios for various exposure pathways and
to demonstrate how data from the Exposure Factors Handbook (U.S. EPA, 1997a) may be
applied for estimating exposures. It should be noted that the example scenarios presented here
have been selected to best demonstrate the use of the various key data sets in the Exposure
Factors Handbook (U.S. EPA, 1997a), and represent commonly encountered exposure pathways.
An exhaustive review of every possible exposure scenario for every possible receptor population
would not be feasible and is not provided. Instead, readers may use the representative examples
provided here to formulate scenarios that are appropriate to the assessment of interest and apply
the same or similar data sets and approaches as shown in the examples.
1.1 CONDUCTING AN EXPOSURE ASSESSMENT
1.1.1 General Principles
Exposure assessment is the process by which: (1) potentially exposed populations are
identified; (2) potential pathways of exposure and exposure conditions are identified; and (3)
chemical intakes/potential doses are quantified. Exposure may occur by ingestion, inhalation, or
dermal absorption routes. Exposure is commonly defined as contact of visible external physical
boundaries (i.e., mouth, nostrils, skin) with a chemical agent (U.S. EPA, 1992a). As described in
EPA's Guidelines for Exposure Assessment (U.S. EPA, 1992a), exposure is dependent upon the
intensity, frequency, and duration of contact. The intensity of contact is typically expressed in
terms of the concentration of contaminant per unit mass or volume (i.e., |^g/g, /^g/L, mg/m3, ppm,
etc.) in the media to which humans are exposed (U.S. EPA, 1992a).
1
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Dose refers to the amount of chemical to which individuals are exposed that crosses the
external boundary. Dose is dependent upon contaminant concentration and the rate of intake
(i.e., ingestion or inhalation) or uptake (i.e., dermal absorption). Potential dose is the amount of
chemical which could be ingested, inhaled, or deposited on the skin. The absorbed dose is the
amount of chemical absorbed into the body through the gastrointestinal tract, lungs, or skin. The
toxicological basis for risk assessment is typically either the potential dose from animal feeding
studies or the absorbed dose from pharmacokinetic studies followed by intraperitoneal or other
injected delivery into the test animal. Potential dose (PD) may be calculated as follows:
PD = C * IR (Eq. 1)
where:
PD = potential dose (mg/day);
C = contaminant concentration in the media of interest (mg/cm2, mg/m3, mg/g,
mg/L); and
IR = intake or contact rate with that media (cm2/day, mVday, g/day, L/day).
The concentration term is based exclusively on site-and chemical-specific data that are
relevant to the site and/or population of interest. Therefore, recommended default values for this
parameter are not provided in the Exposure Factors Handbook (U.S. EPA, 1997a). The exposure
concentration may be based on a site- and chemical-specific modeled or measured concentration
in the medium (e.g., soil, water, air) of interest. The contact rate is the rate of ingestion,
inhalation, or dermal contact. Note that in some cases, the contact rate may be expressed as the
product of more than one term (e.g., the dermal contact rate for soil may be expressed as the
surface area in cm2/day times the soil adherence factor in mg/cm2).
Potential dose rates may be normalized to body weight as a function of time (i.e.,
mg/kg/day) by multiplying by factors for exposure duration and frequency, and dividing by body
weight and averaging time to yield average daily doses, as follows:
ADDPOT = (PD *ED * EF)/(BW * AT) (Eq. 2)
where:
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ADDPOT = potential average daily dose (mg/kg/day);
ED = exposure duration (days/year);
EF = exposure frequency (years);
BW = body weight (kg); and
AT = averaging time (days).
For some scenarios, additional terms may be necessary to better define the time period
over which exposure occurs. For example, if exposure occurs over hours and not days, exposure
time (ET) may be included with units of hours/day. In such cases, the units for intake rate (IR)
and thus potential dose (PD) need to be adjusted to be consistent with this timeframe. These
units would be cm2/hr, mVhr, g/hr, or L/hr for DR. and mg/hr for PD.
Some factors in the Exposure Factors Handbook (U.S. EPA, 1997a) have been
normalized to body weight (e.g., food ingestion rates). Therefore, in Equation 1 above, the
intake rate would have units such as mg/kg/day and thus, use of the body weight parameter in the
denominator of Equation 2 is not necessary for exposure scenarios involving these parameters.
The length of time over which exposure occurs determines whether such exposure is
considered to be acute, subchronic or chronic. Doses averaged over a single event are considered
to be acute exposures. The definitions of chronic and subchronic used for these example
scenarios were taken from the U.S. EPA's A Review of the Reference Dose and Reference
Concentration Processes (EPA, 2002) which considers exposures occurring over 7 years or less
to be subchronic, and exposures of longer duration to be chronic. The definition of subchronic
exposure may differ by EPA program office, or regulatory agency. Thus, the guidelines used
here are not the only available guidelines and the reader is encouraged to use definitions that are
appropriate for their assessment.
In calculating exposures, Equation 2 can be used to calculate average daily dose (ADD),
lifetime average daily dose (LADD) and/or acute dose rate (ADR). The difference between these
three exposures is the averaging time (AT). The ADD, which is used for many noncancer
effects, averages exposures over the period of time during which the exposure occurred. The
LADD is typically used for cancer assessments where the LADD is usually described in terms of
lifetime probabilities, even though the exposure does not occur over the entire lifetime; in
Equation 2, AT is replaced with lifetime. ADR is also calculated using Equation 2, but AT is
equal to one day.
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Absorbed doses may be calculated by including an absorption factor in the equations
above. The portion of the potential dose (e.g., ADDPOT) that actually penetrates through the
absorption barriers of the organism (e.g., the gut, the lung or the skin) is the absorbed dose (e.g.,
ADDABS) or internal dose. In this situation, the absorbed dose may be related to the potential
dose through an absorption factor (ABS) as follows:
ADDABS = ADD^ x ABS (Eq. 3)
Potential dose estimates may not be meaningful for dermal exposures to contaminants in large
volumes of media (e.g., contaminated water in pools, baths and showers). For exposure scenarios
of this type, absorbed dose estimates are necessary.
Central tendency, high-end, and/or bounding estimates may be made using this algorithm.
These exposure descriptors account for individual and population variability and represent points
on the distribution of exposures. Central tendency potential dose rates may be estimated using
central tendency values for all the input values in the algorithm. The high-end potential dose rate
(90th or 99.9th percentile) is a reasonable approximation of dose at the upper end of the
distribution of exposures (U.S. EPA, 1992a). High-end values are estimated by setting some, but
not all, input parameters to upper-end values. Finally, bounding potential dose rates are
exposures that are estimated to be greater than the highest individual exposure in the population
of interest. Bounding estimates use all upper-percentile inputs and are often used in screening-
level assessments. (Note: users are cautioned about using all high-end inputs except in cases
where screening level or acute estimates are desired because setting all exposure factor inputs to
upper-percentile values may result in dose estimates that exceed reasonable maximum values for
the population of interest.) Upper-percentile values are also frequently used in estimating acute
exposures. For example, an assessor may wish to use a maximum value to represent the
contaminant concentration in an acute exposure assessment but evaluate chronic exposures using
an average (or 95% upper confidence level of the mean) contaminant concentration.
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1.1.2 Important Considerations in Calculating Dose
Inputs for the exposure calculations shown above should be representative of the
populations and pathways of exposure. It is important to select the age group, ethnic or regional
population, or other population category of interest. Use of data;from unrelated groups is not
recommended. Frequently, exposure scenarios are developed to assist the assessor in defining
the specific receptor populations and exposure conditions for which doses will be calculated. In
general, an exposure scenario is defined as a set of facts, assumptions, and inferences about how
exposure takes place that aids the exposure assessor in evaluating, estimating, or quantifying
exposure. For the purposes of demonstrating how data from the Exposure Factors Handbook
(U.S. EPA, 1997a) can be used to assess exposures, numerous example scenarios have been
developed. Each scenario is explained in terms of the exposure pathway, receptor population,
duration of exposure (acute, subchronic, chronic or lifetime), and exposure descriptor (i.e.,
central tendency, high-end, or bounding).
In addition to using exposure factor data that are specific to the population/receptor of
interest, several other important issues should be considered in assessing exposure. First, it is
important to ensure that the units of measure used for contact rate are consistent with those used
for intake rate. Examples of where units corrections may be needed are in converting skin
surface areas between units of cm2/event and m2/event to be consistent with surface residue
concentrations, or converting breast milk intake rates from g/day to mL/day to be consistent with
breast milk chemical concentrations. Common conversion factors are provided in Table 2 to
assist the user in making appropriate conversions. Another example of where specific types of
units corrections may be required is with ingestion rates. As described in Volume n of the
Exposure Factors Handbook, residue concentrations in foods may be based on wet (whole)
weights, lipid weights, or dry weights. The assessor must ensure that the units used for
concentration are consistent with those used for ingestion rate. For example, if residue
concentrations in beef are reported as mg of contaminant/g of beef fat, the intake rate for beef
should be g beef fat consumed/day. This may require that the beef ingestion rate presented in
units of g beef, as consumed (whole weight)/day in the Exposure Factors Handbook (U.S. EPA,
1997a) be converted to g beef fat consumed/day using the fat content of beef and the conversion
equations provided in the Exposure Factors Handbook (U.S. EPA, 1997a). Alternatively, the
residue concentration can be converted to units that are consistent with the intake rate units.
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Another important consideration is the linkage between contact rate and exposure
frequency. It is important to define exposure frequency so that it is consistent with the contact
rate estimate. For example, the food ingestion rate can be based on a single event such as a
serving size/event, or on a long-term average (e.g., daily average ingestion rate in g/day). For
contact rates based on a single event, a frequency that represents the number of events over time
(e.g., events/year) would be appropriate. However, when a long-term average is used, the
duration over which the contact rate is based must be used. For example, when an annual daily
average ingestion rate is used, 365 days/year must be used as the exposure frequency because the
food intake rate represents the average daily intake over a year including both days when the food
was consumed and days when the food was not consumed. The objective is to define the terms
so that, when multiplied, they give the appropriate estimate of mass of contaminant contacted.
For some factors such as food, water, and soil ingestion, there is another important issue
to consider. The assessor must decide whether the assessment will evaluate exposure for
consumers only, or on a. per capita basis. Consumer only assessments include only those
individuals who are engaged in the activity of interest (e.g., fish consumption). Thus, the
exposure factors (e.g., fish intake rates) are averaged over users only. In contrast, per capita data
are used to assess exposure over the entire population of both users and non-users. The
variability in the population should also be considered. As described above, central tendency,
high-end, or bounding estimates may be generated, depending on the input factors used.
Also, as described above, for some exposure factors (e.g., intake rates for some foods),
body weight has been factored into the intake rate. In these cases, the intake rates are expressed
in units such as mg/kg/day. When exposure factors have been indexed to body weight, the term
body weight can be eliminated from the denominator of the dose equation because body weight
has already been accounted for.
Uncertainty may be introduced into the dose calculations at various stages of the exposure
assessment process. Uncertainty may occur as a result of: the techniques used to estimate
chemical residue concentrations (these are not addressed in the Exposure Factors Handbook
(U.S. EPA, 1997a) or here), or the selection of exposure scenarios or factors. Variability can
occur as a result of variations in individual day-to-day or event-to-event exposure factors or
variations among the exposed population. Variability can be addressed by estimating exposure
for the various descriptors of exposure (i.e., central tendency, high-end, or bounding) to estimate
points on the distribution of exposure, as described above. The reader should refer to Volume I,
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Chapter 2 of the Exposure Factors Handbook (U.S. EPA, 1997a) for a detailed discussion of
variability and uncertainty. Also, as described in the Exposure Factors Handbook (U.S. EPA,
1997a), some factors have higher confidence ratings than others. These confidence ratings are
based on, among other things, the representativeness, quality, and quantity of the data on which a
specific recommended exposure factor is based. Assessors should consider these confidence
ratings, as well as other limitations of the data in presenting a characterization of the exposure
estimates generated using data from the Exposure Factors Handbook (U.S. EPA, 1997a).
1.1.3 Other Sources of Information on Exposure Assessment
For additional information on exposure assessment, the reader is encouraged to refer to
the following EPA documents:
Guidelines for Exposure Assessment (U.S. EPA 1992a;
http://www.epa.gov/nceawww 1/exposure.htm);
Dermal Exposure Assessment: Principles and Applications (U.S. EPA 1992b;
http://oaspub.epa.gov/eims/eimsapi.detail?deid=12188&partner=ORD-NCEA. Note
that in September 2001, EPA proposed Supplemental Guidance for Dermal Risk
Assessment, under Part E of Risk Assessment Guidance for Superfund (RAGS) (See
below). This guidance updates many portions of this earlier 1992 guidance.
Although still not final, the 2001 guidance is generally more representative of current
thinking in this area and assessors are encouraged to use it instead of U.S. EPA,
1992b.);
Methodology for Assessing Health Risks Associated with Indirect Exposure to
Combustor Emissions (U.S. EPA, 1990);
Risk assessment guidance for Superfund. Human health evaluation manual: Part A.
Interim Final (U.S. EPA., 1989;
http://www.epa.gov/superfund/programs/risk/ragsa/index.htm}
Risk Assessment Guidance for Superfund. Human health evaluation manual: Part B.
Interim Final (U.S. EPA., 1991;
http://www.epa.gov/superfund/programs/risk/ragsb/index.htm)
Risk Assessment Guidance for Superfund. Human health evaluation manual: Part C.
Interim Final (U.S. EPA., 1991;
http://www.epa.gov/superfund/programs/risk/ragsc/index.htm)
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Risk Assessment Guidance for Superfund. Human health evaluation manual: Part D.
Interim Final (U.S. EPA., 1998b;
http://www.epa.gov/superfund/programs/risk/ragsd/index.htm}
Risk Assessment Guidance for Superfund. Human health evaluation manual: Part E.
Interim Final (U.S. EPA., 2001b http://www.epa.gov/superfund/programs/risk/ragse)
Estimating Exposures to Dioxin-Like Compounds (U.S. EPA, 1994);
Superfund Exposure Assessment Manual (U.S. EPA, 1988a);
Selection Criteria for Mathematical Models Used in Exposure Assessments (Surface
water and Ground water) (U.S. EPA 1987 & U.S. EPA 1988b);
Standard Scenarios for Estimating Exposure to Chemical Substances During Use of
Consumer Products (U.S. EPA 1986a);
Pesticide Assessment Guidelines, Subdivisions K and U (U.S. EPA, 1984, 1986b);
Methods for Assessing Exposure to Chemical Substances, Volumes 1-13 (U.S. EPA,
1983-1989, available through NTIS);
Standard Operating Procedures (SOPs) for Residential Exposure Assessments, draft
(U.S. EPA, 1997d; http://www.epa.gov/oscpmont/sap/1997/september/sopindex.htm);
and
Soil Screening Guidance, Technical Background Document (U.S., EPA, 1996b, 2001;
http://www.epa.gov/superfund/resources/soil/introtbd.htm).
Revised Methodology for Deriving Health-Based Ambient Water Quality Criteria
(U.S. EPA 2000b; http://www.epa.gov/waterscience/humanhealth/method/)
1.2 CHOICE OF EXPOSURE SCENARIOS
This document is not intended to be prescriptive, or inclusive of every possible exposure
scenario that an assessor may want to evaluate. Instead, it is intended to provide a representative
sampling of scenarios that depict use of the various data sets in the Exposure Factors Handbook
(U.S. EPA, 1997a). Likewise, this document is not intended to be program-specific. Policies
within different EPA program offices may vary, and the examples presented in this document are
not meant to supercede program-specific exposure assessment methods or assumptions.
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Exposure assessors are encouraged to review the examples provided here and select the examples
that are most applicable to the scenarios they wish to evaluate. The approaches suggested here
are not the only approaches that can be used and the data may be modified, as needed, to fit the
scenario of interest. For instance, an example scenario may use ingestion of drinking water
among children between the ages of 1 and 5 years to demonstrate the use of drinking water intake
data, while the assessor is interested in children between the ages of 12 and 18 years. Therefore,
the assessor may wish to use the suggested approach and the same data set, but use data for a
different age group. Likewise, examples may depict upper bound exposures, while an
assessment of central tendency is required, or chronic exposure may be shown in the example
when an estimate of acute exposure is desired. Again, the suggested approach may be used with
different inputs from the same or related data set. Where site-specific data are available, they
may be used to replace data presented in the examples. Although calculation of health risks and
the use of chemical-specific toxicity data are beyond the scope of this document, selection of
input data requires consideration of the toxicity data for the chemical contaminant being
assessed. For example, averaging times will vary depending on whether the contaminant is a
carcinogen or not. Also, the health-based impact of an exposure may be related to life-stage
because system and organ development vary with time. Thus, exposure factor data that are
relevant to the activities, behaviors, and physical characteristics of the relevant age groups should
be used. Other attributes of the exposed population of interest (e.g., gender, race) should also be
given careful consideration when formulating an exposure scenario and selecting input data.
An effort has been made to present examples that represent a wide range of possible
scenarios in terms of receptor populations, exposure descriptor (i.e., central tendency, high-end,
or bounding exposure), and exposure duration (i.e., acute, subchronic, or chronic). These
example scenarios utilize single values for each input parameter (i.e., point estimates), as
required to conduct deterministic assessments. Probabilistic techniques are not presented.
However, the same algorithms and the same data distributions from which the point estimates are
derived may be used in probabilistic assessments (e.g., Monte Carlo analyses). Readers who
wish to conduct probabilistic assessments should refer to Volume I, Chapter 1 of EPA's
Exposure Factors Handbook (U.S. EPA, 1997a) for general considerations for conducting such
analyses. In addition, multiple pathway/source scenarios are not included in the examples
presented here. These scenarios are being considered and discussed by the U.S. EPA and an
agency workgroup is in the process of developing a framework for evaluating such scenarios.
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Example scenarios are provided in this document according to exposure route (i.e.,
ingestion, inhalation, dermal contact). Each example scenario provides a brief introductory
description of the scenario, the algorithm used for estimating dose, suggested input values and
the rationale for their use as well as the location in the Exposure Factors Handbook (U.S. EPA,
1997a) from where they were derived, example calculations, and an exposure characterization
which includes a description of the uncertainty/limitations of the data and/or approach. The
exposure characterization for each example scenario includes a confidence rating, based in part
on the factor-specific confidence ratings provided in the Exposure Factors Handbook (U.S. EPA,
1997a). The basis of these factor-specific confidence ratings is described in detail in Section
1.3.3 of the Handbook and consider criteria such as the number of and representativeness of
studies used to recommend the exposure factor values. The combination of factor-specific
ratings was used to provide an overall rating for the dose estimate for each example scenario.
These overall ratings are qualitative in nature and reflect the best professional judgement of the
authors of this document, considering the basis of the individual factor-specific ratings and the
relative impact of each factor on the overall estimate. For example, an example scenario result
may be given an overall low rating based on a combination of exposure factors with low and high
confidence individual ratings. This assumes that the low ratings for some factors limits the
overall rating to low. Table 1 provides a road map to the example exposure scenarios.
1.3 CONVERSION FACTORS
Frequently, exposure assessments require the use of weight, area, or volume conversion
factors. Conversion factors may be used to convert these units of measure to those needed to
calculate dose. These factors are used, for example, to ensure consistency between the units used
to express exposure concentration and those used to express intake. Table 2 provides a list of
common conversion factors that may be required in the exposure equations shown above.
10
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Table 1. Roadmap to Example Exposure Scenarios
1 Exposure Calculated
Distribution Dose Receptor Population Exposure Media Section
Ingestion
High-end
High-end
High-end
High-end
Bounding
Bounding
Bounding
Bounding
Central Tendency
Central Tendency
Central Tendency
Central Tendency
Central Tendency
Central Tendency
ADR
ADD
LADD
LADD
ADR
ADR
LADD
LADD
ADD
ADD
ADD
LADD
LADD
LADD
Adults
Children
Farm workers
Young children
General population
Children
Adult males
Native American adults
School children
Infants
Children
Occupational males
adults
Occupation adults
Adults
Fish
Homegrown tomatoes
Drinking water
Indoor dust
Dairy products
Pool water
Drinking water
Fish
Drinking water
Breast milk
Fish
Homegrown vegetables
Indoor dust from outdoor soil
Beef
2.11
2.2
2.5
2.13
2.4
2.8
2.7
2.10
2.6
2.12
2.9
2.1
2.14
2.3
Inhalation
High-end
High-end
Central Tendency
Central Tendency
Central Tendency
ADR
LADD
LADD
LADD
ADD
Adults
Adults
Occupational females
adult
Residential children
School children
Outdoor air
Ambient air
Indoor air
Indoor air
Indoor air
3.2
3.5
3.1
3.3
3.4
Dermal
Central Tendency
Central Tendency
Central Tendency
Central Tendency
ADD
LADD
LADD
LADD
Teen athletes
Adult gardeners
Adults
Children
Outdoor soil
Outdoor soil
Paint preservative
Recreational water
4.2
4.1
4.3
4.4
11
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Table 2. Conversion Factors
, -;4^.^.ife^^v;^
"^ * * / * " t
cubic centimeters (cm3)
cubic centimeters (cm3)
cubic meters (m3)
gallons (gal)
liters (L)
liters (L) (water, milk)
liters (L)
liters (L)
milliliters (mL)
milliliters (mL) (water, milk)
^i^F^ftv,, 4 ^^^K^f*Ji*l^^^f^^^|V'f'*^:ili*
0.001
0.001
1,000
3.785
0.264
1,000
1,000
1,000
0.001
1
;V.H!'''' -'>-% ^Vlifit 4#; - >!:S"?
square centimeters (cm2)
square meters (m2)
0.0001
10,000
cubic meters (m3)
liters (L)
cubic centimeters (cm3)
liters (L)
gallons (gal)
grams (g) (water, milk)
milliliters (mL)
cubic centimeters (cm3)
liters (L)
grams (g) (water, milk)
r ^K^J ^ ;«-^*^y-"4^ >.;]*. '^; ; !*.
pound (Ib)
milliliters (mL) (water, milk)
liters (L) (water, milk)
milligrams (mg)
kilograms (Kg)
grams (g)
milligrams (mg)
grams (g)
micrograms (jig)
grams (g)
1 '^i ' * -'"V-' , H ~ ;>
square meters (m2)
square centimeters (cm2)
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1.4 DEFINITIONS
This section provides definitions for many of the key terms used in these example
scenarios. Most of these definitions are taken directly from EPA's Guidelines for Exposure
Assessment (U.S. EPA, 1992a) or EPA's Exposure Factors Handbook (U.S. EPA, 1997a).
Absorbed Dose - The amount of a substance penetrating across the absorption barriers (the
exchange boundaries) of an organism, via either physical or biological processes. This is
synonymous with internal dose, which is a more general term denoting the amount absorbed
without respect to specific absorption barriers or exchange boundaries. In the calculation of
absorbed dose for exposures to contaminated water in bathing, showering or swimming, the
outermost layer of the skin is assumed to be an absorption barrier.
Absorption Fraction (ABS, percent absorbed) - The relative amount of a substance that
penetrates through a barrier into the body, reported as a percent.
Activity Pattern (time use) Data - Information on activities in which various individuals
engage, length of time spent performing various activities, locations in which individuals spend
time and length of time spent by individuals within those various environments.
Acute Dose Rate (ADR) - Dose from a single event or average over a limited time period (e.g. 1
day)
Ambient - The conditions surrounding a person, sampling location, etc.
Applied Dose - The amount of a substance presented to an absorption barrier and available for
absorption (although not necessarily having yet crossed the outer boundary of the organism).
As Consumed Intake Rates - Intake rates that are based on the weight of the food in the form
that it is consumed.
Average Daily Dose (ADD) - Dose rate averaged over a pathway-specific period of exposure
expressed as a daily dose on a per-unit-body-weight basis. The ADD is used for exposure to
chemicals with non-carcinogenic non-chronic effects. The ADD is usually expressed in terms of
mg/kg-day or other mass/mass-time units.
Averaging Time (AT) - The time period over which exposure is averaged.
Bounding Dose Estimate - An estimate of dose that is higher than that incurred by the person in
the population with the highest dose. Bounding estimates are useful in developing statements
that doses are "not greater than" the estimated value.
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Central Tendency Dose Estimate - An estimate of dose for individuals within the central
portion (average or median) of a dose distribution.
Chronic Intake (exposure) - The long term period over which a substance crosses the outer
boundary, is inhaled, or is in contact with the skin of an organism without passing an absorption
barrier.
Consumer-Only Intake Rate - The average quantity of food consumed per person in a
population composed only of individuals who ate the food item of interest during a specified
period.
Contact Rate - General term used to represent rate of contact with a contaminated medium.
Contact may occur via ingestion, inhalation, or dermal contact.
Contaminant Concentration (C) - Contaminant concentration is the concentration of the
contaminant in the medium (air, food, soil, etc.) contacting the body and has units of
mass/volume or mass/mass.
Deposition - The removal of airborne substances to available surfaces that occurs as a result of
gravitational settling and diffusion, as well as electrophoresis and thermophoresis; substances at
low concentrations in the vapor phase are typically not subject to deposition in the environment.
Distribution - A set of values derived from a specific population or set of measurements that
represents the range and array of data for the factor being studied.
Dose - The amount of a substance available for interaction with metabolic processes or
biologically significant receptors after crossing the outer boundary of an organism.
Dose Rate - Dose per unit time, for example in mg/day, sometimes also called dosage. Dose
rates are often expressed on a per-unit-body-weight basis yielding such units as mg/kg/day. They
are also often expressed as averages over some time period (e.g., a lifetime).
Dry Weight Intake Rates - Intake rates that are based on the weight of the food consumed after
the moisture content has been removed.
Exposed Foods - Those foods that are grown above ground and are likely to be contaminated by
pollutants deposited on surfaces that are eaten.
Exposure - Contact of a chemical, physical, or biological agent with the outer boundary of an
organism. Exposure is quantified as the concentration of the agent in the medium in contact
integrated over the time duration of the contact.
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Exposure Assessment - The determination of the magnitude, frequency, duration, and route of
exposure.
Exposure Concentration - The concentration of a chemical in its transport or carrier medium at
the point of contact.
Exposure Duration (ED) - Total time an individual is exposed to the chemical being evaluated.
Exposure Frequency (EF) - How often a receptor is exposed to the chemical being evaluated.
Exposure Pathway - The physical course a chemical or pollutant takes from the source to the
organism exposed.
Exposure Route - The way a chemical or pollutant enters an organism after contact (e.g., by
ingestion, inhalation, or dermal absorption).
Exposure Scenario - A set of facts, assumptions, and inferences about how exposure takes place
that aids the exposure assessor in evaluating, estimating, or quantifying exposure.
General Population - The total of individuals inhabiting an area or making up a whole group.
Geometric Mean - The n* root of the product of n values.
High-end Dose Estimates - A plausible estimate of individual dose for those persons at the
upper end of a dose distribution, conceptually above the 90th percentile, but not higher than the
individual in the population who has the highest dose.
Homegrown/Home Produced Foods - Fruits and vegetables produced by home gardeners, meat
and dairy products derived form consumer-raised livestock, game meat, and home caught fish.
Inhalation Rate (InhR)- Rate at which air is inhaled. Typically presented in units of mVhr,
mVday or L/min.
Inhaled Dose - The amount of an inhaled substance that is available for interaction with
metabolic processes or biologically significant receptors after crossing the outer boundary of an
organism.
Intake - The process by which a substance crosses the outer boundary of an organism without
passing an absorption barrier (e.g., through ingestion or inhalation).
Intake Rate (IR) - Rate of inhalation, ingestion, and dermal contact, depending on the route of
exposure. For ingestion, the intake rate is simply the amount of food containing the contaminant
of interest that an individual ingests during some specific time period (units of mass/time). For
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inhalation, the intake rate is the inhalation rate (i.e., rate at which air is inhaled). Factors that
can affect dermal exposure are the amount of material that comes into contact with the skin, the
rate at which the contaminant is absorbed, the concentration of contaminant in the medium, and
the total amount of the medium on the skin during the exposure duration.
Internal Dose - The amount of a substance penetrating across absorption barriers (the exchange
boundaries) of an organism, via either physical or biological processes (synonymous with
absorbed dose).
Lifetime Average Daily Dose (LADD) - Dose rate averaged over a lifetime. The LADD is used
for compounds with carcinogenic or chronic effects. The LADD is usually expressed in terms of
mg/kg-day or other mass/mass-time units.
Mean Value - The arithmetic average of a set of numbers.
Median Value - The value in a measurement data set such that half the measured values are
greater and half are less.
Moisture Content - The portion of foods made up by water. The percent water is needed for
converting food intake rates and residue concentrations between whole weight and dry weight
values.
Monte Carlo Technique - As used in exposure assessment, repeated random sampling from the
distribution of values for each of the parameters in a generic (exposure or dose) equation to
derive an estimate of the distribution of (exposures or doses in) the population.
Occupational Tenure - The cumulative number of years a person worked in his or her current
occupation, regardless of number of employers, interruptions in employment, or time spent in
other occupations.
Per Capita Intake Rate - The average quantity of food consumed per person in a population
composed of both individuals who ate the food during a specified time period and those that did
not.
Pica - Deliberate ingestion of non-nutritive substances such as soil.
Population Mobility - An indicator of the frequency at which individuals move from one
residential location to another.
Potential Dose (PD) - The amount of a chemical which could be ingested, inhaled, or deposited
on the skin.
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Preparation Losses - Net cooking losses, which include dripping and volatile losses, post
cooking losses, which involve losses from cutting, bones, excess fat, scraps and juices, and other
preparation losses which include losses from paring or coring.
Probabilistic Uncertainty Analysis - Technique that assigns a probability density function to
one or more input parameters, then randomly selects values from the distributions and inserts
them into the exposure equation. Repeated calculations produce a distribution of predicted
values, reflecting the combined impact of variability in each input to the calculation. Monte
Carlo is a common type of probabilistic technique.
Recreational/Sport Fishermen - Individuals who catch fish as part of a sporting or recreational
activity and not for the purpose of providing a primary source of food for themselves or for their
families.
Representativeness - The degree to which a sample is, or samples are, characteristic of the
whole medium, exposure, or dose for which the samples are being used to make inferences.
Residential Occupancy Period - The time (years) between a person moving into a residence
and the time the person moves out or dies.
Screening-Level Assessments - Typically examine exposures that would fall on or beyond the
high end of the expected exposure distribution.
Serving Sizes - The quantities of individual foods consumed per eating occasion. These
estimates may be useful for assessing acute exposures.
Subchronic Intake - A period over which intake occurs that is less than or equal to 7 years in
duration.
Subsistence Fishermen - Individuals who consume fresh caught fish as a major source of food.
Transfer Fraction (TF) - The fraction of chemical that is transferred to the skin from
contaminated surfaces in contact with that surface.
Upper-Percentile Value - The value in a measurement data set that is at the upper end of the
distribution of values.
Uptake - The process by which a substance crosses an absorption barrier and is absorbed into the
body.
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2.0 EXAMPLE INGESTION EXPOSURE SCENARIOS
2.1 PER CAPITA INGESTION OF CONTAMINATED HOMEGROWN
VEGETABLES: GENERAL POPULATION (ADULTS), CENTRAL TENDENCY,
LIFETIME AVERAGE EXPOSURE
2.1.1 Introduction
At sites where there is localized soil or water contamination, or where atmospheric fallout
of contaminants has been observed or is expected, the potential may exist for uptake of
contaminants by locally grown produce. This may result in exposure among local populations
via ingestion of vegetables grown in the contaminated area. Receptors could include nearby
farming families or home-gardeners and their families, who consume produce grown in the
contaminated area. Exposure via intake of contaminated vegetables considers not only the
concentrations of contaminants in the food item(s) of concern, but also the rate at which the food
is consumed, and the frequency and duration of exposure. For the purposes of this example,
exposure via contaminated vegetables is assumed. Lifetime average daily exposure from- the
ingestion of homegrown vegetables is evaluated for the general population (adults).
2.1.2 Exposure Algorithm
Exposure via this pathway would be calculated as follows:
LADD - ^ * IRves * EF* ED (Eq-4)
LSUJLJ -
where:
veg ing = potential lifetime average daily dose from ingestion of
contaminated vegetables at a contaminated site (mg/kg-day);
Cveg = concentration of contaminant in the homegrown vegetables from
the site (mg/g);
IRveg = per capita intake rate of vegetables homegrown at the site
(g/kg/day);
EF = exposure frequency (days/year);
ED = exposure duration (years); and
AT = averaging time (days).
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2.1.3 Exposure Factor Inputs
C veg - The concentration of contaminant in vegetables grown at the site (Cveg) is either the
measured or predicted concentration, based on modeling, of the chemical of interest in the
vegetables consumed from the site of interest. For estimating central tendency exposures, the
mean or median values would be used. Often, the 95 percent upper confidence limit of the mean
concentration is used as a conservative estimate of the mean concentration. For the purposes of
the example calculations shown below, it is assumed that the modeled 95 percent upper
confidence limit of the mean concentration of contaminant "x" in vegetables is IxlO"3 mg/g.
IRveg- The per capita intake rate for homegrown vegetables (IRveg) can be estimated from
data in the Exposure Factors Handbook (U.S. EPA, 1997a) using two slightly different, but
equally appropriate, approaches. In the first approach, the mean per capita ("as eaten") vegetable
intake rate for all adults (3.78 g/kg-day average of mean intake for ages 20-39,40-69, and 70+
years) from Table 9-4 of the Exposure Factors Handbook (U.S. EPA, 1997a), is multiplied by
the fraction of total vegetable intake represented by homegrown vegetables (0.068) from Table
13-71 of the Exposure Factors Handbook (U.S. EPA, 1997a), based on the NFCS household
consumption analysis. The resulting value represents the per capita homegrown intake rate (0.26
g/kg-day). In the second approach, the mean "consumer only" homegrown intake rate (2.02 g/kg-
day average of mean intake for ages 20-39,40-69, and 70+ years) from Table 13-13 of the
Exposure Factors Handbook (U.S. EPA, 1997a) is multiplied by the average percent of
individuals in these groups consuming homegrown vegetables during the survey period (0.206)
from Table 13-13 to get the per capita homegrown vegetable intake rate. Also, because the
intake data used here are based on household use data (i.e., raw; not "as eaten" as used above in
Approach 1), they are multiplied by 1 minus the weight of the food item lost in preparation
(Table 13-7) to arrive at the per capita "as eaten" homegrown vegetable intake rate. Because
there is no preparation loss value for total vegetables, a mean preparation loss value from data for
17 different vegetables presented in Table 13-7 of the Exposure Factors Handbook (U.S. EPA,
1997a) is used here (0.12 or 12 percent). The resulting value [2.02 g/kg-day * 0.206 * (1-0.12)]
represents the per capita homegrown intake rate (0.37 g/kg-day). The IRveg values calculated by
these two approaches are similar, with the intake rate from the second approach being slightly
higher. The second approach uses data from the household portion of the NFCS in which waste
and spoilage are not considered in calculating intake rates. This may account for the slightly
higher value. However, the difference between 0.26 and 0.37 is probably not significant enough
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to result in a major impact in estimated exposures. Table 3 shows a comparison of these two
approaches.
* ~.' »<4v *JK- *' > 'j£J --
Approach 1 -
CSHI - Per Capita Total Vegetable Intake "as
eaten" (Table 9-4; Average of Means for Ages 20-
39,40-69, and 70+ Years) * Fraction Homegrown
(Table 13-71).
3.78g/kg-day * 0.068 =
0.26 g/kg-day
Approach 2 -
NFCS - Consumer Only Homegrown Intake Rate
(Table 13-13; Average of Means for Ages 20-39,
40-69, and 70+ years) * Mean Fraction of
Individuals in 3 Adult Age Groups Consuming
Homegrown Vegetables During Survey (Table 13-
13) * 1- Preparation Loss Fraction (Table 13-7).
2.02 g/kg-day * 0.206 *
(1-0.12) =
0.37 g/kg-day
EF - Exposure frequency (EF) is 365 days a year because the data used in estimating IRveg
are assumed to represent average daily intake over the long-term (i.e., over a year).
ED - Exposure duration (ED) is the length of time over which exposure occurs. For the
purposes of this example, the average residency time of the household is assumed. Based on the
recommendations in Table 15-174 of the Exposure Factors Handbook (U.S. EPA, 1997a), the
50th percentile residence time is 9 years. Thus, the assumption in this example is that the
exposed population consumes homegrown vegetables that have become contaminated on the site
at which they reside for 9 years. After that time, they are assumed to reside in a location where
the vegetables are not affected by contamination from the site.
AT - Because the lifetime average daily dose is being calculated for a member of the
general population, the averaging time (AT) is equivalent to the lifetime of the individual being
evaluated. For the purposes of this example, the average lifetime for men and women is used
because the exposures are assumed to reflect the general population and are not gender- or age-
specific. This value is assumed to be 70 years. For use in the calculations, this value is
converted to 25,550 days (i.e., 70 years * 365 days/year).
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2.1.4 Calculations
Using the exposure algorithm and exposure factor inputs shown above, the LADDPOTveging
would be as follows using either Approach 1 or Approach 2 for calculating IRveg for the general
population.
Approach 1
r jnn - 1*^Q wg/g * 0.26 glkg- day * 365 days/year * 9 years
'^ = 25,550 days
Approach 2
T/inn - l*-fQ frig/g * Q-37 glkg- day * 365 days/year * 9
= 25,550 days
2.1.5 Exposure Characterization and Uncertainties
The example presented here is used to represent central tendency exposures among the
adult general population from the ingestion of contaminated vegetables. High-end exposures
may be estimated by replacing the mean intake rates and residence time used here with upper-
percentile intake rates and residence time from the Exposure Factors Handbook (U.S. EPA,
21
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1997a) tables cited above. If a bounding exposure estimate is desired, the chemical
concentration in vegetables may also be set to the maximum measured or modeled concentration.
Caution should be used, however, in setting all exposure factor inputs to upper-percentile values,
as the resulting exposure estimates may exceed reasonable maximum exposures for the
population of interest. It also must be noted that the reasonable maximum exposure is specific to
the Superfund program and may not be appropriate for other programs.
The uncertainties associated with this example scenario are related to assumed activity
patterns of the receptor population and the input parameters used. Implicit in this scenario is the
assumption that the population of interest actually consumes produce grown on site, and that
consumption occurs at the rates specified in the Exposure Factors Handbook (U.S. EPA, 1997a).
In reality, only a fraction of individuals surveyed actually consumed homegrown produce during
the survey period, according to the Exposure Factors Handbook (U.S. EPA, 1997a). This means
that some members of the general population may never consume homegrown produce (others
may consume homegrown produce, but did not consume it during the survey period). Thus, the
per capita intake rate of homegrown vegetables used in this example might overestimate the
exposure for general population adults, but underestimate exposure for the population that
regularly consumes homegrown vegetables. Also because rates for intake of total vegetables are
used, and a single value is used to represent the concentration of contaminant in all vegetables, it
is assumed that all vegetables consumed from the site contain contaminant at the average (or 95
percent upper confidence limit) concentration. The intake rates used in this example are based
on survey data collected over short periods (i.e., 3 to 7 days), but are used to represent long-term
averages. The Exposure Factors Handbook (U.S. EPA, 1997a) describes the uncertainty
associated with this assumption, and concludes that for broad food categories such as total
vegetables, the short-term distribution may be a reasonable approximation of the long-term
distribution of average daily intakes, but may overestimate the upper-percentiles of the long-term
distribution. Thus, use of the data from the upper end of the intake distribution is likely to be
conservative.
It should be noted that the confidence ratings given by the Exposure Factors Handbook
(U.S. EPA, 1997a) are high for average intake rates derived from USDA's CSFn (lower for
upper-percentile data because of short-term, 3-day survey data used), medium for average
homegrown intake rates (lower for upper-percentile rates because of the short-term, 7-day survey
data used), and medium for the residence time data. Assuming that the confidence in the
22
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exposure concentration is also at least medium, confidence in the overall central tendency
exposure example provided here should also be at least medium.
23
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2.2 CONSUMER ONLY INGESTION OF CONTAMINATED HOMEGROWN
TOMATOES: CHILDREN, HIGH-END, CHRONIC DAILY EXPOSURE
2.2.1 Introduction
At sites where soil or water contamination exists or where fallout of contaminants has
been observed or is expected, there is potential for contamination of locally grown tomatoes, as a
result of plants taking up contaminants from soil and water, or from air deposition. This might
result in an exposure among local populations via ingestion of tomatoes grown in a contaminated
area. Receptors could include nearby farmers or home-gardeners and their families, who
consume home produced tomatoes. Exposure via home grown tomatoes is estimated based on
the concentration of contaminants in tomatoes, intake rates of tomatoes, exposure frequency, and
exposure duration. In this example, exposure via ingestion of contaminated tomatoes is assumed
and the high-end chronic daily exposure from this pathway is evaluated for the population of
children in households (farmers or home gardeners) with consumption of home grown tomatoes.
2.2.2 Exposure Algorithm
Exposure via this pathway would be calculated as follows:
ADD
Ctomato * IRtomato *
POT tomato ing
AT
EF* ED
(Eq.5)
where:
ADD
POT tomato ing
^"tomato
"^tomato
DW
EF
ED
AT
potential average daily dose from ingestion of contaminated
tomatoes grown at a contaminated site (mg/kg-day);
concentration of contaminant in tomatoes grown at the
contaminated site (mg per gram of dry weight);
"consumer only" intake rate of tomatoes (g/kg/day);
dry weight percentage of tomatoes (only necessary if contamination
is provided in dry weight measurements);
exposure frequency (days/year);
exposure duration (years); and
averaging time (days).
24
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2.2.3 Exposure Factor Inputs
Ctomato - The concentration of contaminants in tomatoes is either the measured or
predicted concentration, based on modeling, of the chemical of interest in tomatoes produced at a
contaminated site. For estimating high-end exposures, a combination of central tendency and
upper-percentile values would be used. The 95% upper confidence limit of the mean
concentration can be used as a conservative estimate of the mean concentration. For the purpose
of the example calculations shown below, it is assumed that the modeled 95% percent upper
confidence limit of the mean concentration of chemical "x" in tomatoes is IxlO"3 mg per gram of
dry weight.
IRtomato - The "consumer only "intake rates of home grown tomatoes for children of ages
1-11 can be estimated based on "consumer only" intake rates of home produced tomatoes
provided in Table 13-59 of the Exposure Factors Handbook (U.S. EPA, 1997a). This "consumer
only" value represents the intake for individuals who consume home produced tomatoes (i.e.,
non-consumers are not included in the average). For the purpose of this example, the 95th
percentile consumer only intake rates of home produced tomatoes for group ages 1-2 years (10.7
g/kg-day), 3-5 years (6.3 g/kg-day), and 6-11 years (5.7 g/kg-day) are averaged to yield a mean
intake rate of 6.8 g/kg-day. This average was weighted by the number of years in each age group
bracket. This value is then adjusted for preparation and cooking loses using data from Table 13-
7 of the Exposure Factors Handbook (U.S. EPA, 1997a). Table 13-7 shows a preparation and
cooking loss of 15% for tomatoes. Therefore, the intake rate is 6.8 g/kg-day * (1 - 0.15) = 5.8
g/kg-day. This value is used to represent the average upper-percentile consumer only intake rate
of home produced contaminated tomatoes for group ages 1-11. The detailed calculation is shown
in Table 4. The intake rate for other age groups of children can also be estimated by averaging
the appropriate intake rates provided in Table 13-59 of the Exposure Factors Handbook (U.S.
EPA, 1997a).
Intake rates from Table 13-59 of
the Exposure Factors Handbook
Ages
1-2
3-5
6-11
Intake rate
10.7 g/kg-day
6.3 g/kg-day
5.7 g/kg-day
Average intake rate for ages 1-11;
(10.7(2) + 6.3(3) + 5.7(6))/ll = 6.8
g/kg-day
6.8 g/kg-day *(1 - 0.15) = 5.8 g/kg-day
25
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DW - Dry weight percentage of tomatoes is used to convert units of tomato intake rates
from g raw/kg-day to g dry-weight/kg-day. The purpose of this conversion is to ensure
consistency between units for concentration data and those for intake rates. The dry weight
percentage of raw tomatoes is estimated as one minus the mean moisture content (93.95%) of
raw tomatoes provided in Table 9-27 of the Exposure Factors Handbook (U.S. EPA, 1997a).
For the purpose of this example, the value of 6.05% as estimated is used to represent the average
dry weight percentage of tomatoes.
EF - Exposure frequency (EF) is 365 days a year because the data used in estimating
IRtomato are assumed to represent average daily intake over the long term (i.e., over a year).
ED - Exposure duration is the length of time over which exposure occurs. For the
purposes of this example, the average residence time of this age group is assumed. Based on the
data provided in Table 15-174 of the Exposure Factors Handbook (U.S. EPA, 1997a), the 50th
percentile residence time is 9 years. Thus, the assumption in this example is that children in a
household with home produced tomato consumption consume tomatoes from a contaminated site
for the average residence time of 9 years. After that time, the household is assumed to move to a
location where home produced tomatoes are no longer affected by contamination from the site.
AT - Because the average daily dose is being calculated in this example, the averaging
time (AT) is equivalent to the exposure duration. As shown above, exposure duration is 9 years;
thus the averaging time (AT) is 3,285 days (i.e., 9 years * 365 days/year).
2.2.4 Calculations
Using the exposure algorithm and exposure factors shown above, the ADDpoT tomatoing is
estimated as follows for the population of 1-11 year old children who consume home produced
tomatoes from a contaminated site.
_ \xlO~* mglg-dry * 5.8 g- raw/kg- day * 0.0605 g-dry/g-raw * 365 days/year * 9 years
-
ADDPOT tomato ing = l-5xl° rng/kg-day
26
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2.2.5 Exposure Characterization and Uncertainties
The example presented here is used to represent high-end exposures among the
population of 1-11 year old children from consumption of home grown tomatoes. The
population of other age groups of children can also be estimated using appropriate intake rates
provided in the Exposure Factors Handbook (U.S. EPA, 1997a) and other parameters provided
in the tables cited above. Central tendency exposures may be estimated using mean intake rates
from the tables cited above, along with the mean contaminant concentration and residence time.
If a bounding exposure estimate is desired, the concentration of contaminant may be set to the
maximum measured or modeled concentration. Caution should be used, however, in setting all
exposure factor inputs to upper-percentile values, as the resulting exposure estimates may exceed
reasonable maximum exposures for the population of interest.
The uncertainties associated with this example scenario are related to the assumed
activity pattern of the receptor population and the input parameters used. First, implicit in this
scenario is the assumption that the population of children consume tomatoes from a
contaminated site at the upper-percentile intake rates of home grown tomatoes specified in the
Exposure Factors Handbook (U.S. EPA, 1997a). Second, the intake rates used in this example
are based on survey data collected over a short period of time (i.e., 1-3 days) but are used to
represent long-term averages. The intake rates collected in such a way might be an appropriate
estimate for the short-term and long-term averages. But the distribution of the average intake
rates generated using a short-term data might not reflect the long term distribution of the average
daily intakes. Thus, there is some degree of uncertainty in using the upper-percentiles of the
long-term distribution of intake rates to estimate high-end exposures. Third, a single value for
average contaminant concentration in tomatoes is used to estimate high-end chronic exposure.
This assumes that all the tomatoes consumed from the site contains contaminant at the average
concentration. The variability in average contaminant concentration in tomatoes might introduce
some degree of uncertainty here.
The confidence in the high-end exposure provided in this example is related to
confidences in upper-percentile intake rates of home produced tomatoes and contaminant
concentration. The confidence rating given by the Exposure Factors Handbook (U.S. EPA,
1997a) is low for the distribution of intake rates of home produced tomatoes because the upper-
percentiles of the short-term distribution may overestimate intake, and the confidence rating is
medium for average residence time. If the rating for the contaminant concentration is medium,
27
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the overall confidence rating for the high-end exposure would be expected to be low because of
the low confidence in the intake rates.
28
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2.3 PER CAPITA INGESTION OF CONTAMINATED BEEF: ADULTS, CENTRAL
TENDENCY, LIFETIME AVERAGE EXPOSURE
2.3.1 Introduction
There is potential for contamination (e.g., lipophilic compounds) of meat products such
as beef as a result of cattle consuming contaminated forage, silage, grain, soil, or drinking water.
This may result in exposure among the general population via consumption of beef that is widely
distributed in the market place. Exposure via consumption of contaminated beef is estimated
based on the concentration of contaminants in beef, the consumption rate of beef, exposure
frequency, and exposure duration. In this example, exposure via contaminated beef is assumed
and central tendency lifetime average daily exposure from this pathway is evaluated for the adult
general population.
2.3.2 Exposure Algorithm
Exposure via this pathway would be calculated as follows:
LADD
POT beef ing
Cbeef * FC * IRbeef * EF * ED
AT
(Eq. 6)
where:
LADD,
POT beef ing
FC
IRbeef
EF
ED
AT
potential lifetime average daily dose from ingestion of
contaminated beef (mg/kg-day);
concentration of contaminant in beef (mg per gram of fat);
fat content or fraction of lipid in beef (percent);
per capita intake rate of beef (g/kg/day);
exposure frequency (days/year);
exposure duration (years); and
averaging time (days).
29
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2.3.3 Exposure Factor Inputs
Cbeef - The concentration of contaminant in beef is either the measured or predicted
concentration, based on modeling, of the chemical of interest in the beef produced at the
contaminated site. For estimating central tendency exposures, the mean or median values may be
used. In this example, the 95% upper confidence limit of the mean concentration is used as a
conservative estimate of the mean concentration. In this example, it is assumed that the modeled
95% upper confidence limit of the mean concentration of chemical "x" in beef is IxlO"3 mg/g-fat,
as consumed.
FC - Table 11-24 of the Exposure Factors Handbook (U.S. EPA, 1997a) provides the
percentage lipid contents for meats and dairy products. Fat content data are provided for six cuts
of beef. As shown in Table 5, the average fat content for these types of beef is 13.88%. Thus,
0.14 is used as the average fat content for the purpose of the example calculation shown below.
Note that this variable is required because the contaminant concentration is indexed to beef fat.
In cases where whole weight beef concentrations are used, this variable is not needed in the
exposure algoritm.
Intake rates from
Table 11-24 of the
Exposure Factors
Handbook
Beef Product
Lean only; raw
Lean and fat; cooked
Brisket (point half; lean only; raw)
Brisket (point half; lean and fat; cooked)
Brisket (flat half; lean and fat; raw)
Brisket (flat half, lean only; raw)
Lipid Content (%)
6.16
9.91
19.24
21.54
22.40
4.03
Average;
(6.16 + 9.91 + 19.24 + 21.54 +
22.40 + 4.03)/6 = 13.88
IR beef - The per capita intake rate of beef produced can be estimated based on the adult
intake rates of beef provided in the Exposure Factors Handbook (U.S. EPA, 1997a). The mean
per capita intake rate (0.675 g/kg-day as consumed) of beef is calculated by averaging the mean
intake rates for three age groups of adults (20-39,40-69, and 70+; 0.789,0.667, and 0.568
mg/kg-day, respectively), as provided in Table 11-3 of the Exposure Factors Handbook (U.S.
EPA, 1997a). A somewhat more accurate intake rate for the adult population may be calculated
by weighting the age-specific intake rates according to the size of the survey population for each
age group. This can be done by multiplying the weighted survey size data for each age group
30
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from Table 9-2 of the Exposure Factors Handbook (U.S. EPA, 1997a) by the intake rates for
each age group, and dividing by the total weighted survey size for the three age groups of adults.
The detailed calculations for these approaches are shown in Table 6. The more conservative of
these values, calculated using the second approach, is used in the calculations (Section 2.3.4).
EF - Exposure frequency (EF) is 365 days a year because the data used in estimating
IRbeef are assumed to represent average daily intake over the long term (i.e., over a year).
ED - Exposure duration is the length of time over which exposure occurs. In this
example, the 50th percentile residence time of 9 years provided in Table 15-174 of the Exposure
Factors Handbook (U.S. EPA, 1997a) is assumed. Use of this value assumes that people would
consume locally produced beef for the average residence time of 9 years. After that time, they
move to another location where locally produced beef is not contaminated.
First Approach
Average of age-specific beef
intake rates from Table 11-2 of
the Exposure Factors Handbook
Age
20-39 years
40-69 years
70+ years
Intake rate
(mg/kg-day)
0.789
0.667
0.568
Average =
(0.0789 + 0.667 + 0.568) / 3 = 0.675
Second Approach
Weighted average intake using
data from Tables 11-2 and 9-2 of
the Exposure Factors Handbook
Age
20-39 years
40-69 years
70+ years
Intake rate
(mg/kg-day)
0.789
0.667
0.568
Weighted N
78,680,000
71,899,000
17,236,000
Weighted average =
[(0.789 * 78,680,000) + (0.667 *
71,899,000) + (0.568 * 17,236,000)] /
[(78,680,000 + 71,899,000 +
17,236,000)] = 0.714
AT - Because the lifetime average daily dose is being calculated in this example for a
member of the general population, the averaging time (AT) is equivalent to the lifetime of the
individual being evaluated. The averaging time (AT) of 70 years is used for members of the
general population. For use in the calculations, this value is converted to 25,550 days (i.e., 70
years * 365 days/year).
31
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2.3.4 Calculations
Using the exposure algorithm and exposure factor inputs shown for the second approach
above, the LADDPOTbeefing may be estimated as follows:
1x10' mg/gfat * 0.14 gfatlgbeef * 0.714 gbeeflkg- day * 365 dayslyr * 9 years
25,550 days
-5
2.3.5 Exposure Characterization and Uncertainties
The example presented here is used to represent per capita central tendency exposures
among adults from ingestion of contaminated beef. High-end exposures may be estimated by
replacing the mean intake rates and residence time used here with upper-percentile values from
the tables cited above. In addition, if a bounding exposure estimate is desired, the chemical
concentration in beef may also be set to the maximum measured or modeled concentration.
However, caution should be used in setting all exposure factor inputs to upper-percentile values,
as the resulting exposure estimate might well exceed reasonable maximum exposures for the
population of interest.
The uncertainties associated with this example scenario are related to the assumed
activity patterns of the receptor population and the input parameters used. First, implicit in this
scenario is the assumption that the general population consumes beef at the average rates
specified in the Exposure Factors Handbook (U.S. EPA, 1997a). Second, the intake rates used in
this example are based on survey data collected over a short period of time (i.e.,1-3 days), but are
used to represent long-term averages. The intake rates collected in such a way might be an
appropriate estimate for the short-term and long-term averages. The distribution of the average
intake rates generated using short-term data might not reflect the long-term distribution of daily
intakes. Thus, there is some degree of uncertainty in using the upper percentiles of the long-term
distribution of intake rates to estimate high-end exposures.
32
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The confidence in the overall central tendency exposure provided in this example is
related to confidences in per capita intake rates of beef, residence time, and the exposure
concentration. The confidence rating given by the Exposure Factors Handbook (U.S. EPA,
1997a) is high for average intake rates of beef and medium for the residence time of the general
population. If the rating for the exposure concentration is also medium, the overall confidence in
the central tendency exposure estimated in this example should be at least medium.
33
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2.4 CONSUMER ONLY INGESTION OF CONTAMINATED DAIRY PRODUCTS:
GENERAL POPULATION (ALL AGES COMBINED), BOUNDING, ACUTE
EXPOSURE
2.4.1 Introduction
At locations where dairy products are contaminated with toxic chemicals, there is the
potential for acute exposure via ingestion of dairy products such as milk, cheese, and cream.
Acute exposure via this pathway is estimated based on the concentration of contaminants in dairy
products, the intake rate of dairy products per eating occasion, exposure frequency, and exposure
duration. In this example, acute exposure via ingestion of milk is assumed and evaluated for the
general population.
2.4.2 Exposure Algorithm
Exposure via this pathway would be calculated as follows:
* EF *
BW * AT
ADRPOTmilk tng RraT AT - (Eq. 7)
where:
ADRPOT milking = acute potential dose rate from ingestion of contaminated milk
(mg/kg-day);
Cmilk = concentration of contaminants in milk (mg/g);
IRmiIk = intake rate of milk per eating occasions (g/eating occasion);
EF = exposure frequency (eating occasions/day);
ED = exposure duration (day);
BW = body weight (kg); and
AT = averaging time (day).
2.4.3 Exposure Factor Inputs
Cmak - The concentration of contaminants in milk is either the measured or predicted
concentration, based on modeling, of the chemical of interest in milk. For acute exposure, the
maximum concentration of chemicals in milk would be used. In this example, it is assumed that
34
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the maximum concentration of chemical "x" in milk is IxlO"3 mg per gram of milk. Because this
is a whole weight concentration (i.e., not a lipid-based value), no lipid fraction value is required
in this exposure algorithm.
IRmiik - The intake rate of milk per eating occasion for the general population is provided
in Table 11-23 of the Exposure Factors Handbook (U.S. EPA, 1997a). In this example, the 99th
percentile of the quantity (as consumed) of milk consumed per eating occasion, 552 g/eating
occasion for the general population (i.e., all ages combined), is used for the example calculation
shown below to provide a bounding estimate of exposure.
EF - Exposure frequency is assumed to be one eating occasion per day.
ED - Exposure duration is the length of time over which exposure occurs. For assessing
acute exposure, the shortest time period which might lead to an acute effect should be used as
exposure duration. For the purpose of the example calculation shown below, the exposure
duration of one day is used.
BW - Since this scenario is calculating a bounding estimate, a low end body weight
would be appropriate. However, only mean values are currently available in the Exposure
Factors Handbook (U.S. EPA, 1997a). Therefore, the weighted average body weight of 63.5
kilograms for the general population (all ages combined) may be calculated using data in Tables
7-2 and 7-3 of the Exposure Factors Handbook (U.S. EPA, 1997a), as shown in Table 7. The
mean body weight of adults (71.8 kg) is used for ages 18 through 75 (a total of 58 years). The
weighted average body weight is then used for the example calculation shown below. This value
is used for the example calculation shown below.
35
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Body weight data from Tables
7-2 and 7-3 of the Exposure
Factors Handbook
Age-specific body
1 vpiar
weight
1 year
2 years
3 years
4 years
5 years
6 years
7 years
8 years
9 years
10 years
11 years
12 years
13 years
14 years
15 years
16 years
17 years
18-75 years
11.3kg
13.3 kg
15.3 kg
17.4 kg
19.7 kg
22.6kg
24.9 kg
28.1 kg
31.5kg
36.3 kg
41.1kg
45.3 kg
50.4 kg
56.0 kg
58.1 kg
62.6 kg
63.2 kg
71.8kg
[11.3 + 13.3 + 15.3 + 17.4 + 19.7 + 22.6
+ 24.9 + 28.1 + 31.5 + 36.3 + 41.1 +
45.3 + 50.4 + 56.0 + 58.1 + 62.6 + 63.2
+ (71.8* 58)] 775 = 63.5 kg
AT - For acute exposure assessment, averaging time is equal to exposure duration. Thus,
the averaging time of one day is used in this example.
2.4.4 Calculations
Using the exposure algorithm and exposure factors shown above,
estimated as follows for the general population:
is
ADR
"POT milk tog
1x10 mglg * 552 g/eating occasion * 1 eating occasion/day * 1 day
63.5 kg * 1 day
pOT mikin
mglkg- day
36
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2.4.5 Exposure Characterization and Uncertainties
The example presented here is used to represent acute exposure among the general
population (i.e., all ages combined) from ingestion of contaminated milk at one eating occasion.
Acute exposures via ingestion of other dairy products such as cream, cheese, and eggs for
different age groups or populations may also be estimated by using the corresponding input
parameters in the tables cited above.
It should be noted that in this scenario, considerable category lumping was performed to
assess the general population and to make use of particular data sets from the Exposure Factors
Handbook. In many exposure cases, however, it may not be useful to lump or aggregate groups
where there are susceptibility differences by age, sex or other category. While lumping may be
useful for conducting a first scoping assessment, caution should be used when lumping groups
into aggregate categories that have no biological meaning.
The confidence in the acute exposure estimate provided in this example is related to
confidences in the 99th percentile intake rate of milk per eating occasion and the exposure
concentration. The confidence rating for the intake rate of milk is expected to be medium, as the
intake rates of milk per eating occasion are estimated based on the 1977-78 USDA NFCS
(National Food Consumption Survey) data. According to the Exposure Factors Handbook (U.S.
EPA, 1997a), the USDA NFCS data were collected from interviews of 37,874 individuals, but
are relatively old and do not consider recent changes in dietary habits. Thus, if the confidence
rating for the exposure concentration is medium or higher, the overall confidence rating for acute
exposure should be at least medium.
37
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2.5 INGESTION OF CONTAMINATED DRINKING WATER: OCCUPATIONAL
ADULTS, BASED ON OCCUPATIONAL TENURE, HIGH-END, LIFETIME
AVERAGE EXPOSURE
2.5.1 Introduction
At sites where surface water or ground water, that is used as a source of potable water, is
contaminated, there may be the potential for exposure via ingestion of drinking water.
Receptors could include any population who consumes tap water from a contaminated site.
Exposure via ingestion of contaminated drinking water is estimated based on the concentration of
contaminants in drinking water, the intake rate of drinking water, exposure frequency, and
exposure duration. In this example, exposure via ingestion of drinking water is assumed and the
high-end chronic lifetime daily exposure from this pathway is evaluated for an adult occupational
population of farm workers.
2.5.2 Exposure Algorithm
Exposure via this pathway would be calculated as follows:
LADD
POT drinking water ing
C * IR * EF * FD
drinking water drinking water
AT
(Eq.8)
where:
LADD,
POT drinking water ing
IR
' drinking water
EF
ED
AT
drinking water
potential lifetime average daily dose from ingestion of
contaminated drinking water (mg/kg-day);
concentration of contaminant in drinking water (mg/mL);
intake rate of drinking water (mL/kg-day);
exposure frequency (days/year);
exposure duration (years); and
averaging time (days).
2.5.3 Exposure Factor Inputs
er - The concentration of contaminants in drinking water is either the measured
or predicted concentration, based on modeling, of the chemical of interest in the tap water
38
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supplied from a contaminated site. For estimating central tendency exposures, the mean or
median values would be used. The 95% upper confidence limit of the mean concentration can be
used as a conservative estimate of the mean concentration. For the purpose of the example
calculations shown below, it is assumed that the modeled 95% upper confidence limit of the
mean concentration of chemical "x" in drinking water is IxlO"3 mg/mL.
IRdrinking water - Table 3-30 of the Exposure Factors Handbook (U.S. EPA, 1997a) provides
recommended drinking water intake rates. For the purpose of the example calculation, the upper-
percentile (i.e., 90th percentile) drinking water intake rate of 34 mL/kg-day recommended for
adults in Table 3-30 is selected to represent the average intake rate of contaminated drinking
water for the occupational population of farm workers. It is assumed in this example that farm
workers always consume the tap water supplied to their farms, as a sole source of drinking water
during working hours.
EF - Exposure frequency is 365 days a year for this example because the data used in
estimating IRdrinking water a*"6 assumed to represent average daily intake over the long term (i.e., over
a year).
ED - Exposure duration is the length of time over which exposure occurs. For the
purposes of this example, the occupational tenure of 39.8 years for the 65+ (years) age group for
farming provided in Table 15-161 of the Exposure Factors Handbook (U.S. EPA, 1997a) is
assumed. This age group is selected because it represents the total occupational tenure by the
end of a working lifetime. This value assumes that farm workers consume the tap water from a
contaminated source during working hours for the average farming occupational tenure of 39.8
years. After that, they either retire or move to a location where the tap water they consume is no
longer contaminated.
AT - Because the lifetime average daily dose is being calculated in this example for a
members of the general population, the averaging time (AT) is equivalent to the lifetime of the
individuals being evaluated. The averaging time (AT) of 70 years is used for a member of the
general population. For use in the calculations, this value is converted to 25,550 days (i.e., 70
years * 365 days/year).
39
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2.5.4 Calculations
Using the exposure algorithm and exposure factors shown above, the LADDPOTdrinkingwater
ing is estimated as follows for the population of farm workers:
mg/mL * 34 ml/kg- day * 365 days/year * 39.8 years
por ***** "- ** 25,550 days
LADDPOTdftMng water ing = 1.9x10-* mg/kg-day
2.5.5 Exposure Characterization and Uncertainties
The example presented here is used to represent high-end exposure among the population
of farm workers via ingestion of drinking water. Central tendency exposures may be estimated
using mean or median intake rates from the table cited above. If a bounding exposure estimate is
desired, the concentration of contaminant may be set to the maximum measured or modeled
concentration. Caution should be used, however, in setting all exposure factor inputs to upper-
percentile values, as the resulting exposure estimates may exceed reasonable maximum
exposures for the population of interest.
The uncertainties associated with this example scenario are related to the assumed
activity pattern of the receptor and the input parameters used. First, implicit in this scenario is
the assumption that farm workers only consume tap water to satisfy their physiological need for
water. In reality, farm workers might consume bottled water or canned beverage (which is not
contaminated) to relieve thirst during working hours. Thus, use of the intake rates provided in
the Exposure Factors Handbook (U.S. EPA, 1997a) might overestimate exposure of the farm
workers via ingestion of drinking water. In addition, some wells may have some sort of
treatment that may remove contaminants. On the other hand, farm workers that work in high-
temperature environments or engage in activities that are physically demanding, may have higher
levels of tapwater intake. For these individuals, exposure may be underestimated. Second, the
upper-percentile intake rates of drinking water used in this example are derived from the data
collected from a short period of time (3 days). The extrapolation to chronic intake in this
40
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example might introduce some degree of uncertainty. There may also be seasonal or regional
differences in drinking water intake that add to the uncertainty in these estimates. Third, a single
value for contaminant concentration (i.e., 95% upper confidence limit of the mean) in drinking
water is used to estimate high-end chronic exposure. This assumes that drinking water always
contains a contaminant at the average concentration. The variability in contaminant
concentrations obtained from different samples introduces some degree of uncertainty.
The confidence in the high-end exposure estimate provided in this example is related to
confidences in average intake rates of drinking water, the occupational tenure, and exposure
concentrations. The confidence rating given by the Exposure Factors Handbook (U.S. EPA,
1997a) is medium for the intake rates of drinking water and high for the occupational tenure.
Thus, if the confidence rating for the exposure concentration is medium, the overall confidence
rating for the high-end exposure is at least medium.
41
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2.6 INGESTION OF CONTAMINATED DRINKING WATER: SCHOOL
CHILDREN, CENTRAL TENDENCY, SUBCHRONIC EXPOSURE
2.6.1 Introduction
At sites where surface water or ground water, that is used as a source of potable water, is
contaminated, there is the potential for exposure via ingestion of drinking water. Receptors
could include any population who consumes tap water from a contaminated site. Exposure via
ingestion of contaminated drinking water is estimated based on the concentration of
contaminants in drinking water, the intake rate of drinking water, exposure frequency, and
exposure duration. In this example, exposure via ingestion of drinking water is assumed and the
central tendency subchronic average daily exposure from this pathway is evaluated for the
population of elementary school children, ages 5-10. It is assumed that the school children's
home drinking water supplies are not contaminated and thus, the children are exposed only at
school.
2.6.2 Exposure Algorithm
Exposure via this pathway would be calculated as follows:
4DD
POT drinking water ing
Cdrinking water * IRdrinking water * ET * EF * EL
AT
(Eq.9)
where:
ADD
POT drinking water ing
drinking water
TO
^^
ET
EF
ED
AT
potential average daily dose from ingestion of contaminated
drinking water (mg/kg-day);
concentration of contaminant in drinking water (mg/mL);
intake rate of drinking water (mL/kg-hour);
exposure time (hours/day);
exposure frequency (days/year);
exposure duration (years); and
averaging time (days).
42
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2.6.3 Exposure Factor Inputs
(-drinking water - The concentration of contaminants in drinking water is either the measured
or predicted concentration, based on modeling, of the chemical of interest in the tap water
supplied from a contaminated site. For estimating central tendency exposures, the mean or
median values would be used. The 95% upper confidence limit of the mean concentration can be
used as a conservative estimate of the mean concentration. For the purpose of the example
calculations shown below, it is assumed that the modeled 95% upper confidence limit of the
mean concentration of chemical "x" in drinking water is IxlO"3 mg/mL.
IR drinking water - The tap water intake rate for elementary school children (5-10 years old) is
estimated first by averaging the mean tap water intake rates for children of ages 4-6 and ages 7-
10 years provided in Table 3-7 of the Exposure Factors Handbook (U.S. EPA, 1997a). The
weighted average is calculated by multiplying each consumption in each age category by the
number of years in the age bracket and dividing by the total number of years. The weighted
average is then divided by 14 hours/day to yield the hourly intake rate of drinking water for
children of ages 4-10 years. This assumes that children in this age group sleep 10 hours per day
(see Table 15-83 of the Exposure Factors Handbook (U.S. EPA, 1997a)). Thus, drinking water
is only consumed over the 14 hours that children are awake. The value of 2.3 mL/kg-hour, as
estimated, is used to represent the intake rate of drinking water for elementary school children (5-
10 years old). The detailed calculation is shown in Table 8 below. It should be noted that these
values are based on data that include the use of tap water in preparing foods and other beverages
(i.e., juices prepared with water).
Table 3-7 of the Exposure
Factors Handbook
Age (yrs) Total tap water intake rate
4-6 37.9 mL/kg-day
7- 10 26.9 mL/kg-day
Intake rate for ages 4-10 yrs;
(37.9(3) + 26.9(4))/7 =31.6
mL/kg-day
31.6/14hrs/day = 2.3 mL/kg-hour
ET- According to Table 15-84 of the Exposure Factors Handbook (U.S. EPA, 1997a),
the median and mean number of minutes spent in school for 5-11 year old children is
approximately 390 minutes (i.e., 6.5 hours). Since data are not specifically available for 5-10
43
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year olds, the value of 6.5 hours for the 5-11 years old range is used for the example calculation
shown below.
EF - Exposure frequency is assumed to be 185 days a year for this example. This is
equivalent to 37 weeks of full-time school, and accounts for 15 weeks off for summer and winter
vacations, Federal and school holidays, etc.
ED - Exposure duration is the length of time over which exposure occurs. For the
purposes of this example, the exposure duration for 5-10 year old school children is assumed to
be six years (i.e., from kindergarten through fifth grade). This assumes that all six years are spent
in the same school where tap water contamination exists.
AT - For assessment of average daily dose, the averaging time is equal to the exposure
duration. Thus, for the purpose of the example calculation shown below, the averaging time of 6
years, or 2,190 days, is used.
2.6.4 Calculations
Using the exposure algorithm and exposure factors shown above, the LADDPOTdrinkingwater
ing is estimated as follows for the population of elementary school children:
ing
.__ _ 1x70' mglmL * 2.3 mL/kg-hour * 6.5 hour!day * 185 days/year * 6 years
AUL>POT drinking Catering 2,190 days
ADDPOT drinking Catering = 7'6^° ^glkg-day
2.6.5 Exposure Characterization and Uncertainties
The example presented here is used to represent central tendency exposure among the
population of elementary school children, ages 5-10, via ingestion of contaminated drinking
water. High-end exposures may be estimated by using upper-percentile values of intake rates and
exposure time from the tables cited above. If a bounding exposure estimate is desired, the
concentration of contaminant may also be set to the maximum measured or modeled
44
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concentration. Caution should be used, however, in setting all exposure factor inputs to upper-
percentile values, as the resulting exposure estimates may exceed reasonable maximum
exposures for the population of interest.
The uncertainties associated with this example scenario are related to the assumed
activity pattern of the receptor and the input parameters used. First, implicit in this scenario is
the assumption that school children consume only tap water to satisfy their physiological need for
water. In reality, children might bring bottled water or juice which has been reconstituted with
water from another source (which is not contaminated) to school. This might overestimate
exposure via ingestion of drinking water. Second, elementary school children often change
schools as their parents change jobs or buy new houses. The use of six years for exposure
duration might overestimate the exposure for some children. Third, intake rates of drinking
water found in the Exposure Factors Handbook (U.S. EPA, 1997a) are derived from the data
collected from a short period of time (3 days). The extrapolation to chronic intake in this
example might introduce some degree of uncertainty. Fourth, many schools have before or after
school activities such as on-site extended care (which is particularly important for working
families) or athletic/sports programs during which water consumption would be increased. The
omission of these programs might underestimate exposure via ingestion of drinking water. Fifth,
children attending summer school would have a greater exposure frequency. The omission of
this uncertainty could also underestimate exposure via ingestion of drinking water.
The confidence in the central tendency exposure estimate provided in this example is
related to confidences in average intake rates of drinking water, the activity pattern data used to
estimate the exposure time, and the exposure concentration. The confidence rating given by the
Exposure Factors Handbook (U.S. EPA, 1997a) is medium for the tap water intake rate and high
for the activity pattern data. Thus, if the confidence in the exposure concentration is medium, the
overall confidence rating for the central tendency exposure would be at least medium.
45
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2.7 INGESTION OF CONTAMINATED DRINKING WATER: ADULT MALES IN
HIGH PHYSICAL ACTIVITY OCCUPATIONS, BOUNDING, AVERAGE
LIFETIME EXPOSURE
2.7.1 Introduction
At sites where ground water or surface water, that is used as a source of potable water, is
contaminated, there is the potential for exposure via ingestion of drinking water. Receptors
could include any population who consumes tap water from a contaminated site. Increased rates
of drinking water ingestion may occur among populations engaging in highly physically
demanding activities or those who work in high temperature conditions. Exposure via ingestion
of contaminated drinking water is estimated based on the concentration of contaminants in
drinking water, intake rates of drinking water, exposure frequency, and exposure duration. In
this example, exposure via ingestion of contaminated drinking water is assumed, and the
bounding lifetime average daily exposure from this pathway is evaluated for the population of
steel mill workers who consume more water than the general population because of their high
level of physical activity and the high temperature working environment.
2.7.2 Exposure Algorithm
Exposure via this pathway would be calculated as follows:
= Cdnn^gWater * CF * IRdrinking water * EF * ED (Eg 10)
water ing T
where:
LADDpOTdrinkingwatering = potential lifetime average daily dose from ingestion of
contaminated drinking water (mg/kg-day);
^drinking water = concentration of contaminants in contaminated drinking water
(mg/mL);
CF = conversion factor for 1,000 mL/L;
= intake rate of drinking water (L/day);
46
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EF = exposure frequency (days/year);
ED = exposure duration (years);
BW = average body weight for the population of interest (kg); and
AT = averaging time (days).
2.7.3 Exposure Factor Inputs
Cdrinking water - The concentration of contaminants in drinking water is either the measured
or predicted concentration, based on modeling, of the chemical of interest in the drinking water
supplied from a contaminated site. For a bounding exposure estimate, the maximum
concentration of contaminant in drinking water would be used. For the purpose of the example
calculations shown below, it is assumed that the maximum concentration of chemical "x" in
drinking water is IxlO"3 mg/mL.
CF - A conversion factor of 1,000 is needed to convert liters to milliliters for the
purposes of calculating a LADD.
IRdrinidng water - According to Table 3-27 and the corresponding text of the Exposure
Factors Handbook (U.S. EPA, 1997a), the mean water intake rate for a male adult working at a
high level of physical activity and at an ambient temperature of 95 °F is 0.54 L/hour. It is
assumed that all steel mill workers are male and those being evaluated work for eight hours a day
under a high level of physical activity and at a high temperature. Thus, the average daily intake
rate of drinking water during working hours is estimated to be 4.32 L/day by multiplying the
hourly intake rate of 0.54 L/hours by 8 hours/day. This value is used for the example calculation
shown below.
EF - Exposure frequency is assumed to be 219 days a year for this example. This
estimate assumes that steel mill workers work 5 days a week, observe 10 Federal holidays, take 4
weeks of vacation a year and an additional 12 personal days per year. This value is one of those
recommended by U.S. EPA (1989) to represent central tendency exposure frequency for
industrial workers.
ED - Exposure duration is the length of time over which exposure occurs. For the
purposes of this example, the occupational tenure of 18.1 years for the 55-64 (years) age group of
Operators, Fabricators, and Laborers provided in Table 15-161 of the Exposure Factors
47
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Handbook (U.S. EPA, 1997a) is assumed. This value assumes that steel mill workers consume
contaminated tap water during working hours for the average occupational tenure of 18.1 years.
After that, they either retire or change their occupation and no longer consume the contaminated
tap water in the steel mill.
BW - The average male adult body weight of 78.1 kilogram is provided in Table 7-4 of
the Exposure Factors Handbook (U.S. EPA, 1997a). This value is used for the example
calculations shown below.
AT - Because the lifetime average daily dose is being calculated in this example for a
member of the general population, the averaging time (AT) is equivalent to the lifetime of the
individual being evaluated. The averaging time (AT) of 70 years is used for members of the
general population. For use in the calculations shown below, this value is converted to 25,550
days (i.e., 70 years * 365 days/year).
2.7.4 Calculations
Using the exposure algorithm and exposure factors shown above, the LADDpoTdrinkingwater
mg
is estimated as follows for the population of steel mill workers:
1x10 3 mg/mL * 1,000 mL/L * 4.32 LI day * 219 days/year * 18.1 years
POT drinking Catering ?g j Mograms 25,550 days
LADDpOTdrinkingwatering = 1.6x10- mg/kg-day
2.7.5 Exposure Characterization and Uncertainties
The example presented here is used to represent bounding exposure via ingestion of
drinking water among the population of steel mill workers that engage in a high level of physical
activity in high temperature environments. Central tendency exposures may be estimated using
the lower drinking water intake rates from the table cited above and an average concentration of
contaminant in drinking water. It should be noted that caution should be used in setting all
48
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exposure factor inputs to upper-percentile values, as in this example, because the resulting
exposure estimates may exceed reasonable maximum exposures for the population of interest.
The uncertainties associated with this example scenario are related to the assumed
activity pattern of the receptor population and the input parameters used. First, implicit in this
scenario is the assumption that steel mill workers only consume tap water to satisfy their
physiological need for water. In reality, the workers might consume bottled water or canned
juice which is not contaminated. Thus, exposure estimates presented in this example might have
overestimated real exposures of the steel mill workers via ingestion of drinking water. Second,
in this example, the average occupational tenure of 18.1 years for 55-64 is used to represent
exposure duration. The use of the occupational tenure here assumes that steel mill workers work
in the same steel mill during their entire occupational tenure. In reality, steel mill workers might
transfer to another steel mill where tap water is not contaminated. Thus, the bounding exposure
estimate based on the occupational tenure might overestimate the exposure for the general
population of steel mill workers. Third, the intake rates of drinking water used in this example
are based on the study on physiological demands of male adults for water at different
temperatures and under different levels of physical activity. This study was conducted on only 7
-18 adult males. Thus, the intake rates are not fully representative of the general population of
workers in high temperature, high physically-demanding jobs. Fourth, the discussion of tap
water consumption does not address the potential that some of the steel mill workers may live
near the site and continue to draw their water supply from a contaminated groundwater source. If
this did occur, it would result in underestimating an individual's exposure.
The confidence in the bounding exposure estimate provided in this example is related to
confidences in average intake rates of drinking water, occupational tenure, and exposure
concentrations. The confidence rating given by the Exposure Factors Handbook (U.S. EPA,
1997a) is high for the occupational tenure, but is not given for the intake rates of drinking water
for high physical activities, as the study is listed as a relevant study rather than a key study. Since
the intake rate of drinking water is derived from a small sample (7-18 male adults), the
confidence rating is presumably low. Thus, even if the rating for the exposure concentration is
high, the overall confidence rating for the bounding exposure is expected to be low.
49
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2.8 INCIDENTAL INGESTION OF POOL WATER: CHILDREN, BOUNDING,
ACUTE EXPOSURE
2.8.1 Introduction
In some situations it is necessary to assess exposure/risk to individuals from biocides or
other chemicals in swimming pools. Both adults and children may incidentally ingest chemicals
in the water when swimming or wading. These chemicals may either be soluble or insoluble.
Depending on the density of the chemical, it could either be floating on the surface of water or it
could sink to the bottom. Receptors could include swimmers or waders in home swimming
pools.
Acute exposure via incidental intake of contaminated surface water considers not only the
concentration of contaminant in the water, but also the ingestion rate, and the duration of
exposure. A bounding exposure for acute incidental ingestion of pool water is evaluated for
children (ages 5-11 years).
2.8.2 Exposure Algorithm
Exposure via this pathway would be calculated as follows:
ADR
'POT pool water ing
Cpoolwater *
* EF * ED
(Eq. 11)
BW * AT
where:
ADR
POT pool water ing
v'pool water
TR
"-"^pool water
ET
EF
ED
AT
BW
acute potential dose rate from incidental ingestion of contaminated
pool water (mg/kg-day);
concentration of contaminant in the pool water (mg/L);
intake rate (L/hr);
exposure time (hours/event);
exposure frequency (events/day);
exposure duration (day);
averaging time (days); and,
body weight (kg).
50
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2.8.3 Exposure Factor Inputs
Cpooi water ~ The concentration of contaminant in pool water at the site (Cp^^,,,.) is either
the measured or predicted concentration, based on modeling, of the chemical of interest in the
pool water consumed. For estimating acute exposures, the maximum value would be used. For
the purposes of the example calculations shown below, it is assumed that the modeled maximum
concentration of chemical "x" in pool water is IxlO"3 mg/L.
IRpooi water - Intake rate (IR) for the swimmer is assumed to be 50 mL/hour or 0.05 L/hr
(U.S. EPA, 1989) for the purposes of this example. Note that this is based on a noncompetitive
swimming scenario. Competitive swimming may increase this rate by 3-4 times. It would be
more likely that competitive swimming events would not be held in home swimming pools.
Note that the EPA's proposed Water Quality Guidance for the Great Lakes (58FR20869) has
proposed 30 ml/hour as an incidental ingestion rate for swimmers.
ET - The exposure time (ET) can be estimated using statistics from Table 15-67 of the
Exposure Factors Handbook (U.S. EPA, 1997a). These data are used to establish the amount of
time swimming in surface water. Data are presented for the number of minutes spent swimming
in one month. For children (ages 5-11 years), the 95th percentile value for swimming is 181
minutes (3 hours) per month. It is assumed, for the purposes of this example, that all 181
minutes spent swimming in a month occur on the same day. Therefore, one event is estimated as
3 hours/event during one day.
EF - Exposure frequency (EF) is assumed to be one event for acute exposure.
ED - Exposure duration (ED) is the length of time over which exposure occurs. For the
purposes of this example, the acute exposure duration is assumed to be one day.
BW - Table 7-3 of the Exposure Factors Handbook (U.S. EPA, 1997a), reports age-
specific body weights for children from 6 months to 19 years old. Using the age-specific mean
body weights for boys and girls at ages 5 to 11 years, the average body weight of 29.2 kg is
calculated.
AT - Because the acute dose is being calculated, the averaging time is equivalent to the
exposure duration. This value is one day.
51
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2.8.4 Calculations
Using the exposure algorithm and exposure factor inputs shown above, the ADRPOT
water ing
i would be as follows for the children (ages 5 to 11 years):
1x10 mg/L * 0.05 L/hr * 3 hrlevent * 1 event/day * 1 day
POT pool water ing ~ 90 9 fr
-------
cannot be captured accurately because of limitations in the survey responses (i.e., 181 minutes
was the maximum allowable response; thus, 181 minutes/month is shown as the 95*, 98th, 99th
and 100th percentile value). Thus, use of the data from the upper end of the intake distribution is
uncertain. Given the uncertainties associated with these exposure parameters (e.g., intake rate
and exposure duration), the overall uncertainty associated with this scenario is also high (i.e., the
confidence rating is low).
53
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2.9 INGESTION OF CONTAMINATED FRESHWATER AND MARINE FISH:
CHILDREN, CENTRAL TENDENCY, CHRONIC EXPOSURE
2.9.1 Introduction
There is the potential for contamination of fish and shellfish as a result of
bioaccumulation of certain types of chemicals (e.g., lipophilic compounds) in fish tissues. This
may result in exposure among the general population via consumption of marine or freshwater
fish. Receptors could include any member of the general population who consume contaminated
fish. Exposure via consumption of contaminated fish is estimated based on the concentration of
chemicals in fish, intake rates of contaminated fish, exposure frequency, and exposure duration.
In this example, central tendency chronic average daily exposures via ingestion of both marine
and freshwater fish are evaluated for children (ages 2-9 years).
2.9.2 Exposure Algorithm
Exposure via this pathway can be estimated as follows:
ADD
'POT fish ing
Cflsh * IRflsh * EF* ED
(Eq. 12)
where:
ADD
POT fish ing
EF
ED
AT
BW
potential average daily dose from ingestion of contaminated fish
caught at a contaminated site (mg/kg-day);
concentration of contaminants in fish (mg/g fish);
per capita intake rate of fish for the population of interest (g/day);
exposure frequency (days/year);
exposure duration (years);
averaging time (days); and
average body weight for the population of interest (kg).
54
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2.9.3 Exposure Factor Inputs
Cfish ~ The concentration of contaminants in fish is either the measured or predicted
concentration, based on modeling, of the chemical of interest in the fish caught in the
contaminated surface water. For estimating central tendency exposures, the mean or median
values would be used. In this example, the 95% upper confidence limit of the mean
concentration is used as a conservative estimate of the mean concentration. For the purpose of
the example calculations shown below, it is assumed that the modeled 95% upper confidence
limit of the mean concentration of chemical "x" in fish is IxlO"3 mg/g fish (as consumed).
IRjish - Survey data for fish intake rates for children are relatively limited. However,
intake rates of marine and freshwater fish for children may be estimated by multiplying the mean
total fish intake rates for children provided in Table 10-1 of the Exposure Factors Handbook
(U.S. EPA, 1997a), with fractions of marine and freshwater fish ingested for the general
population. In this example, only children ages 2-9 years are considered. According to Table 10-
1 of the Exposure Factors Handbook (U.S. EPA, 1997a), the mean total fish intake rate for
children of ages 0-9 years is 6.2 g/day. The fractions of children's total fish consumption
represented by marine and freshwater fish are estimated by dividing the intake rates of total fish
with the intake rates of marine and freshwater fish, based on the recommended general
population (all ages) values provided in Table 10-81 of the Exposure Factors Handbook (U.S.
EPA, 1997a). This assumes that the proportions of the marine and freshwater fish are the same
for children as for other members of the general population. The detailed calculation is
summarized in Table 9. The intake rates of marine (4.34 g/day) and freshwater (1.86 g/day) fish
for children, as estimated, are used for the example calculation shown below. It should be noted
that where site- and/or species-specific intake data are available, they should be used with site-
and/or species-specific data on chemical residues in fish.
55
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Total Intake Rates of Fish
Table 10-1 of the Exposure
Factors Handbook
Fraction of Marine or
Freshwater fish consumed
Table 10-81 of the Exposure
Factors Handbook
Ages Total Fish Intake
0-9 6.2 g/day
Total fish intake rate: 20.1 g/day
Marine fish intake rate: 14.1 g/day
Freshwater fish intake rate: 6.0 g/day
Fraction of marine fish: 0.7
Fraction of freshwater fish: 0.3
Intake rate of marine fish;
6.2 g/day * 0.7 = 4.34 g/day
Intake rate of freshwater fish;
6.2 g/day * 0.3 = 1.86 g/day
EF - Exposure frequency (EF) is 365 days a year because the data used in estimating IRfish
are assumed to represent average daily intake over the long term (i.e., over a year).
ED - Exposure duration (ED) is the length of time over which exposure occurs. In this
example, the 50th percentile residence time of 9 years for the households in the U.S. in Table 15-
174 of the Exposure Factors Handbook (U.S. EPA, 1997a) is used. This example assumes that
children consume the locally produced fish for the 8 years between the ages of 2 and 9. This
assumes that they and their families reside in the same location for the average residence time of
9 years, including the time between ages 2 and 9 years. After that time, they are assumed to
move and reside in a location where the fish caught is no longer affected by the contaminated
surface water body.
AT - Because the chronic average daily dose is being calculated in this example for a
member of the general population, the averaging time (AT) is equivalent to the exposure
duration. Thus, AT is 2,920 days or 8 years.
BW - The average body weight for children ages 2-9 years can be estimated by averaging
the age/gender-specific mean body weights provided in Table 7-6 and Table 7-7 of the Exposure
Factors Handbook (U.S. EPA, 1997a). As estimated, the average body weight for children ages
2-9 years is 21.6 kg. The detailed calculation is shown Table 10 below.
56
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Tables 7-6 and 7-7 of the
Exposure Factors Handbook
Mean Body Weights (kg)
Ages Male Female M/F
Average body weight for 2-9
year old children = 21.6 kg
2 (yr) 13.6
3 (yr) 15.7
4 (yr) 17.8
5 (yr) 19.8
6 (yr) 23.0
7 (yr) 25.1
8 (yr) 28.2
9 (yr) 31.1
13.0
14.9
17.0
19.6
22.6
24.7
27.9
31.9
13.3
15.3
17.4
19.7
22.5
24.9
28.1
31.5
2.9.4 Calculations
Using the exposure algorithm and exposure factor inputs described above, the ADDpoTflsh
ing from ingestion of marine and freshwater fish would be estimated as follows for children, ages
2-9:
Fresh Water Fish
ADD
1x10'
POT fish ing
mg/g * 1.86 g/day * 365 days * 8 years
21.6 kg * 2,920 days
ADD
POT fish ing
= 8.6x70" mg/kg/day
Marine Water Fish
ADD
POT fish ing
1x10 mg/g * 4.34 g/day * 365 days * 8 years
21.6 kg * 2,920 days
57
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ADDpOTsh in = 2-°^° mglkglday
2.9.5 Exposure Characterization and Uncertainties
The example presented here is used to represent central tendency exposures among
children, ages 2-9 years, via consumption of contaminated marine and freshwater fish. High-end
exposures may be estimated by replacing the mean intake rates with the upper-percentile values.
In addition, if a bounding exposure estimate is desired, the concentration in fish may also be set
to the maximum measured or modeled concentration. However, caution should be used in
setting all exposure factor inputs to upper-percentile values, as the resulting exposure estimate
might well exceed reasonable maximum exposures for the population of interest.
Uncertainties associated with this example scenario are related to assumed activity
patterns of the receptor population and the input parameters used. First, implicit in this scenario
is the assumption that children, ages 2-9 years, consume contaminated fish at an intake rate of
fish specified for children, ages 0-9 years, in the Exposure Factors Handbook (U.S. EPA, 1997a)
and that all of the fish consumed are obtained from the contaminated site (as an alternative, a
term denoting the fraction of fish assumed to be derived from the source area could be included
in the dose algorithm). Also, losses of contaminant via cooking are not assumed in this example.
Thus, no term denoting the fraction of contaminant lost during cooking is included. If cooking
losses can be quantified, a term may be added to the dose algorithm to address such losses.
Second, a single value for the average contaminant concentration in fish is used to estimate
central tendency chronic exposure. This assumes that all the fish consumed from the site contain
contaminant at the average concentration. The variability in average contaminant concentration
in fish might introduce some degree of uncertainty as well. In addition, some uncertainty exists
regarding the exposure duration. Use of an average residence time assumes that children move
away from the site of contamination after 9 years. However, it is possible that a move may occur
within the same area of contamination.
The confidence in the overall central tendency exposure provided in this example is
related to confidences in fish intake rates, fraction of marine or freshwater fish ingested, average
residence time for the general population, and the exposure concentration. The confidence rating
58
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given by the Exposure Factors Handbook (U.S. EPA, 1991 a) is medium for intake rates of fish,
and medium for the fraction of marine or freshwater fish ingested. If the rating for the exposure
concentration is also medium, the overall confidence in the central tendency exposure estimated
in this example should be at least medium.
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2.10 INGESTION OF CONTAMINATED FISH: SUBSISTENCE FISHING NATIVE
AMERICAN ADULTS, BOUNDING, AVERAGE LIFETIME EXPOSURE
2.10.1 Introduction
At sites where localized surface water contamination exists, there is the potential for
contamination of fish as a result of bioaccumulation of chemicals of potential concern in fish
tissues. This might result in exposure among local populations via consumption of contaminated
fish caught by subsistence fishermen. Receptors could include fishing families or other sub-
populations who consume the fish caught from the contaminated site. Exposure via consumption
of contaminated fish is estimated based on the concentration of chemicals in fish, the intake rate
of contaminated fish per day, exposure frequency, and exposure duration. Subsistence fishing
occurs in populations throughout the country and varies from location to location. Generally,
information on subsistence fishing is not well documented for all ethnic groups although relevant
fish consumption data are available on Native American subsistence populations. In this
example, exposure via ingestion of contaminated fish is assumed and the bounding lifetime
average daily exposure from this pathway is evaluated for the Native American adult subsistence
population.
2.10.2 Exposure Algorithm
Exposure via this pathway can be estimated as follows:
Cfi. * IR~, * EF * ED
J AT)T) - flstt ft*"
LAUupoTfish .ng - BW * AT (Eq- 13)
where:
T flsh ing = lifetime average potential dose rate from ingestion of contaminated
fish caught at a contaminated site (mg/kg-day);
Cfish = concentration of contaminants in fish (mg/g fish);
IRf]sh = per capita intake rate of fish (g/day);
EF = exposure frequency (days/year);
ED = exposure duration (years);
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BW = body weight (kg); and
AT = averaging time (days).
2.10.3 Exposure Factor Inputs
Cfish - The concentration of contaminants in fish is either the measured or predicted
concentration, based on modeling, of the chemical of interest in the fish caught in the
contaminated surface water. For estimating the bounding exposure, the maximum values would
be used. In this example, it is assumed that the modeled maximum concentration of chemical
"x" in fish is IxlO"3 milligram per gram of fish (mg/g fish), as consumed.
IR fck - Intake rate of fish for the Native American adult subsistence population is
provided in Table 10-72 of the Exposure Factors Handbook (U.S. EPA, 1997a). In this example,
the 95* percentile of the quantity of fish consumed per day, 170 g/day, is used for the example
calculation shown below.
EF - Exposure frequency (EF) is 365 days a year because the data used in estimating
IRflsh are assumed to represent average daily intake over the long term (i.e., over a year).
ED - Exposure duration (ED) is the length of time over which exposure occurs. In this
example, 50 years is assumed. Use of this value assumes that people would consume locally
caught fish for the upper-percentile residence time of 50 years (i.e., during the entire adult
lifetime; between age 20 and 70 years).
AT - Since the lifetime average daily dose is being calculated in this example for an adult,
the averaging time is equal to the lifetime of the individual being evaluated. The averaging time
(AT) of 70 years is used for members of the general population. For use in calculations, this
value is converted to 25,550 days (i.e., 70 years * 365 days/year).
BW - The average body weight of 71.8 kilograms for the general population provided in
Table 7-2 of the Exposure Factors Handbook (U.S. EPA, 1997a) is used for the example
calculation shown below.
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2.10.4 Calculations
Using the exposure algorithm and exposure factor inputs described above, the LADDPOT
fish mg fr°m ingestion of total fish would be estimated as follows for the Native American
subsistence population:
1x10 mg/g-fish * 170 g- fish/day * 365 dayslyr * 50 years
'POT fish ing 71 0 Z , O
LADDPOTJU, ing = L7x10' Slkg- day
2.10.5 Exposure Characterization and Uncertainties
The example presented here is used to represent per capita bounding exposure among the
Native American subsistence population from ingestion of contaminated fish. It should be noted
that caution should be used in setting all exposure factor inputs to upper-percentile values, as was
done in this example, because the resulting exposure estimates may exceed reasonable maximum
exposures for the population of interest. However, such an approach may be appropriate for
screening assessments. Central tendency exposures for subsistence fishing Native American
adults may be estimated by using the mean fish intake rate of 59 g/day from the Table 10-85, of
the Exposure Factors Handbook (U.S. EPA, 1997a). High-end exposure could be estimated by
setting exposure duration to the mean value (9 years) as shown in Table 15-174 of the Exposure
Factors Handbook (U.S. EPA, 1997a). The contaminant concentration could also be set to the
mean or median value. Chronic lifetime exposures via ingestion of fish for children in Native
American subsistence populations may be estimated using the data in Table 10-74 of the
Exposure Factors Handbook (U.S. EPA, 1997a).
Uncertainties associated with this example scenario are related to the assumed activity
patterns of the receptor population and the input parameters used. First, implicit in this scenario
is the assumption that the adult Native American subsistence population consumes fish from a
contaminated site at the 95th percentile rate reported in the Exposure Factors Handbook (U.S.
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EPA, 1997a). This assumption requires that all Native American subsistence fishing exists on
contaminated surface water and all fish consumed by the population of interest are caught from
and contain contaminants from that location. Second, the ingestion rates found in the Exposure
Factors Handbook (U.S. EPA, 1997a) are based on survey data from four tribes in Washington
state. The example calculation assumes that the intake rates for these tribes are representative of
other Native American subsistence populations found around the nation. Third, a single value
for upper-percentile contaminant concentration in fish is used to estimate bounding average
lifetime exposure. This assumes that the consumed fish always contains contaminant at the
average concentration. The variability in average contaminant concentrations obtained from
different samples might introduce some degree of uncertainty. Fourth, the exposure duration of
50 years is based on the entire adult lifetime (i.e., age 20 to 70 years). There is uncertainty as to
whether the Native American population would consume fish from the contaminated location for
this entire timeframe. Also, the life expectancy of Native Americans is not available, therefore
data for Americans as a whole are used.
The confidence in the bounding exposure provided in this example is related to
confidences in the 95th percentile fish intake rate per day, the 90th percentile residence time, and
the exposure concentration. The overall confidence rating given by the Exposure Factors
Handbook (U.S. EPA, 1997a) is medium for per capita intakes, but low for upper-percentiles.
The rating is medium for residence time. If the rating for the exposure concentration is medium,
the overall confidence rating for bounding exposure should be low to medium.
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2.11 CONSUMER ONLY INGESTION OF CONTAMINATED FISH: GENERAL
POPULATION ADULTS, HIGH-END, ACUTE EXPOSURE
2.11.1 Introduction
Surface water or sediment contamination can result in potential contamination of fish
(finfish and shellfish), as a result of bioaccumulation of chemicals of potential concern in fish
tissues. This might result in exposure among individuals who consume fin fish or shellfish.
Receptors could include fishing families, households with recreational fish consumption, and
general or other sub-populations who consume contaminated fish. Acute exposure via
consumption of contaminated fish may be estimated based on the concentration of chemicals in
fish, the intake rate of contaminated fish per eating occasion, exposure frequency, and exposure
duration. In this example, acute exposure via ingestion of total fish (i.e., both marine and
freshwater) is assumed and evaluated for the adult general population.
2.11.2 Exposure Algorithm
Exposure via this pathway can be estimated as follows:
ADR
EF * ED
POT fish ing
BW * AT
(Eq. 14)
where:
ADR
Cfish
iRfish
EF
ED
BW
AT
POT fish ing
acute potential dose rate from ingestion of contaminated fish (mg/kg-
day);
concentration of contaminants in fish (mg/g fish);
per capita intake rate of fish (g/eating occasion);
exposure frequency (eating occasions/day);
exposure duration (day);
body weight (kg); and
averaging time (day).
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2.11.3 Exposure Factor Inputs
Cfisk ~ The concentration of contaminants in fish is either the measured or predicted
concentration, based on modeling, of the chemical of interest in the fish caught in the
contaminated surface water. For acute exposure, the maximum concentration of the chemical of
interest in fish would be used. In this example, it is assumed that the maximum concentration of
chemical "x" in fish is 1x10-3 milligram per gram offish (as consumed).
IRflsh - Intake rates of total fish for various age groups of the general population are
provided in Table 10- 82 of the Exposure Factors Handbook (U.S. EPA, 1997a). In this
example, the 95th percentile of the quantity (as consumed) of fish consumed per eating occasion,
297g/eating occasion, is used for the example calculation shown below. This value is the
average of the 95th percentile intake rates for males and females between the ages of 19 and 75+
years, as shown in Table 11.
Quantity of Fish Consumed per
Eating Occasion from Table 10-45
of the Exposure Factors Handbook
Age (yrsVGender
19-34 Male
19-34 Female
35-64 Male
35-64 Female
65-74 Male
65-74 Female
75+ Male
75+ Female
95th Percentile Intake Rate
362
227
360
280
392
304
227
225
Average = 297
EF - Exposure frequency (EF) is assumed to be 1 eating occasion per day.
ED - Exposure duration (ED) is the length of time over which exposure occurs. For
assessing acute exposure, the shortest period which might lead to an acute effect should be used
as the exposure duration. For the purpose of the example calculation shown below, the exposure
duration of one day is used.
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AT - For acute exposure assessment, averaging time is equal to exposure duration. Thus,
the averaging time of one day is used in this example.
BW - Although Table 7-2 of the Exposure Factors Handbook (U.S. EPA, 1997a) shows
a value of 71.8 kg for adults, an average body weight of 70 kilograms for the adult general
population is used for the example calculation shown below for consistency with toxicity data.
2.11.4 Calculations
Using the exposure algorithm and exposure factor inputs shown below, the LADDPOTfish
ing from ingestion of total fish would be estimated as follows for the general population:
-3
1x10 mglg * 297 gleating occasion * 1 eating occasion/day * 1 day
70 % * 1 day
-3
2.11.5 Exposure Characterization and Uncertainties
The example presented here is used to represent high-end acute exposure among general
population adults from ingestion of contaminated fish. Central tendency exposures may be
estimated by using the mean or median fish intake rate from Table 11.
Uncertainties associated with this example scenario are related to the assumed activity
patterns of the receptor population and the input parameters used. First, implicit in this scenario
is the assumption that the general population consumes contaminated fish at the 95th percentile
as reported in the Exposure Factors Handbook (U.S. EPA, 1997a). Second, the ingestion intake
rates for a single eating occasion found in the Exposure Factors Handbook (U.S. EPA, 1997a)
are derived from data collected in 1977/78 and may not reflect recent changes in eating habits.
Thus, there is some degree of uncertainty in using these intake rates to estimate exposures. Also,
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a single value for the average contaminant concentration in fish is assumed. This assumes that
all the fish consumed contain the contaminant of interest at the average concentration.
The confidence in the acute exposure provided in this example is related to confidences in
the 95th percentile fish intake rate per eating occasion and the exposure concentration. A
confidence rating for the amount of fish consumed per eating occasion is not given in the
Exposure Factors Handbook (U.S. EPA, 1997a). However, the confidence is assumed to be
medium because although it is based on a large national survey, the data are from 1977-78 and
may not accurately reflect current eating patterns. If the rating for the exposure concentration is
medium or higher, the overall confidence rating for acute exposure should be at least medium.
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2.12 INGESTION OF CONTAMINATED BREAST MILK: INFANTS, CENTRAL
TENDENCY SUBCHRONIC EXPOSURE
2.12.1 Introduction
Some contaminants (i.e., lipophilic compounds) can become sequestered in human breast
milk and can be passed on to nursing infants via breastfeeding. Nursing mothers can take up
contaminants from air, water, and locally produced food and pass them on to their nursing
infants, and may have accumulated contaminant loads in adipose tissue over their lifetime.
Breast-feeding infants up to 6 months of age typically obtain most of their dietary intake from
breast milk. Because lipophilic contaminants are the most likely to be transferred through breast
milk, the lipid content of breast milk must be considered. Receptors could include infants who
are fully or partially breast fed. Exposure via ingestion of contaminated breast milk is estimated
based on the concentration of contaminants in breast milk, intake rates of breast milk, exposure
frequency, and exposure duration. In this example, exposure via ingestion of contaminated
breast milk is assumed and the central tendency subchronic daily exposure from this pathway is
evaluated for the population of infants who are fully breast fed for six months after birth.
2.12.2 Exposure Algorithm
Exposure via this pathway would be calculated as follows:
_ C 'breast mi,k * FC * ^ * EF * ED
ing _.
where:
por breast miik ing = potential subchronic average daily dose from ingestion of
contaminated breast milk (mg/kg-day);
= concentration of contaminants in contaminated breast milk (mg/g
lipid);
FC = fat content or lipid content in breast milk (g lipid/g milk)
Abreast milk = intake rate of breast milk for infants who are fully breast fed (g
milk/kg-day);
EF = exposure frequency (days/month);
ED = exposure duration (months); and
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AT = averaging time (days).
2.12.3 Exposure Factor Inputs
- The concentration of contaminants in breast milk is either the measured or
milk
predicted concentration, based on modeling, of the chemical of interest in breast milk. For
estimating central tendency exposures, the mean or median values would be used. The 95%
upper confidence limit of the mean concentration can be used as a conservative estimate of the
mean concentration. For the purpose of the example calculations shown below, it is assumed
that the modeled 95% upper confidence limit of the mean concentration of chemical "x" in breast
milk is IxlO"3 mg/g lipid.
FC - The average fat content of breast milk is used to convert the unit of concentration
from mg/g lipid to mg/g breast milk. The purpose is to ensure consistency between the units for
concentration and intake rate of breast milk. Table 14-9 of the Exposure Factors Handbook
(U.S. EPA, 1997a) provides data on the lipid content of breast milk of mothers who nurse infants
at different months after child birth. In this example, the average lipid content of 0.04 g lipid/g
milk, as recommended in Table 14-16 of the Exposure Factors Handbook (U.S. EPA, 1997a), is
used.
Abreast miik ~ The average intake rate of breast milk for infants from birth to 6 months of
age can be estimated based on intake rates of breast milk for infants (1-12 months) provided in
Table 14-15 of the Exposure Factors Handbook (U.S. EPA, 1997a). The intake rates provided in
Table 14-15 are not on the basis of body weight. Thus, the intake rates in units of mL/day for 1
month, 3 month, and 6 month old infants are first converted to the intake rates in units of mL/kg-
day by dividing by the average body weights for corresponding age groups of infants provided in
Table 7-1 of the Exposure Factors Handbook (U.S. EPA, 1997a). The resulting intake rates are
then averaged to yield the average intake rate for infants from birth to six months of age. The
detailed calculations are summarized in the table below. The average breast milk intake rate of
135 mL/kg-day, as estimated, is converted to g/kg-day using the human milk density factor of
1.03 g/mL. Thus, the intake rate becomes 139 g/kg-day and is used for the example calculation
shown below.
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Table 14-15 of the Exposure
Factors Handbook
Ages Breast milk intake rate
1 month 702 mL/day
3 month 759 mL/day
6 month 765 mL/day
Table 7-1 of the Exposure Factors
Handbook
Ages Mean body weight (kg)
Girl Boy Girl/Boy
1 month 3.98 4.29 4.14
3 month 5.40 5.98 5.69
6 month 7.21 7.85 7.53
Ages Breast Milk Intake Rate
1 month 169.6 mL/kg-day
3 month 133.4 mL/kg-day
6 month 101.6 mL/kg-day
Average for 135 mL/kg-day
1-6 months
135 mL/day x 1.03 g/mL (human
milk density factor) = 139 g/kg-day
EF - Exposure frequency is 30 days per month.
ED - Exposure duration is the length of time over which exposure occurs. For the
purposes of this example, it is assumed that infants are breast fed for only six months. After that
time, infants either switch to breast milk substitutes or solid food. Thus, the exposure duration of
six months is used in this example.
AT - Because the subchronic average daily dose is being calculated in this example, the
averaging time (AT) is equivalent to the exposure duration. Thus, AT is 6 months. This value is
converted to 180 days (i.e., 6 months * 30 days/month) for the purposes of the calculations.
2.12.4 Calculations
Using the exposure algorithm and exposure factors shown above, the ADDpoT breast milking
is estimated as follows for the population of infants who are breast fed.
ADD,
POT breast milk tag
mglg lipid * 0.04g- lipid/g- milk * 139 glkg-day * 30 days/month * 6 months
180 days
ADD
POT breast milk ing
-day
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2.12.5 Exposure Characterization and Uncertainties
The example presented here is used to represent central tendency exposure among the
population of infants who are fully breast fed for six months after birth by nursing mothers with
contaminated breast milk. High-end exposures may be estimated using upper-percentile intake
rates from the table cited above. If a bounding exposure estimate is desired, the concentration of
contaminant may also be set to the maximum measured or modeled concentration. Caution
should be used, however, in setting all exposure factor inputs to upper-percentile values, as the
resulting exposure estimates may exceed reasonable maximum exposures for the population of
interest.
The uncertainties associated with this example scenario are related to the assumed
activity pattern of the receptor population and the input parameters used. The assumption made
in this scenario is that the population of infants are breast fed for six months at the average intake
rates of breast milk specified in the Exposure Factors Handbook (U.S. EPA, 1997a). In reality,
the Mothers Survey (Ross Laboratories, 1999) found that 30.7% of mothers who began breast
feeding in the hospital were still breast feeding at 6 months of infant age and 17.1% were still
breast feeding at 12 months of age. Thus, it is possible that the exposure estimates based on an
assumed exposure duration of 6 months would overestimate the actual exposure for most breast-
fed infants if a lifetime average daily dose were to be calculated. There are three types of
uncertainty associated with the intake rates used in this scenario. First, the intake rates may not
represent the nationwide average intake rates for the population of interest due to the relatively
small size of the sample used. These data may not accurately reflect the range of intra- and inter-
individual variability intake over time among infants in the United States. Second, the
distribution of the average intake rates generated using short-term (1-3 days) data might not
reflect the long-term distribution of the average daily intakes. Thus, there would be some degree
of uncertainty in using the upper-percentiles of the long-term distribution of intake rates to
estimate high-end exposures. Third, the use of average body weights in conjunction with these
intake rates contributes to the uncertainty since these were not the actual body weights for the
infants from which the intake rates were derived. An additional source of uncertainty includes
the fact that a single value for the average contaminant concentration in breast milk is used to
estimate the central tendency subchronic exposure. This assumes that all the breast milk from
the population of interest contains a contaminant at the average concentration. The variability in
average contaminant concentrations obtained from different samples might introduce some
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degree of uncertainty. Also, this analysis assumes the surface of the breast is uncontaminated.
Thus, the infants' exposure is from breast milk only, and not contaminants present on the
mother's skin.
The confidence in the central tendency exposure provided in this example is related to
confidences in average intake rates of breast milk and exposure concentrations. The confidence
rating given by the Exposure Factors Handbook (U.S. EPA, 1997a) is medium for the average
intake rates. If the rating for exposure concentration is also medium, the overall confidence
rating for the central tendency exposure should be at least medium.
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2.13 INGESTION OF CONTAMINATED INDOOR DUST: YOUNG CHILDREN,
HIGH-END, AVERAGE LIFETIME EXPOSURE
2.13.1 Introduction
At sites where soil contamination exists, there is the potential for exposure via ingestion
of indoor dust originating from outdoor soil. Receptors could include child or adult residents,
office workers, or any other populations who work inside a building or live in a house near a
contaminated site. Exposure via this pathway is estimated based on the concentration of
contaminants in indoor dust or outdoor soils, the ingestion rate of indoor dust, exposure
frequency, and exposure duration. In this example, exposure via ingestion of indoor dust is
assumed and the high-end lifetime average daily exposure from this pathway is evaluated for the
population of young children who often crawl on the floor and play with dusty toys.
Young children are exposed to indoor dust primarily through hand-to-mouth activities.
2.13.2 Exposure Algorithm
Exposure via this pathway would be calculated as follows:
LADD
dust
CF
EF * ED
POT dust ing
BW * AT
(Eq. 16)
where:
LADD
C
CF
"Slust
EF
ED
BW
AT
POT dust ing"
potential lifetime average daily dose from ingestion of indoor dust
(mg/kg-day);
concentration of contaminants in indoor dust (mg/g);
conversion factor for 0.001 g/mg;
ingestion rate of dust (nig/day);
exposure frequency (days/year);
exposure duration (years);
average body weight (kg); and
averaging time (days).
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2.13.3 Exposure Factor Inputs
Cdust - The concentration of contaminants in indoor dust is either the measured or
predicted concentration, based on modeling, of the chemical of interest in indoor dust or outdoor
soil at the contaminated site. For estimating central tendency exposures, the mean or median
values would be used. The 95% upper confidence limit of the mean concentration can be used as
a conservative estimate of the mean concentration. In this example, it is assumed that the
modeled 95% upper confidence limit of the mean concentration of chemical "x" in indoor dust is
lxlO-3mg/g.
CF - A conversion factor is required to convert between mg and g.
IRdust - The upper-percentile intake rate of indoor dust for young children (1-5 years old)
is calculated as the difference between the upper-percentile soil and dust ingestion rate (587
mg/day) and the upper-percentile soil ingestion rate (383 mg/day) in Table 4-22 of the Exposure
Factors Handbook (U.S. EPA, 1997a). The indoor dust intake rate of 200 mg/day, as estimated,
is used for the example calculation shown below.
EF - Exposure frequency is assumed to be 350 days a year for this example, because the
indoor dust intake rate provided in the Table 4-22 of the Exposure Factors Handbook (U.S. EPA,
1997a) is the annual average intake rate. Young children are assumed to be away from the
indoor source of contamination (e.g., on vacation) for 2 weeks per year.
ED - In this example, an exposure duration of 5 years (from age 1 to age 5) is used, based
on the assumption that after 5 years of age, children no longer crawl on the floor and their indoor
dust ingestion is limited compared to that of younger children.
BW - The average body weight for children between the ages of 1 and 5 years can be
estimated by averaging the age-specific average body weights for children of ages 1, 2, 3,4, and
5 provided in Table 7-3 of the Exposure Factors Handbook (U.S. EPA, 1997a). The average
body weight for 1-5 year old children of 15.7 kilograms, as estimated, is used for the example
calculation shown below.
AT - Because the lifetime average daily dose is being calculated in this example for a
member of the general population, the averaging time (AT) is equivalent to the lifetime of the
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individual being evaluated. The averaging time (AT) of 70 years is used for a member of the
general population. For use in the calculations, this value is converted to 25,550 days (i.e., 70
years * 365 days/year).
2.13.4 Calculations
Using the exposure algorithm and exposure factors shown above, the LADDPOTdusting is
estimated as follows for the population of young children:
1x70" mgfg * 0.001 g/mg * 200 mg/day * 350 days/year * 5 years
15.7 kg * 25,550 days
-day
2.13.5 Exposure Characterization and Uncertainties
The example presented here is used to represent high-end exposure among a population
of young children, ages 1-5, via ingestion of indoor dust. Central tendency exposures may be
estimated using mean indoor dust intake rates. If a bounding exposure estimate is desired, the
concentration of contaminants may also be set to the maximum measured or modeled
concentration. Caution should be used, however, in setting all exposure factor inputs to high-end
values, as the resulting exposure estimates may exceed reasonable maximum exposures for the
population of interest.
The uncertainties associated with this example scenario are mainly related to the
following assumed activity patterns of the receptor population and the input parameters used.
First, implicit in this scenario is that young children of ages 1 to 5 ingest indoor dust at the same
intake rate specified in the Exposure Factors Handbook (U.S. EPA, 1997a). It should be noted
that intake rates might decrease as activity patterns change with increased ages. Second, the
annual average intake rate of indoor dust for young children provided in the Exposure Factors
Handbook (U.S. EPA, 1997a) is calculated based on the intake rates for both soil and dust
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combined and soil alone. These data are derived from data collected from a variety of studies,
rather than from data collected from a specific study on indoor dust. The uncertainty for the
exposure estimate in this example is expected to be high for three reasons: 1) the uncertainty of
estimates of soil/dust ingestion which tends to increase with upper percentile estimates; 2) the
uncertainty associated with the attribution of ingestion of soil versus indoor dust; and 3) as noted
in Table 4-22, 'The ingestion rate studies were of short duration and are not estimates of usual
intake." For a more reliable exposure estimate, a study would need to be conducted to
specifically estimate the indoor dust intake rate for young children.
The confidence in the high-end exposure estimate provided in this example is related to
confidences in the upper-percentile intake rate of indoor dust and the exposure concentration. No
confidence rating for indoor dust intake rate is given in the Exposure Factors Handbook (U.S.
EPA, 1991 a). Considering the fact that the annual average indoor dust intake rate is calculated
based on the differences in soil intake rates and soil/dust intake rates from a variety of studies,
rather than the data collected from a specific study, the confidence rating is expected to be low.
Thus, even if the confidence rating for the exposure concentration is medium or higher, the
overall confidence rating for the central tendency exposure is expected to be low.
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2.14 INGESTION OF INDOOR DUST ORIGINATING FROM OUTDOOR SOIL:
OCCUPATIONAL ADULTS, CENTRAL TENDENCY, AVERAGE LIFETIME
EXPOSURE
2.14.1 Introduction
At sites where soil contamination exists, there is the potential for the transfer of
contaminated soil to indoor locations, and subsequent occupational exposure via ingestion of
indoor dust that adheres to food, cigarettes, or hands. Receptors could include administrative
workers, or any other populations who work indoors at a site where soil contamination exists.
Exposure via this pathway is estimated based on the concentration of contaminants in soils, soil
ingestion rate, exposure frequency, and exposure duration. In this example, exposure via
ingestion of contaminated indoor dust is assumed and the central tendency lifetime average daily
exposure from this pathway is evaluated for an adult population (i.e., administrative workers).
2.14.2 Exposure Algorithm
Exposure via this pathway would be calculated as follows:
LADD
Csoil *
POT soil ing
* IRsoil * EF * ED
BW * AT
(Eq.17)
where:
LADD
POT soil ing'
CF
EF
ED
BW
AT
potential lifetime average daily dose from ingestion of contaminated
soil (mg/kg-day);
concentration of contaminants in soil (mg/g);
conversion factor for O.OOlg/mg;
rate of soil ingestion (mg/day);
exposure frequency (days/year);
exposure duration (years);
average body weight (kg); and
averaging time (days).
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2.14.3 Exposure Factor Inputs
Csoil - The concentration of contaminants in soil is either the measured or predicted
concentration, based on modeling, of the chemical of interest in the soil at a contaminated site.
For estimating central tendency exposures, the mean or median values would be used. The 95%
upper confidence limit of the mean concentration can be used as a conservative estimate of the
mean concentration. For the purpose of the example calculations shown below, it is assumed that
the modeled 95% upper confidence limit of the mean concentration of chemical "x" in soil is
IxlO'3 mg/g.
IRsoil - According to Table 4-23 of the Exposure Factors Handbook (U.S. EPA, 1997a),
the recommended average soil intake rate for adults is 50 mg/day.
EF - Exposure frequency is assumed to be 350 days a year for this example, as the soil
intake rate provided in the Table 4-23 of the Exposure Factors Handbook (U.S. EPA, 1997a) is
the annual average intake rate. Individuals are assumed to be away from the contaminated source
(e.g., on vacation) for 2 weeks per year.
ED - Exposure duration is the length of time over which exposure occurs. For the
purposes of this example, the occupational tenure of 39.8 years for the 65+ age group of
individuals categorized in administrative occupations in Table 15-161 of the Exposure Factors
Handbook (U.S. EPA, 1997a) is assumed.
BW - Although Table 7-2 of the Exposure Factors Handbook (U.S. EPA, 1997a) shows a
value of 71.8 kg for adults, an average body weight of 70 kilograms for the adult general
population is used for the example calculation shown below for consistency with toxicity data.
AT - Because the lifetime average daily dose is being calculated in this example for a
member of the general population, the averaging time (AT) is equivalent to the lifetime of the
individual being evaluated. The averaging time (AT) of 70 years is used for a member of the
general population. For use in the calculations, this value is converted to 25,550 days (i.e., 70
years * 365 days/year).
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2.14.4 Calculations
Using the exposure algorithm and exposure factors shown above, the LADDPOT soi| ing is
estimated as follows for the individuals categorized in administrative occupations:
, .__. 1x10^ mg/g * 0.001 g/mg * 50 mg/day * 250 days/year * 39.8 years
= 70 kg * 25,550 days
POT somng = I-IWO' mglkg-day
2.14.5 Exposure Characterization and Uncertainties
The example presented here is used to represent central tendency exposure among a
population of administrative workers via ingestion of indoor dust originating from contaminated
soil. If a bounding exposure estimate is desired, the concentration of contaminants may be set to
the maximum measured or modeled concentration. Caution should be used, however, in setting
all exposure factor inputs to upper-percentile values, as the resulting exposure estimates may
exceed reasonable maximum exposures for the population of interest.
The uncertainties associated with this example scenario are mainly related to the annual
average intake rate of soils for adults provided in the Exposure Factors Handbook (U.S. EPA,
1997a), which is based on a limited data set for adults. Thus, the uncertainty for the exposure
estimate in this example is high. For a more reliable exposure estimate, a study needs to be
conducted to estimate the soil intake rate for adults who work outdoors. Another uncertainty for
this scenario is the representativeness of the soil contaminant concentration to characterize
inadvertent soil ingestion of soil particles adhered to food or hands. This is often addressed by
using sieved soil samples to characterize the finer particles that are more likely to be adhered and
subsequently ingested (U.S. EPA Technical Review Workgroup for Lead, 2000c). Soil particle
size was initially explored by (Calabrese, Stanek et al., 1996) and (Stanek, Calabrese et al., 1999).
Additionally, most of the soil ingestion studies did not adequately address exposure to house
(indoor) dusts.
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The confidence in the central tendency exposure estimate provided in this example is
related to confidences in the average intake rate of soils, the occupational tenure for administrative
workers, and the exposure concentration. The confidence rating given by the Exposure Factors
Handbook (U.S. EPA, 1997a) is high for the administrative worker occupational tenure. No
confidence rating for soil intake rate is given in the Exposure Factors Handbook (U.S. EPA,
1997a). Considering the fact that the annual average soil intake rate is based on limited data, the
confidence rating is expected to be low. Thus, even if the confidence rating for the exposure
concentration is medium or higher, the overall confidence rating for the central tendency exposure
is expected to be low.
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3.0 EXAMPLE INHALATION EXPOSURE SCENARIOS
The exposure to a chemical from the inhalation pathway is not a simple function of the
inhalation rate and body weight. The physicochemical characteristics of the inhaled agent are key
determinants to its interaction with the respiratory tract and ultimate deposition. Current EPA
methodology uses the principles of inhalation dosimetry to determine the human equivalent
concentration (HEC) for calculating a Reference Concentration (RfC) or Inhalation Unit Risk
(IUR). According to these procedures, it is unnecessary to calculate inhaled dose when using
dose-response factors from the Integrated Risk Information System (IRIS) in a risk assessment.
Inhalation risk assessments require only an average air concentration adjusted to continuous
exposure to evaluate health concerns:
For non-carcinogens, IRIS uses Reference Concentrations (RfC) which are
expressed in concentration units. Hazard is evaluated by comparing the measured
or modeled concentration of the chemical in the inspired air adjusted to continuous
exposure to the RfC.
For carcinogens, IRIS uses unit risk values which are expressed in inverse
concentration units. Risk is evaluated by multiplying the unit risk by the measured
or modeled concentration of the chemical in the inspired air adjusted to continuous
exposure.
Exposure information, specifically information related to activity patterns (e.g., exposure
time, frequency, and duration, as well as contaminant concentration) may vary across age groups
and other population groups. Consequently, such variation should be taken into account in
deriving both lifetime excess cancer risk and hazard quotient estimates. Beyond the consideration
of time spent in the area of contamination and any change in concentration of the contaminant in
that area, no additional corrections to the risk calculations for specific age groups are necessary.
The exposure scenarios presented in the sections that follow show how these adjustments in
concentration are applied to various populations.
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3.1 INHALATION OF CONTAMINATED INDOOR AIR: OCCUPATIONAL
FEMALE ADULTS, CENTRAL TENDENCY, AVERAGE LIFETIME EXPOSURE
3.1.1 Introduction
At sites where the use of occupationally related chemical products results in indoor air
contamination, there may be a potential for occupational exposure via inhalation. Receptors could
include commercial/ industrial workers, doctors and nurses, or any population who inhales
contaminated air as a result of their occupation.
3.1.2 Exposure Algorithm
The equations in the sections below provide the appropriate equations for calculating the
concentration of the chemical in the inspired air adjusted to continuous exposure that can be used
directly in the risk assessment.
indoor air adjusted
* ED
AIT,
where:
ndoor ^r (adjusted)
ET
EF
ED
AT
concentration of contaminants in indoor air adjusted (mg/m3);
concentration of contaminants in indoor air (mg/m3);
exposure time (hr/day);
exposure frequency (days/year);
exposure duration (years); and
averaging time (hours).
3.1.3 Exposure Factor Inputs
Cindoorair ~ The concentration of contaminants in air is either the measured or predicted
concentration, based on modeling, of the chemical of interest in the air at the site of interest. For
estimating central tendency exposures, the mean or median values would be used. The 95% upper
confidence limit of the mean concentration can be used as a conservative estimate of the mean
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concentration. For the purpose of the example calculations shown below, it is assumed that the
modeled 95 percent upper confidence limit of the mean concentration of chemical "x" in air is
IxlO'3 mg/m3.
ET- Exposure time is 8 hours/day, as female nurses are assumed to work eight hours per
day in this example. It should be noted that site-specific values may be used if available. For
example, some hospitals require that nurses work shifts (e.g., 12 hour shifts) over fewer days (e.g.,
3 days/week). Note that these alternate exposure times and frequencies would result in exposure
estimates that closely resemble those provided in this example.
EF - Exposure frequency is assumed to be 219 days a year for this example. This estimate
assumes that female nurses work 5 days a week, observe 10 Federal holidays, take 4 weeks of
vacation a year and an additional 12 personal days. This value is recommended by U.S. EPA
(1989) to represent central tendency exposure frequency for industrial/technical workers.
ED - Exposure duration is the length of time over which exposure occurs. For the
purposes of this example, the occupational tenure of 22.2 years for the 65+ age group of
Technicians and Related Support provided in Table 15-161 of the Exposure Factors Handbook
(U.S. EPA, 1997a) is assumed. This value assumes that female nurses inhaled occupationally
related contaminated air in a hospital for the occupational tenure of 22.2 years. After that time,
female nurses at the ages of 65+ are assumed to be retired and no longer inhale the contaminated
air.
AT - Because the lifetime average daily exposure for a member of the general female
population is of interest in this example, the averaging time (AT) is equivalent to the lifetime of
the individual being evaluated. According to Section 8.2 of the Exposure Factors Handbook
(U.S. EPA, 1997a), the averaging time (AT) of 70 years is recommended for a member of the
general population. For use in the calculations, this value is converted to 613,200 hours (i.e., 70
years * 365 days/year * 24 hours/day).
3.1.4 Calculations
Using the exposure factors shown above and equation 18, the Cindoorairadjusted is estimated as
follows:
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1x10 mg/m3 * 8 hours/day* 219 days/year * 22.2 years
~"indoor air adjusted £1390^)
Cindoor air adjusted ~ 6.4x70
3.1.5 Exposure Characterization and Uncertainties
The example presented here is used to represent central tendency occupational exposure
among the population of female nurses who inhale certain work-related chemicals. High-end
exposures may be estimated by increasing the exposure time, frequency, and duration. If a
bounding exposure estimate is desired, the concentration of contaminants may be set to the
maximum measured or modeled concentration. Caution should be used, however, in setting all
exposure factor inputs to high-end values, as the resulting exposure estimates may exceed
reasonable maximum exposures for the population of interest.
The uncertainties associated with this example scenario are related to the assumed activity
pattern of the receptor population and the input parameters used. The assumption of a 5-day work
week introduces some uncertainty since this may not reflect the shift approach employed by
certain hospitals. The specific working hours employed by the workers being assessed should be
used in calculating the exposure scenario. The assumption of retirement age may introduce some
uncertainty also and may vary for different receptor populations.
The confidence in the central tendency exposure estimate provided in this example is
related to confidences in an assumed activity pattern, occupational tenure, and exposure
concentrations. The confidence rating given by the Exposure Factors Handbook (U.S. EPA,
1997a) is high for the occupational tenure. Thus, if the confidence rating is medium for the
assumed activity pattern and medium for the exposure concentration, the overall confidence rating
for the central tendency exposure is at least medium.
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3.2 INHALATION OF CONTAMINATED INDOOR AIR: RESIDENTIAL CHILD,
CENTRAL TENDENCY, AVERAGE LIFETIME EXPOSURE
3.2.1 Introduction
At sites where localized volatile contaminants intrude into residences or where the use of
commercial products or other materials results in indoor air contamination, there may be the
potential for exposure among residents via inhalation. In this example, exposure via inhalation of
contaminated indoor air is assumed and the central tendency lifetime average daily exposure from
this pathway is evaluated for the residential child (ages 3-11 years).
3.2.2 Exposure Algorithm
The adjusted indoor air concentration (Cindoorairadjusted) is estimated as follows:
indoor air adjusted
EF* ED
where:
indoor air (adjusted)
ET
EF
ED
AT
3.2.3 Exposure Factor Inputs
concentration of contaminants in indoor air adjusted (mg/m3);
concenti"ation of contaminants in indoor air (mg/m3);
exposure time (hr/day);
exposure frequency (days/year);
exposure duration (years); and
averaging time (hours).
~ The concentration of contaminants in air is either the measured or predicted
concentration, based on modeling, of the chemical of interest in the air at the site of interest. For
estimating central tendency exposures, the mean or median values would be used. The 95% upper
confidence limit of the mean concentration can be used as a conservative estimate of the mean
concentration. For the purpose of the example calculations shown below, it is assumed that the
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modeled 95% upper confidence limit of the mean concentration of chemical "x" in air from the
breathing zone of 3-11 year old children is IxlO"3 mg/m3.
ET- Exposure time is 24 hours/day, assuming the child spends his/her entire day in a
contaminated indoor environment.
EF - Exposure frequency is 350 days a year in this example as the child is assumed to be
away from the contaminated source for 2 weeks per year (e.g., on vacation).
ED - Exposure duration is the length of time over which exposure occurs. For the purpose
of this example, the 50th percentile residential time of 9 years provided in Table 15-174 of the
Exposure Factors Handbook (U.S. EPA, 1997a) is assumed. The assumption is that the children
live in a residence for the average residential time of 9 years. After that time, they move to
another location where the indoor air is no longer contaminated. This also corresponds to the
exposure duration between the ages of 3-11 years, inclusive.
AT - Because the lifetime average daily dose is being calculated in this example for a
member of the general population, the averaging time (AT) is equivalent to the lifetime of the
individual being evaluated. The averaging time (AT) of 70 years is used for members of the
general population. For use in the calculations, this value is converted to 613,200 (i.e., 70 years *
365 days/year* 24 hours/day).
3.2.4 Calculations
Using the exposure factors shown above and equation 18, the Cindoorairadjusted is estimated as
follows:
_ 1x10 3 mg/m3 *24hrs/day * 350 days/year * 9 years
indoor air adjusted ~ 613,200
C indoor air adjusted * -2x7 0
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3.2.5 Exposure Characterization and Uncertainties
The example presented here is used to represent central tendency exposure among
residential children from inhalation of contaminated indoor air. High-end exposures may be
estimated by using the upper-percentile values for the residence time. If a bounding exposure
estimate is desired, the concentration of contaminants may also be set to the maximum measured
or modeled concentration.
The confidence in the central tendency exposure estimate provided in this example is
related to confidences in the residential time, and exposure concentrations. The confidence rating
given by the Exposure Factors Handbook (U.S. EPA, 1997a) is medium for the residence time.
Thus, if the confidence rating is medium for the exposure concentration, the overall confidence
rating for the central tendency exposure is at least medium. -
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3.3 INHALATION OF CONTAMINATED INDOOR AIR: SCHOOL CHILDREN,
CENTRAL TENDENCY, SUBCHRONIC EXPOSURE
3.3.1 Introduction
Volatile contaminants may intrude into buildings or chemicals may volatilize from
consumer products or other materials resulting in indoor air contamination. This may result in the
potential for exposure via inhalation. Receptors could include residents, commercial/industrial
workers, students, recreational populations, etc. For the purposes of this example, exposure
among elementary school children (i.e., 6 to 11 year olds) via inhalation of contaminated air inside
a school building is assumed. Central tendency subchronic daily exposure from inhalation is
evaluated for this population.
3.3.2 Exposure Algorithm
Exposure via this pathway would be calculated as follows:
* ET * EF * ED
C
orair
indoor air adjusted A CEo 20)
where:
air adjusted = concentration of contaminants in indoor air adjusted (mg/m3);
= concentration of contaminant in the indoor air (mg/m3);
ET = exposure time (hr/day);
EF = exposure frequency (days/year);
ED = exposure duration (years); and
AT = averaging time (hours).
3.3.3 Exposure Factor Inputs
Ctndoorair - The concentration of contaminant in air at the site (Ciaaootlil) is either the
measured or predicted concentration, based on modeling, of the chemical of interest in the air at
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the site of interest. For estimating central tendency exposures the mean or median values would
be used. Often, the 95% upper confidence limit of the mean concentration is used as a
conservative estimate of the mean concentration. For the purposes of this example, it is assumed
that the 95 percent upper confidence limit of the mean measured concentration of chemical "x" in
air is lxlO"3mg/m3.
ET - Table 15-84 of the Exposure Factors Handbook (U.S. EPA, 1997a) shows that both
the median and mean number of minutes spent in school for 5 to 11 year old children is 390
minutes (i.e., 6.5 hours). Data are not specifically available for 6 to 11 year olds; therefore, the
value for the 5 to 11 year old range is used for this scenario. Use of this value assumes that the
children spend all of their time in the building (i.e., it does not account for time that might be
spent outdoors in the playground). Thus, under certain circumstances, this value may slightly
overestimate the exposure time indoors.
EF - Exposure frequency is assumed to be 185 days a year for this example. This is
equivalent to 37 weeks of full-time school, and accounts for 15 weeks off for summer and winter
vacation, Federal and school holidays, etc.
ED - Exposure duration is the length of time over which exposure occurs. For the
purposes of this example, the exposure duration for 6 to 11 year old school children is assumed to
be six years (i.e., first grade through sixth grade). This assumes that all six years are spent in the
same building where indoor air contamination exists.
AT - Because the subchronic average daily dose is being calculated for a member of the
general population, the averaging time is equivalent to the exposure duration. For the purposes of
this example, the averaging time is converted to 52,560 hours (i.e., 6 years * 365 days/year * 24
hours/day).
3.3.4 Calculations
Using the exposure algorithm and exposure factor inputs shown above, the Cindoorair(adjusted)
for elementary school age children would be as follows:
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_ 1x10 3 mg/m3 * 6.5 hours/day * 185 days/year * 6 years
indoor air adjMd 52,560 hoWS
indoor air adjusted = 1-4x10
3.3.5 Exposure Characterization and Uncertainties
The example presented here is used to represent central tendency exposures among the
general population of elementary school children from the inhalation of contaminated air inside
the school building. High-end exposures may be estimated by increasing exposure durations and
frequencies. Caution should be used, however, in setting all exposure factor inputs to upper-
percentile values, as the resulting exposure estimates may exceed reasonable maximum exposures
for the population of interest.
The uncertainties associated with this example scenario are related to the concentrations
and assumed exposure durations and frequencies. Assuming that the confidence in the exposure
concentration is at least medium, confidence in the overall central tendency exposure example
provided here should be at least medium.
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4.0 EXAMPLE DERMAL EXPOSURE SCENARIOS
4.1 DERMAL CONTACT WITH CONTAMINATED SOIL: RESIDENTIAL ADULT
GARDENERS, CENTRAL TENDENCY, AVERAGE LIFETIME EXPOSURE
4.1.1 Introduction
At sites where soil contamination exists, there may be the potential for exposure via
dermal contact with soil during outdoor activities. Exposure may also occur from soil that is
"tracked in" to the home or other buildings (i.e., schools, businesses, etc.). Therefore, receptors
could include nearby residents, commercial/industrial workers, students, recreational populations,
etc. Exposure via dermal contact with the soil considers not only the concentration of
contaminants in the soil, but also the surface area of the skin that contacts the soil, the amount of
soil that adheres to the skin per unit surface area, the fraction of contaminant in the soil that
penetrates the skin, and the frequency and duration of exposure. For the purposes of this example,
exposure among residential adult gardeners via dermal contact with contaminated soil is assumed.
Central tendency lifetime average daily exposure from soil contact is evaluated for residential
adult gardeners.
4.1.2 Exposure Algorithm
Exposure via this pathway would be calculated as follows:
C ., * CF * SAIBW * AF , * EF * ED
- sml sml
POT soil contact dermal ...
. zl)
soil contact dermal LADDpOT soil contact dermal * ABS (gq 22)
where:
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LADDPOTsoilcontactdennal = potential lifetime average daily dose from
dermal contact with contaminated soil
(mg/kg-day);
LADDABS soil contact dennal = absorbed lifetime average daily dose from
dermal contact with contaminated soil
(mg/kg-day);
Csoil = concentration of contaminant in the soil at the
site (mg/kg);
CF = conversion factor (lxlO"6kg/mg);
SA/BW = surface area of the skin that contacts the soil
(cm2/event) divided by body weight (kg);
AFsoiI = adherence factor for soil (mg/cm2);
EF = exposure frequency (events/year);
ED = exposure duration (years);
ABS = absorption fraction; this value is chemical-
specific; and
AT = averaging time (days).
4.1.3 Exposure Factor Inputs
Csoii ~ The concentration of contaminant in soil at the site (Csoil) is either the measured or
predicted concentration, based on modeling, of the chemical of interest in the soil at the site of
interest. For estimating central tendency exposures the mean or median values would be used.
Often, the 95% upper confidence limit of the mean concentration is used as a conservative
estimate of the mean concentration. For the purposes of the example calculations provided below,
it is assumed that the 95 % upper confidence limit of the mean measured concentration of
chemical "x" in soil is 1 mg/kg.
CF - A conversion factor is required to convert between mg/kg and kg/mg. The value is 1
x 10~6 kg/mg because there are 1,000,000 mg per kg.
SA/BW - The surface area of the skin that comes into contact with the soil (SA) during
each exposure event can be estimated in several ways. The three approaches described below are
meant to highlight the available data in the Exposure Factors Handbook (U.S. EPA, 1997a) and to
show the various ways in which these data can be used to calculate the surface area of the skin
that comes in contact with the contaminated soil. One method may be preferable over the other
depending on the exposure scenario being evaluated and the data available to the assessor. For
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the first approach, an estimate of the percentage of the body exposed to soil can be made. This
percentage is used in conjunction with the total surface area of the body. For the purposes of this
example, it is assumed that 25 percent of the body is exposed. The total surface area of the body
is assumed to be 18,150 cm2, based on the average 50th percentile surface areas for adult males
(1.94 m2;19,400 cm2) and females (1.69 m2; 16,900 cm2), as cited in Table 6-4 of the Exposure
Factors Handbook (U.S. EPA, 1997a). The resulting exposed surface area (SA) value is 4,540
cm2/event. This value is divided by the average body weight for male and female adults between
the ages of 18 and 75 years (71.8 kg), as shown in Table 7-2 of the Exposure Factors Handbook
(U.S. EPA, 1997a) to estimate a SA/BW of 63.2 cm2/event-kg. According to EPA's Risk
Assessment Guidance for Superfund (U.S. EPA, 1998b), 50th percentile surface area values
should also be used for reasonable maximum exposure estimates (i.e., instead of 95th percentile
surface area values), when using an average body weight, because of the strong correlation
between surface area and body weights, and because 50th percentile values are "most
representative of the surface areas of individuals of average weight" (U.S. EPA, 1989). A second
approach is to make assumptions about the specific body parts that are expected to be exposed to
soil, given the likely clothing scenario for the activity of interest. For this example scenario (i.e.,
gardening), it is assumed that an individual will wear short pants and short sleeve shirt, and that
the hands, lower arms, and lower legs will come into contact with the soil. Using Tables 6-2 and
6-3 of the Exposure Factors Handbook (U.S. EPA, 1997a), surface area values are obtained and
averaged for male and female hands and lower legs. One-half the values for arms are used to
represent only the lower arms. The values for the three body parts are then summed to represent
the average total exposed surface area for males and females (4,578 cm2/event), and divided by
the average body weight for males and females (71.8 kg) to obtain the SA/BW value (63.8
cm2/event-kg). A third approach is to use the surface area to body weight ratio values presented in
Table 6-9 of the Exposure Factors Handbook (U.S. EPA, 1997a). The data in Table 6-9 were
developed by dividing the measured total surface areas for 401 individuals by their corresponding
body weights and developing a distribution of SA/BWs for the study population. The advantage
of using the data from this distribution is that the correlation between surface area and body
weight is accounted for. Because these SA/BWs are based on total body surfaces, they are
multiplied by 0.25 to estimate the surface area assumed to be exposed in this example. As shown
in the following table, the estimates obtained by these three methods are similar, with a slightly
higher value being obtained by Approach 3. These differences are relatively small and are not
expected to significantly impact the doses estimated for this example.
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Approach 1 - SA/BW
Average of Median Total Surface Area for
Males and Females (Table 6-4) * Assumed
Percentage of the Body Exposed / Average
Adult Body Weight (Table 7-2).
[(19,400 cmVevent + 16,900 cmVevent)
12
*(0.25)]/(71.8kg) =
63.2 cm2/event-kg
Approach 2 - SA/BW
Average of Sum of Hand, Lower Leg, and
Arm Surface Areas for Male (Table 6-2)
and Female (Table 6-3) Adults / Average
Body Weight (Table 7-2).
Hands
Lower Legs
Vi Arms
SUM
Males
990 cm2
2,560 cm2
1,455 cm2
5,005 cm2
Females
820 cm2
2,180cm2
1,150cm2
4,150 cm2
63.8 cm2/event-kg
[(5,005 cmVevent + 4,150 cm2/event) / 2]
/ (71.8 kg) =
Approach 3 - SA/BW
Total Surface Area to Body Weight Ratio
for ages >18 Years (Table 6-9) * Assumed
Percentage of the Body Exposed.
(2,840 cm2/event-kg * 0.25) =
71.0cm2/event-kg
AFsoil - The Exposure Factors Handbook (U.S. EPA, 1997a) provides soil adherence
factors (AFsoil) for several different activities involving soil contact (Table 6-12). For the purposes
of this example, the values for gardeners (i.e., Gardener No. 1 and Gardener No. 2) from Table 6-
12 are used. The adherence factor can be estimated using either of two methods. The approaches
described below are meant to highlight the available data in the Exposure Factors Handbook and
to show the various ways in which these data can be used to calculate the soil adherence factors.
One method may be preferable over the other depending on the exposure scenario being
evaluated. Using either method, averages are calculated for hands, arms, and legs from the data
for the two gardeners listed in Table 6-12. The average soil adherence values are: 0.19 mg/cm2
for hands, 0.052 mg/cm2 for arms, and mg/cm2 for legs. Using the first method, these soil
adherence values for hands, arms, and legs are simply averaged. The result is 0.096 mg/cm2. The
second approach apportions the adherence among the body parts that contribute to the total
surface area in contact with the soil, as shown in Table 14. For example, adherence is greater on
the hands than on the arms and legs, but the hands account for less than 20 percent (i.e., 0.198) of
the total surface area exposed. Thus, the surface area fraction of the hands is multiplied by the
adherence value for hands and added to the surface area fractions of arms and legs multiplied by
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the adherence values for arms and legs to estimate the overall soil adherence for this combination
of body parts. Using this approach the resulting value is 0.078 mg/cm2.
- .!* '-A-?
, Data Source
Approach 1 -
Table 6-12;
Exposure
Factors
Handbook
Approach 2 -
Table 6-12;
Exposure
Factors
Handbook
--, __ ''< j; 'Ifv « "*>yjK^»Ti'.fT*""*-v-'^K
Hands
Legs
Arms
AVERAGE
Hands
Lower Legs
Vi Arms
Adherence Gardener 1
0.20 mg/cm2
0.072 mg/cm2
0.050 mg/cm2
0.1 07 mg/cm2
Avg.
M & F S A Frac. of Total
905 cm2 0.198
2,370cm2 0.518
1,303 cm2 0.284
1$~S "' ,-- "" I *'' .^f ^ :4 tJ--,₯;^-' -
apWsrta-A* , f > 1 ..' , '/,
Adherence Gardener 2
0.18 mg/cm2
0.022 mg/cm2
0.054 mg/cm2
0.085 mg/cm2
Average Adherence.
0.19 mg/cm2
0.052 mg/cm2
0.047 mg/cm2
Average
0.19 mg/cm2
0.047 mg/cm2
0.052 mg/cm2
0.096 mg/cm2
Weighted
Adherence
0.038 mg/cm2
0.027 mg/cm2
0.013 mg/cm2
SUM = 0.078 mg/cm2
EF - Exposure frequency is the number of times that exposure is expected to occur in a
year. EF is assumed to be 12 events a year (i.e., 12 days/year) for this example. This assumes that
individuals contact soil from working in their gardens once per month, on average. It should be
noted that the Exposure Factors Handbook (U.S. EPA, 1997a) provides information on the
number of hours per month spent working with soil in a garden (Tables 15-61 and 15-62) from the
National Human Activity Pattern Survey (NHAPS). However, the data in these tables are not
suitable for use in this scenario because they provide information on duration of exposure and not
frequency of exposure. An implicit assumption in this scenario is that exposure (and absorption
of the contaminants by the skin) occurs for each event in which soil contacts (and adheres to) a
given surface area of the skin. This occurs without regard to the duration of the exposure event
because a certain fraction of the contaminant in the soil on the skin is assumed to be absorbed for
each event.
ED - Exposure duration is the length of time over which exposure occurs. For the
purposes of this example, the average residency time of the household is assumed. Based on the
recommendations in Table 15-174 of the Exposure Factors Handbook (U.S. EPA, 1997a), the
50th percentile residence time is 9 years. Thus, the assumption in this example is that the exposed
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population contacts contaminated soil from the site at which they reside for 9 years. After that
time, they are assumed to reside in a location where the soil is not affected by contamination from
the site.
ABS - This value is chemical specific. Information on absorption fractions can be
obtained from EPA's Dermal Exposure Assessment: Principles and Applications (U.S. EPA,
1992b). EPA has also developed the draft Part E Supplemental Guidance for Dermal Risk
Assessment of the Risk Assessment Guidance for Superfund, Volume I: Human Health
Evaluation Manual (U.S. EPA, 2001b). This document provides another source of data on dermal
absorption. Although this document is not final, it is generally more representative of current
thinking in this area and assessors are encouraged to use it instead of U.S. EPA (1992b). For the
purposes of the calculations provided below for this example, it is assumed that the absorption
fraction for the chemical of interest (i.e., chemical "x") is 0.1.
AT - Because the lifetime average daily dose is being calculated for a member of the
general population, the averaging time is equivalent to the lifetime of the individual being
evaluated. For the purposes of this example, the average lifetime for men and women is used
because the exposures are assumed to reflect the general population and are not gender- or age-
specific. The averaging time of 70 years is used in the calculations. This value is converted to
25,550 days (i.e., 70 years * 365 days/year).
4.1.4 Calculations
Using the exposure algorithm and exposure factor inputs shown above, the
LADDABSsoilcontactdennal would be as follows using either Approach 1, Approach 2, or Approach 3
for calculating SA/BW for the adults, combined with the results of Approach 2 for calculating the
adherence value:
Approach 1
. ._n 1 mglkg * lxlO~* kg/mg * 63.2 cm2/event- kg * 0.078 mg/cm2 * 12 events/year * 9 years
LAJJJJPOT,a,lcon,ac, dermal- 25,550 days
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Approach 2
pOT soil contact dermal
- day
soil C0nu,ct
mg/kg-day * 0.1
LADDABS soil contact dermal = 2.1x10^ mg/kg-day
1 mg/kg * 1x10 kg/mg * 63.8 cm2/event- kg * 0.078 mg/cm2 * 12 events/year * 9 years
25,550 days
contact dermal
= 2.1x10'* mg/kg- day
ABS soil contact dermal = ^xl°~ S/kg- day * 0.1
soil contact dermal
= 2.1x1 0'' mg/kg- day
Approach 3
_ 1 mg/kg * 1x10 kg/mg * 71.0 cm1 1 event- kg * 0.078 mg/cm2 * 12 events/year * 9 years
=
"""*' * 25,550 days
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POT soa contact = 2-3xl°
S0il contact aennal = 2.3x70" mglkg- day * 0.1
ABS S0il contact dennal
- day
As shown above, the estimated doses are almost identical using these three approaches for
calculating surface area to body weight ratios, based on the second method for estimating
adherence (i.e., the adherence value is 0.076 mg/cm2). Using the first method for estimating
adherence (i.e., the adherence value is 0.096 mg/cm2), the results are only slightly higher: 2.6xlO"9
for Approaches 1 and 2, and 2.9xlO"9 for Approach 3.
4.1.5 Exposure Characterization and Uncertainties
The example presented here is used to represent central tendency exposures among adult
gardeners from dermal contact with contaminated soil. High-end exposures may be estimated by
replacing the mean surface areas or surface area to body weight ratios used here with upper-
percentile values. Caution should be used, however, in using upper-percentile values when
average body weights are used because of the correlation between these two factors. It should be
noted that using separate distributions for surface area and body weight may be less of a problem
when deterministic exposure assessment approaches are used (e.g., the average of the 95th
percentile surface areas for males and females from Table 6-2 and 6-3 is 21,850 cm2; dividing by
71.8 kg gives 304 cm2/kg, which is comparable to the 95th percentile surface area to body weight
ratio for adults of 329 cm2/kg in Table 6-9), but may result in significant uncertainties when used
in probabilistic assessments in which correlation between these two variables is not taken into
consideration. Therefore, if probabilistic approaches are used, it may be desirable to use the data
for surface area to body weight ratios in Table 6-9 of the Exposure Factors Handbook (U.S. EPA,
1997a) because these data account for this correlation. Upper-percentile residence time from the
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table cited above may also be used to estimate high-end exposures. If a bounding exposure
estimate is desired, the concentration in soil may be set to the maximum measured or modeled
concentration, and the assumed frequency of exposure may be increased (e.g., once per day).
Caution should be used, however, in setting all exposure factor inputs to upper-percentile values,
as the resulting exposure estimates may exceed reasonable maximum exposures for the population
of interest.
The uncertainties associated with this example scenario are related to assumed activity
patterns of the receptor population and the input parameters used. Implicit in this scenario is the
assumption that the population of interest contacts the contaminated soil from the site, and that
adherence occurs over the assumed surface area of the skin at the rates shown in the Exposure
Factors Handbook (U.S. EPA, 1997a). Another implicit assumption is that the soil is on the skin
for the entire exposure event, which is assumed to be a day. This means that each event (whether
it consists of a few minutes or several hours) is assumed to be one day. Multiple soil contact
events in a single day are still treated as one event. Use of a one day exposure event is consistent
with absorption values, which are typically based on 24-hour exposure periods. The assumption
that absorption from contaminants in soil adhering to the skin occurs over 24 hours contributes to
the uncertainty of the resulting estimates because it is possible that individuals may bathe.
Selection of the clothing scenario or percentage of the body exposed should be based on the
assessors knowledge of the populations/activities and should be designed to reflect, as closely as
possible, the skin surface area exposed for the activity of interest. However, the assumptions used
regarding the clothing worn and the surface area exposed results in uncertainty in the assessment.
The Exposure Factors Handbook (U.S. EPA, 1997a) describes the uncertainty associated with the
surface area and adherence data, and concludes that although there may be some selection bias
associated with the surface area data upon which the recommended values are based, they are the
best available data for use in exposure assessment. The uncertainties associated with the
adherence data result from the limited size of the data set, and the fact that adherence may be
influenced by the clothing worn by the study participants, and soil properties (e.g., moisture
content, particle size) that are not entirely accounted for in the available data.
It should be noted that the confidence ratings given by the Exposure Factors Handbook
(U.S. EPA, 1997a) are high for surface area data, but low for soil adherence data and low for the
absorption fraction. Assuming that the confidence in the exposure concentration is also at least
medium, confidence in the overall central tendency exposure example provided here should be
low based on the soil adherence data and absorption fraction.
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4.2 DERMAL CONTACT WITH SOIL: TEEN ATHLETE: CENTRAL TENDENCY,
SUBCHRONIC EXPOSURE
4.2.1 Introduction
At sites where localized soil contamination exists, there may be the potential for exposure
via dermal contact with soil during outdoor activities. Exposure may also occur from soil that is
"tracked in" to the home or other buildings (i.e., schools, businesses, etc.). Therefore, receptors
could include nearby residents, commercial/industrial workers, students, recreational populations,
etc. Exposure via dermal contact with the soil considers not only the concentrations of
contaminants in the soil, but also the surface area of the skin that contacts the soil, the amount of
soil that adheres to the skin per unit surface area, the fraction of contaminant in the soil that
penetrates the skin, and the frequency and duration of exposure. For the purposes of this example,
exposure among teen athletes via dermal contact with contaminated soil is assumed. A
subchronic average daily dermal dose from soil contact is evaluated for the teen athlete. For the
purposes of this assessment a teen athlete (age 13-15 years) playing soccer for one-half of the year
is evaluated.
4.2.2 Exposure Algorithm
Exposure via this pathway would be calculated as follows:
C . * CF * SAIBW * AF . * EF * ED * ABl
_ _
ABS soil contact dermal AJ, (Eo. 23)
where:
ADDABS soil contact dennal = absorbed average daily dose from dermal contact with
contaminated soil (mg/kg-day);
Csoil = concentration of contaminant in the soil at the site (mg/kg);
CF = con version factor (lxlO'6kg/mg);
SA/BW = surface area of the skin that contacts the soil (cm2/event)
divided by body weight (kg);
AFsoil = adherence factor for soil (mg/cm2);
EF = exposure frequency (events/yr);
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ED = exposure duration (years);
ABS = absorption fraction; this value is chemical-specific; and
AT = averaging time (days).
4.2.3 Exposure Factor Inputs
Csoil - The concentration of contaminant in soil at the site (Csoil) is either the measured or
predicted concentration, based on modeling, of the chemical of interest in the soil at the site of
interest. In the case of a central tendency scenario, the 95% upper confidence limit of the mean
concentration is used as a conservative estimate of the mean concentration. For the purposes of
the example calculations provided below, it is assumed that the 95% upper confidence limit of the
mean measured concentration of chemical "x" in soil is IxlO"3 mg/kg.
CF - A conversion factor is required to convert between mg/kg and kg/mg. The value is
IxlO"6 kg/mg because there are 1,000,000 mg per kg.
SA/BW - For this assessment, assumptions will be made regarding the surface area of
specific body parts that are expected to be exposed to soil. For this example scenario (i.e., teen
athlete), it is assumed that an individual will wear short pants and short sleeve shirt, and that the
hands, arms, and legs will come into contact with the soil. The SA/BW calculation is developed in
Table 15. First, Table 6-8 of the Exposure Factors Handbook (U.S. EPA, 1997a) is used to obtain
the percent surface area contribution of arms, legs, and hands to the total surface area. The
percent contribution for each body part is added together to represent the total percentage of
exposed skin expected for exposed hands, arms, and legs. Next, Tables 6-6 and 6-7 of the
Exposure Factors Handbook (U.S. EPA, 1997a) are used to identify the 50th percentile total body
surface areas for male and female children (age 13-15 years). The age group data for males and
females are averaged to represent exposure to this age group. The same general procedure is used
to calculate the 50th percentile body weights. Tables 7-6 and 7-7 of the Exposure Factors
Handbook (U.S. EPA, 1997a) are used to identify male and female body weights for children aged
13 to 15 years.
The total surface area for children (age 13-15 years) is calculated to be 15,633 cm2. The
total surface area is multiplied by the percent ratio of exposed arms, legs and hands (49.2%) to
calculate exposed surface area for males and females to obtain 7,691 cmVevent. The average
101
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body weight for male and females is then divided by the average body weight for male and female
children (53.2 kg) to obtain the SA/BW value of 144 cm2/event-kg.
,*L
;" ^ "%'iigT r*; '*"*>
-**
Surface Area (Tables 6-6 and 6-7)
Percentage of Total Surface Area
Represented by Hands, Legs, and Arms for
Children (Table 6-8) / Average Body
Weight (Table 7-6 and 7-7). Tables from
Exposure Factors Handbook
Bodv Part
Hands
Legs
Arms
SUM
THPWSii*1*
*$£ *?!
IS; XV* ' I V ^
Percent of Total
5.11 %
32.0 %
12.1 %
49.2 %
Median Total Body Surface Area
for Children (cm2)
Age
13<14
14<15
15<16
Average
Male
14,700
16,100
17,000
15,933
Female
14,800
15,500
15,700
15,333
Median Total Body Weights
for Children (Kg)
Age
13
14
15
Average
Male
48.4
56.4
60.1
55.0
Female
49.0
53.1
53.3
51.8
[(15,933 cm2 + 15,333 cm2) / 2] x 0.492
/[ (55.0 kg + 51.8 kg)/2] =
~"v%i wir**' * *. ""
f -
144 cm2/event-kg
AFsoU - The Exposure Factors Handbook (U.S. EPA, 1997a) provides soil adherence
factors (AFsoil) for several different activities involving soil contact (Table 6-12). For the purposes
of this example, the values for soccer players (e.g., Soccer No.l) from Table 6-12 are used. The
other soccer players (e.g., Soccer No. 2 and No. 3) presented in this table are not in the correct age
group (i.e., they represent age 24 to 34 years) and are not appropriate for this scenario. The ages
of these soccer populations are shown in Table 6-11 of the Exposure Factors Handbook (U.S.
EPA, 1997a).
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The adherence factor can be estimated using two methods (see the following table). The
approaches described below are meant to highlight the available data in the Exposure Factors
Handbook and to show the various ways in which these data can be used to calculate the soil
adherence factors. One method may be preferable over the other depending on the exposure
scenario being evaluated. Using the first method, the individual soil adherence values for hands,
arms, and legs are simply averaged. The result is 0.052 mg/cm2. The second approach apportions
the adherence among the body parts that contribute to the total surface area in contact with the soil
(see the following table). First, the surface areas of the exposed body parts for children (age 13 to
15 years) are calculated using the average total body surface area (15,633 cm2) multiplied by the
percent surface area per body part (Table 6-8). Next, the surface areas for each body part are
divided by the total surface area of all the exposed body parts to represent a fraction of the total
exposed surface area. Finally, this fraction is multiplied by the soil adherence value for each body
part. The sum of the adherences for each body part represents the estimated adherence factor for
the second approach as shown in the following table.
Approach 1 - Soil Adherence
Average of adherence data from Table 6- 12 of the
Exposure Factors Handbook
Approach 2 - Soil Adherence
Mean total surface area from Tables 6-6 and 6-7; body
part surface area fractions from Table 6-8 and
adherence data from Table 6-12 of the Exposure
Factors Handbook
Hands
Legs
Arms
AVERAGE
Hands
Legs
Arms
SUM
Hands
Legs
Arms
Hands
Legs
Arms
SUM
Soccer No. 1 Adherence
0.11 mg/cm2
0.031 mg/cm2
0.0 11 mg/cm2
0.052 mg/cm2
Average SA
15,633 cm2 x 0.051 = 797 cm2
15,633 cm2 x 0.32 = 5,002 cm2
15,633 cm2 x 0.121= 1,892 cm2
7,691 cm2
Fraction of Total Exposed SA
0.10
0.65
0.25
Adherence Factors c
0.1 1 mg/cm2 x 0.10= 0.01 1 mg/cm2
0,031 mg/cm2 x 0.65= 0.020 mg/cm2
0.011 mg/cm2 x 0.25= 0.0028 mg/cm2
0.034 mg/cm2
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EF - Exposure frequency is the number of times that exposure is expected to occur in a
year. EF is assumed to be 130 events/year (i.e., 130 days/year). This assumes that individuals
contact soil from athletic fields once per day for 5 days/week for 6 months of a year (i.e.,
assuming no exposure associated with this athletic activity during the winter and summer
months). It should be noted that the Exposure Factors Handbook (U.S. EPA, 1997a) provides
information on the number of minutes per day spent on sports (Table 15-2 and 15-3); however,
the data in these tables are not suitable for use in this scenario because they provide information
on duration of exposure and not frequency of exposure. Also, note that this frequency assumption
is used for illustrative purposes only. There may be cases where the exposure frequency is higher
or lower. An implicit assumption in this scenario is that exposure (and absorption of the
contaminants by the skin) occurs for each event in which soil contacts (and adheres to) a given
surface area of the skin. This occurs without regard to the duration of the exposure event because
a certain fraction of the contaminant in the soil on the skin is assumed to be absorbed for each
event.
ED - Exposure duration is the length of time over which exposure occurs. For the
purposes of this example, the exposure duration for 13 to 15 year old school children is assumed
to be three years. This assumes that three years are spent playing soccer on contaminated athletic
fields.
ABS - This value is chemical specific. Information on absorption fractions can be
obtained from EPA's Dermal Exposure Assessment: Principles and Applications (U.S. EPA,
1992b). EPA has also developed the draft Part E Supplemental Guidance for Dermal Risk
Assessment of the Risk Assessment Guidance for Superfund, Volume I: Human Health
Evaluation Manual (U.S. EPA, 2001b). This document is a source of data on dermal absorption.
Although this document is not final, it is generally more representative of current thinking in this
area and assessors are encouraged to use it instead of U.S. EPA (1992b). For the purposes of the
calculations provided below for this example, it is assumed that the absorption fraction for the
chemical of interest (i.e., chemical "x") is 0.1.
AT - Because the average daily dose is being calculated for a specific age group (e.g. 13 to
15 year old children), the averaging time is equivalent to the exposure duration, except that the
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duration is expressed in days. For use in the calculations, this value is converted to 1,095 days
(i.e., 3 years * 365 days/year).
4.2.4 Calculations
Using the exposure algorithm and exposure factor inputs shown above, the ADDABS soil contact
dennai w°uld be as follows using both Approach 1 and Approach 2 for calculating the adherence
value.
Approach 1
1x10^ mg/kg * lxlO~* kg/mg * 144 cm*/event-kg * 0.052 mg/cm2 * 130 events/year * 3 years * 0.1
*' «"' a*"*1 *""' 1,095 days
ADDabs soil contact dermal = 2.7x70"'° mg/kg- day
Approach 2
\xlO~* mg/kg * 1x10'* kg/mg * 144 cm2/evenf- kg * 0.034 mg/cm2 * 130 events/year * 3 .yeara * 0.1
1,095 days
-10
ADDabSSoil contact dennal = 1-7^0" mg/kg- day
As shown above, the estimated doses are similar using these two approaches. Based on
the first method for estimating adherence (i.e., the adherence value is 0.052 mg/cm2) doses are
slightly higher 2.7x 10"10 than the second method for estimating adherence (i.e., the adherence
value is 0.034 mg/cm2), which is 1.7xlO'10.
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4.2.5 Exposure Characterization and Uncertainties
The example presented here is used to represent central tendency exposures among teen
athletes, ages 13-15, from dermal contact with contaminated soil. High-end exposures may be
estimated by replacing the mean surface areas or surface area to body weight ratios used here with
upper-percentile values. Caution should be used, however, in using upper-percentile values when
average body weights are used because of the correlation between these two factors. It should be
noted that using separate distributions for surface area and body weight may be less of a problem
when deterministic exposure assessment approaches are used, but may result in significant
uncertainties when used in probabilistic assessments in which correlation between these two
variables is not taken into consideration. If a bounding exposure estimate is desired, the
concentration in soil may also be set to the maximum measured or modeled concentration, and the
assumed frequency of exposure may be increased (e.g., 250 times per year; 5 days per week for 12
months per year). Caution should be used, however, in setting all exposure factor inputs to upper-
percentile values, as the resulting exposure estimates may exceed reasonable maximum exposures
for the population of interest.
The uncertainties associated with this example scenario are related to the assumed activity
patterns of the receptor population and the input parameters used. Implicit in this scenario is the
assumption that the population of interest contacts the contaminated soil from the site, and that
adherence occurs over the assumed surface area of the skin at the rates shown in the Exposure
Factors Handbook (U.S. EPA, 1997a). Another implicit assumption is that the soil is on the skin
for the entire exposure event, which is assumed to be a day. This means that each event (whether
it consists of a few minutes or several hours) is assumed to be one day. Multiple soil contact
events in a single day are still treated as one event. Use of a one day exposure event is consistent
with absorption values, which are typically based on 24-hour exposure periods. The assumption
that absorption from contaminants in soil adhering to the skin occurs over 24 hours contributes to
the uncertainty of the resulting estimates because it is possible that individuals may bathe.
Selection of the clothing scenario or percentage of the body exposed should be based on the
assessors knowledge of the populations/activities and should be designed to reflect, as closely as
possible, the skin surface area exposed for the activity of interest. However, the assumptions used
regarding the clothing worn and the surface area exposed results in uncertainty in the assessment.
The Exposure Factors Handbook (U.S. EPA, 1997a) describes the uncertainty associated with the
surface area and adherence data, and concludes that although there may be some selection bias
associated with the surface area data upon which the recommended values are based, they are the
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best available data for use in exposure assessment. The uncertainties associated with the
adherence data result from the limited size of the data set, and the fact that adherence may be
influenced by the clothing worn by the study participants, and soil properties (e.g., moisture
content, particle size) that are not entirely accounted for in the available data.
It should be noted that the confidence ratings given by the Exposure Factors Handbook
(U.S. EPA, 1997a) are high for surface area data, but low for soil adherence data. Assuming that
the confidence in the exposure concentration is also at least medium, confidence in the overall
central tendency exposure example provided here should be low, based on the low confidence in
the soil adherence data.
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4.3 DERMAL CONTACT WITH CONSUMER PRODUCTS: GENERAL
POPULATION ADULTS, CENTRAL TENDENCY, AVERAGE LIFETIME
EXPOSURE
4.3.1 Introduction
In many instances, it is necessary to estimate exposure for consumer products. Under the
Toxic Substances Control Act (TSCA) which was introduced in 1976, for example, EPA is
required to conduct an exposure assessment on consumer products before the chemical substance
is introduce in the marketplace. Under other laws such as the Federal Food, Drug, and Cosmetic
Act (FFDCA); the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA); and the Food
Quality Protection Act (FQPA), EPA and FDA have established rules and regulations for
exposure assessments for consumer products when new drugs and pesticides are registered or
reregistered (DeVito and Farris, 1997). Frequently, a new chemical registrant may also conduct
assessments to determine the safety of their product before they decide to market or manufacture
the consumer product. For these groups, Chapter 16 of the Exposure Factors Handbook (U.S.
EPA, 1997a) may be a useful source of information on the frequency of use, duration of exposure,
amount of the product used, and activities that would lead to the use of a particular consumer
product. The assessor may also use other sources of information. For the purposes of this
example, dermal exposure to a preservative present in wet latex household paints is examined.
Central tendency exposure to paint products is used to evaluate a lifetime average daily dose for
the general population adult.
4.3.2 Exposure Algorithm
Exposure via this pathway would be calculated as follows:
DSY * CF * * Th * WF * DIL * EF * ED * ABS
ABS paint dermal ~ ^ (Eq. 24)
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where:
LADDABSpaimdermal = absorbed lifetime average daily dose from dermal contact with paint
(mg/kg-day);
DS Y = density of product (g/cm3);
CF = conversion factor (mg/g);
SA/BW = surface area of the skin that is exposed to paint (cm2/kg/event)
divided by body weight;
Th = film thickness on skin (cm);
WF = weight fraction of preservative in paint;
DIL = dilution of product;
EF = event frequency (events/year);
ED = exposure duration (years);
ABS = absorption fraction, this value is chemical specific; and
AT = averaging time (days).
4.3.3 Exposure Factor Inputs
DSY - The density of wet latex paint is 1.24 g/cm3. This is based on the mean density of
latex paint (U.S. EPA, 1986a).
CF - A conversion factor of 1,000 is needed to convert grams to milligrams for the
purposes of calculating a LADD.
SA/BW - In order to predict the surface area to body weight ratio, exposed skin surface
area must be measured. For this example scenario (i.e., painting), it is assumed that an individual
will wear short pants and a short sleeve shirt. Thus, the exposed skin may include the hands,
forearms, and lower legs. It is assumed that paint on the face and neck would be washed off
immediately after application.
The age group that will be examined is all adults over 18 years of age. Table 6-9 of the
Exposure Factors Handbook (U.S. EPA, 1997a) presents descriptive statistics based on the
surface area/body weight ratios. The mean surface area to body weight (SA/BW) ratio is 0.0284
m2/kg (e.g., 284 cm2/kg). Table 6-5 of the Exposure Factors Handbook (U.S. EPA, 1997a)
provides the percentage of total body surface areas for adults. The following table provides the
109
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relevant percent contribution of the total surface area for each body part used for the example
calculation.
Body part percentages from Table 6-5
of the Exposure Factors Handbook
Hands
Forearms
Lower Legs
Total
5.9
12.8
23.9
5.1
Not available; male
value of 5.9 assumed
12.8
23.8
Since it is likely that only a small portion of the skin might become exposed to paint from
splatters, drips, or unintentional contact, an estimate of how much paint contacts the exposed skin
is needed. A conservative assumption that ten percent of the skin surface area has paint on it is
used in this example (U.S. EPA, 1986a). Using the total SA/BW of 284 cm2/kg times the ratio of
exposed skin versus total body surface area (e.g., 0.239) times a ratio of paint on exposed skin
(e.g., 0.10), a total SA/BW of 6.79 cm2/kg/event is estimated for exposed skin of the hands,
forearms and lower legs.
Th - The film thickness of paint on skin is estimated at 9.81E-03 cm (U.S. EPA, 1986a).
Data on film thickness of paint on skin are not available ; however, EPA assumed that the initial
film thickness value resulting from immersion of hands in an oil/water mixture most closely
approximates the film thickness of paint splattered onto skin. This liquid was selected because
paint is closely analogous to the oil and water mixture (U.S. EPA, 1986a).
WF - For this example, it is assumed that the weight fraction of the preservative (i.e.,
chemical "x") measured in the paint is 0.0025 (U.S. EPA, 1986a). This means that chemical "x"
comprises approximately 2.5% of the overall weight of the paint.
DIL - The paint product is not diluted; thus, a ratio of 1 is assumed (U.S. EPA, 1986a).
EF -The event/frequency is expressed as the number of events per year. Table 16-18 of
the Exposure Factors Handbook (U.S. EPA, 1997a) provides information on the frequency of
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occasions spent painting the interior of a home per year. The overall mean for painting with latex
paints is 4 events/year (i.e., 4 days/year) (U.S. EPA, 1997a).
ED- Exposure duration is the length of time over which exposure occurs. For consumer
products, exposure duration could be set equal to the length of time a product or chemical is
expected to remain in the marketplace or some other measure of the length of time that a
consumer will be exposed. The assumption in this example is that the exposed population may
use paint containing the chemical being evaluated for 20 years, which is the time the product is
assumed to be on the market.
ABS - This value is chemical specific. Information on absorption fractions can be
obtained from EPA's Dermal Exposure Assessment: Principles and Applications (U.S. EPA,
1992b). EPA has also developed the draft Part E Supplemental Guidance for Dermal Risk
Assessment of the Risk Assessment Guidance for Superfund, Volume I: Human Health
Evaluation Manual (U.S. EPA, 1999). This document is a source of data on dermal absorption.
Although this document is not final, it is generally more representative of current thinking in this
area and assessors are encouraged to use it instead of U.S. EPA (1992b). For the purposes of the
calculations provided below for this example, it is assumed that the absorption fraction for the
chemical of interest (i.e., chemical "x") is 0.1.
AT - Because the lifetime average daily dose is being calculated for a member of the
general population, the averaging time is equivalent to the lifetime of the individual being
evaluated. For the purposes of this example, the average lifetime for men and women is used
because the exposures are assumed to reflect the general population and are not gender- or age-
specific. The averaging time of 70 years is used in the calculations; this value is converted to
25,550 days (i.e., 70 years * 365 days/year).
4.3.4 Calculations
Using the exposure algorithm and exposure factor inputs shown above, the LADD^ ^
dermal would be calculated as follows.
_ 1.24 g/COT3 * 1000 mg/g * 6.79 cm2/kg/event * 9.81x/Q'3 cm * 0.0025 * 4 eventslyr * 20 * 0.
MS paM dermal ~ 25,55QdayS
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, -5
^spaint ^ - 6.5x10- mglkg-day
4.3.5 Exposure Characterization and Uncertainties
The example presented here is used to represent central tendency exposures among general
population adults from dermal contact with paint. High-end exposures may be estimated by
replacing the mean surface areas to body weight ratios used here with upper-percentile values.
Caution should be used, however, in using upper-percentile values when average body weights are
used because of the correlation between these two factors. Exposure frequencies may also be
increased for estimating high-end exposures. For example, the 95th percentile exposure
frequency listed in Table 16-18 of the Exposure Factors Handbook (U.S. EPA, 1997a) is 10
events per year. There are uncertainties associated with the exposed skin surface area assumed for
this example (i.e., 10 percent of the hands, forearms, and lower legs). Further, hair on these body
parts may limit direct deposition on the skin. Uncertainties also exist for both the film thickness
and density. The film thickness is based on closely related liquids because actual film thickness
data for paint were not available. These values should only be viewed as estimates and the values
would be improved if actual experimental data were utilized. It appears that the uncertainty for
density would be lower because density data are typically provided by manufacturers of consumer
products and are based on actual experimental data. As a result of these factors, there is a
moderate level of uncertainty for this assessment.
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4.4 DERMAL CONTACT WITH SURFACE WATER: RECREATIONAL
CHILDREN, CENTRAL TENDENCY, AVERAGE LIFETIME EXPOSURE
4.4.1 Introduction
The potential for exposure to chemical substances exists at sites where localized surface
water bodies (i.e., streams, ponds, lakes, bays, or rivers) have been contaminated. Both adults and
children may dermally absorb chemicals that are in the water as a result of activities such as
swimming or wading. Receptors could include recreational swimmers or waders that trespass
onto a site or commercial/industrial workers working in and around water (e.g., construction
around reservoirs and drainage ditches and sampling activities to measure water quality).
Exposure via dermal contact considers not only chemical concentrations in contact with the skin,
but also the surface area of the skin that contacts the water, the absorption of the chemical that
comes into contact with the skin, exposure duration, exposure time, and exposure frequency. For
the purposes of this example, surface water exposure among recreational child swimmers and
waders (age 7-12 years) is assumed. Dermal exposure is assessed based on central tendency
lifetime average daily intakes.
4.4.2 Exposure Algorithm
Exposure via this pathway would be calculated as follows:
LADD
ABS surface -water dermal
DAevent* SA * EV * EF * ED
BW * AT
(Eq. 25)
where:
LADD
ABS surface water dermal
DA,
SA
EV
event
absorbed lifetime average daily dose from dermal
contact with contaminated surface water (mg/kg-
day);
absorbed dose per event (mg/cm2/event);
surface area of the skin that contacts surface water
(cm2);
event frequency (events/day);
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EF = exposure frequency (days/year);
ED = exposure duration (years);
BW = body weight of a child (kg); and
AT = averaging time (days).
4.4.3 Exposure Factor Inputs
DAevent - The absorbed dose per event (DAevent) is estimated to consider the following
factors:
the permeability coefficient from water;
the chemical concentration in water; and,
the event duration.
The approach to estimate DAevent differs with respect to inorganic and organic chemicals.
This is consistent with current EPA policy directives (U.S. EPA 2001b; U.S. EPA 1997a; U.S.
EPA 1992b). Note that this is an update from previous EPA policy directives (U.S. EPA 1989).
For inorganics, EPA recommends using the steady state approach to estimate dermally absorbed
doses. In this approach:
DAevent = FA x Kp x Cw (Eq. 26)
where:
DAevent = Absorbed dose per event (mg/cm2/event);
FA = Fraction absorbed (dimensionless);
Kp = Dermal permeability coefficient of compound in water (cm/hr); and
Cw = Chemical concentration in water (mg/cm3 or mg/mL).
For organics, the EPA provides two equations. These equations are different based on the
event duration versus the lag time per event. If the duration of the event (tevent) is less then the
time to reach steady state (2.4 x T) then the following equation is used to estimate DAevent (U.S.
EPA, 2001b; U.S. EPA, 1992b):
114
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'M
6 X T X t
event
It
(Eq. 27)
where:
FA
CL =
t,
event
Absorbed dose per event (mg/cm2/event);
Fraction absorbed (dimensionless);
Dermal permeability coefficient of compound in water (cm/hr);
Chemical concentration in water (mg/cm3 or mg/mL);
Lag time per event (hr/event); and,
Event duration (hr/event).
If the duration of the event (tevent) is greater than the time to reach steady state (2.4 * t)
then the equation incorporates a new coefficient B, which is a dimensionless ratio of the
permeability coefficient of a compound through the stratum corneum relative to its permeability
across the epidermis. The following equation is used to estimate this DAevent (U.S. EPA 1999;
U.S. EPA 1992b):
FA X Kp X Cw
t
event
1 + B
1 + 3B + IB2
(Eq. 28)
where:
FA
KP =
Cw =
T =
^event ~~
B
Absorbed dose per event (mg/cm2/event);
Fraction absorbed (dimensionless);
Dermal permeability coefficient of compound in water (cm/hr);
Chemical concentration in water (mg/cm3 or mg/mL);
Lag time per event (hr/event);
Event duration (hr/event); and,
Dimensionless ratio of the permeability coefficient of a compound through
stratum corneum relative to its permeability coefficient across the viable
epidermis.
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Guidance for using these equations is detailed in Section 5.3.2- Estimating DAevent for
Organics from the document entitled Dermal Exposure Assessment: Principles and Applications
(U.S. EPA, 19925). For the purposes of this example the organic chemical phenol is used.
Phenol, which is identified on Table 5-7 of U.S. EPA (1992b) and Appendix A of RAGS, Part E
(U.S. EPA, 2001b), has a molecular weight (MW) of 94, a log K^ of 1.46. The K,, for phenol is
4.3E-03 cm/hr and the FA is 1.0, as shown in Appendix A of EPA's RAGS, Part E (U.S. EPA,
2001b). In order to identify which equation must be used to calculate DAevent. The lag time per
event (T) must be calculated. The following equation can be used :
6 D (Eq- 29)
sc
In this equation lsc (the thickness of the stratum corneum) is 10~3 cm; therefore, Dsc (the stratum
corneum diffusion coefficient) would be S.lxlO"7 cm2/hr.
Log -Z= -2.72 - 0.0061 MW
I (Eq. 30)
The lag time per event (T) is 0.36 hr. Since the time to reach steady-state (t*) is defined as 2.4 T,
the t* would actually be 0.86 hr. The values for lag time per event (T), permeability ratio (B), and
steady-state (t*) can be verified on Table B-3, of RAGS Part E (U.S. EPA, 2001b). Based on
Table 15-67 on page 15-83 of the Exposure Factors Handbook (U.S. EPA, 1997a), the exposure
time for swimming for a child age 5-11 years is 1 hour per day, which is the 50th percentile for
swimming in fresh water swimming pools. Using this value as the event duration (tevent), tevent > t*,
thus Equation 28 would be used for the calculation of DAevent. The term B must be calculated:
B = K
'p\
MW .,
cm/hr
2.6
(Eq. 31)
In the case of phenol, B=0.016. Assuming a concentration in water (Cw) of 1 mg/mL an example
calculation is provided as follows:
116
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= 1.0 x 4.3x10 cmlhr x 1 mglmL
1 + 0.016
2 x 0.36
(1 + 0.016)2
DAmtint =0.0074 mgi
-------
34% based on data for ages 9<10 years and 12<13 years only (data for the other age groups
considered in this example were not available). An estimate of the total child surface area used to
represent a wading scenario for children (age 7 to 12 years) would be 3,842 cm2.
Percentage of Total Body Surface
Area from Table 6-8 of the
Exposure Factors Handbook
9<10
6.15
5.30
12<13
6.85
5.39
Avg
6.5
5.35
Total %
34
14.35
15.25
14.8
7.58
7.03
7.31
EV - The event frequency is the number of events per day since the LADD accounts for
daily exposure. For the purposes of this example 1 event is assumed per day.
EF - Since the event/frequency is expressed as number of events per day, exposure
frequency (EF) is expressed in days/yr. Table 15-176 of the Exposure Factors Handbook (U.S.
EPA, 1997a) recommends using a value of one swimming event per adult per month. This is the
recommended time for swimming at an outdoor swimming pool. Table 15-65 provides a more
conservative estimate of the number times swimming per month based on age. Note that for the
particular age group examined for this example (age 7 to 12 years), no data are available. Thus,
data for the nearest age group (i.e., 5 to 11 years) may be used as surrogates. According to the
table, the number of respondents for this age group (total N) is 100. Using the 50th percentile
frequency for this age group, up to five events per month is estimated as the number of swimming
and wading events for the summer months. It should be noted that these results are based on
swimming at a pool and may not be entirely representative of wading or swimming in a lake, pond
or stream. Therefore, one swimming event per month for children is assumed in this example.
Because children would typically only swim or wade during the summer months, an
estimate of 5 months per year is used. Assuming one swimming/wading event per month and
swimming/wading five months per year, an exposure frequency of five days per year is assumed.
118
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ED - Exposure duration (ED) is the length of time over which exposure occurs. For the
purposes of this example, the exposure duration for 7 to 12 year old school children is assumed to
be six years. This assumes that six years are spent swimming or wading in contaminated lakes,
ponds or streams near their homes.
BW - Table 7-6 of the Exposure Factors Handbook (U.S. EPA, 1997a) reports body
weights for children from 6 months to 20 years old. Using the published body weights for boys
and girls aged 7 to 12 years, an average weight of 32.9 kg is calculated. This is the 50th percentile
of the distribution.
AT - Because the lifetime average daily dose is being calculated, the averaging time is
equivalent to the lifetime of the individual being evaluated. For the purposes of this example, the
average lifetime for men and women is used because the exposures are assumed to reflect the
general population and are not gender- or age-specific. The averaging time of 70 years is used in
the calculations. This value is converted to 25,550 days (i.e., 70 years * 365 days/year).
4.4.4 Calculations
Using the exposure algorithm and exposure factor inputs shown above, the LADDABS surface
water dermal would be as follows for both swimming and wading.
Swimming
- 0-0074 mg/cm2/event* 11,300 cm2 * 1 event/day * 5 days/yr * 6 yi
MS surface^ dermal = 32 9
ABS turface vater dermal
~ day
Wading
0.0074 mg/cm2/event* 3,842 cm2 * 1 event/day * 5 days/yr * 6 yr
ABS surface water dermal
119
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LADDABS surface ^ater dermal = l-0xl°~ glkg-day
4.4.5 Exposure Characterization and Uncertainties
The example presented here is used to represent central tendency exposures among
children (age 7 to 12 years) swimming and wading in surface water. Note that high end exposures
may be adjusted based on replacing 50th percentile surface areas with upper 95th percentile
surface areas. If the surface areas are adjusted then a corresponding adjustment may also need to
be made to the body weight. Exposure durations and frequencies may also be increased for
estimating high end exposures. Note that the exposure durations and frequencies used in this
example are based on data for swimming in freshwater pools and not in freshwater streams, lakes,
and ponds. In addition, there are also uncertainties with regard to the use of data for swimming to
represent wading. It is possible that the exposure durations and frequencies for wading may be
higher; however, there are no definitive studies to prove this assumption. In addition, there are
uncertainties related to calculation of the absorbed dose per surface water exposure event (e.g.,
DAevent). According to Dermal Exposure Assessment: Principles and Applications, "the dermal
permeability estimates are probably the most uncertain of the parameters in the dermal dose
equation. Accordingly, the final dose and risk estimates must be considered highly uncertain
(U.S. EPA, 1992b)." Frequently Kp's are predicted using octanol/water coefficients (Kow). The
Dermal Exposure Assessment: Principles and Applications states that "the uncertainty in the
predicted Kp's is judged to be within plus or minus one order of magnitude from the best fit value
(U.S. EPA, 1992b)." A lack of measured data for a variety of chemicals makes the validation of
the model difficult.
Because of these uncertainties, U.S. EPA (1992b) recommends that an assessor conduct a
"reality check" by comparing the total amount of contaminant in the water to which an individual
is exposed, to the total estimated dose. U.S. EPA (1992b) states that "As a preliminary guide, if
the dermal dose exceeds 50 percent of the contaminant in the water, the assessor should question
the validity of the dose estimate. Assessors are cautioned to consider the various uncertainties
associated with this scenario and ensure that exposure estimates are adequately caveated.
120
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5.0 REFERENCES
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particle size of soil ingested by children: implications for exposure assessment at waste sites
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U.S. EPA. (1986a) Standard scenarios for estimating exposure to chemical substances during use
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139928/AS.
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U.S. EPA. (1988a) Superfund exposure assessment manual. Washington, DC: Office of
Emergency and Remedial Response. EPA/540/1-88/001. Available from NTIS, Springfield, VA;
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groundwater models. Washington, DC: Exposure Assessment Group, Office of Health and
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Part A. Interim Final. Washington, DC: Office of Solid Waste and Emergency Response.
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Part B. Interim Final. Washington, DC: Office of Solid Waste and Emergency Response.
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U.S. EPA (1997a) Exposure factors handbook. Washington, DC: Environmental Protection
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of pesticide programs'health effects division -Draft, Office of Pesticide Programs, Washington,
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Part D. Interim Final. Washington, DC: Office of Solid Waste and Emergency Response.
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Solid Waste and Emergency Response.Washington, DC.
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