Child-Specific Exposure

Scenarios Examples

National Center for Environmental Assessment

Office of Research and Development

EPA 600/R-14/217F | September 2014 | www.epa.gov/ncea
EPA/600/R-14/217F

September 2014

www.epa.gov/ncea

Child-Specific Exposure Scenarios Examples

National Center for Environmental Assessment

Office of Research and Development

U.S. Environmental Protection Agency

Washington, DC 20460
ii

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

The purpose of the Child-Specific Exposure Scenarios Examples is to outline scenarios 

for various child-specific exposure pathways and to demonstrate how data from the Exposure 

Factors Handbook (hereinafter EFH) (U.S. EPA, 2011a) may be applied for estimating dose. 

Exposure scenarios are tools to help the assessor develop estimates of exposure and dose to 

assess potential health risks. An exposure scenario generally includes facts, data, assumptions, 

inferences, and sometimes professional judgment about how the exposure takes place. In 2004, 

EPA published the Example Exposure Scenarios (U.S. EPA, 2004a) using human physiological 

and behavioral data from the Exposure Factors Handbook (U.S. EPA, 1997a), which has been 

superseded by the EFH (U.S. EPA, 2011a). This document provides an update of the 2004 

Example Exposure Scenarios, focusing specifically on scenarios involving children. The 

example scenarios presented here have been selected to best demonstrate the use of the various 

key data sets in the EFH (U.S. EPA, 2011a) and to 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 to apply the same or similar data sets and approaches as shown in the examples.

Preferred citation:

U.S. Environmental Protection Agency (EPA). (2014) Child-Specific Exposure Scenarios Examples. National 

Center for Environmental Assessment, Washington, D.C.; EPA/600/R-14/217F. Available from the National 

Technical Information Service, Springfield, VA and online at http://www.epa.gov/ncea.
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CONTENTS

LIST OF TABLES.......................................................................................................................VII

LIST OF FIGURES ....................................................................................................................VIII

ABBREVIATONS AND ACRONYMS ...................................................................................... IX

PREFACE.......................................................................................................................................X

AUTHORS, CONTRIBUTORS, AND REVIEWERS ...............................................................XII

1. INTRODUCTION AND PURPOSE...........................................................................................1

PURPOSE........................................................................................................................2

RELATIONSHIP TO OTHER RELEVANT EPA REPORTS.......................................2

EXPOSURE ASSESSMENT GENERAL PRINCIPLES ...............................................2

EXPOSURE SCENARIOS..............................................................................................7

CUMULATIVE EXPOSURES .....................................................................................13

OTHER SOURCES OF INFORMATION ON EXPOSURE ASSESSMENT.............14

COMMON CONVERSION FACTORS .......................................................................16

2. EXAMPLE INGESTION SCENARIOS ...................................................................................18

PER CAPITA INGESTION OF CONTAMINATED HOMEGROWN 

EXPOSED VEGETABLES: CHILDREN AGED 1 TO <11 YEARS, IN 

GARDENING HOUSEHOLDS, CENTRAL TENDENCY, CHRONIC 

AVERAGE DAILY DOSE .........................................................................................18

2.1.1. Introduction........................................................................................................18

2.1.2. Dose Algorithm..................................................................................................19

2.1.3. Input for Exposure Factor Variables..................................................................19

2.1.4. Calculations........................................................................................................22

2.1.5. Uncertainties......................................................................................................23

INGESTION OF CONTAMINATED SOIL AND DUST IN AND AROUND 

THE HOME: YOUNG CHILDREN AGED 1 TO <6 YEARS, CENTRAL 

TENDENCY, LIFETIME AVERAGE DAILY DOSE...............................................24

2.2.1. Introduction........................................................................................................24

2.2.2. Dose Algorithm..................................................................................................25

2.2.3. Input for Exposure Factor Variables..................................................................25

2.2.4. Calculations........................................................................................................26

2.2.5. Uncertainties......................................................................................................27

INGESTION OF CONTAMINATED INDOOR DUST: CHILDREN AT 

SCHOOL AGED 6 TO <11 YEARS, CENTRAL TENDENCY, 

SUBCHRONIC AVERAGE DAILY DOSE ..............................................................28

2.3.1. Introduction........................................................................................................28

2.3.2. Dose Algorithm..................................................................................................28

2.3.3. Input for Exposure Factor Variables..................................................................29

2.3.4. Calculations........................................................................................................30

2.3.5. Uncertainties......................................................................................................30

INGESTION OF AN ENVIRONMENTAL CONTAMINANT BY 

NONDIETARY HAND-TO-MOUTH BEHAVIORS: INFANTS AND 
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TODDLERS 3 MONTHS TO <2 YEARS, BOUNDING, ACUTE DOSE 

RATE...........................................................................................................................31

2.4.1. Introduction........................................................................................................31

2.4.2. Dose Algorithm..................................................................................................32

2.4.3. Input for Exposure Factor Variables..................................................................32

2.4.4. Calculations........................................................................................................34

2.4.5. Uncertainties......................................................................................................35

EXPOSURE TIME OF INCIDENTAL INGESTION OF CONTAMINATED 

POOL WATER TO REACH A REFERENCE DOSE LEVEL OF 

EXPOSURE: CHILDREN AGED 6 TO <11 YEARS, BOUNDING ........................36

2.5.1. Introduction........................................................................................................36

2.5.2. Dose Algorithm..................................................................................................36

2.5.3. Input for Exposure Factor Variables..................................................................37

2.5.4. Calculations........................................................................................................38

2.5.5. Uncertainties......................................................................................................38

INGESTION OF CONTAMINATED DRINKING WATER: CHILDREN 

AGED <21 YEARS, DISTRIBUTION OF CHRONIC AVERAGE DAILY 

DOSE...........................................................................................................................39

2.6.1. Introduction........................................................................................................39

2.6.2. Dose Algorithm..................................................................................................39

2.6.3. Input for Exposure Factor Variables..................................................................40

2.6.4. Calculations........................................................................................................42

2.6.5. Uncertainties......................................................................................................44

INGESTION OF CONTAMINATED HUMAN MILK: INFANTS AGED 

BIRTH TO <12 MONTHS, HIGH-END, SUBCHRONIC AVERAGE 

DAILY DOSE .............................................................................................................45

2.7.1. Introduction........................................................................................................45

2.7.2. Dose Algorithm..................................................................................................45

2.7.3. Input for Exposure Factor Variables..................................................................46

2.7.4. Calculations........................................................................................................47

2.7.5. Uncertainties......................................................................................................48

INGESTION OF CONTAMINATED RECREATIONAL ATLANTIC 

MARINE FINFISH: CHILDREN AGED 3 TO <6 YEARS, CENTRAL 

TENDENCY, SUBCHRONIC AVERAGE DAILY DOSE.......................................49

2.8.1. Introduction........................................................................................................49

2.8.2. Dose Algorithm..................................................................................................49

2.8.3. Input for Exposure Factor Variables..................................................................50

2.8.4. Calculations........................................................................................................50

2.8.5. Uncertainties......................................................................................................51

3. EXAMPLE INHALATION EXPOSURE SCENARIOS..........................................................54

3.1. INHALATION OF CONTAMINATED AIR WHILE PLAYING IN A 

SCHOOL YARD: SCHOOL CHILDREN AGED 6 TO <11 YEARS, 

CENTRAL TENDENCY, SUBCHRONIC ADJUSTED AIR 

CONCENTRATION ...................................................................................................55

3.1.1. Introduction........................................................................................................55
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3.1.2. Exposure Algorithm...........................................................................................55

3.1.3. Input for Exposure Factor Variables..................................................................56

3.1.4. Calculations........................................................................................................56

3.1.5. Uncertainties......................................................................................................57

INHALATION OF AEROSOLIZED CONTAMINANTS FROM WATER 

DURING AND AFTER SHOWERING: CHILDREN AND TEENS AGED 6 

TO <18 YEARS, CENTRAL TENDENCY, LIFETIME ADJUSTED AIR 

CONCENTRATION ...................................................................................................57

3.2.1. Introduction........................................................................................................57

3.2.2. Exposure Algorithm...........................................................................................58

3.2.3. Input for Exposure Factor Variables..................................................................58

3.2.4. Calculations........................................................................................................59

3.2.5. Uncertainties......................................................................................................60

INHALATION OF CONTAMINATED INDOOR AIR: RESIDENTIAL 

CHILDREN AGED 3 TO <11 YEARS, BOUNDING, ACUTE DOSE RATE.........60

3.3.1. Introduction........................................................................................................60

3.3.2. Dose Algorithm..................................................................................................61

3.3.3. Input for Exposure Factor Variables..................................................................61

3.3.4. Calculations........................................................................................................64

3.3.5. Uncertainties......................................................................................................64

INHALATION OF CONTAMINATED AIR DURING BUS 

TRANSPORTATION: SCHOOL CHILDREN AND TEENS AGED 6 TO 

<16 YEARS, HIGH-END, CHRONIC AVERAGE DAILY DOSE ..........................64

3.4.1. Introduction........................................................................................................64

3.4.2. Dose Algorithm..................................................................................................65

3.4.3. Input for Exposure Factor Variables..................................................................65

3.4.4. Calculations........................................................................................................66

3.4.5. Uncertainties......................................................................................................67

4. EXAMPLE DERMAL EXPOSURE SCENARIOS..................................................................68

DERMAL CONTACT WITH CONTAMINATED SOIL: TEEN ATHLETES 

AGED 11 TO <16 YEARS, CENTRAL TENDENCY, SUBCHRONIC 

AVERAGE DAILY DOSE .........................................................................................68

4.1.1. Introduction........................................................................................................68

4.1.2. Dose Algorithm..................................................................................................68

4.1.3. Input for Exposure Factor Variables..................................................................69

4.1.4. Calculations........................................................................................................71

4.1.5. Uncertainties......................................................................................................71

DERMAL CONTACT WITH INORGANIC CONTAMINANTS WHILE 

WADING IN A RECREATIONAL POND: CHILDREN AGED 6 TO 

<16 YEARS, BOUNDING, ACUTE DOSE RATE ...................................................73

4.2.1. Introduction........................................................................................................73

4.2.2. Dose Algorithm..................................................................................................73

4.2.3. Input for Exposure Factor Variables..................................................................73

4.2.4. Calculations........................................................................................................76

4.2.5. Uncertainties......................................................................................................76
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DERMAL CONTACT WITH AN ORGANIC CONTAMINANT IN WATER 

WHILE SHOWERING: CHILDREN AND TEENS, AGED 6 TO 

<16 YEARS HIGH-END, LIFETIME AVERAGE DAILY DOSE ...........................77

4.3.1. Introduction........................................................................................................77

4.3.2. Dose Algorithm..................................................................................................77

4.3.3. Input for Exposure Factor Variables..................................................................78

4.3.4. Calculations........................................................................................................82

4.3.5. Uncertainties......................................................................................................82

GLOSSARY ..................................................................................................................................84

REFERENCES ..............................................................................................................................96
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LIST OF TABLES

Table 1. Exposure durations and dose metrics................................................................................9

Table 2. Child-Specific Exposure Scenarios Examples roadmap.................................................11

Table 3. Common conversion factors............................................................................................17

Table 4. Estimation of age specific per capita mean homegrown exposed vegetable intake 

rates for children in gardening households (g/kg-day) for four age ranges among 

children aged 1 to <11 years...........................................................................................21

Table 5. Summary of average daily dose of contaminant associated with consumption of 

homegrown exposed vegetables (mg/kg-day) for four age ranges among 

children in gardening households, aged 1 to <11 years..................................................22

Table 6. Consumer-only estimates of direct and indirect water ingestion: community 

water (mL/kg-day) ..........................................................................................................41

Table 7. Input values by age range for ingestion of contaminated drinking water........................42

Table 8. Average daily doses (ADD; μg/kg-day) from birth to 21 years of age for 

ingestion of contaminated drinking water.......................................................................43

Table 9. Upper-percentile lipid intake rates from human milk......................................................47

Table 10. Summary of ADD of contaminant associated with human milk for four age 

ranges among infants aged birth to <12 months.............................................................47

Table 11. Summary of ADD for children and teens aged 6 to 16 years for inhalation of 

contaminated air on bus transportation...........................................................................66

Table 12. Soil adherence factors (AFsoil) for teen athletes playing soccer.....................................71

Table 13. Summary of ADR for children aged 6 to <16 years for acute potential dose 

from dermal contact in recreational surface water while wading ...................................76

Table 14. Summary of ADD for children aged 6 to <16 years for high-end potential dose 

from dermal contact while showering.............................................................................82
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LIST OF FIGURES

Figure 1. Distribution of average daily doses (ADD) from birth to 21 years of age. ....................43
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ABBREVIATONS AND ACRONYMS

ADAF Age-dependent adjustment factors

ADD Average daily dose

ADR Acute dose rate

BW Body weight

EPA U.S. Environmental Protection Agency

HEC Human equivalent concentration

IRIS Integrated Risk Information System

IUR Inhalation Unit Risk

LADD Lifetime average daily dose

NCEA National Center for Environmental Assessment

RfC Reference concentration

RfD Reference dose
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PREFACE

The National Center for Environmental Assessment (NCEA) of EPA’s Office of 

Research and Development has prepared the Child-Specific Exposure Scenarios Examples to 

outline scenarios for various exposure pathways and to demonstrate how data from the EFH 

(U.S. EPA, 2011a) may be applied for estimating exposures for children. A similar document 

entitled Example Exposure Scenarios was published by EPA in 2004 (U.S. EPA, 2004a). The 

Child-Specific Exposure Scenarios Examples updates the children’s exposure scenarios included 

in U.S. EPA 2004a.

An exposure scenario considers the physical setting, potential uses of a contaminated 

resource (e.g., future residential land use or consumption of fish), the population that may be 

exposed (infant, child, or adolescent), fate and transport of contaminants, and how exposure may 

occur including ingestion, dermal contact, and inhalation. Consideration of frequency and 

duration of exposure as well as seasonal variations are part of the development of an exposure 

scenario. The Child-Specific Exposure Scenarios Examples is intended to be a companion 

document to the EFH. The example scenarios were compiled from questions and inquiries 

received from users of the earlier versions of the EFH on how to select data from the Handbook. 

The scenarios presented in this report promote the use of the standard set of age groups 

recommended by the EPA in the report entitled Guidance on Selecting Age Groups for 

Monitoring and Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA, 

2005a).

Each scenario examined in this report refers to a single-chemical exposure route and 

pathway. EPA recognizes that individuals may be exposed to mixtures of chemicals through 

more than one pathway and one route. In the past few years there has been an increased 

emphasis in cumulative risk assessments1, aggregate exposures2, and chemical mixtures 

(U.S. EPA, 2008a, 2003). 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 

 

1Cumulative risk assessment―An analysis, characterization, and possible quantification of the combined risks to 

health or the environment from multiple agents or stressors.

2Aggregate exposures―The combined exposure of an individual (or defined population) to a specific agent or 

stressor via relevant routes, pathways, and sources.
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risks. This basic structure is presented in the Framework for Cumulative Risk Assessment

published in May 2003 (U.S. EPA, 2003). Additional guidance is available from EPA’s 

Concepts, Methods and Data Sources for Cumulative Health Risk Assessment of Multiple 

Chemicals, Exposures and Effects: A Resource Document (U.S. EPA, 2007a). EPA encourages 

and supports the use of new and innovative approaches and tools to improve the quality of public 

health and environmental protection.

In general, the Child-Specific Exposure Scenarios Examples document provides examples 

using the point-estimate approach, but also includes an example of a simple probabilistic 

assessment for one scenario. In contrast to the point-estimate approach, probabilistic methods 

allow for a better characterization of variability and/or uncertainty in risk estimates. The use of 

probabilistic methods is contingent on the availability and quality of the data. Additional 

information on characterization of variability and uncertainty can be found in Chapter 2 of the 

EFH (U.S. EPA, 2011a).
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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 Battelle under EPA contract No. EP09H001685. Jacqueline Moya served as a Work

Assignment Manager, providing overall direction, technical assistance, and contributing author.

AUTHORS AND CONTRIBUTORS

U.S. EPA

Jacqueline Moya

Linda Phillips

John Schaum, retired

Laurie Schuda

Battelle

Ann Gregg

Marcia Nishioka

Technical Editing

Vicki Soto, U.S. EPA

REVIEWERS

The following EPA individuals reviewed an earlier draft of this document and provided valuable 

comments:

Heidi Bethel, OW

Iris Camacho, OW detail

Becky Cuthbertson, OSWER

Lynn Delpire, OPPT 

Peter Egeghy, ORD/NERL

Michael Firestone, OCHP

Ann Johnson, ORPM

Youngmoo Kim, Region 3

Geneice Lehmann, ORD/NCEA-RTP

Eva McLanahan, ORD/NCEA-RTP

Margaret McDonough, retired, Region 1

David Miller, OPP

Marian Olsen, Region 2

Haluk Özkaynak, ORD/NERL

Yvette Selby-Mohamadu, OPPT

Nicolle Tulve, ORD/NERL

Dana Vogel, OPP
xiii

AUTHORS, CONTRIBUTORS, AND REVIEWERS (continued)

This document was reviewed by an external panel of experts. The panel was composed of the 

following individuals:

Dr. David O. Carpenter, Director, Institute for Health and the Environment University at Albany

Dr. Alesia Ferguson, University of Arkansas for Medical Science

Dr. Annette Guiseppi-Elie, Principal Consultant, Risk Assessment DuPont Engineering

Dr. P. Barry Ryan, Emory University Atlanta, Georgia

Dr. Alan H. Stern, University of Medicine and Dentistry of New Jersey
1

1. INTRODUCTION AND PURPOSE

Children’s environmental exposures to contaminants can change significantly as they 

develop through infancy, childhood, and adolescence. These exposure differences are a result of 

both behavioral and rapid physiological changes as they grow. Children, therefore, may be 

physiologically susceptible to some environmental contaminants during certain life stages. 

Greater susceptibility due to greater exposure can lead to greater risk of adverse health effects for 

children relative to adults exposed to the same contaminants.

Since 1995, the U.S. Environmental Protection Agency (EPA) has specified that children 

must be explicitly considered when conducting risk assessments as part of a public health 

decision-making process. Subsequently, the Supplemental Guidance for Assessing Susceptibility 

from Early-Life Exposure to Carcinogens (U.S. EPA, 2005b) stressed the importance of 

considering life stage differences in both exposure and dose-response when assessing cancer 

risks from early life exposures. The guidance promotes the summing of doses or risks across all 

relevant life stages instead of averaging an age-specific dose over the entire lifetime. For 

carcinogens acting via a mutagenic mode of action, age-dependent adjustment factors (ADAFs) 

are used to account for susceptibility at various life stages (U.S. EPA, 2005b).

In 2002, EPA published the interim final version of the Child-Specific Exposure Factors 

Handbook, which was designed specifically to address the exposure factors related to children

(U.S. EPA, 2008a). In 2008, the Child-Specific Exposure Factors Handbook was republished 

(U.S. EPA, 2008a), incorporating information from the Guidance on Selecting Age Groups for 

Monitoring and Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA, 

2005a). The 2008 version of the Child-Specific Exposure Factors Handbook rearranged the data 

and recommendations, to the extent possible, to be consistent with the standard set of childhood 

age groups provided in the 2005 guidance. The Exposure Factors Handbook published in 2011 

retained the same age groupings for children. These childhood age groups are as follows:

 Less than 12-months old: birth to <1 month, 1 to <3 months, 3 to <6 months, and 6 to 

<12 months

 Greater than 12-months old: 1 to <2 years, 2 to <3 years, 3 to <6 years, 6 to <11 years, 

11 to <16 years, and 16 to <21 years
2

PURPOSE

The purpose of the Child-Specific Exposure Scenarios Examples is to present childhood 

exposure scenarios using data from the Child-Specific Exposure Factors Handbook and updated 

children’s data from the Exposure Factors Handbook (U.S. EPA, 2011a, 2008a; referred to 

throughout as EFH). These scenarios are not meant to be inclusive of every possibility, but they 

are intended to provide a range of scenarios that show how to apply exposure factors data to 

characterize childhood exposures. As such, these scenarios are not meant as templates for 

exposure assessors, but can be modified to meet specific needs. 

RELATIONSHIP TO OTHER RELEVANT EPA REPORTS

In 2011, EPA published the EFH, which supersedes the Child-Specific Exposure Factors 

Handbook and previous versions of the EFH (U.S. EPA, 2011a, 2008). The Child-Specific 

Exposure Scenarios Examples supersedes the children’s exposure scenarios included in U.S.

EPA 2004a.

EXPOSURE ASSESSMENT GENERAL PRINCIPLES

Exposure assessment is a “process of estimating or measuring the magnitude, frequency, 

and duration of exposure to an agent, along with the number and characteristics of the population 

exposed” (Zartarian et al., 2007a). Exposure assessments are conducted for a variety of purposes 

including risk assessments, trend analyses, and epidemiological studies (U.S. EPA, 1992a). In 

the risk assessment context, the output of an exposure assessment is typically the estimation of 

the potential dose (U.S. EPA, 1992a). The potential dose is dependent on the concentration of 

the contaminant in a medium (e.g., soil, water, air) and the intake or contact rate of the 

population with the medium. This potential dose can be adjusted to include additional factors 

that further characterize the population being assessed and describe the exposure in terms of 

exposure duration and frequency.

The terms exposure and dose are closely related. Exposure is defined as the “contact of 

an organism with a chemical or physical agent, quantified as the amount of chemical available at 

the exchange boundaries of the organism and available for absorption” (IPCS, 2001). The dose 

refers to the amount of agent (e.g., chemical) that enters a target in a specified period of time 

after crossing a contact boundary. The units of dose are typically mg/kg-day. The example 
3

scenarios provided in this report focus on the calculation of dose and not exposure. Often times, 

dose is calculated and combined with toxicity information to calculate risk. However, 

calculations of risk are outside the scope of this document. The principal focus of this document 

is on childhood doses from exposure to chemicals, but the concepts may apply to other agents.

Exposure can occur via ingestion, inhalation, or direct contact (i.e., dermal). Chemicals 

can be introduced into the gastrointestinal tract through dietary ingestion of foods and beverages 

or nondietary ingestion of foreign substances (e.g., soil). The outer contact boundary for 

ingestion exposures is the mouth. A chemical can enter the respiratory tract through the 

inhalation of particles, gases, vapors, and aerosols. For inhalation exposure, the outer contact 

boundary is the oral/nasal boundary. The characteristics of the inhaled agent affect its 

deposition, retention, translocation, and distribution within the respiratory system and other 

tissues in the body (U.S. EPA, 1994). Dermal absorption is governed by the characteristics of 

the skin (contact boundary) on the exposed part of the body, and the characteristics of the agent 

(e.g., physical-chemical properties) and the matrix in which it exists (e.g., water, soil); 

environmental conditions (e.g., temperature and humidity) can also play a role. The example 

scenarios presented in this document are organized according to these three routes of exposure 

(i.e., ingestion, inhalation, and dermal contact).

The population of interest in an exposure assessment, also known as the receptor 

population, may include children at various life stages to account for their rapidly changing 

physiology and behavior. In addition, the exposure assessment can evaluate only the population 

that is potentially exposed (i.e., “doers-only,” “consumers-only”) or it can assess the exposure 

over the entire population on a per capita basis. If one could sample everyone in the population, 

the “doers-only” or “consumers-only” will be those individuals who engage in the specific 

activity of interest. “Per capita” will be everyone in the population. Since not everyone in the 

population can be studied, in this report, “doers only” refers to only those individuals who 

reported doing the activity during the survey period. “Consumers-only” refers to only those 

individuals who reported food or water intake during the survey period. “Doers-only” or 

“consumers-only” contact rates are calculated by averaging activity rates or food or water intake

rates across only the individuals in the survey who engaged in those activities or consumed those 

foods or beverages. Conversely, “per capita” contact rates are generated by averaging 
4

consumer-only rates over the entire population, including those individuals that reported no 

activity or intake during the survey period. Generally, “per capita” contact rates are appropriate 

for use in exposure assessments for which average dose estimates are of interest. They are also 

useful for comparisons with other population groups. For example, for foods, they represent 

both individuals who ate the foods during the survey period and individuals who may eat the 

food items at some time, but did not consume them during the survey period. Per capita intake 

may underestimate consumption for the subset of the population that consumed the food in 

question (U.S. EPA, 2011a).

The equation used to express dose is based on the intensity, duration, and frequency of 

the exposure to the receptor population. The intensity typically is expressed as the concentration 

of the contaminant per unit mass or volume (i.e., μg/g, μg/L, mg/m3, ppm, etc.) in the medium

multiplied by the contact rate (e.g., intake rate, inhalation rate). In the following examples, the 

concentration of a contaminant “x” is used as a generic term. Except for the concentration, the 

terms used in the dose equation are referred to as exposure factors. Exposure factors are factors 

related to human behavior and characteristics that help determine an individual's exposure to an 

agent. The concentration is based on site- and chemical-specific data that are not provided in the 

EFH. 

Each of the main exposure routes has a range of exposure descriptors that explains the 

distribution of exposures occurring in the exposed population. The central tendency scenario is 

developed using means or 50th percentiles for contaminant concentration and exposure factors or 

by selecting the mean or median from the dose distribution. A high-end exposure scenario 

typically represents an individual in the upper end of the exposure distribution (i.e., over the 

90th percentile, but less than the most exposed individual [U.S. EPA, 1992a]). High-end 

scenarios are developed using a combination of central and upper estimates for the contaminant 

concentration and/or exposure factors or by selecting an upper-percentile from the dose 

distribution. The choice of the parameters the assessor sets at a central tendency value versus an 

upper-percentile depends on judgement, the sensitivity of the parameters, and regulatory 

requirements. 

A bounding scenario is defined as an exposure higher than any expected to occur in the 

actual population (U.S. EPA, 1992a). A theoretical upper bound is estimated by assuming limits 
5

for all the variables used to calculate exposure and dose that, when combined, will result in the 

mathematically highest exposure or dose (highest concentration, highest intake rate, lowest body 

weight [BW]) (U.S. EPA, 1992a). However, it is generally not necessary to use the theoretical 

upper bound to assure that the exposure or dose calculated is above the actual distribution 

(U.S. EPA, 1992a). Thus, bounding estimates in the examples included in this report are 

estimated using upper-percentile estimates for most of the dose equation, but keeping some 

variables at the mean value (i.e., BW, surface area). An upper-percentile estimate of an exposure 

factor is defined as a value between the 90th and the 99.9th percentile in the exposure factor 

distribution (U.S. EPA, 2011a). In the EFH, the 95th percentile, if available, was used to 

represent the upper-percentile in the recommendations because it is the middle of the range 

between the 90th and 99.9th percentiles. For some factors, a specific upper-percentile could not 

be defined because the data were not available.

Another aspect of exposure assessment is the duration and the frequency over which the 

exposure occurred. An acute exposure is a one-time exposure to a contaminant by the oral, 

dermal, or inhalation route for 24 hours or less. Chronic exposure is defined as a repeated 

exposure by the oral, dermal, or inhalation route for more than approximately 10% of the life 

span in humans (more than approximately 90 days to 2 years in typically used laboratory animal 

species). A subchronic exposure is defined as a repeated exposure by the oral, dermal, or 

inhalation route for more than 30 days, up to approximately 10% of the life span in humans 

(U.S. EPA, 2011b).

The potential dose may be calculated as a potential average daily dose (ADD), lifetime 

average daily dose (LADD), or the acute dose rate (ADR). The ADD, calculated for a 

noncarcinogenic contaminant exposure, is a dose averaged over a specified timeframe. The 

general equation used for ADD is presented below (see eq 1). Equations used to calculate a 

dermal dose include some additional terms (e.g., surface area, dermal permeability coefficient) 

and are presented in Section 4. Historically, the LADD is calculated for contaminant exposure 

that is expressed over an adult lifetime (e.g., 70 years). LADD is generally used when assessing 

exposure to carcinogens. However, consistent with the Supplemental Guidance for Assessing 

Susceptibility from Early-Life Exposure to Carcinogens, if exposure is less than lifetime, the 

dose is calculated by summing time weighted doses that occur during each life stage and 
6

averaging across the total exposure period (U.S. EPA, 2005b). It is important to note that the 

average life expectancy has increased to an average of 78 years for males and females combined, 

as stated in the EFH (U.S. EPA, 2011a). The increase in life expectancy in humans is largely 

attributed to decreases in nonmalignant disease mortality, with little change in malignant disease 

mortality. The use of 70 years has been a policy decision due to the fact that there is no evidence 

to suggest that cancer risk per year of exposure has changed simply due to increased life 

expectancy. Dividing the LADD over a period of 78 years instead of 70 years will have the

effect of lowering the cancer risk by approximately 10%. Although this is not a significant 

difference, for consistency, an average lifetime of 70 years is used as a reference value when 

calculating the LADD. For noncarcinogenic acute exposures, the ADR is used. To calculate the 

ADR, the exposure frequency, exposure duration, and averaging time are all set equal to 1 to 

adjust the calculation for a one-time exposure.

ADD =

C × CR × EF × ED

BW × AT

(1)

where:

ADD = potential average daily dose of the contaminant of interest (mg/kg-d);

C = concentration of the contaminant within the media of interest (mg/g; 

mg/L; mg/cm2; mg/m3);

CR = average daily contact rate of the media of interest (g/d; L/d; cm2/d; 

m3/d);

EF = exposure frequency (d/yr);

ED = exposure duration (yr);

BW = body weight (kg); and

AT = averaging time (d).

Note that, in some cases, contact rate may be expressed in units of less than a day (e.g.,

L/hr). When this occurs, an additional term (e.g., exposure time) may be included to account for 

the portion of a day spent engaging in the activity of interest (e.g., hours/day). Also, for some 

exposure pathways, contact rates are expressed as intake rates. In some cases, the contact rate is 

provided on a body-weight (BW) basis (e.g., g/kg-day or L/kg-day); therefore, BW is not needed 

in the denominator of the dose equation. Also note that other algorithms or approaches may be 
7

used to calculate dose depending on available data, software capabilities, regulatory goals, and

statutory requirements. EPA program offices may also have guidances specific to their 

programs. In addition, the assessor may need to consider the bioavailability of the contaminant in 

the specific medium. The bioavailability will vary depending on the physicochemical 

characteristics of the contaminant and the characteristics of the medium (e.g., particle size in 

soil).

In the risk assessment context, the dose calculations are often combined with toxicity

information to estimate risk. Exposure assessors are encouraged to consult with toxicologists 

regarding the appropriate application of toxicity values with the exposure assessment. For 

example, it may not be appropriate to use toxicity values derived to reflect chronic exposures 

(e.g., Reference Dose, cancer slope factors) when characterizing acute or subchronic exposures. 

In addition, when assessing cancer risk from exposures to mutagenic carcinogens, the assessor 

needs to consider the ADAFs to account for early life sensitivities. The reader is referred to the 

Supplemental Guidance for Assessing Susceptibility from Early-Life Exposure to Carcinogens

for further information about ADAFs and their application (U.S. EPA, 2005b).

The EPA uses inhalation dosimetry methodology for estimating exposure through the 

inhalation pathway because the amount of chemical that reaches the target organ is not a simple 

function of the inhalation rate and BW (U.S. EPA, 2009). In contrast with the ingestion pathway, 

the inhalation dosimetry methodology only requires a derivation of a time weighted average 

concentration adjusted for the duration and frequency of exposure (U.S. EPA, 2009). To 

estimate risk, the adjusted concentration is then compared with a Reference Concentration (RfC) 

or an Inhalation Unit Risk (IUR), which are expressed in units of concentration and the inverse 

of concentration, respectively. There may be cases in which an inhalation dose is of interest

(e.g., the estimation of aggregate and cumulative doses; an analysis of relative pathway 

contribution).

EXPOSURE SCENARIOS

This document is intended to present example exposure scenarios that reflect the possible 

ways that data reported in the EFH (U.S. EPA, 2011a) may be used in childhood exposure 

assessments and risk assessments. The scenarios are representative of generic applications and 

should be tailored to specific program needs and the population and life stages of interest. As 
8

such, they are not intended to supplant specific guidance issued by EPA program offices. In 

developing risk assessments under specific EPA programs, the risk assessor should consult 

specific programmatic guidance and requirements. The selection of life stages used in each 

scenario is not meant to imply that those are the only life stages for which the scenario could 

apply.

This report shows multiple examples for each of the main exposure routes (ingestion, 

inhalation, and dermal penetration), a range of exposure descriptors (e.g., central tendency, 

high-end, or bounding exposure), exposure durations (i.e., acute, subchronic, or chronic), and 

receptor populations (e.g., single or multiple age ranges, only participants in an activity called 

“doers-only,” “consumers-only,” and per capita population). For demonstration purposes, only 

one exposure descriptor was chosen for each exposure scenario. This is not meant to imply that 

only those chosen descriptors will be of interest for that particular scenario. Throughout the 

report, high-end scenarios are constructed using a combination of central tendency estimates and 

high-end estimates for the various parameters of the dose equation. The intent of the report is 

not to provide prescriptive guidance on how to estimate a high-end dose, since subjective 

judgement is required. 

Specific scenarios were selected based on inquiries received from users of the past 

version of the EFH. These are scenarios that exposure and risk assessors may frequently 

encounter. For example, food intake scenarios were selected to illustrate the use of per capita 

versus consumer-only data. Fish consumption was of particular interest because of the 

associations between contaminants that may be found in fish and children’s susceptibility to 

these chemicals. Human milk intake and nondietary exposures are pathways that are unique to 

children. Likewise, the inhalation and dermal scenarios were selected based on locations where 

children spend their time and activities in which they are engaged (e.g., schools, indoor 

environments, outdoor activities). Exposure durations and the corresponding dose metrics are 

presented in Table 1.
9

Table 1. Exposure durations and dose metrics

Exposure type Exposure duration Dose metric

Acute ≤24 hours ADR

Subchronic >30 days <10% life span in humans ADDsubchronic

Chronic >10% life span in humans ADDchronic

Lifetime Life span LADD

The example scenarios are presented according to exposure route. Each scenario 

assumes that the concentration of the chemical in the specific medium is known, either measured 

or modeled. Mean values for the exposure concentration are used throughout the report when 

calculating central tendency dose estimates. It should be noted that some exposure assessors use 

the upper confidence limit of the mean for a more conservative estimate. Since the concentration 

values are assumed to be known, this report does not address fate and transport considerations 

for the estimation of the concentration term. In addition, the scenarios do not address exposures 

via multiple routes. This is not meant to imply that exposures from other routes are negligible 

for a particular scenario. For example, exposure to contaminated homegrown vegetables implies 

contaminated soils, which may also result in exposures via the nondietary pathway. In addition, 

the scenarios described do not include potential exposures that may be experienced by the 

parents, care givers, or other workers present in the same microenvironments. Each example 

provides an introduction describing the scenario, the algorithm used for estimating dose, the 

suggested input values of exposure factors with the calculation of the estimated dose, and the 

uncertainties and limitations of the data and/or approach used in the example. Exposure factors 

input values were derived from the recommendations published in the EFH (U.S. EPA, 2011a). 

Table 2 provides a summary of the example exposure scenarios presented in this 

document. The outcome for most of the scenarios included in this document is a point estimate 

for the described scenario. However, one scenario (2.6―Ingestion of Contaminated Drinking 

Water: Children <21 Years, Distribution of Chronic Daily Exposure) presents a simple example 

of the use of a probabilistic approach for estimating dose. Toxicity values needed to calculate 

risk from each exposure scenario described in Table 2 should match the exposure duration of 

interest (i.e., acute, subchronic, chronic). The exposure duration should also match the health 
10

end point of interest (i.e., carcinogens and noncarcinogens). For additional information on 

exposure assessment, refer to Chapter 1 of the EFH (U.S. EPA, 2011a).
11

Table 2. Child-Specific Exposure Scenarios Examples roadmap

# Scenario Title

Exposure 

media

Receptor 

population

Exposure 

distribution

Calculated 

dose or 

concentration

Age range

(yr, unless

stated otherwise)

Ingestion scenarios

2.1 Per Capita Ingestion of Contaminated Homegrown

Exposed Vegetables: Children Aged 1 to <11 Years, in 

Gardening Households, Central Tendency, Chronic

Average Daily Dose

Homegrown

exposed

vegetables

Children, 

per capita

Central 

Tendency

ADD, 

chronic

1 to <11

2.2 Ingestion of Contaminated Soil and Dust in and Around 

the Home: Young Children Aged 1 to <6 Years, Central 

Tendency, Lifetime Average Daily Dose

Soil and dust Young children Central 

tendency

LADDa, 

chronic

1 to <6

2.3 Ingestion of Contaminated Indoor Dust: Children at 

School Aged 6 to <11 Years, Central Tendency, 

Subchronic Average Daily Dose

Indoor dust School children Central 

tendency

ADD, 

subchronic

6 to <11

2.4 Ingestion of an Environmental Contaminant by 

Nondietary Hand-to-mouth Behaviors: Infants and 

Toddlers 3 Months to <2 Years, Bounding, Acute Dose 

Rate

Nondietary 

hand-to-mouth 

activity

Infants and 

toddlers

Bounding ADR, 

acute

3 mo to <2 yr

2.5 Exposure Time of Incidental Ingestion of Contaminated 

Pool Water to Reach a Reference Dose (RfD) Level of 

Exposure: Children Aged 6 to <11 Years, Bounding 

Pool water Children, 

doers-only 

Bounding RfD used to 

calculate ET

6 to <11

2.6 Ingestion of Contaminated Drinking Water: Children 

Aged <21 Years, Distribution of Chronic Average Daily 

Dose

Drinking water Children, 

consumers-only

Distribution ADD, 

chronic

Birth to 

<21 yr

2.7 Ingestion of Contaminated Human Milk: Infants Aged 

Birth to <12 Months, High-end, Subchronic Average 

Daily Dose

Human milk Infants, 

consumers-only

High-end ADD, 

subchronic

Birth to 

<12 mo

2.8 Ingestion of Contaminated Recreational Atlantic 

Marine Finfish: Children Aged 3 to <6 Years, Central 

Tendency, Subchronic Average Daily Dose

Recreational 

Marine fish

Children, 

consumers-only

Central 

tendency

ADD, 

subchronic

3 to <6
12

Table 2. Child-specific Exposure Scenarios Examples roadmap (continued)

# Scenario Title 

Exposure 

media

Receptor 

population

Exposure 

distribution

Calculated 

dose

Age range

(years, unless

stated otherwise)

Inhalation scenarios

3.1 Inhalation of Contaminated Air while Playing in a 

School Yard: School Children Aged 6 to <11 Years, 

Central Tendency, Subchronic Adjusted Air 

Concentration

Outdoor air School 

children, 

doers-only

Central

tendency

C air adjusted,

subchronic

6 to <11

3.2 Inhalation of Aerosolized Contaminants from Water 

During and After Showering: Children and Teens Aged

6 to <18 Years, Chronic Central Tendency, Lifetime 

Adjusted Air Concentration

Aerosolized 

water

Children and 

teens, 

doers-only

Central 

tendency

C air adjusteda,

chronic

6 to <16

3.3 Inhalation of Contaminated Indoor Air: Residential 

Children Aged 3 to <11 Years, Bounding, Acute Dose 

Rate

Indoor air Residential 

children, 

doers-only

Bounding ADR 3 to <11

3.4 Inhalation of Contaminated Air During Bus 

Transportation: School Children and Teens Aged 6 to 

<16 Years, High-end, Chronic Average Daily Dose

Air on bus 

transportation

Children and 

teens, 

doers-only

High-end ADD, 

chronic

6 to <16

Dermal scenarios

4.1 Dermal Contract with Contaminated Soil: Teen 

Athletes Aged 11 to <16 Years, Central Tendency, 

Subchronic Average Daily Dose

Outdoor soil Teen athletes, 

doers-only

Central 

tendency

ADD, 

subchronic

11 to <16

4.2 Dermal Contact with an Inorganic Contaminant while 

Wading in a Recreational Pond: Children Aged 6 to 

<16 Years, Bounding, Acute Dose Rate

Recreational 

water

Children, 

doers-only

Bounding ADR 6 to <16

4.3 Dermal Contact with an Organic Contaminant in Water 

While Showering: Children and Teens Aged 6 to 

<16 Years, High-end, Lifetime Average Daily Dose

Potable water Children and 

teens, 

doers-only

High-end LADDa 6 to <16

aThese scenarios assess exposure to a carcinogen; thus, the exposure is averaged over a lifetime value.
13

CUMULATIVE EXPOSURES

This report provides childhood exposure scenario examples, each relating to one route of 

exposure and one chemical. EPA recognizes that childhood exposure can occur from multiple 

routes and to one or multiple stressors. The Framework for Cumulative Risk Assessment (U.S. 

EPA, 2003) provides a simple and flexible structure for conducting and evaluating cumulative 

risk assessment. EPA (2003) defines cumulative risk as “the combined risks from aggregate 

exposures to multiple agents or stressors.” Agents or stressors are defined in a broader sense to 

include chemicals, as well as biological or physical agents (e.g., noise, nutritional status), or the 

change or loss of a necessity such as habitat. 

Considerations regarding the cumulative evaluation of chemical stressors are discussed in 

EPA’s report entitled A Framework for Assessing Health Risks of Environmental Exposures to 

Children (U.S. EPA, 2006). The first step in quantifying exposure for a cumulative risk 

assessment is the characterization of the population and study area so that all existing and future 

pathways can be identified (U.S. EPA, 2007a). It is particularly important when assessing 

childhood exposures to identify the relevant and unique exposure factors that may be used to 

adjust the exposure estimate based on differential exposures (U.S. EPA, 2007a). The next step is 

to group the chemicals of concern according to the timing, medium, or exposure pathway 

(U.S. EPA, 2007a). This step typically requires the exposure analyst to consult with 

toxicologists to determine the types of chemical exposures that could be associated with a 

particular end point. Information about the potential chemicals’ co-occurrence in each 

compartment/medium and their potential interactions affecting transformation, fate, and transport 

are also useful (U.S. EPA, 2007a). 

Concepts, methods, and data sources for cumulative health risk assessment are described 

in more detailed in EPA’s report entitled Concepts, Methods, and Data Sources for Cumulative 

Health Risk Assessment of Multiple Chemicals, Exposures and Effects: A Resource Document

(U.S. EPA, 2007a). Cumulative exposure assessments can be complex and may require the use 

of models. Modeling tools have been developed that facilitate the evaluation of cumulative 

exposures (e.g., U.S. EPA Stochastic Human Exposure and Dose Simulation Model for 

Multimedia, Multipathway Chemicals (SHEDS-Multimedia); 

http://www.epa.gov/heasd/products/sheds_multimedia/sheds_mm.html) (U.S. EPA 2008b; 

Zartarian et al., 2007b).
14

OTHER SOURCES OF INFORMATION ON EXPOSURE ASSESSMENT 

For additional information on exposure assessment resources, the reader is encouraged to 

refer to EPA-Expo-Box (a toolbox for exposure assessors) (available at

http://www.epa.gov/risk/expobox/). Links to the following EPA resources included in EPAExpo-Box may be useful:

 Methods for Assessing Exposure to Chemical Substances, Volumes 1–13 (U.S. EPA, 

1983-1989); 

 Pesticide Assessment Guidelines, Subdivisions K and U (U.S. EPA, 1984, 1986a); 

 Standard Scenarios for Estimating Exposure to Chemical Substances During Use of 

Consumer Products (U.S. EPA, 1986b); 

 Selection Criteria for Mathematical Models Used in Exposure Assessments: Surface 

Water Models (U.S. EPA, 1987); 

 Selection Criteria for Mathematical Models Used in Exposure Assessments: Groundwater 

Models (U.S. EPA, 1988a); 

 Superfund Exposure Assessment Manual (U.S. EPA, 1988b); 

 Risk Assessment Guidance for Superfund, Volume I, Part A, Human Health Evaluation 

Manual (U.S. EPA, 1989); 

 Methodology for Assessing Health Risks Associated with Indirect Exposure to 

Combustor Emissions (U.S. EPA, 1990); 

 Risk Assessment Guidance for Superfund, Volume I, Part B, Development of Preliminary 

Remediation Goals (U.S. EPA, 1991a); 

 Risk Assessment Guidance for Superfund, Volume I, Part C, Risk Evaluation of 

Remedial Alternatives (U.S. EPA, 1991b); 

 Guidelines for Exposure Assessment (U.S. EPA, 1992a); 

 Dermal Exposure Assessment: Principles and Applications (U.S. EPA, 1992b); 

 Soil Screening Guidance (U.S. EPA, 1996a); 
15

 Occupational and Residential Exposure Test Guidelines: OPPTS 875.1000 Background 

for Application Exposure Monitoring Test Guidelines. Group A (U.S. EPA, 1996b); 

 Occupational and Residential Exposure Test Guidelines: OPPTS 875.2000 Background 

for Postapplication Exposure Monitoring Test Guidelines. Group B. (U.S. EPA, 1996c); 

 Guiding Principles for Monte Carlo Analysis (U.S. EPA, 1997b); 

 Policy for Use of Probabilistic Analysis in Risk Assessment at the U.S. Environmental 

Protection Agency (U.S. EPA, 1997c); 

 Sociodemographic Data Used for Identifying Potentially Highly Exposed Populations 

(U.S. EPA, 1999a); 

 Report of the Workshop on Selecting Input Distributions for Probabilistic Assessments

U.S. EPA, 1999b); 

 Options for Development of Parametric Probability Distributions for Exposure Factors 

(U.S. EPA, 2000a); 

 Revised Methodology for Deriving Health-Based Ambient Water Quality Criteria (U.S. 

EPA, 2000b);

 Risk Assessment Guidance for Superfund, Volume I, Part D, Standardized Planning, 

Reporting, and Review of Superfund Risk Assessments (U.S. EPA, 2001a); 

 Risk Assessment Guidance for Superfund Volume III, Part A, Process for Conducting 

Probabilistic Risk Assessments (U.S. EPA, 2001b);

 Framework for Cumulative Risk Assessment (U.S. EPA, 2003b); 

 Risk Assessment Guidance for Superfund, Volume I, Part E, Supplemental Guidance for 

Dermal Risk Assessment (U.S. EPA, 2004b); 

 Guidance on Selecting Age Groups for Monitoring and Assessing Childhood Exposures 

to Environmental Contaminants (U.S. EPA, 2005a); 

 Supplemental Guidance for Assessing Susceptibility from Early-Life Exposure to 

Carcinogens (U.S. EPA, 2005b); 

 Cancer Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005c); 
16

 Human Health Risk Assessment Protocol for Hazardous Waste Combustion Facilities 

(U.S. EPA, 2005d); 

 A Framework for Assessing Health Risk of Environmental Exposures to Children from 

Environmental Exposures (U.S. EPA, 2006); 

 Concepts, Methods, and Data Sources For Cumulative Health Risk Assessment of 

Multiple Chemicals, Exposures and Effects: A Resource Document (U.S. EPA, 2007a);

 Dermal Exposure Assessment: A Summary of EPA Approaches (U.S. EPA, 2007b); 

 Child-Specific Exposure Factors Handbook (U.S. EPA, 2008a); 

 Stochastic Human Exposure and Dose Simulation Model for Multimedia, Multipathway 

Chemicals (SHEDS-Multimedia) Dietary Model. Details of SHEDS-Multimedia Version 

3: Technical Manual (U.S. EPA, 2008);

 Risk Assessment Guidance for Superfund Volume I: Human Health Evaluation Manual 

Part F, Supplemental Guidance for Inhalation Risk Assessment (U.S. EPA, 2009); 

 Exposure Factors Handbook: 2011 Edition (U.S. EPA 2011a); 

 Highlights of the Exposure Factors Handbook (U.S. EPA 2011c); 

 Recommended Use of Body Weight3/4 (BW3/4) as the Default Method in Derivation of the 

Oral Reference Dose (U.S. EPA, 2011d);

 Standard Operating Procedures for Assessing Residential Pesticide Exposure Assessment 

(U.S. EPA, 2012a); and

 The Stochastic Human Exposure and Dose Simulation Model for Multimedia, 

Multipathway Chemicals (SHEDS-Multimedia): Dietary Module. SHEDS-Dietary 

version 1. Technical Manual. (U.S. EPA, 2012b).

COMMON CONVERSION FACTORS 

Frequently, exposure assessments require the use of volume, mass or area 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 3 provides a list of 

common conversion factors that may be required in the exposure equations. 
17

Table 3. Common conversion factors

To Convert Multiply To Obtain

Volume

cubic centimeters (cm3) 0.000001 cubic meters (m3)

cubic centimeters (cm3) 0.001 liters (L)

cubic meters (m3) 1,000,000 cubic centimeters (cm3)

gallons (gal) 3.785 liters (L) 

liters (L) 0.264 gallons (gal) 

liters (L) (water) 1,000 grams (g) (water) 

liters (L) 1,000 milliliters (mL) 

liters (L) 1,000 cubic centimeters (cm3) 

milliliters (mL) 0.001 liters (L) 

milliliters (mL) (water) 1 grams (g) (water) 

 Mass

grams (g) 0.0022 pound (lb) 

grams (g) (water) 1 milliliters (mL) (water) 

grams (g) (water) 0.001 liters (L) (water) 

grams (g) 1,000 milligrams (mg) 

grams (g) 0.001 kilograms (kg) 

kilograms (kg) 1,000 grams (g) 

micrograms (μg) 0.001 milligrams (mg) 

milligrams (mg) 0.001 grams (g) 

milligrams (mg) 1,000 micrograms (μg) 

pounds (lb) 454 grams (g) 

Area

square centimeters (cm2) 0.0001 square meters (m2) 

square meters (m2) 10,000 square centimeters (cm2) 
18

2. EXAMPLE INGESTION SCENARIOS

PER CAPITA INGESTION OF CONTAMINATED HOMEGROWN EXPOSED 

VEGETABLES: CHILDREN AGED 1 TO <11 YEARS, IN GARDENING 

HOUSEHOLDS, CENTRAL TENDENCY, CHRONIC AVERAGE DAILY DOSE

2.1.1. Introduction

At sites with soil or water contamination, or where deposition of atmospheric 

contaminants has been observed or is expected based on modeling, the potential exists for locally 

grown exposed vegetables to become contaminated. Exposed vegetables are those that are grown 

above ground and do not have outer protective coatings that are removed before consumption.

Thus, chronic exposure to these contaminants may exist among children who ingest exposed 

vegetables grown in gardens in the contaminated area. The dose via intake of contaminated 

exposed vegetables is a function of the concentrations of the contaminants in the vegetables, the 

rate at which children consume the food, and the frequency and duration of exposure.

This example assumes exposure via contaminated homegrown exposed vegetables. The 

example calculates the central tendency average daily dose from the ingestion of homegrown 

exposed vegetables for consumers consisting of children aged 1 to <11 years. This example uses 

intake data for four age ranges (1 to <2 years, 2 to <3 years, 3 to <6 years, and 6 to <11 years) 

derived from the EFH (U.S. EPA, 2011a). Values obtained from tables within the EFH (U.S. 

EPA, 2011a) are cited as EFH Table X-X. The mean consumer-only homegrown exposed 

vegetable intake rate, based on the population that gardens, from Table EFH 13-60 is converted 

to a mean per capita rate. This value is the per capita mean for the entire survey population that 

gardens (i.e., all ages combined). It is used with age-specific per capita intake data for all 

exposed vegetables (i.e., not just homegrown exposed vegetables, and not just gardening 

households) from EFH Table 9-20 to develop age-specific mean per capita intake rates for 

homegrown exposed vegetables in gardening households for the four age groups of children 

between the ages of 1 and <11 years. The information on homegrown intake originates from 

analyses performed by EPA on data from the 1987−1988 Nationwide Food Consumption 

Survey, which currently is the best source of data available to EPA on consumption of 

home-produced food. This example assumes that the quantity of homegrown exposed vegetables 

produced in the garden is sufficient to support intake at this rate. The intake rates used in this 

example represent per capita intake rates for households that participate in home gardening. In 
19

addition, the intake rates are adjusted to account for losses during food preparation, as described 

in U.S. EPA (2011a).

This scenario assumes that the children live within the contaminated area over the 

duration of the exposure (and thus are continually exposed from 1 to <11 years of age) and that 

they eat homegrown exposed vegetables throughout each year. It is also assumed that all of the 

homegrown exposed vegetables are obtained from the contaminated area.

2.1.2. Dose Algorithm

For consumers, the dose of a specified contaminant via ingestion of homegrown exposed 

vegetables is expressed as an average daily dose (ADDhg exp-veg ing) per BW and is calculated as 

follows:

ADDhg exp−veg ing =

Chg exp-veg × IRhg exp-veg per capita mean-adj × EF × ED

AT

(2)

where:

ADDhg exp-veg ing = potential average daily dose per kg BW of the contaminant from 

ingestion of homegrown exposed vegetables (mg/kg-d);

Chg exp-veg = concentration of the contaminant in the homegrown exposed vegetables 

(mg/g);

IRhg exp-veg per capita mean-adj = age-specific daily intake rate of homegrown exposed 

vegetables among children in gardening households; per capita mean, 

adjusted for preparation losses (g/kg-d);

EF = exposure frequency (d/yr);

ED = exposure duration (yr); and

AT = averaging time (d).

As detailed in the following subsections, the ADD hg exp-veg ing values are calculated for 

each of the four age ranges of 1 to <2 years, 2 to <3 years, 3 to <6 years, and 6 to <11 years, 

using available data from the EFH). These estimates are then summed to obtain an ADD hg exp-veg 

ing estimate for the entire 1- to <11-year-old age range.

2.1.3. Input for Exposure Factor Variables

Chg exp-veg―The concentration of the contaminant in homegrown exposed vegetables is 

either the measured or predicted concentration (e.g., based on modeling). Since the scenario is 
20

estimating central tendency dose, the mean or median contaminant concentration would be used. 

For the purposes of the example calculations shown below, it is assumed that the mean 

concentration of the contaminant in homegrown exposed vegetables is 1 × 10−3 mg/g for all 

consumers within the 1- to <11-year age range.

IRhg exp-veg per capita mean-adj―The age-specific average intake rates of homegrown exposed 

vegetables for children in gardening households are estimated by first converting the consumeronly mean intake rate of homegrown exposed vegetables for the total population of gardening 

households (IRhg exp-veg-consumer only mean) from EFH Table 13-60 to the mean per capita rate (IRhg expveg-per capita mean) as follows:

IRhg exp-veg-per capita mean =

(IRhg exp-veg-consumer only mean × Nc)

Nt

(3)

where:

Nc = weighted number of gardening individuals who consumed homegrown exposed 

vegetables during the survey period (EFH Table 13-60); and

Nt = weighted total number of individuals who garden (EFH Table 13-4).

IRhg exp-veg-per capita mean =

1.57 g

kg-d

× 25,737,000

68,152,000

IRhg exp-veg-per capita mean = 0.59 g

kg-d

This mean value (IRhg exp-veg-per capita mean-unadj) represents the quantity of food brought into 

the house, and does not account for preparation or postcooking losses (i.e., unadjusted value). 

The value can be adjusted to represent the quantity of food as-eaten (IRhg exp-veg-per capita mean-adj) as 

follows:

IRhg exp-veg-per capita mean-adj =

IRhg exp-veg-per capita mean-unadj × (1 −

% preparation loss

100

) × (1 −

% post cooking loss

100 ) (4)
21

where: 

Preparation loss = 12% (see EFH Table 13-69); and

Postcooking loss = 22% (see EFH Table 13-69).

IRhg exp-veg-per capita mean-adj = 0.59

g

kg-d

× (1 −

12

100) × (1 −

22

100)

IRhg exp-veg-per capita mean-adj = 0.41 g

kg-d

This mean per capita value represents the average rate of homegrown exposed vegetable 

intake across all age groups of the population that gardens; age-specific intake rates are not 

available in the EFH for homegrown exposed vegetable intake among gardening households. 

Thus, age-specific intake rates are estimated by assuming that the ratios of age-specific intake to 

total population intake for homegrown exposed vegetables for children in gardening households 

would be the same as the ratios for intake of all exposed vegetables (i.e., not just homegrown 

exposed vegetables, and not just gardening households), based on data from EFH Table 9-20 and 

presented here in Table 4.

Table 4. Estimation of age specific per capita mean homegrown exposed 

vegetable intake rates for children in gardening households 

(g/kg-day) for four age ranges among children aged 1 to <11 years

Age

Mean Per Capita 

Intake

All Exposed Vegetables 

(g/kg-d)

Ratio of Age-Specific to 

Total Population Intakes 

of All Exposed Vegetables1

Mean Per Capita Intake

Homegrown Exposed Vegetables;

Gardening Households

(g/kg-d)2

Total Population 1.3 1.0 0.41

1 to <2 yr 2.0 1.54 0.63

2 to <3 yr 2.0 1.54 0.63

3 to <6 yr 1.6 1.23 0.50

6 to <11 yr 1.2 0.92 0.38

1 Calculated as the age-specific intake rate for all exposed vegetables divided by the total population intake rate for 

all exposed vegetables (from EFH Table 9-20 [U.S. EPA, 2011a]).

2Calculated as the mean adjusted per capita intake of homegrown exposed vegetables for the total population of 

children in gardening households (0.41g/kg-d), times the ratios of age-specific to total population intakes of all 

exposed vegetables.
22

EF―Exposure frequency is 365 days per year for each age range because the intake rate 

used in this example represents a long-term average daily intake over the entire year. (It does not 

mean that contaminated homegrown exposed vegetables are consumed each day of the year; 

instead, any intake that occurs during the year is averaged over the year to yield an average daily 

rate.)

ED―Exposure duration is the length of time over which exposure occurs, in years. This 

example assumes that a child is exposed continuously from ages 1 to <11 years. Thus, exposure 

duration is assumed to be 1, 1, 3, and 5 years for the 1 to <2 year, 2 to <3 year, 3 to <6 year, and 

6 to <11 year age ranges, respectively, for a total of 10 years.

AT―Because the chronic average daily dose is being calculated in this example, the 

averaging time is equivalent to the exposure duration expressed in days. To determine this 

value, 365 days/year is multiplied by the value of exposure duration for the given age range, and 

summed for all age ranges.

2.1.4. Calculations

Using the dose algorithm and exposure factors shown above, the potential ADDhg exp-veg ing

for a child in a specific age range from consuming homegrown exposed vegetables is estimated 

by applying eq 2 to the exposure factor data for that age range. The value of ADDhg exp-veg ing

depends on values established for IRhg exp-veg per capita mean-adj, Chg exp-veg, EF, ED, and AT. For 

children within the four age ranges, Table 5 presents mean point estimates of ADDhg exp-veg ing.

Table 5. Summary of average daily dose of contaminant associated with 

consumption of homegrown exposed vegetables (mg/kg-day) for four 

age ranges among children in gardening households, aged 1 to <11 

years

Dose Equation

Parameters and Output

Age Ranges

1 to <2 yr 2 to <3 yr 3 to <6 yr 6 to <11 yr

Chg expo-veg (mg/g) 1.0 × 10−3 1.0 × 10−3 1.0 × 10−3 1.0 × 10−3

IRhg exp-veg per capita mean-adj

(g/kg-d) 0.63 0.63 0.50 0.38

EF (d/yr) 365 365 365 365

ED (yr) 1 1 3 5

AT (d) 365 365 1,095 1,825

ADDhg expo-veg ing 

(mg/kg-d) 6.3 × 10−4 6.3 × 10−4 5.0 × 10−4 3.8 × 10−4
23

In the following calculation, the ADDs for each age group are averaged over the 10-year 

time period representing ages 1 to <11 years.

ADDhg exp-veg ing=

[(6.3 × 10−4 mg

kg-d

× 1 yr) + (6.3 × 10−4 mg

kg-d

× 1 yr) + (5.0 × 10−4 mg

kg-d

× 3 yr) + (3.8 × 10−4 mg

kg-d

× 5 yr)]

10 yr

ADDhg exp-veg ing = 4.7 × 10−4 mg

kg-d

2.1.5. Uncertainties

The example here presents results for the mean per capita dose via homegrown exposed 

vegetable ingestion for the population of children aged 1 to <11 years, in gardening households. 

High-end dose may be estimated by replacing the mean intake rates with upper-percentile values, 

or by using a high-end concentration with mean intake rates. The choice of which parameter 

should be set to the high-end would be dependent upon the sensitivities of the parameters, 

professional judgement, and regulatory requirements. U.S. EPA (2011a) and Phillips and Moya 

(2012) provide information about converting upper-percentile consumer only intake rates to per 

capita upper-percentile rates. If a bounding estimate is desired, both the concentration in the 

homegrown exposed vegetables and the intake rates may be set to high-end or maximum values.

The estimate reflects per capita doses among children in households that garden. The per 

capita data for the population that gardens includes both individuals who ate homegrown 

exposed vegetables during the survey period as well as those that did not, but may eat 

homegrown exposed vegetables at some other time during the year. The uncertainties associated 

with this example include the source data for the intake rate and concentration data. The 

concentration of the chemical will vary depending on preparation and cooking methods. The 

intake data were collected more than 30 years ago and over a short period of 1 week for an 

estimated 3,000 children in 4,300 households across the U.S. The extrapolation of a short survey 

data over a long period adds to the uncertainty of the intake rate data. Therefore, these data may 

not reflect current eating patterns and long-term distributions. These data were considered to be 

collected using sound methodology and were considered to have a high degree of quality 

assurance. Although the data were adjusted to account for preparation losses, there is added 
24

uncertainty in that adjustment factors based on a mixture of vegetables were used. This may not 

always be representative of the mixtures of vegetables eaten by the population of interest. There 

may also be uncertainties in the contaminant concentration as a result of sampling or analytical 

methods.

INGESTION OF CONTAMINATED SOIL AND DUST IN AND AROUND THE

HOME: YOUNG CHILDREN AGED 1 TO <6 YEARS, CENTRAL TENDENCY, 

LIFETIME AVERAGE DAILY DOSE

2.2.1. Introduction

Exposure via ingestion of soil and dust can occur in areas where soil contamination 

exists. Indoor dust can also be contaminated with outdoor soil. Receptors could include all 

children, especially those who spend time playing both outdoors, and indoors on the floor. The 

dose via this exposure pathway is estimated based on the concentration of contaminants in 

outdoor soils or indoor dust at or near the child’s residence, the intake rate, exposure frequency, 

and exposure duration. Young children are exposed to soil and dust primarily through hand-tomouth and object-to-mouth activities. As defined in the EFH (U.S. EPA, 2011a), soil and dust 

are:

Soil. Particles of unconsolidated mineral and/or organic matter from the earth’s 

surface that are located outdoors, or are used indoors to support plant growth. It 

includes particles that have settled onto outdoor objects and surfaces (outdoor 

settled dust).

Indoor Settled Dust. Particles in building interiors that have settled onto objects, 

surfaces, floors, and carpeting. These particles may include soil particles that 

have been tracked or blown into the indoor environment from outdoors as well as 

organic matter.

Outdoor Settled Dust. Particles that have settled onto outdoor objects and 

surfaces due to either wet or dry deposition. Note that it may not be possible to 

distinguish between soil and outdoor settled dust, since outdoor settled dust 

generally would be present on the uppermost surface layer of soil.

In this example, exposure via ingestion of soil and dust is assumed and the central 

tendency LADD from this pathway is evaluated for the population of young children who often 

play outdoors, and crawl and play on the floor indoors, and handle toys or other objects that may 

contain soil and/or dust (ages 1 to <6 years). The LADD is calculated because the contaminant in 
25

this scenario is assumed to be a carcinogen and the carcinogen toxicity values are expressed as 

lifetime values; thus, the childhood exposure period must be spread over a lifetime. 

Furthermore, it is assumed that the receptor population is not exposed to this carcinogen after 

this exposure period.

2.2.2. Dose Algorithm

The LADD of a specified contaminant via ingestion of contaminated soil and dust is 

calculated as follows:

LADDsoil + dust ing =

Csoil + dust × CF × IRsoil + dust × EF × ED

BW × LT

(5)

where:

LADDsoil + dust ing = potential lifetime average daily dose from ingestion of soil and dust 

(mg/kg-d);

Csoil + dust = concentration of contaminant in soil and dust (mg/g);

CF = conversion factor of 0.001 g/mg;

IRsoil + dust = intake rate of soil and dust (mg/d);

EF = exposure frequency (d/yr);

ED = exposure duration (yr);

BW = average body weight (kg); and

LT = lifetime (d).

2.2.3. Input for Exposure Factor Variables

Csoil + dust―The concentration of contaminants in soil and dust is either the measured level 

of the chemical of interest or predicted concentration, based on modeling. For estimating central 

tendency doses, the assessor typically uses an estimate of the mean or median concentration. For 

this example, the estimated mean concentration of chemical “x” in soil and dust is 

1 × 10−3 mg/g.

CF―A conversion factor is required to convert between milligrams (mg) and grams (g), 

0.001 g/mg to translate the intake rate to units of g/d.

IRsoil + dust―The recommended central tendency intake rate of soil and dust for young 

children (1 to <6 years old) is 100 mg/d, (EFH Table 5-1).
26

EF―This example uses an exposure frequency of 350 days per year, assuming that 

young children are away from home (e.g., on vacation), the source of contamination, for two 

weeks per year. The home and surrounding yard are assumed to be the only sources of 

contamination.

ED―This example uses an exposure duration of 5 years (from age 1 to <6 years), based 

on the assumption that after 5 years of age, children no longer play in outdoor soil or crawl on 

the floor, and their soil and dust ingestion is limited compared to that of younger children.

BW―The average BW for children between the ages of 1 and <6 years can be estimated 

by calculating a time weighted average for children 1 to <2 years, 2 to <3 years, and 3 to 

<6 years. These BWs are provided in EFH Table 8-1. The average BW for 1 to <6 year old 

children is 16.2 kg using the calculation shown below. This BW was used in these example 

calculations.

BW =

(11.4 kg × 1 yr) + (13.8 kg × 1 yr) + (18.6 kg × 3 yr)

5 yr

BW = 16.2 kg

LT―Because the contaminant used in this example is assumed to be a carcinogen, the 

dose is averaged over the lifetime (i.e., the LADD is calculated). A lifetime (LT) of 70 years for 

a member of the general population is used as a reference value. For use in the calculations, this 

value is converted to 25,550 days (i.e., 70 years × 365 days/year).

2.2.4. Calculations

Using the dose algorithm and exposure factors shown above, the LADD soil + dust ing is 

estimated as follows for the population of young children:

LADDsoil + dust ing =

1 × 10−3 mg

g

× 0.001 g

mg

× 100 mg

d

× 350 d

yr

× 5 yr

16.2 kg × 25,550 d

LADDsoil + dust ing = 4.2 × 10−7 mg

kg-d
27

2.2.5. Uncertainties

The example presented here is used to represent central tendency dose among a 

population of young children, ages 1 to <6 years, via ingestion of soil and indoor dust. The high 

end dose can be estimated by replacing the mean intake rate with a higher intake rate, or by using 

a high-end concentration with a mean intake rate. The choice of which parameter should be set 

to the high-end would be dependent upon the sensitivities of the parameters, professional 

judgement, and regulatory requirements. If a bounding dose estimate is desired, the 

concentration of contaminants may also be set to the maximum measured or modeled 

concentration.

The uncertainties associated with this example scenario are mainly related to assumed 

activity patterns of the receptor population and the input parameters used. Soil ingestion rates 

are highly uncertain. Implicit in this scenario is that young children ages 1 to <6 years ingest soil

and dust at the same intake rate specified in the EFH (U.S. EPA, 2011a). It should be noted that 

intake rate might decrease as activity patterns change with age. Also, the intake rate for children 

in specific age ranges may not represent long-term behaviors and day-to-day and seasonal 

variability. These input parameters are derived from data collected from a variety of studies 

focused on soil ingestion with limited data on dust ingestion. The uncertainties associated with

this example are as follows: (1) the assumption is made that 100% of the soil and dust that the 

children ingest comes from their home environment (i.e., it does not consider any portion of soil 

intake that may come from time spent away from home such as at daycare or school, nor does it 

consider difference in contaminant concentration from sources other than the home 

environment); (2) the methodologies of the soil/dust intake studies are considered to have 

limitations with numerous sources of measurement error; (3) the studies have limited 

representativeness of the U.S. population; and (4) eight of the nine EFH supporting studies were 

focused on soil or combined soil and dust ingestion with no, or very limited, focus on dust 

ingestion. There may also be uncertainties in the contaminant concentration as a result of 

sampling or analytical methods. The assessor should also consider the bioavailability of the 

contaminant in soil and dust. The bioavailability will vary depending on the physicochemical 

characteristics of the contaminant and the characteristics of the soil and dust (e.g., particle size).
28

INGESTION OF CONTAMINATED INDOOR DUST: CHILDREN AT SCHOOL 

AGED 6 TO <11 YEARS, CENTRAL TENDENCY, SUBCHRONIC AVERAGE 

DAILY DOSE

2.3.1. Introduction

Indoor dust can become contaminated from a variety of sources (e.g., use of pesticides, 

building materials, particle-bound contaminants infiltrating indoors from outdoors). The 

exposure scenario for this example is ingestion of contaminated indoor dust at a school. 

Receptors could include all school children. This example assumes that the outdoor soil is not 

contaminated, and exposure occurs only to indoor dust at school. Dose via this pathway is 

estimated based on the concentration of contaminants in indoor dust, the intake rate of indoor 

dust, exposure frequency, exposure time, and exposure duration. In this example, exposure via 

ingestion of indoor dust at school is assumed and the central tendency subchronic (<7 years) 

average daily exposure from this pathway is evaluated for children ages 6 to <11 years. Values 

obtained from tables within the EFH (U.S. EPA, 2011a) are cited as EFH Table X-X. 

2.3.2. Dose Algorithm

The ADD of a specified contaminant via ingestion of contaminated dust by children at 

school is calculated as follows:

ADDdust ing =

Cdust × CF × IRdust × EF × ET × ED

BW × AT

(6)

where:

ADDdust ing = potential subchronic average daily dose of the contaminant from 

ingestion of contaminated dust (mg/kg-d);

Cdust = concentration of the contaminant in the ingested dust (mg/g dust);

CF = conversion factor of 0.001 g/mg;

IRdust = average daily intake rate of dust for children aged 6 to <11 years (mg/d);

EF = exposure frequency (d/yr);

ET = exposure time (unitless fraction representing the portion of the day spent 

in school);

ED = exposure duration (yr);

BW = average body weight (kg); and

AT = averaging time (d).
29

2.3.3. Input for Exposure Factor Variables

Cdust―The concentration of contaminants in indoor dust is either the measured level of 

the chemical of interest in the indoor dust or predicted concentration, based on modeling. For 

estimating central tendency doses, the mean or median values would be used. In this example, it 

is assumed that the mean concentration of chemical “x” in indoor dust is 1 × 10−3 mg/g.

CF―A conversion factor is required to convert between milligrams and grams, 

0.001 g/mg.

IRdust―The recommended central tendency intake rate of indoor dust for young children 

(6 to <11 years old) is 60 mg/day (EFH Table 5-1; U.S. EPA, 2011a).

EF―School is in session for approximately 37 weeks/year or 185 days/year. The school 

is assumed to be the only source of contamination.

ET―For “doers-only”, the average time spent in school for 6 to <11 year-old children is 

approximately 400 minutes/day (i.e., 6.7 hours/day) (EFH Table 16-17). Since dust ingestion 

only occurs during waking hours, the fraction of time spent in school should be based on waking 

hours and not on 24 hours. Children 6 to <11 years spend 613 minutes/day or 10 hours/day 

sleeping or napping (EFH Table 16-25; U.S. EPA, 2011a). Thus, these children are awake 

approximately 14 hours/day (24 hours/day – 10 hours/day). Assuming that 6.7 hours/day during 

the time they are awake is spent at school, 0.48 of the day (i.e., 6.7/14) is spent in school where 

they may be ingesting indoor dust. The school is assumed to be the only source of 

contamination.

ED―Exposure duration is the length of time over which the exposure occurs. In this 

example, an ED of 5 years (from age 6 to <11 years) is used. It is assumed that the children 

attend the contaminated school the entire 5 years.

BW― The average BW for children from 6- to <11-years old of 31.8 kg EFH Table 8-1 

(U.S. EPA, 2011a).

AT―Because the subchronic ADD is being calculated in this example, the averaging 

time is equivalent to the exposure duration. The averaging time of 5 years is converted to 

1,825 days for this calculation (i.e., 5 years × 365 days/year).
30

2.3.4. Calculations

Using the dose algorithm and exposure factors shown above, the ADDdust ing is estimated 

as follows for the population of children:

ADDdust ing =

(1 × 10−3)

mg

g

× 0.001 g

mg

× 60 mg

d

× 185 d

yr

× 0.48 × 5 yr

31.8 kg × 1,825 d

ADDdust ing = 4.6 × 10−7 mg

kg-d

2.3.5. Uncertainties

The example presented here is used to represent central tendency dose among a 

population of school children, ages 6 to <11 years, via ingestion of indoor dust. For high-end 

estimates, a combination of upper-percentile and central tendency inputs would be used. The 

choice of which parameter(s) should be set to the high-end would be dependent upon the 

sensitivities of the parameters, professional judgement, and regulatory requirements. If a 

bounding dose estimate is desired, both the intake rate and the concentration of contaminant may 

be set to the upper-percentile values. It is important to note that the bounding estimate results in 

dose estimates that may be unreasonably high for the population of interest.

The uncertainties associated with this example scenario are mainly related to assumed 

activity patterns of the receptor population and the input parameters used. This scenario 

represents a central tendency dose; higher exposures may occur depending on activity patterns. 

Implicit in this scenario is that school children ages 6 to <11 years ingest indoor dust at the same 

intake rate specified in the EFH (U.S. EPA, 2011a). It should be noted that intake rates might 

decrease as activity patterns change with age. The periods studied may not represent long-term 

behaviors, and day-to-day and seasonal variability were not well characterized. These input 

parameters are derived from data collected from a variety of studies. The uncertainties

associated with this example are as follows: (1) the methodologies of the dust intake studies are 

considered to have limitations with numerous sources of measurement error; (2) the dust intake 

studies have limited representativeness of the U.S. population; and (3) eight of the nine dust 

intake studies were focused on soil ingestion with no, or limited, focus on dust ingestion. These 
31

facts make it difficult to characterize the individual contributions from soil and dust to the total 

intake. 

The assessor may also consider the bioavailability of the contaminant in soil and dust. 

The bioavailability will vary depending on the physicochemical characteristics of the 

contaminant and the characteristics of the dust (e.g., particle size). Also, this scenario assumes 

that the contaminant is not present in outdoor soils and that children are not exposed to the 

contaminant in soil or dust outside the school environment. This may be true for some 

contaminants, however, indoor dust will often be a mixture of outdoor soils and indoor sources. 

Children who participate in after-school programs may spend more time at school. In those

cases, it would be appropriate to use a higher number of hours spent at school to estimate the ET. 

It should be noted that the contaminant may be brought into other microenvironments (e.g., 

home) on the children’s body, shoes, or clothing, in which case adjustments to the ET based on 

the fraction of time spent in school would not be appropriate. In addition, the approach used 

here assumes that dust ingestion occurs at a steady rate throughout the time that one is awake. 

The supporting studies are not detailed enough to show if this is true. For a more reliable dose 

estimate, a study would need to be conducted to specifically estimate the indoor dust intake rate 

for children. This scenario only considers exposure via dust ingestion, dermal exposure may also 

be a concern and would need to be evaluated.

INGESTION OF AN ENVIRONMENTAL CONTAMINANT BY NONDIETARY 

HAND-TO-MOUTH BEHAVIORS: INFANTS AND TODDLERS 3 MONTHS TO 

<2 YEARS, BOUNDING, ACUTE DOSE RATE

2.4.1. Introduction

Infants and toddlers exhibit a high frequency of hand-to-mouth and object-to-mouth 

behaviors. In instances where infants and toddlers are playing in a contaminated room, they may 

be exposed to contaminants through mouthing of contaminated surfaces and objects and/or 

transferring contaminants from surfaces to their hands and subsequently into their mouths. 

Potential exposure to contaminants by nondietary hand-to-mouth and object-to-mouth behaviors 

may occur, for example, after use of a sprayed biocide or household cleaning product. This 

example estimates bounding acute dose via ingestion of contaminants through hand-to-mouth 

behaviors for infants and toddlers ages 3 months to <2 years. Values obtained from tables within 

the EFH (U.S. EPA, 2011a) are cited as EFH Table X-X. 
32

2.4.2. Dose Algorithm

Dose via this pathway would be calculated as follows:

ADRhand-to-mouth ing =

⌈Csurface × CRhand-to-mouth × CSAhands⌉×⌊TESH × TEHM × ET × EF × ED⌋

BW × AT

(7)

where:

ADRhand-to-mouth ing = acute potential dose rate from contaminated surface (mg/kg-d);

Csurface = contaminant loading on surface (mg/cm2);

CRhand-to-mouth = contact rate (contacts/hr);

CSAhands = contact surface area of hand (cm2/contact);

TESH = transfer efficiency from surface to hand (%);

TEHM = transfer efficiency from hand-to-mouth (%);

ET = exposure frequency (hr/event);

EF = exposure frequency (events/d);

ED = exposure duration (d);

BW = average body weight (kg); and

AT = averaging time (d).

2.4.3. Input for Exposure Factor Variables

Csurface―The contaminant loading on indoor surfaces can be measured or predicted based 

on modeling the chemical of interest on a floor surface or object. For estimating the acute dose

in this example, the maximum value is used. For the purposes of the example calculations 

shown below, it is assumed that the modeled maximum loading of chemical “x” on a surface is 

1 × 10−6 mg/cm2.

CRhand-to-mouth―The upper-percentile contact rate for children is presented in EFH 

Table 4-1 (U.S. EPA, 2011a). In this example, the 95th percentile contact rates are used to 

calculate the acute bounding dose. For children ages 3 months to <6 months, 6 months to 

<12 months, and 1 year to <2 years, the 95th percentile contact rates are 65, 52, and 63 contacts 

per hour, respectively. The weighted average of these contact rates is 60 contacts per hour and is 

calculated as follows:
33

CRhand-to-mouth =

[

(65 contacts

hr × 3 mo) + (52 contactshr × 6 mo) +

(63 contacts

hr × 12 mo)

]

21 mo

CRhand-to-mouth = 60

contacts

hr

CSAhands―The surface area for body parts is presented in EFH Table 7-2 (U.S. EPA, 

2011a). In this example, mean surface areas are used because surface area and BW are strongly 

correlated and the mean values are most representative of the surface area of individuals with an 

average BW. For children 3 months to <6 months, 6 months to <12 months, and 1 year to 

<2 years the mean contact surface areas (CSA) for hands are 0.020, 0.024, and 0.030 m2per 

contact, respectively. A square meter is converted to square centimeters using the conversion of 

1 m2 = 10,000 cm2. For this example, the contact surface areas used to calculate the weighted 

average CSA are 200 cm2for 3 months to <6 months, 240 cm2for 6 months to <12 months, and 

300 cm2for 1 year to <2 years. It is assumed that the contact surface area is 100% of the hands 

for children. The weighted CSAhands is 269 cm2and is calculated as follows:

CSAhands =

[

(200 cm2

contact × 3 mo) + (240 cm2contact × 6 mo) +

(300 cm2

contact × 12 mo)

]

21 mo

CSAhands = 269

cm2

contact

TESH―The transfer efficiency (TESH) from surface to hand is 14%, as estimated in EFH

Table 7-27 (U.S. EPA, 2011a). This is the highest transfer efficiency reported by Cohen-Hubal 

et al. (2005) from a study in which adult volunteers contacted surfaces treated with nontoxic 

fluorescent tracer material to estimate the percentage transferred from a variety of surface types 

by the hands under a variety of conditions. This maximum value represents the initial surface 

contact with “sticky” hands.

TEHM―The transfer efficiency from hand-to-mouth (also referred to as the saliva transfer 

efficiency) is assumed to be 16%. This value is based on results reported by Kissel et al. (1998), 
34

who estimated the geometric mean transfer efficiencies from hand-to-mouth from thumb sucking 

and finger mouthing to be 10.1% and 15.9%, respectively.

ET―The exposure time is assumed to be a one-time acute exposure. For the purpose of 

this example, a 4-hour visit to a contaminated indoor space is assumed.

EF―The exposure frequency is assumed to be one event for acute exposure. This means 

that residues are transferred to the hand during the day of exposure without washing and 

reloading.

ED―The exposure duration is the length of time over which exposure occurs. For the 

purposes of this example, the acute exposure duration is assumed to be 1 day.

BW―EFH Table 8-1 (U.S. EPA, 2011a) reports recommended values for BWs for 

children. Using the age-specific mean BWs, the average BWs of 7.4, 9.2, and 11.4 kg are used 

for the age ranges of 3 to <6 months, 6 to <12 months, and 1 year to <2 years, respectively. The 

weighted average BW for this example is as follows:

BW =

(7.4 kg × 3 mo) + (9.2 kg × 6 mo) + (11.4 kg × 12 mo)

21 mo

BW = 10.2 kg

AT―Because the acute dose is being calculated, the averaging time is 1 day.

2.4.4. Calculations

Using the dose algorithm and exposure factors shown above, the potential ADR for 

hand-to-mouth ingestion of a contaminant, ADR hand-to-mouth ing, is estimated:

ADRhand-to-mouth ing =

[

(1.0 × 10−6)

mg

cm2 × 60 contacts

hr × 269 cm2

contact ×

0.14 × 0.16 × 4

hr

event × 1

event

d

× 1 d

]

10.2 kg × 1 d

ADRhand-to-mouth ing = 1.4 × 10−4 mg

kg-d
35

2.4.5. Uncertainties

The example demonstrates a bounding estimate of dose to infants and toddlers resulting 

from exposure to contaminated surfaces. Central tendency doses may be estimated by replacing 

the contact rates and concentrations with central tendency values (e.g., mean or median). The 

high-end dose may be estimated by using a combination of mean and upper-percentile values for 

the exposure factors. The choice of which parameter should be set to the high-end would be 

dependent upon the sensitivities of the parameters, professional judgement, and regulatory 

requirements.

The uncertainties associated with this example scenario are related to assumed activity 

patterns and contact rates of the receptor populations. This is an acute scenario and the 

maximum concentration was used. However, for other measures of dose (e.g., central tendency), 

the variability in the chemical concentration in the different rooms of the house where the child 

spends his/her time may need to be considered. The studies that derived the recommended 

values for contact rates were conducted with very small sample sizes over short data collection 

periods and in a small number of locations in the U.S. The data may not be representative of 

long duration exposure or of large populations. In addition, the transfer efficiency studies were 

conducted using adults with organic fluorescent tracers, rather than children. Chemical-specific 

transfer efficiencies may differ from those assumed here. Transfer efficiency studies did not 

evaluate surface-to-hand and hand-to-mouth transfer efficiency for particles such as dust. 

Hand-to-mouth transfer efficiency was assumed to be 16%, and this value may vary depending 

on the chemical as well as other factors. The scenario also assumes that there is a constant 

loading of the contaminant into the hand after each mouthing event with no hand washing. In 

reality, there may not be a constant replenishment of the chemical into the hand before each 

mouthing event and the amount transferred to the mouth is a fraction of the loading that remains 

from the prior insertion. Özkaynak et al. (2011) developed a model to simulate frequent 

mouthing events without contaminant replenishment which estimates soil and dust ingestion that 

may be used to further refine this scenario example.
36

EXPOSURE TIME OF INCIDENTAL INGESTION OF CONTAMINATED POOL 

WATER TO REACH A REFERENCE DOSE LEVEL OF EXPOSURE: CHILDREN 

AGED 6 TO <11 YEARS, BOUNDING

2.5.1. Introduction

Children may incidentally ingest chemicals in the water when swimming. This scenario 

estimates how long it would take to exceed a reference dose (RfD) for children playing and/or 

swimming in a swimming pool containing the chemical of interest. For the purpose of this 

example, it is assumed that the chemical is well mixed in the pool water. Receptors in this 

example include swimmers in swimming pools (i.e., owned privately, municipally, or by 

schools). Values obtained from tables within the EFH (U.S. EPA, 2011a) are cited as EFH Table 

X-X. 

This example is designed to derive a daily exposure time that one could have over a 

subchronic exposure duration, to a specified concentration, without exceeding the RfD. A 

bounding dose for acute incidental ingestion of pool water is evaluated here for children aged 6 

to <11 years. As a bounding estimate, it is assumed that the children swim every day (i.e., 

365 days/year) in the same pool, and the pool water is not drained or cleaned over the duration of 

the exposure. In other cases, the assessor may want to solve the dose equation for the maximum 

concentration to which the swimmer can be exposed without exceeding the RfD. In that case, the 

assessor needs to assume an exposure time.

2.5.2. Dose Algorithm

The time-to-exceed a given dose via ingestion of contaminated pool water would be 

calculated using the following dose equation (eq 8) rearranged to solve for exposure time and 

replacing ADDwater ing with the RfD as shown in eq 9.

ADDwater ing =

Cpool water × IRpool water × ET × EF × ED

BW × AT

(8)

ET =

RfDwater ing × BW × AT

Cpool water × IRpool water × EF × ED

(9)

where:
37

ADDwater ing = potential average daily dose of the contaminant from ingestion of 

contaminated pool water (mg/kg-d);

RfDwater ing = reference dose (mg/kg-d);

Cpool water = concentration of chemical in the pool water (mg/L);

IRpool water = water intake rate (L/hr);

ET = exposure time (hr/d), length of time necessary to exceed the reference 

for the chemical;

EF = exposure frequency (d/yr);

ED = exposure duration (yrs);

BW = average body weight (kg); and

AT = averaging time (d).

2.5.3. Input for Exposure Factor Variables

RfDwater ing―A reference dose is an estimate (with uncertainty spanning perhaps an order 

of magnitude) of a daily oral exposure to the human population (including sensitive subgroups) 

that is likely to be without an appreciable risk of deleterious effects during a lifetime (U.S. EPA, 

2011b). For the purposes of the example calculations shown below, it is assumed that the RfD of 

chemical “x” is 1 × 10−3 mg/kg-day.

BW―EFH Table 8-1 (U.S. EPA, 2011a) reports recommended mean values for BWs for 

children. The age-specific mean BW for 6- to <11-year-old children of 31.8 kg BW is used in 

this example.

AT―Because the ADD is being calculated in this example, the averaging time is 

equivalent to the exposure duration. The averaging time of 5 years is converted to 1,825 days for 

this calculation (i.e., 5 years × 365 days/year).

Cpool water―The concentration in pool water at the site is either the measured or predicted 

concentration, based on modeling, of the chemical of interest in the pool water consumed. It also 

is assumed that the pool water is well mixed and the chemical is equally distributed in the water. 

For estimating bounding exposures, the maximum value would be used. For the purposes of the 

example calculations, it is assumed that the modeled maximum concentration of chemical “x” in 

pool water is 0.1 mg/L.

IRpool water―The upper-percentile intake rate for the swimmer is assumed to be 

120 mL/hour or 0.12 L/hour from EFH Table 3-5 (U.S. EPA, 2011a).

EF―Exposure frequency is assumed to be 365 days/year for this bounding estimate.
38

ED―Exposure duration is assumed to be 5 years.

2.5.4. Calculations

Using the dose algorithm and exposure factor inputs shown above, the ET would be 

calculated as follows for children (ages 6 to <11 years):

ET =

(1 × 10−3)

mg

kg-d

× 31.8 kg × 1,825 d

0.1

mg

L

× 0.12 L

hr × 365 d

yr

× 5 yr

= 2.7

hr

d

2.5.5. Uncertainties

The example presented is used to represent bounding doses among a specific population 

from the incidental ingestion of pool water. This scenario does not include dermal penetration or 

inhalation dose, both of which may contribute to total exposure to pool water. Central tendency 

doses may be estimated by replacing the intake rate and concentrations with mean or median 

values. Also, exposure frequency may be replaced by mean values obtained from EFH 

Table 16-1 (U.S. EPA, 2011a). High-end doses may be estimated by using a combination of 

central tendency and upper-percentile values for the intake rates, concentrations, and exposure 

frequency. The choice of which parameter should be set to the high-end would be dependent 

upon the sensitivities of the parameters, professional judgement, and regulatory requirements.

The uncertainties associated with this example scenario are related to assumed activity 

patterns and intake rates of the receptor populations and include uncertainties such as ingestion 

differences due to playing or swimming behaviors. Implicit in this scenario is the assumption 

that the child swimmer or wader actually consumes the chemicals in the pool water at the rates 

specified. It also assumes that the child visits the same pool for all 5 years and that the same 

chemicals are used in the pool for those 5 years. These assumptions are appropriate for the 

bounding estimate, but may be unrealistic for other estimates (e.g., central tendency). Another 

uncertainty is that RfDs are developed to represent chronic doses and may not be applicable to 

subchronic doses. The intake rate of pool water has a high uncertainty, because the data 

available are limited for this factor. The intake rate used in this assessment is 0.12 L/hour as 
39

reported from only one study (U.S. EPA, 2011a). This study does not break out age ranges and 

encompasses all children less than 16 years of age. It also is not considered representative of the 

U.S. population. 

INGESTION OF CONTAMINATED DRINKING WATER: CHILDREN AGED 

<21 YEARS, DISTRIBUTION OF CHRONIC AVERAGE DAILY DOSE

2.6.1. Introduction

In areas where contaminated surface water or ground water is used as a source of 

drinking water, there is the potential for contaminant exposure via ingestion of tap water. The 

dose via ingestion of contaminated drinking water is estimated based on the concentration of 

contaminants in the 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 a 

distribution of chronic average daily doses from this pathway is evaluated for the population of 

children, birth to <21 years. It is assumed that the children’s community water is contaminated; 

therefore, both the home and school drinking water supplies are contaminated, and the children 

ingest contaminated water from birth (e.g., formula prepared with water) through childhood until 

21 years of age. Values obtained from tables within the EFH (U.S. EPA, 2011a) are cited as EFH 

Table X-X. 

Instead of a point estimate, this example scenario uses a probabilistic method to estimate 

the distributions of contaminant intakes in the exposed population. This approach is used to 

demonstrate how a probabilistic method could be used to estimate a dose. It does not mean that 

this is the only, or most appropriate, method for this scenario. Distributions are used to represent 

the contaminant concentration and intake rates. All other input parameters are held constant at 

their central values. The final output distribution is developed using a Monte Carlo simulation 

with the Crystal Ball version 7 software.

2.6.2. Dose Algorithm

The ADDdrinking water ing resulting from consumption of contaminated drinking water, is 

calculated for each age group as follows:

ADDdrinking water =

Cdrinking water × IRi × EF × EDi

AT

(10)
40

where:

ADDdrinking water ing = potential chronic average daily dose from ingestion of 

contaminated drinking water (μg/kg-d);

Cdrinking water = concentration of contaminant in contaminated drinking water 

(μg/mL);

IRi = intake rate of drinking water for age group i (mL/kg-d);

EF = exposure frequency (d/yr);

EDi = exposure duration for age group i (yr); and

AT = averaging time (d).

The ADDdrinking water ing can also be calculated as the average over all of the age ranges as 

follows:

ADDdrinking water =

Cdrinking water × EF × ∑(IRi × EDi)

AT

(11)

2.6.3. Input for Exposure Factor Variables

Cdrinking water―The concentration of contaminant in drinking water is either the measured 

or predicted concentration based on modeling. For the purposes of this example, it is assumed 

that a measurement survey of the contaminated drinking water produced a mean concentration of 

1 μg/mL with a standard deviation of 0.5 μg/mL. Contaminant concentrations in natural 

environments typically are log normally distributed (Cullen and Frey, 1999), and this was 

assumed for this example.

IRdrinking water―The distribution of intake rate of drinking water for ages birth to 

<21 years are presented in EFH Table 3-19 (U.S. EPA, 2011a). These data are summarized in 

Table 6 for 11 age ranges of children <21 years of age. These data are for consumers-only of 

community water including both direct and indirect sources. Water consumption data are 

positively skewed and have been found to be well represented by log-normal distributions 

(Roseberry and Burmaster, 1992). The Crystal Ball version 7 software was used to fit the data to 

log-normal distributions based on the mean and 90th percentile values.

EF―Exposure frequency is assumed to be 350 days per year for each age range. This is 

equivalent to 50 weeks of living where the water is contaminated, and accounts for 2 weeks 

away from the contaminated area for vacations. This value was held constant in the simulation.
41

ED―Exposure duration is the length of time over which exposure occurs in each age 

group expressed in years. For example, the 1- to <2-year age group has an exposure duration of 

1 year. This value was held constant in the simulation.

AT―Because the chronic ADD is being calculated in this example, the averaging time is 

equivalent to the exposure duration. This value was held constant in the simulation.

All input values are summarized in Table 7.

Table 6. Consumer-only estimates of direct and indirect water ingestion: 

community water (mL/kg-day)

Age range

Sample 

size Mean

Percentiles

10 25 50 75 90 95 99

Birth to <1 mo 37 137a 11a 65a 138a 197a 235a 238a 263a

1 to <3 mo 108 119 12a 71 107 151 228a 285a 345a

3 to <6 mo 269 80 7 27 77 118 148 173a 222a

6 to <12 mo 534 53 5 12 47 81 112 129 186a

1 to <2 yr 880 27 4 9 20 36 56 75 109a

2 to <3 yr 879 26 4 9 21 36 52 62 121a

3 to <6 yr 985 21 3 8 17 29 43 52 83

6 to <11 yr 1,410 17 2 6 13 23 35 47 78

11 to <16 yr 2,113 12 1 4 8 15 26 35 62

16 to <18 yr 944 10 1 4 8 15 23 30 47

18 to <21 yr 1,086 11 1 3 7 15 26 36 58

aEstimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and 

Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group 

Recommendations (NCHS, 1993).

Source: U.S. EPA (2011a).
42

Table 7. Input values by age range for ingestion of contaminated drinking 

water

Age range

C

(μg/mL)a

IR

(mL/kg-d)a

EF

(d/yr)

ED

(yr)

AT

(d)

0 to <1 mo

1.0

137

350

0.08 30

1 to <3 mo 119 0.17 60

3 to <6 mo 80 0.25 90

6 to <12 mo 53 0.5 180

1 to <2 yr 27 1 365

2 to <3 yr 26 1 365

3 to <6 yr 21 3 1,095

6 to <11 yr 17 5 1,825

11 to <16 yr 12 5 1,825

16 to <18 yr 10 2 730

18 to <21 yr 11 3 1,095

aThis exposure factor is represented by a log-normal distribution with only the mean shown here.

2.6.4. Calculations

The distribution of potential ADDdrinking water ing, values in the exposed population was 

estimated by conducting a Monte Carlo analysis using the Crystal Ball version 7 software. A 

total of 10,000 trials were used in the simulation. For each trial, a set of parameter values was 

obtained by randomly sampling the parameter distributions described above and then computing 

the ADD. The ADDs from each trial were combined to form the final distribution. The results 

are summarized in Table 8 and illustrated in Figure 1.
43

Table 8. Average daily doses (ADD; μg/kg-day) from birth to 21 years of age 

for ingestion of contaminated drinking water

Age range Mean SD 10% 50% 90% 95%

0 to <1 mo 145 103 52 119 266 334

1 to <3 mo 132 107 42 103 253 326

3 to <6 mo 87 65 29 69 165 210

6 to <12 mo 61 46 17 46 120 155

1 to <2 yr 31 26 9 23 61 77

2 to <3 yr 29 24 9 22 57 72

3 to <6 yr 24 20 7 18 47 61

6 to <11 yr 19 17 6 15 38 48

11 to <16 yr 14 13 4 10 28 36

16 to <18 yr 12 11 3 8 24 33

18 to <21 yr 13 13 3 10 27 38

Birth to <21 yr 21 12 9 18 37 42

Figure 1. Distribution of average daily doses (ADD) from birth to 21 years of 

age.
44

2.6.5. Uncertainties

Log-normal distributions were used to represent drinking water intake rates for the 

purposes of this example because water consumption data have been found to be well 

represented by log-normal distributions (Roseberry and Burmaster, 1992). The fitted 

distributions were based on means and 90th percentiles; however, more accurate fits may be 

possible using more data. Alternatively, the raw data could be used to derive empirical 

distributions.

This scenario assumes that all of the ingested water is contaminated community tap 

water. However, children may ingest water from other sources that are either not contaminated 

or have different levels of contamination. The intake rates of drinking water in the EFH

(U.S. EPA, 2011a) are derived from the data collected over a short period of time (2 days). The 

extrapolation to chronic intake in this example might introduce some degree of uncertainty and 

would not account for variation in children activity levels due to seasonal changes over a long 

timeframe of 21 years.

Information on uncertainty and variability and probabilistic risk analysis can be found in 

Chapters 1 and 2 of the EFH (U.S. EPA, 2011a). The Monte Carlo simulation conducted for this 

example scenario assumed that all variables were independent. However, drinking water intake

rates for the age groups may be positively correlated. This is because generally a high water 

consumer at one age is likely to be a high water consumer at other ages. This positive 

correlation may not be too strong at the young ages included in this example because children’s 

habits may change. This is a potential source of uncertainty in the simulation across all ages 

(i.e., birth to <21 years). The correlations between variables can be defined in the Crystal Ball 

version 7 program. To assess the possible uncertainty associated with the assumption of 

independence, a second simulation was run assuming a correlation coefficient of 0.8 between the 

drinking water intake rates for all age groups. The results did not change significantly. 

The ADD could also be calculated using a deterministic approach. Assuming average 

inputs for all exposure parameters, the central tendency point estimate would be:

ADDdrinking water =

1

μg

mL × 350 dyr

×

[ (137 mL

kg-d

× 0.08 yr)+(119 mL

kg-d

× 0.17 yr)+(80 mL

kg-d

× 0.25 yr)+(53 mL

kg-d

× 0.5 yr)+(27 mL

kg-d

× 1 yr)

+(26 mL

kg-d

× 1 yr)+(21 mL

kg-d

× 3 yr)+(17 mL

kg-d

× 5 yr)+(12 mL

kg-d

× 5 yr)+(10 mL

kg-d

× 2 yr)+(11 mL

kg-d

× 3 yr)]

7,660 d
45

ADDdrinking water = 17.9 μg/kg-d

This ADD is similar to the central tendency estimate derived using the probabilistic 

approach as shown in Table 8.

INGESTION OF CONTAMINATED HUMAN MILK: INFANTS AGED BIRTH TO 

<12 MONTHS, HIGH-END, SUBCHRONIC AVERAGE DAILY DOSE

2.7.1. Introduction

For infants who are breastfed, the potential exists for intake of contaminants through 

nursing. The mother may be exposed to contaminants through ingestion, inhalation, and dermal 

absorption. In addition, the mother may have stores of contaminants in adipose tissue from past 

exposures. These contaminants may reenter the maternal circulation during pregnancy or 

nursing. Because of the high lipid content in human milk, contaminants that are lipophilic are 

likely to be passed to a nursing child via this exposure pathway. The aqueous portion of human 

milk also could allow transfer of hydrophilic contaminants to the infant. The potential receptors 

are infants who consume human milk with no other milk substitutes. In this example, exposure 

via contaminated human milk is assumed for infants who are breastfed from 0 to <12 months of 

age. Covered are four age ranges (0 to <1, 1 to <3, 3 to <6, and 6 to <12 months). Values 

obtained from tables within the EFH (U.S. EPA, 2011a) are cited as EFH Table X-X. According 

to the EFH (U.S. EPA, 2011a), the potential subchronic daily dose for all four of the age ranges

should be calculated separately for each age range and then the weighted average calculated for 

the entire age range for this scenario. In this example, the high-end dose of a lipophilic 

contaminant is calculated using central estimates of the concentration of the contaminant in the 

lipid portion of human milk, the upper-percentile lipid intake rates of human milk, the exposure 

frequency, the exposure duration, and the averaging time.

2.7.2. Dose Algorithm

The ADD of a specified contaminant via ingestion of contaminated human milk is 

calculated as follows:

ADDhuman milk ing =

Clipid × IRlipid human milk × EF × ED

AT

(12)
46

where:

ADDhuman milk ing = potential subchronic average daily dose from ingestion of 

contaminated human milk (mg/kg-d);

Clipid = concentration of contaminants in the lipid portion of contaminated 

human milk (mg/g lipid);

IRlipid human milk = lipid intake rate of human milk for infants who are fed human milk 

(g lipid/kg-d);

EF = exposure frequency (d/mo);

ED = exposure duration (mo); and

AT = averaging time (d).

2.7.3. Input for Exposure Factor Variables

Clipid―The concentration of a contaminant in the lipid portion of human milk is either the 

measured or predicted concentration based on modeling, of the contaminant in this medium. 

When estimating central tendency, the mean or median values would be used. For the purposes 

of the example calculations shown below, it is assumed that the central tendency concentration 

of chemical “x” in human milk is 1 × 10−3 mg/g lipid.

IRlipid human milk―The upper-percentile intake rate of lipids from human milk for infants 

from birth to <12 months of age can be estimated based on intake rate of lipids from human milk 

for infants provided in EFH Table 15-1 (U.S. EPA, 2011a). The intake rates presented in this 

table are normalized to BW and are calculated as the mean for each age range. It is assumed that 

in the general population, each age group is equally represented. The recommended intake rates

are then converted from mL/kg-day to g/kg-day assuming the density of human milk is 

1.03 g/mL (NAS, 1991). The lipid intake rates for human milk are summarized here in Table 9. 

For the purpose of this example, intake rates for exclusively breastfed infants are used. 

Exclusively breastfed infants are those whose sole source of milk comes from human milk, with 

no other milk substitutes (U.S. EPA, 2011a). Also, it is assumed that the contaminant is only 

present in the lipid portion of human milk.
47

Table 9. Upper-percentile lipid intake rates from human milk

Age range Lipid intake rate

(mL/kg-d)

Density-converted

lipid intake rate

(g/kg-d)

0 to <1 mo 8.7 9.0

1 to <3 mo 8.0 8.2

3 to <6 mo 6.1 6.3

6 to <12 mo 5.2 5.4

EF―Exposure frequency is 30 days/month.

ED―Exposure duration is the length of time over which the exposure occurs. For the 

purpose of this example, it is assumed that infants are breastfed for the first year of life. After 

that time, the infant’s diet is changed. Thus, the exposure duration is equal to the number of 

months within each age range.

AT―Because the subchronic ADD is being calculated in this example, the averaging 

time is equivalent to the exposure duration. This value is converted to days using 30 days/month 

for the purposes of this calculation and is different for each age range (Table 10).

2.7.4. Calculations

Using the dose algorithm (eq 12) and the input for the exposure factors shown above, the 

potential ADDhuman milk ing from human milk ingestion is estimated for the individual age ranges.

Table 10. Summary of ADD of contaminant associated with human milk for 

four age ranges among infants aged birth to <12 months

Equation 12

input and output

Age ranges

0 to <1 

mo

1 to <3 

mo

3 to <6 

mo

6 to <12 

mo

C (mg/g) 1 × 10−3 1 × 10−3 1 × 10−3 1 × 10−3

IR (g/kg-d) 9.0 8.2 6.3 5.4

EF (d/mo) 30 30 30 30

ED (mo) 1 2 3 6

AT (d) 30 60 90 180

ADD (mg/kg-d) 9.0 × 10−3 8.2 × 10−3 6.3 × 10−3 5.4 × 10−3

The weighted average ADD for the entire age range is calculated as follows:
48

ADDHuman milk ing =

[

 

 

 

 

 

 

 ((9.0 × 10−3

)

mg

kg-d

× 30 d) + ((8.2 × 10−3)

mg

kg-d

× 60 d) +

(

(6.3 × 10−3) mg

kg-d

× 90 d) + (

(5.4 × 10−3) mg

kg-d

× 180 d)

]

 

 

 

 

 

 

 

360 d

ADDHuman milk ing = 6.4 × 10−3 mg

kg-d

2.7.5. Uncertainties

The example presented here represents a high-end exposure scenario for the receptor 

population of infants 0 to <12 months of age who are breastfed. Central tendency and bounding 

dose estimates also can be derived from the data in Tables 9 and 10 using all central tendency or 

all upper-percentile input values, respectively.

This scenario specifies that a population of infants is breastfed the first year of life, using 

weight-averaged intake rates for human milk specified in the EFH (U.S. EPA, 2011a). It also is 

assumed here that the contaminant concentration is constant in human milk composition; 

however, studies have shown that contaminant concentrations may be affected by maternal 

nutrition (U.S. EPA, 2011a). In addition, the concentration of the chemical may decline as 

lactation continues and the mother’s body burden declines. 

This scenario also assumes a measured concentration. Models used to estimate human 

milk concentrations introduce additional uncertainties. Description of these models can be found 

in EPA’s Human Health Risk Assessment Protocol (HHRAP) for Hazardous Waste Combustion 

Facilities (U.S. EPA, 2005d). Another assumption in this scenario is that the exposure is to the 

contaminant dissolved in the lipid portion of the human milk. However, some of the 

contaminant may also be present in the nonlipid portion of the human milk which is not 

considered here. The intake rate estimates are a source of uncertainty because they are based on 

studies from 1980−2000, where participants were white in the mid-to-upper socioeconomic 

classes. The intake rates are based on studies that have small sample sizes and cover short time 

periods. These may not be a good representation of intake rates over longer periods of time. 

Finally, there is uncertainty in the lipid content correction. It has been reported that the lipid 
49

content of human milk varies with the length of time of nursing and increases from the beginning 

(foremilk) to the end (hindmilk) of the nursing session (NAS, 1991).

INGESTION OF CONTAMINATED RECREATIONAL ATLANTIC MARINE 

FINFISH: CHILDREN AGED 3 TO <6 YEARS, CENTRAL TENDENCY, 

SUBCHRONIC AVERAGE DAILY DOSE

2.8.1. Introduction

There is the potential for contamination of finfish and shellfish as a result of 

bioaccumulation of certain types of chemicals (e.g., methylmercury and lipophilic compounds 

such as dioxins and PCBs) in fish tissues. This may result in exposure among the general 

population via consumption of marine or freshwater fish. Receptors could include children of 

any age who consume contaminated fish. In this example, the dose via consumption of 

contaminated recreationally caught Atlantic marine finfish is estimated based on the 

concentration of chemicals in Atlantic marine finfish, intake rates of recreationally caught 

Atlantic marine finfish, exposure frequency, and exposure duration. In this example, central 

tendency subchronic average daily doses via ingestion of recreationally caught Atlantic marine 

finfish are evaluated for children (3 to <6 years of age) residing in a contaminated area. Values 

obtained from tables within the EFH (U.S. EPA, 2011a) are cited as EFH Table X-X. 

2.8.2. Dose Algorithm

The ADD of a specified contaminant via ingestion of contaminated marine finfish can be 

estimated as follows:

ADDfish ing =

Cfish × IRfish × EF × ED

BW × AT

(13)

where:

ADDfish ing = potential average daily dose from ingestion of fish caught at a 

contaminated site (mg/kg-d);

Cfish = concentration of a contaminant in uncooked fish (mg/g fish);

IRfish = intake rate of uncooked recreational Atlantic marine finfish for the 

population of interest (g/d);

EF = exposure frequency (d/yr);

ED = exposure duration (yr);
50

BW = average body weight (kg); and

AT = averaging time (d).

2.8.3. Input for Exposure Factor Variables

Cfish―The concentration of a contaminant in Atlantic marine finfish is either the 

measured or predicted concentration, based on modeling. For estimating central tendency doses, 

the mean or median values would be used. For the purpose of the example calculations, it is 

assumed that the mean concentration of chemical “x” in uncooked fish is 1 × 10−3 mg/g.

IRfish―Survey data for Atlantic marine finfish intake rates for children are relatively 

limited. However, a recommended mean consumption of recreationally caught Atlantic marine 

finfish for children 3 to < 6 years of age is 2.5 g/day, as measured uncooked, is provided in EFH 

Table 10-3. The value represents both survey anglers who ate recreational fish during the survey 

period and those that did not, but may eat recreationally caught fish during other periods. EFH 

Table 10-3 (U.S. EPA, 2011a) provides intake rates in terms of the wet weight mass of uncooked 

fish. The assessor should ensure that measurements of the contaminant concentration in fish also 

are on an uncooked, wet weight basis.

EF―Exposure frequency is 350 days/year because the data used in estimating IRfish are 

assumed to represent average daily intake over a long term (i.e., over a year). However, it is 

assumed that the children are away from the contaminated source (i.e., on vacation) for 2 weeks 

during the year.

ED―Exposure duration is the length of time over which exposure occurs. This example 

assumes that children consume recreationally caught marine finfish for only the 3 years of life 

indicated.

BW―EFH Table 8-1 (U.S. EPA, 2011a), reports recommended values for BWs for 

children aged 3- to <6-years old. The mean BW for children in this age group is 18.6 kg.

AT―Because the subchronic ADD is calculated in this example, the averaging time is 

equivalent to the exposure duration. Thus, AT is 1,095 days (i.e., 3 years).

2.8.4. Calculations

ADDfish ing =

(1 × 10−3)

mg

g

× 2.5

g

d

× 350 d

yr

× 3 yr

18.6 kg × 1,095 d
51

ADDfish ing = 1.3 × 10−4 mg

kg-d

2.8.5. Uncertainties

The example presented here is used to represent central tendency doses among children, 

aged 3 to <6 years, via consumption of contaminated recreationally caught Atlantic marine 

finfish. High-end doses may be estimated by replacing the mean intake rate with an 

upper-percentile value or by using a high-end concentration and mean intake rate. The choice of 

which parameter should be set to the high-end would be dependent upon the sensitivities of the 

parameters, professional judgement, and regulatory requirements. In addition, if a bounding 

dose estimate is desired, the concentration in fish also may be set to the maximum measured or 

modeled concentration. It is important to note that the bounding estimate may result in a dose 

estimate that is unreasonably high 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. Implicit in this scenario are 

the assumptions that children, aged 3 to <6 years, remain living near the site of contamination 

over that timeframe and consume only Atlantic marine recreationally caught finfish that were

obtained from the contaminated site. As an alternative, a term denoting the fraction of fish 

assumed to be obtained from the source area could be included in the dose algorithm. Ideally, 

both concentration and intake rate data on a species-specific basis would be preferred. However,

reliable estimates of species-specific intake rates are rarely available. 

In this example, a single value for the average contaminant concentration in fish is used 

to estimate central tendency subchronic dose. This assumes that the average concentration of the 

fish consumed is equal to the sample/modeled average concentration. The variability in average 

contaminant concentration in fish might introduce some degree of uncertainty. In reality, the 

contaminant concentration may vary with the species of fish. Variability may result from 

differences in bioaccumulation of contaminants in different fish species, and in fish differing in 

size and placement in the food chain. Finally, the intake rate value associated with this scenario 

is derived from short-term consumption survey data used to estimate the distribution of the fish 

intake rate over a long period. There are no adjustments made for losses that may occur during 

preparation and cooking. The choice of using uncooked or as-consumed intake rate also depends 
52

on how the contaminant concentration is reported. It is more conservative to use the uncooked 

intake rate values in this scenario; however, if the as-consumed information is desired, data are 

presented in EFH Table 13-69 (U.S. EPA, 2011a) to adjust the intake rate for moisture and fat 

loss during preparation. 

In some instances, it also may be necessary to convert wet weight (either as-consumed or 

uncooked) intakes to dry weight intakes, or to convert wet weight into lipid weight intake rates 

(i.e., whichever state of preparation was used in the study reporting contaminant concentrations 

should also be used for the intake rates). The equations used in these conversions are presented 

in EFH Section 10.9 (U.S. EPA, 2011a). Below are the equations and sample calculations for 

converting the 2.5 g/day wet weight of uncooked fish used in this scenario to dry weight and to 

lipid weight. For these sample calculations, the average moisture and lipid contents for all 

marine fish and shellfish species from EFH Table 10-125 were calculated (U.S. EPA, 2011a). 

The average moisture and lipid content for all marine fish and shellfish species were 75.54% and 

4.05%, respectively. The dry weight intake rate (g/day) is calculated by

IRdw = IRww (

100−W

100 ) (14)

where:

IRdw = dry weight intake rate (g/d);

IRww = wet weight intake rate (g/d); and

W = percentage water content (%).

IRdw = 2.5

g

d

(

100 − 75.54

100 )

IRdw = 0.61

g

d

The lipid weight intake rate (g/day) is similarly calculated by:

IRlw = IRww (

L

100) (15)

where:

IRlw = lipid weight intake rate (g/d);

IRww = wet weight intake rate (g/d); and
53

L = percentage lipid (fat) content (%).

IRlw = 2.5

g

d

(

4.05

100)

IRlw = 1.0 × 10−1

g

d
54

3. EXAMPLE INHALATION EXPOSURE SCENARIOS

Inhalation of a contaminant is not necessarily a simple function of inhalation rate and

BW. The amount of chemical that reaches the target organ is highly dependent on the human 

respiratory anatomy and physiology and the physicochemical properties of the contaminant 

(U.S. EPA, 2009). Current EPA methodology uses the principles of inhalation dosimetry to 

determine the human equivalent concentration (HEC) for calculating an RfC or IUR (U.S. EPA,

2009, 1994). To apply the RfC methodology, it is unnecessary to calculate an inhaled dose when 

using toxicity values from the Integrated Risk Information System (IRIS) in a risk assessment. 

To estimate risk via inhalation, EPA recommends the use of the concentration of the chemical in 

air as the exposure metric (e.g., mg/m3), rather than inhalation intake of a contaminant in air 

based on intake rate and BW (e.g., mg/kg-d). Inhalation risk assessments require an air 

concentration adjusted to represent a continuous exposure. The risk calculations are different for 

noncarcinogens and carcinogens:

 For noncarcinogens, RfCs are used. These are expressed in concentration units. The RfC

methodology uses the measured or modeled concentration of the chemical in the inspired 

air, adjusted to represent a continuous exposure.

 For carcinogens, IRIS uses unit risk values. These are expressed in inverse concentration 

units. In this approach, the unit risk is multiplied by the measured or modeled 

concentration of the chemical in the inspired air adjusted to represent a continuous 

exposure (U.S. EPA, 1994).

Advances in inhalation gas dosimetry show some evidence of higher inhaled doses in 

young children (i.e., 3 months) than in adults (U.S. EPA, 2012c). This life stage may warrant 

alternative modeling approaches or adjustments based on chemical-specific information. More 

information about advances in inhalation gas dosimetry and life stages can be found in EPA’s 

Advances in Inhalation Gas Dosimetry for Derivation of a Reference Concentration (RfC) and 

Use in Risk Assessment (U.S. EPA, 2012c).

Example Exposure Scenarios 3.1 and 3.2 demonstrate how the adjusted air concentrations 

may be calculated. Although EPA recommends the use of the chemical concentration in air as 

the exposure metric, there may be cases where an inhalation dose is of interest. Estimations of 

cumulative doses or analyses of relative pathway contributions are examples where an inhaled 
55

dose may be necessary. Example Exposure Scenarios 3.3 and 3.4 demonstrate the use of 

inhalation rates to fully calculate the ADR and ADD, respectively.

3.1. INHALATION OF CONTAMINATED AIR WHILE PLAYING IN A SCHOOL 

YARD: SCHOOL CHILDREN AGED 6 TO <11 YEARS, CENTRAL TENDENCY, 

SUBCHRONIC ADJUSTED AIR CONCENTRATION

3.1.1. Introduction

Contaminants may be released into the outdoor air from industrial sources or 

transportation. This may result in exposure via inhalation by residents, commercial/industrial 

workers, students, and recreational populations. The following is an example of an inhalation 

exposure estimate for elementary school-age children 6- to <11-years old exposed to

contaminated outdoor air while playing in a school yard. Central tendency subchronic daily 

exposure from inhalation is evaluated for this population. This approach would be used in 

conjunction with subchronic toxicity values to characterize risk of adverse noncancer health 

effects. In this example, the outdoor air concentration is adjusted for the time children spent in 

school to reflect a continuous exposure. Values obtained from tables within the EFH (U.S. EPA, 

2011a) are cited as EFH Table X-X. 

3.1.2. Exposure Algorithm

Adjusted outdoor air concentration via inhalation of contaminated air while playing in a 

school yard would be calculated as follows:

ECoutdoor air adjusted =

Coutdoor air × ET × CF × EF × ED

AT

(16)

where:

ECoutdoor air adjusted = adjusted exposure concentration of contaminant in the outdoor air 

(mg/m3);

Coutdoor air = concentration of contaminant in the outdoor air (mg/m3);

ET = exposure time (min/d);

CF = conversion factor (d/min);

EF = exposure frequency (d/yr);

ED = exposure duration (yr); and

AT = averaging time (d).
56

3.1.3. Input for Exposure Factor Variables

Coutdoor air―The concentration of contaminant in air at the site 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 are used. For the 

purposes of this example, it is assumed that the mean measured concentration of chemical “x” in 

air is 1 × 10−3 mg/m3.

ET―EFH Table 16-19 (U.S. EPA, 2011a) reports the age-specific time spent on the 

playground at school for “doers-only.” The mean exposure time (ET) is 80 minutes/ day for 

children aged 6 to <11 years.

CF―The conversion factor needed to convert the exposure time of minutes to days is

1 day/1,440 minutes.

EF―For this example, exposure frequency is assumed to be 185 days/year. This is 

equivalent to 37 weeks of full-time school, and accounts for 15 weeks off for summer and winter 

vacation, or other school closings.

ED―Exposure duration is the length of time over which exposure occurs. For the 

purposes of this example, the ED for 6- to <11-year-old school children is assumed to be 5 years 

(i.e., first grade through fifth grade). This assumes that the exposure occurs in the same school 

yard where outdoor air contamination exists.

AT―The averaging time is equivalent to the exposure duration because this example 

assumes the assessor is evaluating risk of noncancer health effects. For the purposes of this 

example, the AT is converted to 1,825 days (i.e., 5 years × 365 days/year).

3.1.4. Calculations

Using the exposure algorithm and the input for the exposure factor variables, the 

ECoutdoor air adjusted for elementary school-age children would be as follows:

ECoutdoor air adjusted =

1 × 10−3 mg

m3 × 80 min

d

×

1 d

1,440 min × 185 dyr

× 5 yr

1,825 d

ECoutdoor air adjusted = 2.8 × 10−5 mg

m3
57

3.1.5. Uncertainties

The example presented here represents a central tendency adjusted air concentration of 

contaminant reflecting the inhalation exposures of the general population of elementary school 

children playing in a school yard. A high-end adjusted exposure concentration may be estimated 

by using a high-end concentration and also increasing exposure time or exposure frequency. 

Caution should be used, however, in setting all exposure factor inputs to upper-percentile values, 

as the resulting dose estimates may exceed reasonable maximum exposures for the population of 

interest. The choice of which parameter should be set to the high-end would be dependent upon 

the sensitivities of the parameters, professional judgement, and regulatory requirements.

The uncertainties associated with this example scenario are related to the concentrations 

and assumed exposure time and exposure frequency. Uncertainty related to seasonal and 

weather variations (e.g., temperature, wind direction and strength) may lead to overestimates or 

underestimates of exposure. An underestimate of exposure concentration may also occur if the 

contaminant migrates from outdoors to indoors, resulting in additional exposures. This 

calculation does not account for these additional potential exposures, season or weather 

variations.

INHALATION OF AEROSOLIZED CONTAMINANTS FROM WATER DURING 

AND AFTER SHOWERING: CHILDREN AND TEENS AGED 6 TO <18 YEARS, 

CENTRAL TENDENCY, LIFETIME ADJUSTED AIR CONCENTRATION 

3.2.1. Introduction

Because volatile contaminants can be released into the air from contaminated water, there 

is the potential for exposure among residents via inhalation during and after showering. In this 

example, the lifetime average adjusted exposure concentration from this pathway is evaluated for 

children and teens aged 6 to <18 years. It should be noted that exposures can also result from 

inhalation during other water uses around the household as well as dermal exposures. This 

scenario, however, focuses on the exposures via inhalation during and after showering. The 

approach below would be used for carcinogen exposure when using chronic toxicity values (e.g., 

from IRIS) in a risk assessment. It is assumed that children move away from the contaminated 

source after age 18 (e.g., moving away to attend college). Values obtained from tables within the 

EFH (U.S. EPA, 2011a) are cited as EFH Table X-X. If this is a mutagenic carcinogen, 
58

appropriate ADAFs would need to be applied in accordance with Supplemental Guidance for 

Assessing Susceptibility from Early-Life Exposure to Carcinogens (U.S. EPA, 2005b).

3.2.2. Exposure Algorithm

The adjusted exposure air concentration (ECair adjusted) via inhalation would be calculated 

as follows:

ECair adjusted =

Cair × ET × CF × EF × ED

LT

(17)

where:

ECair adjusted = adjusted exposure concentration of contaminant in the air during and 

after showering (mg/m3);

Cair = concentration of contaminant in the air during and after showering 

(mg/m3);

ET = exposure time (min/d);

CF = conversion factor (d/min);

EF = exposure frequency (d/yr);

ED = exposure duration (yr); and

LT = lifetime (d).

3.2.3. Input for Exposure Factor Variables

Cair―The concentration of contaminants in air is either the measured or predicted 

concentration based on modeling, of the chemical of interest in the air of the shower room. For 

estimating central tendency exposures, mean or median values are used. For the purposes of this 

example, it is assumed that mean measured concentration of chemical “x” in air is 

1 × 10−3 mg/m3.

ET―Exposure time is the estimated time spent showering and in the bathroom after 

showering occurs. EFH Table 16-29 (U.S. EPA, 2011a) presents the estimated time spent 

showering and time spent in the shower room immediately following showering. For the 

purpose of this example, the mean ET for children ages 6 to <11 years is 24 minutes/day and for 

teens ages 11 to <16 years is 26 minutes/day. Although the Guidance on Selecting Age Groups 

for Monitoring and Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA, 

2005a) recommends 16 to < 21 years as the next age group for children, for this scenario it was 
59

assumed that children moved away from the contaminated source at age 18. Time spent in the 

shower and immediately following showering is not available for children 16 to < 18 years. 

Therefore, the value for 16 to < 21 years (i.e., 28 minutes/day) is used in this example. The 

average of the two 5-year and the 2-year age ranges is calculated as:

ET =

(24 min

d

× 5 yr) + (26 min

d

× 5 yr) + (28 min

d

× 2 yr)

12 yr

ET = 25.5

min

d

CF―The conversion factor needed to convert the exposure time of minutes to days is

1 day/1,440 minutes.

EF―Exposure frequency is the number of times an exposure is expected to occur in a 

year and is expressed in days/year. For the purposes of this example, it is assumed that children 

shower 350 days of the year (i.e., once per day) assuming that they are away from the 

contaminated sources for approximately 2 weeks out of the year.

ED―Exposure duration is the length of time over which exposure occurs. For the 

purpose of this example, the ED is 5 years for the first two life stages and 2 years for the third

life stage, i.e., 12 total years.

LT―The averaging time is equivalent to the lifetime of an individual in the receptor 

population because this example calculates the average exposure air concentration over a 

lifetime. For the purpose of this example, the average lifetime of 70 years for men and women is

used because the exposure is assumed to reflect the general population. The value is converted 

to 25,550 days (i.e., 70 years × 365 days/year).

3.2.4. Calculations

Using the exposure algorithm and exposure factor inputs shown above, the ECair adjusted for 

children and teens during and after showering would be as follows:

ECair adjusted =

(1 × 10−3)

mg

m3 × 25.5

min

d

×

1 d

1,440 min × 350 dyr

× 12 yr

25,550 d
60

ECair adjusted = 2.9 × 10−6 mg

m3

3.2.5. Uncertainties

The example presented here is used to represent a central tendency adjusted air 

concentration for children and teens from exposure via inhalation to contaminated air during and 

after showering. An adjusted air concentration, based on high-end exposures may be estimated 

by using a combination of mean and upper-percentile values for the exposure factors. The 

choice of which parameter should be set to the high-end would be dependent upon the 

sensitivities of the parameters, professional judgement, and regulatory requirements. If a 

bounding dose estimate is desired, the concentration of contaminants may be set to the maximum 

measured or modeled concentrations.

Uncertainties in this scenario relate to assumptions regarding the concentration variable 

used in the calculation. It was assumed that the concentration will be steady. It is unclear how 

well the average concentration of contaminant in indoor air represents the true time weighted 

average. This example assumes that the concentration was measured. Assessors typically 

estimate a different concentration in the shower stall than in the bathroom immediately after 

showering using models; however there are uncertainties with the models used to estimate these 

concentrations. The concentration will vary depending on various factors including for example: 

water temperature, volatility of the chemical, bathroom size, use of exhaust fan, water flow 

rate—just to name a few. This scenario also assumes that children are not exposed to the 

contaminant at other locations where they may spend their time. Another uncertainty relates to 

the amount of time spent showering and in the shower room immediately after. This example 

assumes that children take showers instead of baths. The time spent taking baths will be slightly 

higher than the time spent taking showers. It also assumes that children take one shower per day.

INHALATION OF CONTAMINATED INDOOR AIR: RESIDENTIAL CHILDREN 

AGED 3 TO <11 YEARS, BOUNDING, ACUTE DOSE RATE

3.3.1. Introduction

At sites where localized volatile contaminants intrude into residences either from the use 

of contaminated water in the household or from the use of commercial products or other 

materials results in indoor air contamination, there exists the potential for exposure among 
61

residents via inhalation. In this example, a one-time exposure via inhalation of contaminated 

indoor air is assumed and the bounding acute dose from this pathway is evaluated for children 

aged 3 to <11 years playing at a residence. Values obtained from tables within the EFH (U.S. 

EPA, 2011a) are cited as EFH Table X-X. An ADR is calculated in this example to be used as an 

input in a cumulative dose estimate or a relative pathway contribution analysis. This inhalation 

dose rate is not used to estimate risks. Risks from the inhalation pathway would be estimated by 

calculating a time weighted average exposure concentration or a peak exposure concentration to 

be used with an acute inhalation toxicity value. For chronic exposure scenarios, RfCs or IURs

would be used, as appropriate.

3.3.2. Dose Algorithm

The ADR via inhalation of contaminated indoor air is calculated as follows:

ADRindoor air inh =

Cindoor air × ET × IR × ED

AT

(18)

where:

ADRindoor air inh = acute dose rate of contaminated indoor air (mg/kg-d);

Cindoor air = concentration of contaminants in the indoor air (mg/m3);

ET = exposure time (min/d);

IR = inhalation rate (m3/min-kg);

ED = exposure duration (d); and

AT = averaging time (d).

3.3.3. Input for Exposure Factor Variables

Cindoor air―The concentration of a contaminant 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 bounding doses, the maximum values would be used. For the purpose of the example 

calculations, it is assumed that the modeled bounding concentration of chemical “x” in air from 

the breathing zone is 1 × 10-3 mg/m3.

ET―EFH Table 16-1 (U.S. EPA, 2011a) reports the age-specific time spent indoors at a 

residence over a 24-hour period. This scenario represents a one-time exposure for children at 

any age within the age range of 3 to <11 years. Therefore, a time weighted average exposure 
62

time was estimated to represent a child within that age range. The upper-percentile times are 

1,355 minutes/day (22.6 hours/day) for ages 3 to <6 years and 1,275 minutes/day 

(21.3 hours/day) for children ages 6 to <11 years. The weighted average of these is calculated as 

follows:

ET =

(1,355 min

d

× 3 yr) + (1,275 min

d

× 5 yr)

8 yr

ET = 1,305

min

d

IR―The recommended inhalation rates on a BW basis for children during short-term 

exposures are given in EFH Table 6-18 (U.S. EPA, 2011a). For the purpose of this example, it is 

assumed that the children spend some time sleeping and napping, some time playing at light 

intensity, and some time sedentary. A weighted average inhalation rate is calculated using 

inhalation rate data for each age range (i.e., 3 to <6 years and 6 to <11 years). Children age 3 to 

<6 years spend an average of 681 minutes/day (11.4 hours/day) sleeping or napping (EFH

Table 16-25). Whereas children age 6 to <11 years spend 613 minutes/day (10.2 hours/day) 

sleeping or napping. In this example, the rest of the time is apportioned equally between 

sedentary and light activities for each age range (i.e., [(1,355 minutes/day

− 681 minutes/day) ÷ 2 = 337 minutes/day] for children 3 to <6 years; and [(1,275 minutes/day –

613 minutes/day) ÷ 2 = 331 minutes/day] for children 6 to <11 years). The 95th percentile 

inhalation rate values for sleeping or napping are 3.5 × 10−4 m3/minute-kg for children from age 

3 to <6 years and 2.1 × 10−4 m3/minute-kg for children from age 6 to <11 years (EFH

Table 6-18). The 95th percentile sedentary inhalation rate values are 3.5 × 10−4 m3/minute-kg for 

children from age 3 to <6 years and 2.2 × 10−4 m3/minute-kg for children from age 6 to 

<11 years. The 95th percentile inhalation rate values for a light intensity activity are 8.7 × 10−4

m3/minute-kg for children from age 3 to <6 years and 5.3 × 10−4 m3/minute-kg for children from 

age 6 to <11 years. Using these values, the adjusted inhalation rate for activity intensity is 

calculated below for each age range.
63

IR3 to<6 =

[

((3.5 × 10−4)

m3

min-kg × 681 mind

) + ((3.5 × 10−4)

m3

min-kg × 337 mind

) +

((8.7 × 10−4)

m3

min-kg × 337 mind

)

]

1,355 min

d

IR3 to<6 = 4.8 × 10−4 m3

min-kg

IR6 to<11 =

[

((2.1 × 10−4)

m3

min-kg × 613 mind

) + ((2.2 × 10−4)

m3

min-kg × 331 mind

) +

((5.3 × 10−4)

m3

min-kg × 331 mind

)

]

1,275 min

d

IR6 to<11 = 3.0 × 10−4 m3

min-kg

The weighted average IR is calculated as follows:

IR3 to<11yr =

((4.8 × 10−4)

m3

min-kg × 3 yr) + ((3.0 × 10−4

)

m3

min-kg × 5 yr)

8 yr

IR3 to<11yr = 3.7 × 10−4 m3

min-kg

ED―Exposure duration is the length of time over which exposure occurs. For the 

purpose of this example, the exposure duration is assumed to be 1 day.

AT―Because the ADR is calculated in this example, the averaging time is equivalent to 

the exposure duration—1 day. 
64

3.3.4. Calculations

Using the dose algorithm and exposure factors shown above, the ADRindoor air inh is 

estimated using the input for children ages 3- to <11-years old.

ADRindoor air inh =

1 × 10−3 mg

m3 × 1,305 min

d

× 3.7 × 10−4 m3

min-kg × 1 d

1 d

ADRindoor air inh = 4.8 × 10−4 mg

kg-d

3.3.5. Uncertainties

The example presented here is used to represent bounding dose among residential 

children from inhalation of contaminated indoor air. Central tendency doses may be estimated 

by using mean values for contaminant concentration, exposure time, and inhalation rate. If a 

high-end dose estimate is desired, some high-end and some central tendency input values may be 

used. The choice of which parameter should be set to the high-end would be dependent upon the 

sensitivities of the parameters, professional judgement, and regulatory requirements.

The uncertainties associated with this example scenario are related to the variation in 

activity level of the children during the day. Another uncertainty relates to the contaminant 

concentration. A contaminant will disperse and have varying concentrations throughout the 

residence. These variations may be modeled, but for the purpose of this example it is assumed 

that the concentration is constant throughout the home. In reality, the concentration will be 

affected by seasonality, temperature, and house characteristics. In addition, this scenario 

assumes that children are not exposed to the contaminant outside the residence.

INHALATION OF CONTAMINATED AIR DURING BUS TRANSPORTATION: 

SCHOOL CHILDREN AND TEENS AGED 6 TO <16 YEARS, HIGH-END, 

CHRONIC AVERAGE DAILY DOSE

3.4.1. Introduction

Air contamination on a bus may occur via (1) intrusion of volatile contaminants from 

outdoor ambient air, (2) volatilization from personal consumer products, and (3) volatilization 

from commercial materials in seats and flooring on the bus. This may result in exposure via 

inhalation. For the purposes of this example, exposure among school children and teens 6 to 
65

<16 years old via inhalation of contaminated air occurs during bus transportation to and from 

school, which may include infiltration of the bus exhaust. Values obtained from tables within 

the EFH (U.S. EPA, 2011a) are cited as EFH Table X-X. High-end chronic daily dose from 

inhalation is evaluated for doers-only of this population. An ADD is calculated in this example 

to be used as input in a cumulative dose estimate or a relative pathway contribution analysis. 

This inhalation dose estimate is not used to estimate risks. Risks from the inhalation pathway 

would be estimated by calculating a time weighted average concentration or a peak concentration 

to be used with a chronic toxicity value (e.g., RfC or IUR).

3.4.2. Dose Algorithm

Dose via this pathway would be calculated as follows:

ADDair inh =

Cair × IR × ET × EF × ED

AT

(19)

where:

ADDair inh = average daily dose of contaminated air on bus transportation (mg/kg-d);

Cair = concentration of contaminant in the air on bus transportation (mg/m3);

IR = inhalation rate (m3/min-kg);

ET = exposure time (min/event);

EF = exposure frequency (events/yr);

ED = exposure duration (yr); and

AT = averaging time (d).

3.4.3. Input for Exposure Factor Variables

Cair―The concentration of contaminant in air at the site is either the measured or 

predicted concentration, based on modeling, of the chemical of interest in the air on bus 

transportation. For the purposes of this example, for a high-end dose, the 95th percentile 

concentration of chemical “x” in air is 1 × 10-3 mg/m3.

IR―The recommended inhalation rates for children during short-term exposures are 

given in EFH Table 6-2 (U.S. EPA, 2011a). For the purpose of this example, it is assumed that 

the children’s activity level is sedentary/passive. The mean inhalation rate values used for this 

example are 1.60 × 10−4 m3/minute-kg for children aged 6 to <11 years and 

1.05 × 10−4 m3/minute-kg for children aged 11 to <16 years.
66

ET―The exposure time is estimated from EFH Table 16-23 (U.S. EPA, 2011a) for 

doers-only on bus transportation. The 95th percentiles for school children aged 6 to <11 years 

and teens aged 11 to <16 years are 107 minutes and 131 minutes per day, respectively.

EF―Exposure frequency is assumed to be 185 days/year for this example. This is 

equivalent to 37 weeks of full-time school, accounting for 15 weeks off for summer and winter 

vacation, or other school closings.

ED―Exposure duration is the length of time over which exposure occurs. For the 

purpose of this example, the ED is 5 years for each age range (10 years total). This assumes that 

all 10 years of the school commuting time are spent traveling through the same contaminated 

area and that the same contaminants are present in the bus exhaust.

AT―Because the chronic ADD is being calculated in this example, the averaging time is 

equivalent to the exposure duration. For the purposes of this example, the averaging time for 

each age group is converted to 1,825 days (i.e., 5 years × 365 days/year).

3.4.4. Calculations

Using the dose algorithm and input for the exposure factors, the ADD for each of the age 

ranges is calculated in Table 11.

Table 11. Summary of ADD for children and teens aged 6 to 16 years for 

inhalation of contaminated air on bus transportation

Equation 19

input and output

Age ranges

6 to <11 yr 11 to <16 yr

C (mg/m3) 1 × 10−3 1 × 10−3

IR (m3/min-kg) 1.60 × 10−4 1.05 × 10−4

ET (min/d) 107 131

EF (d/yr) 185 185

ED (yr) 5 5

AT (d) 1,825 1,825

ADD (mg/kg-d) 8.7 × 10−6 7.0 × 10−6

The ADD for school children and teens averaged over the 10 years would be calculated as 

follows:
67

ADDair inh =

(8.7 × 10−6 mg

kg-d

× 5 yr) + (7.0 × 10−6 mg

kg-d

× 5 yr)

10 yr

ADDair inh = 7.9 × 10−6 mg

kg-d

3.4.5. Uncertainties

The example presented here represents high-end doses among the general population of 

school children and teens from the inhalation of contaminated air during bus transportation and 

uses a high-end concentration with a mean inhalation rate. Alternatively, the high-end can be 

estimated by using a mean concentration with a high-end inhalation rate. The choice of which 

parameter should be set to the high-end would be dependent upon the sensitivities of the 

parameters, professional judgement, and regulatory requirements. Central tendency doses may 

be estimated by decreasing exposure time and using a mean concentration instead of a 

95th percentile concentration.

The uncertainties associated with this example scenario are related to the contaminant 

concentration and assumed exposure time and exposure frequency. The concentration may be 

uncertain because it is typically obtained from outdoor measurements and using some 

penetration modeling factors or tools. The study used to derive the assumption for exposure time 

was conducted with small sample sizes and over short data collection period (24 hours) (U.S. 

EPA, 2011a). Therefore, the data may not be representative of long term behaviors. The 

exposure frequency may be higher if children attend summer school. This scenario also assumes 

that children are not exposed to the contaminant at other locations where they may spend time. 

There are also uncertainties associated with the inhalation rate data and assumptions regarding 

activity levels. These inhalation rates were derived from a wide range of groups within the 

U.S. population using indirect methods (U.S. EPA, 2011a).
68

4. EXAMPLE DERMAL EXPOSURE SCENARIOS

DERMAL CONTACT WITH CONTAMINATED SOIL: TEEN ATHLETES AGED

11 TO <16 YEARS, CENTRAL TENDENCY, SUBCHRONIC AVERAGE DAILY 

DOSE

4.1.1. Introduction

At sites where localized soil contamination exists, there is the potential for exposure via 

dermal contact with soil during outdoor activities. Exposure also may occur from soil that is 

tracked into the home or other buildings (i.e., schools, businesses, etc.). Therefore, receptors 

could include nearby residents, students, and recreational populations. Estimating the dose 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, the dose to teen athletes 

via dermal contact with contaminated soil is calculated. Values obtained from tables within the 

EFH (U.S. EPA, 2011a) are cited as EFH Table X-X. A subchronic dermal ADD from soil 

contact is evaluated for the teen athlete. For this example, a teen athlete (aged 11 to <16 years) 

playing soccer for one-half of the year is evaluated. It is assumed that the athlete is exposed to 

the same source of contaminated soil during the entire duration of exposure. An average soil 

concentration is used to account for the variability of soil concentration at the site.

4.1.2. Dose Algorithm

The ADD of a contaminant by dermal contact in a soil would be calculated as follows:

ADDABS soil contact dermal =

Csoil × CF × EF × ED × ABS ×

SA

BW × AFsoil

AT

(20)

where:

ADDABS soil contact dermal = absorbed average daily dose from dermal contact with 

contaminated soil (mg/kg-d);

Csoil = concentration of contaminant in the soil at the site (mg/kg);

CF = conversion factor (kg/mg);

EF = exposure frequency (events/yr);
69

ED = exposure duration (yr);

ABS = absorption fraction; this value is chemical specific (unitless); 

SA/BW = surface area of the skin that contacts the soil (cm2/event-kg);

AFsoil = adherence factor for soil (mg/cm2); and

AT = averaging time (d).

4.1.3. Input for Exposure Factor Variables

Csoil―The concentration of contaminant in soil at the site is either the measured or 

predicted concentration based on modeling, of the chemical of interest in the soil at the site of 

interest. For the purposes of the example calculations, it is assumed that the mean measured 

concentration of chemical “x” in soil to which the athlete is exposed is 1 × 10−3 mg/kg. Also

assumed is that the concentration of contaminant in the soil that contacts the skin surface and is 

available to be absorbed.

CF―A conversion factor of 1 × 10−6 kg/mg is required to convert between mg/kg and 

kg/mg.

EF―Exposure frequency is the number of times that exposure is expected to occur in a 

year. Exposure frequency 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, 6 months/year 

(i.e., assumes no exposure associated with this athletic activity during the winter and summer 

months). It should be noted 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 of

this scenario is that exposure (and absorption of the contaminants through 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. Also assumed is that one ‘event’ 

occurs on each of the 130 days/year; on these occasions, soil adheres to the skin and remains 

there for the duration of the exposure event (i.e., until the fraction of contaminant specified in the 

absorption fraction (ABS) assumption below has been absorbed). However, in some cases 

alternate loading and removal mechanisms may affect the frequency of events (i.e., if hand

washing and reloading of soil on the skin occurs).
70

ED―Exposure duration is the length of time over which exposure occurs. For the 

purposes of this example, the ED for 11- to <16-year-old teen is assumed to be 5 years. This 

assumes that 5 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 also has 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, 2004b). This document is a source of data on dermal absorption. 

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 (i.e., 10%). Thus, it is 

assumed that 10% of the chemical in the soil contacting the skin is absorbed.

SA/BW―SA/BW is the ratio of skin surface area to BW and is expressed as cm2of skin 

surface area per kg of BW. Assumptions have been made regarding the surface area of specific 

body parts that are expected to be exposed to soil per event. For this example scenario (i.e., teen 

athlete), it is assumed that an individual will wear short pants and a short-sleeved shirt, and that 

the hands, arms, and legs will come into contact with the soil. EFH Table 7-2 provides the mean 

recommended surface area contribution of hands, arms, and legs in m2needed to obtain a 

summed surface area value. Next, the summed surface area value is converted into cm2using the 

conversion factor of 1 m2 = 10,000 cm2. The total estimated surface area of the hands, arms, and 

legs is divided by the BW to yield the SA/BW ratio (cm2/kg). The mean BW for children in this 

age range, 56.8 kg, was obtained from EFH Table 8-1.

SAhands =

0.072 m2 × 10,000 cm2

m2

56.8 kg = 12.7

cm2

kg

SAarms =

0.227m2 × 10,000 cm2

m2

56.8 kg = 40.0

cm2

kg

SAlegs =

0.483 m2 × 10,000 cm2

m2

56.8 kg = 85.0

cm2

kg
71

AFsoil―The assessor should use adherence factor data that most closely resemble the 

exposure scenario of concern. In this case, the mean AFsoil for outdoor activities were used. The 

soil adherence factors for this scenario were obtained from EFH Table 7-4 (U.S. EPA, 2011a)

and are tabulated in Table 12.

Table 12. Soil adherence factors (AFsoil) for teen athletes playing soccer

Body parts Mean adherence factors (mg/cm2)

Hands 0.11

Arms 0.011

Legs 0.031

AT―Because the ADD is being calculated for a specific age range (e.g., 11- to 

<16-year-old teens), the averaging time is equivalent to the exposure duration, except that the 

duration is expressed in days. For use in the calculations, this value is converted to 1,825 days 

(i.e., 5 years × 365 days/year).

4.1.4. Calculations

Using the dose algorithm and exposure factor inputs shown above, the 

ADDABS soil contact dermal would be calculated for each body part exposed and summed across body 

parts as follows:

ADDABS soil contact dermal =

(

(1 × 10−3)

mg

kg × (1 × 10−6

)

kg

mg

× 130 events

yr

× 5 yr × 0.1

) ×

(

(12.7

cm2

event-kg × 0.11 mg

cm2) + (40.0

cm2

event-kg × 0.011 mg

cm2) + (85.0

cm2

event-kg × 0.031 mg

cm2)

)

1,825 d

ADDABS soil contact dermal = 1.6 × 10−10 mg

kg-d

4.1.5. Uncertainties

The example presented here is used to represent central tendency doses among teen 

athletes, aged 11 to <16 years, from dermal contact with contaminated soil. High-end doses may 

be estimated by assuming a different clothing scenario and replacing the assumptions regarding 

areas of the body exposed (e.g., including the face and torso). Alternatively, exposure frequency 
72

may be increased to estimate high-end doses. If a bounding dose estimate is desired, the 

concentration in soil may be set to the maximum measured or modeled concentration, the 

assumed frequency of exposure may be increased (e.g., 250 times/year; 5 days/week;

12 months/year), and the clothing scenario may be revised to increase the areas of the body 

exposed. It is important to note that the bounding estimate results in dose estimates that may be 

unreasonably high 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 

EFH (U.S. EPA, 2011a; see Table 12). 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 1 day. Multiple soil contact events 

in a single day are still treated as one event. Use of a 1-day exposure event is consistent with 

absorption values, which typically are 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 reasonable that individuals may shower or 

bathe after a sporting event. 

Selection of the clothing scenario or percentage of the body exposed should be based on 

the assessor’s 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 result in uncertainty 

in the assessment. In addition, clothing is not 100% effective in blocking exposure as dust can 

penetrate through cloth or deposit under loose clothing. In the EFH (U.S. EPA, 2011a), EPA

recognizes the uncertainty associated with the surface area and adherence data and concludes 

that although there may be some selection bias associated with the recommended surface areas, 

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.
73

DERMAL CONTACT WITH INORGANIC CONTAMINANTS WHILE WADING 

IN A RECREATIONAL POND: CHILDREN AGED 6 TO <16 YEARS, 

BOUNDING, ACUTE DOSE RATE

4.2.1. Introduction

The potential for exposure to chemical substances exists at sites where local surface 

water bodies (i.e., streams, ponds, lakes, bays, or rivers) have become contaminated. Children 

may be exposed to chemicals in the water via dermal absorption as a result of swimming and/or 

wading. Acute dose 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 in contact with the skin, exposure frequency, and exposure time. For the purposes of 

this example, surface water exposure among wading children (aged 6 to <16 years) is evaluated. 

Dermal exposure is assessed based on bounding acute exposure to an inorganic chemical while 

wading in contaminated surface water. Values obtained from tables within the EFH (U.S. EPA, 

2011a) are cited as EFH Table X-X. 

4.2.2. Dose Algorithm

The ADR of an inorganic contaminant via dermal contact while wading is calculated as 

follows:

ADRwading water dermal =

DAevent × SA × EF × ED

BW × AT

(21)

where:

ADRwading water dermal = acute potential dose from dermal contact in recreational surface 

water while wading (mg/kg-d);

DAevent = absorbed dose per hour (mg/cm2-event);

SA = surface area of the skin (cm2);

EF = exposure frequency (events/d);

ED = exposure duration (d); 

BW = body weight of child (kg); and

AT = averaging time (d).

4.2.3. Input for Exposure Factor Variables

DAevent―The absorbed dose per event (DAevent) is estimated considering the following 

factors:
74

 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, 2004b, 1997a, 1992b). For a 

dermal exposure in water using organic chemicals, see the approach presented in Scenario

4.3―Dermal Contact with an Organic Contaminant in Water while Showering. For inorganic 

chemicals, EPA recommends using the steady-state approach to estimate dermally absorbed 

doses. In this approach,

DAevent = Kp × ET × Cw (22)

where:

DAevent = absorbed dose per event (mg/cm2-event);

Kp = dermal permeability coefficient of compound in water (cm/hr);

ET = event time (hr/event); and

Cw = chemical concentration in water (mg/cm3).

For the purpose of this example, the inorganic chemical “x” is used. It is assumed that 

chemical “x,” a permeability coefficient of 1 × 10−3 cm/hour, and a maximum chemical 

concentration of 1 × 10−6 mg/cm3.

ET―EFH Table 16-19 (U.S. EPA, 2011a) reports time spent in selected outdoor 

locations for children from 6 to <16 years of age. The 95th percentile exposure time spent in 

pool, river, or lake (doers-only) for children aged 6 to <11 years is 359 minutes/day 

(6.0 hours/day) and 228 minutes/day (3.8 hours/day) for children aged 11- to <16-years old. 

Assuming that these exposure times represent an event occurring over the course of 1 day, the 

exposure time would be 6 hours/event for children aged 6 to <11 years and 3.8 hours/event for 

children aged 11 to <16 years (i.e., a child’s skin is immersed in water for a total of either 6 or 

3.8 hours over the course of the daily event, depending on the age of the child).

This results in a DAevent calculation for children aged 6 to <11 years of:
75

DAevent = (1 × 10−3)

cm

hr × 6

hr

event

× (1 × 10−6)

mg

cm3

DAevent = 6 × 10−9 mg

cm2-event

This results in a DAevent calculation for children aged 11 to <16 years of:

DAevent = 1 × (1 × 10−3)

cm

hr × 3.8

hr

event

× (1 × 10−6)

mg

cm3

DAevent = 3.8 × 10−9 mg

cm2-event

SA―The surface area of the skin of a child (aged 6 to <16 years) for various body parts 

can be found in EFH Table 7-2 (U.S. EPA, 2011a). In this scenario, wading is assumed; 

therefore, only the SA of the legs and feet will be used. In this example, mean surface areas of 

the legs and feet are used because surface area and BW are strongly correlated and the mean 

values are most representative of the surface area of individuals with an average BW. Because 

surface area is divided by the body weight in the dose equation, using an upper-percentile surface 

area with an upper-percentile BW would be similar to using a mean surface area with a mean 

BW. The estimates are given in m2and must be converted to cm2 (1 m2 = 10,000 cm2). For this 

example, the surface area is 0.311 m2 for legs and 0.073 m2 for feet (3,110 + 730 = 3,840 cm2), 

respectively, for ages 6 to <11 years, and 0.483 m2and 0.105 m2 (4,830 + 1,050 = 5,880 cm2) for 

legs and feet, respectively, for ages 11 to <16 years.

EF―Exposure frequency is assumed to be one event per day.

ED―Exposure duration is the number of days over which exposure occurs. For the 

purposes of this example, the acute ED is assumed to be 1 day.

BW―EFH Table 8-1 (U.S. EPA, 2011a) reports recommended BWs for children from 6 

to <16 years of age. The BW for boys and girls are averaged for ages 6 to <16 years. This 

calculation, using the mean of this distribution, also is weight averaged according to the number 

of years in each age range. For children aged 6 to <11 years of age, the mean recommended BW

is 31.8 kg. For children aged 11 to <16 years of age, the mean recommended BW is 56.8 kg.

AT―Because the potential acute bounding dose is being calculated, the averaging time is 

equivalent to the ED of 1 day.
76

4.2.4. Calculations

Using the dose algorithm and the input for the exposure factors, the ADRwading water dermal

for children aged 6 to <11 and 11 to <16 is calculated in Table 13.

Table 13. Summary of ADR for children aged 6 to <16 years for acute 

potential dose from dermal contact in recreational surface water while 

wading

Equation 21

input and output

Age ranges

6 to <11 yr 11 to <16 yr

DAevent (mg/cm2-event) 6 × 10−9 3.8 × 10−9

SA (cm2) 3,840 5,880

EF (events/d) 1 1

ED (d) 1 1

AT (d) 1 1

BW (kg) 31.8 56.8

ADR (mg/kg-d) 7.2 × 10−7 3.9 × 10−7

The ADRwading water dermal averaged over the 10 years of exposure for children aged 6 to <11 

and 11 to <16 is calculated as follows:

ADRwading water dermal =

[

(5 yr × 7.2 × 10−7 mg

kg-d

)

+ (5 yr × 3.9 × 10−7 mg

kg-d

)

]

10 yr

ADRwading water dermal = 5.6 × 10−7 mg

kg-d

4.2.5. Uncertainties

The example presented here is used to represent bounding doses among children aged 6 

to <16 years while wading in surface water. Note that central tendency doses may be calculated 

by using mean concentrations and exposure time, and a lower FA.

There are uncertainties related to calculation of the absorbed dose per surface water 

exposure event (e.g., DAevent). As noted in 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 
77

considered highly uncertain” (U.S. EPA, 1992b). A lack of measured data for a variety of 

chemicals makes the validation of the model difficult. There are also uncertainties associated 

with the surface areas and exposure times used in this example scenario.

DERMAL CONTACT WITH AN ORGANIC CONTAMINANT IN WATER WHILE 

SHOWERING: CHILDREN AND TEENS, AGED 6 TO <16 YEARS HIGH-END, 

LIFETIME AVERAGE DAILY DOSE

4.3.1. Introduction

The potential for exposure to chemical substances exists if children and teens shower in 

water from a contaminated source or in water that has been treated with substances that convert 

into toxicants over time. Receptors could include any children and teens who shower using such 

water. The dose via dermal contact considers not only the chemical concentration in the water, 

but also the surface area of the skin in contact with the water, the behavior of the chemical when 

it comes in contact with the skin, exposure duration, exposure time, and exposure frequency. 

This example examines the high-end dermal dose via showering in contaminated water for 

children and teens aged 6 to <16 years (age ranges: 6 to <11 and 11 to <16 years) and calculates 

the ADD for both age ranges, then weights the average daily doses according to the length of 

time these exposures occur to calculate the LADD. Values obtained from tables within the EFH 

(U.S. EPA, 2011a) are cited as EFH Table X-X. In this example, it is assumed that the receptors

are not exposed to the contaminant again for the remainder of their lives. The LADD is 

calculated because the contaminant in this scenario is assumed to be a carcinogen and the 

carcinogen toxicity values are expressed as a lifetime value.

4.3.2. Dose Algorithm

Dose via this pathway would be calculated as follows:

LADDshower water dermal =

DAevent × SA × EV × EF × ED

BW × AT

(23)

where:

LADDshower water dermal = absorbed lifetime average daily dose from dermal contact with 

water during showering (mg/kg-d);

DAevent = absorbed dose per event (mg/cm2-event);

SA = surface area of the skin (cm2);

EV = event frequency (events/d);
78

EF = exposure frequency (d/yr);

ED = exposure duration (yr);

BW = body weight of child (kg); and

AT = averaging time (d).

4.3.3. Input for Exposure Factor Variables

DAevent―The absorbed dose per event (mg/cm2-event) is estimated considering the 

following factors:

 The permeability coefficient from water,

 The chemical concentration in water, and

 The event duration.

Current EPA policy directs differing approaches to estimate DAevent with respect to 

inorganic and organic chemicals (U.S. EPA, 2004b, 1992b). For inorganic chemicals, the EPA 

recommends using a steady-state approach to estimate dermal absorption doses. This approach 

is illustrated in Scenario 4.2―Dermal Contact with Inorganic Contaminants while Wading in a 

Recreational Pond.

For organic chemicals, EPA provides two equations. The choice of appropriate equation 

is based on the event duration versus the lag time per event. If the duration of the event (tevent) is 

less than the time to reach steady-state (2.4τ), then the following equation is used to estimate 

DAevent (U.S. EPA, 2004b, 1992b):

If tevent ≤ t*, then: DAevent = 2 × FA × Kp × Cw √

6 × τ × tevent

π

(24)

where:

DAevent = absorbed dose per event (mg/cm2-event);

FA = fraction available for absorption (dimensionless);

Kp = dermal permeability coefficient of compound in water (cm/hr);

Cw = chemical concentration in water (mg/cm3);

τ = lag time per event (hr/event); 

tevent = event duration (hr/event); and

t* = time to reach steady-state.
79

If the duration of the event (tevent) is greater than the time to reach steady-state (2.4τ), 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. U.S. EPA (2004) indicates that the lag time is the time during which absorption 

continues after the exposure has ended; for chemicals that exhibit a long lag time, “some of the 

chemical dissolved into skin may be lost due to desquamation during that absorption period.” It 

should be noted that the fraction available for absorption (FA) is different than the absorption 

fraction used in Scenario 4.1―Dermal Contact with Soil (ABS). The variable FA is used to 

account for the loss of chemical due to the desquamation of the outer skin layer and a 

corresponding reduction in the absorbed dermal dose.

The following equation is used to estimate this DAevent (U.S. EPA, 2004b, 1992b):

If tevent > t*, then: DAevent = FA × Kp × Cw [

tevent

1 + B

+ 2τ (

1 + 3B + 3B

2

(1 + B)

2 )] (25)

where:

DAevent = absorbed dose per event (mg/cm2-event);

FA = fraction absorbed (dimensionless);

Kp = dermal permeability coefficient of compound in water (cm/hr);

Cw = chemical concentration in water (mg/cm3);

τ = lag time per event (hr/event);

tevent = event duration (hr/event);

B = dimensionless ratio of the permeability coefficient of a compound 

through stratum corneum relative to its permeability coefficient across 

the viable epidermis; and

t* = time to reach steady-state.

Guidance for using these equations is detailed in Dermal Exposure Assessment: 

Principles and Applications (U.S. EPA, 1992b) and Risk Assessment Guidance for Superfund, 

Part E (U.S. EPA, 2004b). The organic chemical benzene is used for the purposes of this

example. Benzene, estimates for which are given in Appendix B of Risk Assessment Guidance 

for Superfund, Part E (U.S. EPA, 2004b), has a molecular weight (MW) of 78.1 and a log Kow of 

2.13. The Kp for benzene is 1.5 × 10−2 cm/hour and the FA is 1.0. To determine which equation 
80

must be used to calculate DAevent, the lag time per event (τ) must be calculated. The following 

equation can be used:

τ =

lsc

2

6 Dsc

(26)

In this equation, lsc (the thickness of the stratum corneum) is 10−3 cm. This is a default 

recommended for use by EPA’s Risk Assessment Guidance for Superfund, Part E (U.S. EPA, 

2004b). Dsc is the stratum corneum diffusion coefficient (cm2/hour), which can be calculated as 

follows:

Dsc = 10(−2.80−0.0056 MW) × lsc (27)

Using eq 26, the lag time per event (τ) is 0.29 hour/event, as shown in Table B-3 of Risk 

Assessment Guidance for Superfund, Part E (U.S. EPA, 2004b). Because the time to reach 

steady-state (t*) is defined as 2.4 τ, the t* actually would be 0.70 hour or 42 minutes (U.S. EPA, 

2004b). Based on EFH Table 16-1 (U.S. EPA, 2011a), the 95th percentile recommended value 

for shower duration is 41 minutes for a child aged 6 to <11 years, and 40 minutes for a child 

aged 11 to <16 years. Using these values as the event duration (tevent), tevent ≤ t*; thus, eq 24

would be used for the calculation of DAevent. If tevent had been greater than t*, eq 25 would be 

used, and variable B would need to be calculated, as shown in eq 28:

B = Kp

√MW

2.6

(28)

Assuming the mean concentration in water (Cw) is 1 × 10−3 mg/cm3, an example dose 

calculation for DAevent is as follows, and is the same for both age ranges using eq 25:

DAevent =

2 × 1.0 × (1.5 × 10−2)

cm

hr × (1 × 10−3

)

mg

cm3

√

6 × 0.29 hr

event × 0.70 hrevent

π

DAevent = 1.9 × 10−5 mg

cm2-event

SA―The total surface area of the skin of a child can be found in EFH Table 7-1 

(U.S. EPA, 2011a) for all children according to the age increments in the Guidance on Selecting 
81

Age Groups for Monitoring and Assessing Childhood Exposures to Environmental Contaminants 

(U.S. EPA, 2005a) document. In this example, mean total surface areas are used because surface 

area and BW are strongly correlated and the mean values are most representative of the surface 

area of individuals with an average BW. Because surface area is divided by the BW in the dose 

equation, using an upper-percentile surface area with an upper-percentile BW would be similar to 

using a mean surface area with a mean BW. The estimates are given in m2and must be 

converted to cm2(1 m2 = 10,000 cm2). For this example, the averages of 1.08 m2for 6 to 

<11 years of age and 1.59 m2for 11 to <16 years of age are converted and used as 10,800 cm2

and 15,900 cm2, respectively.

EV―Since the LADD accounts for daily exposure, the event frequency is the number of 

events per day. For this scenario, it is assumed that one shower is taken daily (i.e., 1 event/day).

EF―Exposure frequency is the number of times an exposure is expected to occur in a 

year and is expressed in days per year. For the purposes of this scenario, it is assumed that 

children shower at home 350 days/year. This assumes that young children are away from home 

(e.g., on vacation) for 2 weeks/year.

ED―Exposure duration is the length of time over which the exposure occurs. This 

scenario covers a total duration of 10 years: 5 years from age 6 to <11 years and 5 years from 

age 11 to <16 years.

BW―EFH Table 8-1 (U.S. EPA, 2011a) reports recommended BWs for children aged 6 

to <16 years. The BWs for boys and girls are averaged from age 6 to <11 years old and 11 to 

<16 years old. These calculations, using the mean of this distribution, are 31.8 kg and 56.8 kg, 

respectively.

AT―The averaging time (AT) of 5 years is used in the individual calculations of DAevent

for each age range. Note that this assumes that no further exposures to the water contaminant of 

interest occur via showering after or before the 10 years examined here (i.e., aged 6 to 

<16 years). This AT value is converted to 1,825 days (that is, 5 years × 365 days/year). Because 

the LADD dose is calculated, the overall averaging time is equivalent to the lifetime (LT) of an 

individual in the receptor population. For the purposes of this example, the average lifetime of 

70 years (25,550 days) for men and women is used because the receptors exposures are assumed 

to reflect the general population (U.S. EPA, 2011a).
82

4.3.4. Calculations

Using the dose algorithm and input for the exposure factors variables, the dermal ADD

for children and teens while showering, is estimated for each age range in Table 14.

Table 14. Summary of ADD for children aged 6 to <16 years for high-end 

potential dose from dermal contact while showering

Equation 23

inputs and output

Age ranges

6 to <11 yr 11 to <16 yr

DAevent (mg/cm2-event) 1.9 × 10−5 1.9 × 10−5

SA (cm2) 10,800 15,900

EV (events/d) 1 1

EF (d/yr) 350 350

ED (yr) 5 5

AT (d) 1,825 1,825

BW (kg) 31.8 56.8

ADD (mg/kg-d) 6.2 × 10−3 5.1 × 10−3

The ADDs shown in Table 14 are then used to estimate the LADDshowering water dermal. 

Assuming exposure for 5 years as a 6- to <11-year old, 5 years of exposure as an 11- to <16-year 

old, and no exposure for the rest of the life time (i.e., 60 years), the weighted average over a 

lifetime for the LADD is calculated as:

LADDshowering water dermal =

(5 yr × 6. 2 × 10−3 mg

kg-d

) + (5 yr × 5. 1 × 10−3 mg

kg-d

)+ (60 yr × 0

mg

kg-d

)

 

70 yr

LADDshowering water dermal = 8.1 × 10−4 mg

kg-d

4.3.5. Uncertainties

The example presented here is used to represent high-end doses among children aged 6 to 

<16 years for showering in contaminated water. Note that central tendency doses may be 
83

estimated by replacing the 95th percentile shower duration with a mean value. The bounding 

estimate can be estimated by setting all the input parameters to upper-percentile values.

There are uncertainties related to calculation of the 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, for organic chemicals, Kp values are predicted using Kow. Dermal Exposure 

Assessment: Principles and Applications states that “the uncertainty in the predicted Kps 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% 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 to ensure that dose estimates are adequately 

represented.
84

GLOSSARY1

Absorbed dose― The amount of a substance penetrating across an absorption barrier (the 

exchange boundaries) of an organism, via either physical or biological processes. Sometimes 

called internal dose. See also Absorption barrier and Dose.

Absorption barrier―Any exposure surface that may retard the rate of penetration of an agent 

into a target. Examples include the skin, respiratory tract lining, and gastrointestinal tract wall. 

See also Target and Agent.

Activity pattern data―Information on human activities used in exposure assessments. These 

may include a description of the activity, frequency of activity, duration spent performing the 

activity, and the microenvironment in which the activity occurs.

Acute dose rate (ADR)―Dose per unit time received over a short period of time. Units may 

include mg/day.

Acute exposure―A single exposure to a toxic substance that may result in severe biological 

harm or death. Acute exposures are usually characterized as lasting no longer than a day, as 

compared to longer, continuing exposure over a period of time. The ADR is used for an acute, 

noncarcinogenic exposure.

Adherence factor―The amount of a material (e.g., soil) that adheres to the skin per unit of 

surface area.

Age-dependent adjustment factors (ADAFs)―In cases where age-related differences in 

toxicity occur, differences in both toxicity and exposure need to be integrated across all relevant 

age intervals, by the use of ADAFs. This is a departure from the way cancer risks have 

historically been calculated based upon the premise that risk is proportional to the daily average 

of the long-term adult dose. For example, for chemicals or compounds with a mutagenic mode 

of action for carcinogenesis, in the absence of chemical-specific data, the risk from exposures 

that occur at early life stages should be calculated by applying the following ADAFs to the non-

 

1 Glossary entries are adapted from IPCS (2004) and EPA (U.S. EPA, 1992a, 2004a, 2005a, 2011a, 2011b) 

publications.
85

age-specific slope factor: a factor of 10 for ages 0 to < 2 years; a factor of 3 for ages 2 to < 16 

years; and a factor of 1 for ages >16 years.

Agent―A chemical, biological, or physical entity that contacts a target. See also Target.

Aggregate exposure―The combined exposure of an individual (or defined population) to a 

specific agent or stressor via relevant routes, pathways, and sources. Aggregate exposure can 

include exposure through multiple routes (e.g., dermal, inhalation, and ingestion).

Assessment―A determination or appraisal of possible consequences resulting from an analysis 

of data.

Average daily dose (ADD)―The mean daily amount of an agent to which a person is exposed, 

often averaged over a long period of time. EPA is transitioning from average daily dose 

methodologies to more refined aggregate and cumulative approaches for estimating exposure 

across each life stage. See also Lifetime average daily dose (LADD) and Time-averaged 

exposure.

Bias―A systematic error inherent in a method or caused by some feature of the measurement 

system.

Bounding estimate―An estimate of exposure, dose, or risk that is higher or lower than that 

incurred by the person with the highest or lowest exposure, dose, or risk in the population being 

assessed. Bounding estimates are useful in developing statements that exposures, doses, or risks 

are "not greater than" or “less than” the estimated value, because assumptions are used which 

define the likely bounding conditions.

Carcinogen―A substance or agent capable of causing cancer.

Central tendency exposure/dose―A measure of the middle or the center of an exposure/dose

distribution. The mean is the most commonly used measure of central tendency.

Childhood exposure―Contact between an agent and a child. See also Agent.

Children―Individuals under the age of 21 years are classified as youth or children. For 

children less than 12 months old, the following age groups are recommended: birth to <1 month, 
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1 to <3 months, 3 to <6 months, and 6 to <12 months. For children older than 12 months, the 

following age groups are recommended: 1 to <2 years, 2 to <3 years, 3 to <6 years, 6 to 

<11 years, 11 to <16 years, and 16 to <21 years.

Chronic exposure―Repeated exposure by the oral, dermal, or/and inhalation route for more 

than approximately 10% of the life span in humans (more than approximately 90 days to 2 years 

in typically used laboratory animal species).

Chronic intake―The long term period over which a substance crosses the outer boundary of an 

organism without passing an absorption barrier.

Community water―Includes tap water ingested from community or municipal water supply.

Consumer only―Refers to only those individuals who reported food or water during the survey 

period.

Contaminant concentration―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.

Cumulative exposure―Exposure via mixtures of contaminants through more than one pathway. 

Risk assessments in EPA are placing more emphasis on total exposures via multiple pathways.

Cumulative risk assessment―An analysis, characterization, and possible quantification of the 

combined risks to health or the environment from multiple agents or stressors. See also Risk 

assessment.

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.

Dermal absorption―A route of exposure by which substances can enter the body through the 

skin (i.e., uptake across the skin barrier following dermal exposure).

Dermal permeability―Measure of the ability of the substance to penetrate and move through 

the skin.
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Direct water ingestion―Consumption of tap water as a beverage. It does not include water 

used for preparing beverages such as coffee or tea.

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.

Doers―Survey respondents who report participating in a specified activity.

Dose―The amount of an agent that enters a target after crossing an exposure surface. If the 

exposure surface is an absorption barrier, the dose is an absorbed dose. If the exposure surface 

is not an absorption barrier, the dose is an intake dose.

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 units such as mg/kg-day. 

They are also often expressed as averages over some time period, for example a lifetime.

Drinking water―All water consumed by individuals to satisfy body needs for internal water.

Dry weight intake rates―Intake rates that are based on the weight of the food consumed after 

the moisture content has been removed.

Dust ingestion―Consumption of dust that results from various behaviors including, but not 

limited to, mouthing objects or hands, eating dropped food, consuming dust directly, or inhaling 

dust that passes from the respiratory system into the gastrointestinal tract.

Effect―Change in the state or dynamics of an organism, system, or population caused by 

exposure to an agent. See also Agent.

Exclusively breastfed―Infants whose sole source of milk comes from human milk with no 

other milk substitutes. See also Infant.

Exposure―Contact between an agent and a target. See also Agent and Target.

Exposure assessment―The process of estimating or measuring the magnitude, frequency, and 

duration of exposure to an agent, along with the number and characteristics of the population 

exposed. See also Agent, Exposure duration, and Exposure frequency.
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Exposure concentration―The concentration of a chemical in its transport or carrier medium at 

the point of contact.

Exposure duration―Length of time over which contact with the contaminant lasts.

Exposure event―The occurrence of continuous contact between an agent and a target.

Exposure factor―Factors related to human behavior and characteristics that help determine an 

individual’s exposure to an agent.

Exposure frequency―The number of exposure events in an exposure duration. See also 

Exposure duration.

Exposure time―The length of time an individual engages in an activity which results in 

exposure.

Exposure pathway―The physical course a chemical takes from the source to the organism 

exposed.

Exposure route―The way a chemical 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 exposures.

General population―All individuals inhabiting an area or making up a whole group.

High-end exposure/dose―An estimate of individual exposure or dose for those persons at the 

upper end of an exposure or dose distribution, conceptually above the 90th percentile, but not 

higher than the individual in the population who has the highest exposure or dose. See also 

Bounding estimate.

Human equivalent concentration or dose (HEC or HED)―The concentration (for inhalation 

exposure) or dose (for other routes of exposure) of an agent that is believed to induce the same 

magnitude of toxic effect in humans experienced by an experimental animal species. This 

adjustment may incorporate toxicokinetic information on the particular agent and/or target, if 
89

available, or use a default procedure, such as assuming that daily oral doses experienced for a 

lifetime are proportional to BW raised to the 0.75 power.

Indirect water ingestion―Includes water added during food preparation, but not water intrinsic 

to purchased foods. Indirect water includes for example, water used to prepare baby formulas, 

cake mix, or concentrated orange juice.

Infant―A life stage that covers four age ranges, from birth to <1, 1 to <3, 3 to <6, and 6 to 

<12 months. See also Children.

Inhalation dosimetry―Process of measuring or estimating inhaled dose.

Inhalation unit risk (IUR)―The upper-bound excess lifetime cancer risk estimated to result 

from continuous exposure to an agent at a concentration of 1 μg/m3in air for a lifetime.

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―Rate of inhalation, ingestion, and dermal contact depending on the route of 

exposure. For ingestion, the intake rate is simply the amount of food or drink containing the 

contaminant of interest that an individual ingests during some specific time period (units of 

mass/time). For inhalation, the intake rate is the rate at which contaminated air is inhaled. 

Factors that affect dermal exposure are the amount of material that comes into contact with the 

skin, and the rate at which the contaminant is absorbed.

IRIS―EPA’s Integrated Risk Information System (IRIS) is a human health assessment program 

that evaluates information on health effects that may result from exposure to environmental 

contaminants. The IRIS database is an online database and contains information on more than 

550 chemical substances.
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Key study/data―A study that is useful for deriving exposure factors. Alternatively, studies 

may be classified as “relevant” and not “key” for one or more of the following: (1) they provide 

supporting data (e.g., older studies on food intake that may be useful for trend analysis); (2) they 

provide information related to the factor of interest (e.g., data on prevalence of breastfeeding); or 

(3) the study design or approach makes the data less applicable for exposure assessment purposes 

(e.g., data on mouthing behavior that was intended to be used in reducing the risk of choking 

hazards). 

Life stage―A distinguishable time frame in an individual’s life characterized by unique and 

relatively stable behavioral and/or physiological characteristics that are associated with 

development and growth. See also Infant and Children.

Lifetime―The average lifetime of 70 years for men and women is assumed to reflect the general 

population for consistency by EPA when calculating cancer risks.

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. Often used in carcinogen risk assessments that 

employ linear low-dose extrapolation methods. See also Average daily dose and Time-averaged 

exposure.

Mean value―Simple or arithmetic average of a range of values, computed by dividing the total 

of all values by the number of values.

Measurement error―A systematic error arising from inaccurate measurement (or 

classification) of subjects on the study variables.

Median value―The value in a data set such that half the measured values are greater and half 

are less.

Moisture content―The portion of food that is made up by water. The percentage of water is 

needed for converting food intake rates and residue concentrations between whole weight and 

dry weight values.
91

Monte Carlo technique―A 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. A form of probabilistic exposure 

estimation. See also Distribution.

Mouthing behavior―Activities in which objects, including fingers, are touched by the mouth or 

put into the mouth except for eating and drinking, and includes licking, sucking, chewing, and 

biting (usually infants and children).

Octanol/water partition coefficient (KOW)―The ratio of the solubility of a compound in 

octanol to its solubility in water. The higher the KOW, the more nonpolar the compound is. The 

Log KOW of a compound may be used as an indication of how well the compound will adsorb to 

soil.

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―Pica behavior is the repeated eating of nonnutritive substances, whereas soil-pica is a 

form of soil ingestion that is characterized by the recurrent ingestion of unusually high amounts 

of soil (i.e., on the order of 1,000−5,000 mg/day or more).

Plain tap water―Water obtained directly from the faucet or tap. It excludes water intrinsic in 

foods, juices, and other beverages.

Potential average daily dose (ADD)―is the amount of substance ingested, inhaled, or applied 

to skin per day, not all of which will be absorbed.

Potential dose―The amount of a chemical contained in material ingested, air breathed, or bulk 

material applied to the skin.

Preparation losses―Net cooking losses, which include dripping and volatile losses, 

postcooking losses, which involve losses from cutting, bones, excess fat, scraps and juices, and 

other preparation losses, which include losses from paring or coring.
92

Random samples―Samples selected from a statistical population such that each sample has an 

equal probability of being selected.

Range―The difference between the largest and smallest values in a measurement data set.

Reasonable maximum exposure―A semiquantitative term referring to the lower portion of the 

high end of the exposure, dose, or risk distribution. As a semiquantitative term, it should refer to 

a range that can conceptually be described as above the 90th percentile in the distribution, but 

below the 98th percentile.

Receptor/receptor population―The population of interest, also known as the receptor 

population, is described by specific age ranges. For children, these age ranges take into account 

their rapidly changing physiology. See also Infant and Children.

Reference Concentration (RfC)―An estimate (with uncertainty spanning perhaps an order of 

magnitude) of a continuous inhalation exposure to the human population (including sensitive 

target groups) that is likely to be without an appreciable risk of deleterious effects during a 

lifetime. It can be derived from a NOAEL, LOAEL, or benchmark concentration, with 

uncertainty factors generally applied to reflect limitations of the data used. Generally used in 

EPA’s noncancer health assessments. Durations include acute, short-term, subchronic, and 

chronic.

Reference Dose (RfD)―An estimate (with uncertainty spanning perhaps an order of magnitude) 

of a daily oral exposure to the human population (including sensitive target groups) that is likely 

to be without an appreciable risk of deleterious noncancer effects during a lifetime. It can be 

derived from a NOAEL, LOAEL, or benchmark dose, with uncertainty factors generally applied 

to reflect limitations of the data used. Generally used in EPA's noncancer health assessments. 

Durations include acute, short-term, subchronic, and chronic.

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.

Risk―The probability of an adverse effect in an organism, system, or population caused under 

specified circumstances by exposure to an agent.
93

Risk assessment―A process intended to calculate or estimate the risk to a given target 

organism, system, or population, including the identification of attendant uncertainties, following 

exposure to a particular agent, taking into account the inherent characteristics of the agent of 

concern as well as the characteristics of the specific target system. The risk assessment process 

includes four steps: hazard identification, dose-response assessment, exposure assessment, and 

risk characterization. 

Sample―A small part of something designed to show the nature or quality of the whole.

Exposure-related measurements are usually samples of environmental or ambient medium, 

exposures of a small portion of a population for a short time, or biological samples, all for the 

purpose of inferring the nature and quality of parameters important to evaluating exposure.

Soil―Particles of unconsolidated mineral and/or organic matter from the earth’s surface that are 

located outdoors, or are used indoors to support plant growth.

Soil adherence―The quantity of soil that adheres to the skin and from which chemical 

contaminants are available for uptake at the skin surface.

Soil ingestion―The intentional or unintentional consumption of soil, resulting from various 

behaviors including, but not limited to, mouthing, contacting dirty hands, eating dropped food, or 

consuming soil directly. Soil-pica is a form of soil ingestion that is characterized by the 

recurrent ingestion of unusually high amounts of soil (i.e., on the order of 1,000−5,000 mg/ day 

or more). Geophagy is also a form of soil ingestion defined as the intentional ingestion of earths 

and is usually associated with cultural practices.

Subchronic exposure―Repeated exposure by the oral, dermal, or inhalation route for more than 

30 days, up to approximately 10% of the life span in humans (more than 30 days up to 

approximately 90 days in typically used studies with laboratory animal species).

Surface area―Coating, triangulation, and surface integration are direct measurement techniques 

that have been used to measure total body surface area and the surface area of specific body 

parts. Consideration has been given for differences due to age, gender, and race. 

Target―Any physical, biological, or ecological object exposed to an agent. See also Agent.
94

Time-averaged exposure―The time-integrated exposure divided by the exposure duration. An 

example is the daily average exposure of an individual to carbon monoxide (also called time 

weighted average exposure).

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.

Toddler―A child over the age of 12 months and generally younger than 36 months. See also 

Infant and Children.

Transfer efficiency―The percentage of a material that ends up as a coating on the desired 

surface.

Uncertainty―Uncertainty represents a lack of knowledge about factors affecting exposure/dose

or risk and can lead to inaccurate or biased. The types of uncertainty include scenario, 

parameter, and model.

Unit risk―The quantitative estimate in terms of either risk per μg/L drinking water (water unit 

risk) or risk per μg/m3air breathed (air unit risk).

Upper percentile―Values in the upper tail (i.e., between 90th and 99.9th percentile) of the 

distribution of values for a particular exposure factor. Values at the upper end of the distribution 

for a particular set of data.

Uptake―The process by which a substance crosses an absorption barrier and is absorbed into 

the body.

Variability―Variability arises from true heterogeneity across people, places, or time and can 

affect the precision of exposure/dose estimates and the degree to which they can be generalized. 

The types of variability include spatial, temporal, and inter-individual.

Wet-weight intake rates―Intake rates that are based on the wet (or whole) weight of the food 

consumed. This is in contrast to dry-weight intake rates.
95
96

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