Characteristics of the Receptor for the Biosphere Model REV 03, ICN 00
 
ANL-MGR-MD-000005

September 2004 

1. PURPOSE 
This analysis report is one of a series of technical reports that document the Environmental 
Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the 
total system performance assessment (TSPA) for the geologic repository at Yucca Mountain. 
This report is one of the five biosphere reports that develop input parameter values for the 
biosphere model. The Biosphere Model Report (BSC 2004 [DIRS 169460]) describes the 
conceptual model, as well as the mathematical model and its input parameters. 
Figure 1-1 is a graphical representation of the documentation hierarchy for the ERMYN. This 
figure shows relationships among the products (i.e., scientific analyses and model reports) 
developed for biosphere modeling and biosphere abstraction products for TSPA, as identified in 
the Technical Work Plan: for Biosphere Modeling and Expert Support (BSC 2004 
[DIRS 169573]). 
The purpose of this analysis report is to define values for biosphere model parameters that are 
related to the dietary, lifestyle, and dosimetric characteristics of the receptor. The biosphere 
model, consistent with the licensing rule at 10 CFR Part 63 [DIRS 156605], uses a hypothetical 
person called the reasonably maximally exposed individual (RMEI) to represent the potentially 
exposed population. The parameters that define the RMEI are based on the behaviors and 
characteristics of the residents of the unincorporated town of Amargosa Valley, consistent with 
the requirements of 10 CFR 63.312 [DIRS 156605]. The output of this report is used as direct 
input in the two analyses identified in Figure 1-1 that calculate the values of biosphere dose 
conversion factors (BDCFs) for the groundwater and volcanic ash exposure scenarios. The 
parameter values developed in this report are reflected in the TSPA through the BDCFs. The 
analysis was performed in accordance with AP-SIII.9Q, Scientific Analyses, and the technical 
work plan (BSC 2004 [DIRS 169573]). 
This analysis supports the treatment of 15 features, events, and processes (FEPs) applicable to 
the reference biosphere (Table 1-1). See the Biosphere Model Report (BSC 2004 
[DIRS 169460], Section 6.2) for information on treatment of FEPs in the biosphere model. Use 
of MO0407SEPFEPLA.000 [DIRS 170760] in Table 1-1 is a deviation from the technical work 
plan (BSC 2004 [DIRS 169573]); that plan refers to an earlier revision of the FEP list. 
Biosphere modeling focuses on radionuclides screened for the TSPA-license application (LA) 
(BSC 2004 [DIRS 169460], Section 6.1.3). The same list of radionuclides is used in this analysis 
(Section 6.5.1). The analysis includes consideration of two human exposure scenarios: 
groundwater and volcanic ash. For the groundwater exposure scenario, radionuclides enter the 
biosphere from a well that extracts contaminated groundwater from an aquifer. Human exposure 
arises from using the contaminated water for domestic and agricultural purposes. The 
groundwater scenario applies to the TSPA-LA modeling cases that consider groundwater release 
of radionuclides from the repository at Yucca Mountain. The nominal scenario class and some 
modeling cases from the disruptive scenario classes (i.e., igneous intrusion or human intrusion) 
may result in the release of radionuclides to groundwater. For the volcanic ash scenario, the 
mode of radionuclide release into the biosphere is a volcanic eruption through the repository with 
the resulting entrainment of contaminated waste in the ash and other tephra and the subsequent 
atmospheric transport and dispersion of contaminated material in the biosphere. This scenario 

applies to the volcanic eruption modeling case of the igneous scenario class (BSC 2003 
[DIRS 166296], Section 4.2), which is one of the TSPA disruptive scenario classes. 
Figure 1-1. Biosphere Model Documentation 

Characteristics of the Receptor for the Biosphere Model 
ANL-MGR-MD-000005 REV 03 1-3 September 2004 
Table 1-1. Parameters and Included Features, Events, and Processes 
Parameter(s) FEPa 
YMP FEP 
Numbera 
Associated 
Submodel(s) Summary of Dispositionb 
Human lifestyle 2.4.04.01.0A 
External exposure, 
Inhalation 
The treatment of this parameter is described in 
Section 6.3.1 and summarized in Table 6-5. Population proportion Inhalation 3.3.04.02.0A 
External exposure 3.3.04.03.0A 
External exposure 3.3.04.03.0A 
External exposure, 
Inhalation 
The treatment of this parameter is described in 
Section 6.3.2 and summarized in Table 6-12. 
Human lifestyle 2.4.04.01.0A 
Exposure time Wild and natural land and water use 2.4.08.00.0A 
Agricultural land use and irrigation 2.4.09.01.0B 
Urban and industrial land and water use 2.4.10.00.0A 
Inhalation 3.3.04.02.0A 
Breathing rate 
Human characteristics (physiology, 
metabolism) 
2.4.01.00.0A 
Inhalation The treatment of this parameter is described in 
Section 6.3.3 and summarized in Table 6-15. 
Inhalation 3.3.04.02.0A 
Fraction of houses with Dwellings 2.4.07.00.0A 
Inhalation The treatment of this parameter is described in 
Section 6.3.4.1. evaporative coolers Inhalation 3.3.04.02.0A 
Climate change 1.3.01.00.0A 
Inhalation The treatment of this parameter is described in 
Section 6.3.4.2. 
Evaporative cooler use 
factor 
Biosphere characteristics 2.3.13.01.0A 
Dwellings 2.4.07.00.0A 
Inhalation 3.3.04.02.0A 
Consumption rate of 
Contaminated drinking water, foodstuffs 
and drugs 3.3.01.00.0A 
Ingestion 
The treatment of this parameter is described in 
Section 6.4. The consumption rate of water is 
described in Section 6.4. The consumption rate 
of food is described in Section 6.4.2 and 
summarized in Table 6-21. 
locally produced food 
(including water) 
Wild and natural land and water use 2.4.08.00.0A 
Ingestion 3.3.04.01.0A 
Annual inadvertent soil 
ingestion rate 
Contaminated drinking water, foodstuffs 
and drugs 3.3.01.00.0A 
Ingestion The treatment of this parameter is described in 
Section 6.4.3. 
Ingestion 3.3.04.01.0A 
Radionuclide half-lives 
and branching fractions Radioactive decay and ingrowth 3.1.01.01.0A 
Inhalation, 
Ingestion, External 
Exposure 
The treatment of this parameter is described in 
Section 6.5.1 and summarized in Table 6-23. 

Characteristics of the Receptor for the Biosphere Model 
ANL-MGR-MD-000005 REV 03 1-4 September 2004 
Table 1-1. Parameters and Included Features, Events, and Processes (Continued) 
Parameter(s) FEPa 
YMP FEP 
Numbera 
Associated 
Submodel(s) Summary of Dispositionb 
Human characteristics (physiology, 
metabolism) 2.4.01.00.0A 
Inhalation The treatment of this parameter is described in 
Section 6.5.3.1 and summarized in Table 6-24. 
Dose conversion factors Inhalation 3.3.04.02.0A 
for inhalation Radioactive decay and ingrowth 3.1.01.01.0A 
Radiation doses 3.3.05.01.0A 
Human characteristics (physiology, 
metabolism) 2.4.01.00.0A 
Ingestion The treatment of this parameter is described in 
Section 6.5.3.1 and summarized in Table 6-24. 
Dose conversion factors 
for ingestion 
Ingestion 3.3.04.01.0A 
Radioactive decay and ingrowth 3.1.01.01.0A 
Radiation doses 3.3.05.01.0A 
Dose coefficient for 
Human characteristics (physiology, 
metabolism) 2.4.01.00.0A 
External exposure The treatment of this parameter is described in 
Section 6.5.3.2 and summarized in Table 6-25. 
exposure to 
contaminated ground 
surface 
External exposure 3.3.04.03.0A 
Radioactive decay and ingrowth 3.1.01.01.0A 
Radiation doses 3.3.05.01.0A 
Dose coefficient for 
Human characteristics (physiology, 
metabolism) 2.4.01.00.0A 
External exposure The treatment of this parameter is described in 
Section 6.5.3.2 and summarized in Table 6-25. 
exposure to soil 
contaminated to an 
infinite depth 
External exposure 3.3.04.03.0A 
Radioactive decay and ingrowth 3.1.01.01.0A 
Radiation doses 3.3.05.01.0A 
Human characteristics (physiology, 
metabolism) 2.4.01.00.0A 
Inhalation The treatment of this parameter is described in 
Section 6.5.4. 
Dose conversion factor 
for inhalation of radon 
decay products 
Inhalation 3.3.04.02.0A 
Radioactive decay and ingrowth 3.1.01.01.0A 
Radon and radon daughter exposure 3.3.08.00.0A 
Radiation doses 3.3.05.01.0A 
Building shielding factor 
Dwellings 2.4.07.00.0A External exposure The treatment of this parameter is described in 
Section 6.6 and summarized in Table 6-28. External exposure 3.3.04.03.0A 
a Features, events, and processes are from the LA FEP List (DTN: MO0407SEPFEPLA.000 [DIRS 170760]). 
b The effects of the related FEPs are included in the TSPA through the BDCFs. See the Biosphere Model Report ( BSC 2004 [DIRS 169460], Section 6.2) for a 
complete description of the inclusion and treatment of listed FEPs in the biosphere model. 
BDCF=biosphere dose conversion factor; FEP=feature, event, and process; YMP = Yucca Mountain Project 

2. QUALITY ASSURANCE 
Development of this report involves analysis of data to support performance assessment as 
identified in the technical work plan (BSC 2004 [DIRS 169573]) and is a quality-affecting 
activity in accordance with AP-2.27Q, Planning for Science Activities. Approved quality 
assurance procedures identified in Section 4 of the technical work plan have been used to 
conduct and document the activities described in this report. Electronic data used in this analysis 
were controlled in accordance with the methods specified in Section 8 of the technical work plan. 
The natural barriers and items identified in the Q-List (BSC 2004 [DIRS 168361]) are not 
pertinent to this analysis, and a safety category per AP-2.22Q, Classification Analysis and 
Maintenance of the Q List, is not applicable. 

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3. USE OF SOFTWARE 
The only software used during this analysis was the commercial, off-the-shelf product Microsoft 
Excel (Version 97 SR-2). Standard Excel functions were used to calculate parameter values, as 
described in the appendices to this document, and to produce histograms shown in Section 6 of 
this report. Use of the Excel functions, including formulas or algorithms, inputs, and outputs, are 
described in the appendices. 

INTENTIONALLY LEFT BLANK 

4. INPUTS 
4.1 DIRECT INPUTS 
The list of parameters related to the characteristics of the receptor for the biosphere model 
addressed in this analysis and the sources of direct input used to develop the parameter values are 
shown in Table 4-1. 
Table 4-1. Biosphere Model Input Parameters Developed in This Analysis Report and the Sources of 
Data 
Parameter Sources of Direct Input 
Population proportion Bureau of the Census 2002 (DIRS 159728) 
Bureau of the Census 2002 (DIRS 159728) 
Exposure time EPA 1997 (DIRS 116135) 
Klepeis et al. 1996 (DIRS 159299) 
Lide and Frederikse 1997 (DIRS 103178) 
Breathing rate 
ICRP 1994 (DIRS 153705) 
Bureau of the Census 2002 (DIRS 159728) 
DTN: MO0010SPANYE00.001 (DIRS 154976) 
Fraction of houses with evaporative coolers Cleaned Nye County Food Consumption Frequency 
Survey 
Evaporative cooler use factor 
DTN: MO04019SUM9397.000 (DIRS 167054) 
Summary of 1993-1997 Site 9 Meteorological Data 
National Climatic Data Center [n.d.] (DIRS 161091) 
DTN: MO0010SPANYE00.001 (DIRS 154976) 
Cleaned Nye County Food Consumption Frequency 
Consumption rate of locally produced food (including 
water) 
Survey 
USDA 2000 (DIRS 154158) 
Bureau of the Census 2002 (DIRS 159728) 
10 CFR Part 63 (DIRS 156605) 
Inadvertent soil ingestion rate 
EPA 1997 (DIRS 103038) 
Simon 1998 (DIRS 160098) 
Radionuclide half-lives and branching fractions 
Eckerman and Ryman 1993 (DIRS 107684) 
Lide and Frederikse 1997 (DIRS 103178) 
Dose conversion factor for inhalation by radionuclide Eckerman et al. 1988 (DIRS 101069) 
Dose conversion factor for ingestion by radionuclide Eckerman et al. 1988 (DIRS 101069) 
Dose coefficient for exposure to contaminated ground 
surface Eckerman and Ryman 1993 (DIRS 107684) 
Dose coefficient for exposure to soil contaminated to an 
infinite depth Eckerman and Ryman 1993 (DIRS 107684) 
Dose conversion factor for inhalation of radon decay 
products 
ICRP 1981 (DIRS 163051) 
Eckerman et al. 1988 (DIRS 101069) 
10 CFR Part 20 (DIRS 104787) 

Table 4-1. Biosphere Model Input Parameters Developed in This Analysis Report and the Sources 
of Data (Continued) 
Parameter Sources of Direct Input 
NCRP 1999 (DIRS 155894) 
Building shielding factor 
Bureau of the Census 2002 (DIRS 159728) 
Lide and Frederikse 1977 (DIRS 103178) 
Eckerman and Ryman 1993 (DIRS 107684) 
4.1.1 U.S. Census 2000 
Information on population size, age distribution, industry of employment, and travel time of the 
residents of the Amargosa Valley census county division from the 2000 census conducted by the 
Bureau of the Census (2002 [DIRS 159728]) were used in Sections 5.2 and 6.3.1 to determine 
the proportion of the population of the Amargosa Valley in four population groups. This 
information also was used to develop distributions of the time the population groups spend in 
five environments (Section 6.3.2), calculate gender-weighted breathing rates (Section 6.3.3) and 
food consumption rates (Section 6.4.2), and determine the types of dwellings in the Amargosa 
Valley (Section 6.6). 
The 2000 census data are appropriate for use in this analysis and considered established fact as 
they are based on the most recent and comprehensive census of the Amargosa Valley population 
conducted by the U.S. Bureau of the Census. The data are specific to the people who reside in 
the Amargosa Valley, consistent with the requirements of 10 CFR 63.312(b) [DIRS 156605] and 
discussed in Section 6.1. The data were collected and summarized in accordance with the 
requirements of the Census Bureau for census data. The U.S. Bureau of the Census is the federal 
agency chartered to collect, analyze, and supply key economic and demographic data. The data 
used in this analysis are identified and presented in Tables 6-2, 6-3, 6-4, 6-6, 6-7, 6-8, and 6-10. 
4.1.2 U.S. Environmental Protection Agency Data on Human Activity Patterns 
Estimates from the Exposure Factors Handbook (EPA 1997 [DIRS 116135]) and the Analysis of 
the National Human Activity Pattern Survey (NHAPS) Respondents from a Standpoint of 
Exposure Assessment (Klepeis et al. 1996 [DIRS 159299]) of time spent in various activities and 
locations were used to develop distributions of exposure times (Section 6.3.2). This information 
is appropriate for this use because the NHAPS and associated data in the Exposure Factors 
Handbook (EPA 1997 [DIRS 116135]) were collected by the EPA, and because this is the largest 
and most complete compilation of activity patterns and time spent exposed to toxic pollutants by 
people in the U.S. (EPA 1997 [DIRS 116135], p. 15-5; Klepeis 1999 [DIRS 160094], pp. 368 to 
371). 
The purpose of the Exposure Factors Handbook is to (1) summarize data on human behavior 
and characteristics which affect exposure to environmental contaminants, and (2) recommend 
values to use for these factors (EPA 1997 [DIRS 103038], p. 1-1). The handbook is intended to 
support and promote consistency among exposure assessment activities carried out by the EPA. 
As such, this information is recognized as an authoritative source of exposure factors by the 
scientific community, and is therefore appropriate for use in this analysis and considered 
established fact. For the 1992-1994 NHAPS, minute-by-minute, 24-hour diaries were kept by 

9,386 people in the 48 contiguous U.S. states. The data were collected, summarized, and 
analyzed in accordance with rigorous, well-defined methodologies, as described by Klepeis et al. 
(1996 [DIRS 159299]). Applicability of data from this national survey to conditions in the 
Amargosa Valley is described in Section 6.3.2. The data used in this analysis are identified and 
presented in Tables 6-9 and 6-11. 
4.1.3 Parameters Related to Breathing Rate and the Respiratory Tract Model of ICRP 
Publication 66 
Information related to the respiratory tract model of International Commission on Radiation 
Protection (ICRP) Publication 66 (ICRP 1994 [DIRS 153705]), including the breathing rates and 
the nominal mix of exercise levels for various environments, was used to develop the values of 
breathing rate by population group and environment for the biosphere model (Section 6.3.3). The 
data used in this analysis are identified and presented in Tables 6-13 and 6-14. 
The ICRP is an international, independent, non-governmental advisory organization established 
to advance for the public benefit the science of radiological protection, in particular by providing 
recommendations and guidance on protection against ionizing radiation. The U.S. National 
Council on Radiation Protection and Measurements (NCRP, see Section 4.1.10) works closely 
with international bodies, such as the ICRP, so that its recommendations reflect the consensus of 
leading scientific thinking. These recommendations are considered for adoption by U.S. 
governmental organizations, including the U.S. Nuclear Regulatory Commission (NRC), the 
Public Health Service, the EPA, and state governments, to support specific advice, codes of 
practice, regulatory requirements, or other radiation protection activities. 
The dosimetric model of the respiratory tract used in the biosphere model is that of ICRP 
Publication 30 (ICRP 1979 [DIRS 110386], Section 5). This is consistent with the concept of 
total effective dose equivalent (Section 6.5.2). ICRP Publication 30 does not consider breathing 
rates for various levels of activity; instead, it uses the breathing rate of the reference man under 
conditions of light activity (ICRP 1979 [DIRS 110386], Section 3.4). The ICRP Publication 
66 (ICRP 1994 [DIRS 153705]) data include the most recent recommended values of breathing 
rates for people involved in various levels of activity (sleeping, sitting, light exercise, heavy 
exercise). These activity-dependent breathing rates are used to calculate environment-dependent 
breathing rates for the biosphere model and are appropriate for their intended use and considered 
established fact. 
4.1.4 Food and Nutrient Intakes by Individuals in the United States 
Information from the U.S. Department of Agriculture (USDA) Food and Nutrient Intakes by 
Individuals in the United States, 1994-1996 (USDA 2000 [DIRS 154158]) was used in this 
analysis to develop consumption rate values for the receptor. This report is one in a series of 
nationwide dietary intake surveys conducted periodically by the USDA. These surveys are an 
authoritative source of information on the food consumption patterns for various segments of the 
U.S. population. The survey data used in this analysis included the values of average daily 
intake of food by food categories, the fraction of population consuming the food in these 
categories, and the errors associated with these values for the western region of the United 
States. The USDA data are appropriate for use in this analysis because they are based on a large 

sample of consumption rates and reflect the dietary intake of the surveyed individuals, which on 
average, are not expected to differ among populations. The USDA consumption data are thus 
considered established fact and appropriate for use in this analysis. The values were used to 
develop the probability distribution functions for the consumption rates of locally produced food 
(Section 6.4.2 and Table 6-20). 
4.1.5 Dietary and Living Style Characteristics 
Information on the dietary and lifestyle characteristics of the people who reside in the town of 
Amargosa Valley was obtained from a survey of the residents of the Yucca Mountain region. 
This survey is described in The 1997 Biosphere Food Consumption Survey Summary Findings 
and Technical Documentation (DOE 1997 [DIRS 100332]; DTN: MO0010SPANYE00.001 
[DIRS 154976]). The objective of the survey was to collect dietary and socioeconomic 
information for biosphere modeling. Dietary and lifestyle data were collected from adults 
residing within 50 miles of Yucca Mountain. Nearly 13,000 adults were estimated to reside in 
that area at the time of the survey, with about 900 of them in the Amargosa Valley (DOE 1997 
[DIRS 100332], p. vi). The survey sample consisted of 1,079 responses, with an Amargosa 
Valley sample of 195 (DOE 1997 [DIRS 100332], Table 2.3.1). To meet the requirements of 
10 CFR 63.312(b), only information from full-time residents of the Amargosa Valley was used 
in this analysis (see Section 6 and Appendix A). Information from eight people who were 
seasonal or part-time residents, had resided in Amargosa Valley for less than 1 year, or refused to 
answer questions about residency were not considered in this analysis. The data that were used 
in this analysis from the 187 respondents and from the eight that were eliminated are displayed in 
Appendix C (file Consumption rates with uncertainties.xls). 
Data on food consumption frequencies were used to develop consumption rates for locally 
produced food (Section 6.4.2 and Table 6-21), and data related to evaporative cooler use were 
used to develop a distribution of the proportion of homes with evaporative coolers 
(Section 6.3.4). These data are appropriate because they are from a survey of the diet and living 
style of the people residing in the Amargosa Valley and are consistent with the requirements of 
10 CFR 63.312(b) [DIRS 156605]. 
4.1.6 Meteorological Monitoring Data 
The information regarding temperature for the Amargosa Valley was obtained from the data for 
Meteorological Monitoring Site 9, which is the southern most Yucca Mountain Site station in the 
direction of Amargosa Valley. The data for 1994 to 1997 were summarized in BSC 2004 
[DIRS 167055] and are available in DTN: MO04019SUM9397.000 [DIRS 167054]. Summaries 
of the number of days per year that the temperature exceeded 80, 85, and 90 degrees F are 
displayed in Table 6-18 and were used to develop the evaporative cooler use factor for the 
Amargosa Valley in Section 6.3.4.2. The meteorological data for Meteorological Monitoring 
Site 9 are appropriate for use in this analysis because this site is located in northern Amargosa 
Valley at Gate 510 along the southern boundary of the Nevada Test Site (CRWMS M&O 1999 
[DIRS 102877], p. 5), at the approximate boundary of the accessible environment defined in 
10 CFR 63.302 [DIRS 156605]. 

4.1.7 Hourly United States Weather Observations 
Hourly temperatures collected during 1990 through 1995 from the weather station at Spokane 
International Airport (Station ID 24157) were used to develop the evaporative cooler use factor 
for the glacial transition climate predicted to occur in the future at Yucca Mountain 
(Section 6.3.4.2). These data are appropriate for this use and considered established fact because 
the current climate at Spokane, Washington, is predicted to be representative of the future 
climate at Yucca Mountain during a glacial transition period (BSC 2004 [DIRS 170002], 
Table 6-1). The data were obtained from the National Climatic Data Center (NCDC [n.d.] 
[DIRS 161091]), and were collected and summarized using the standardized methods of that 
agency. The data used in this analysis are in Appendix C, Spokane Hourly Temperatures and 
Daily Max Temperatures.xls. 
4.1.8 Inadvertent Soil Ingestion Rate 
The soil ingestion rate is developed in Section 6.4.3 is based on the mean values of inadvertent 
soil ingestion recommended in the Exposure Factors Handbook (EPA 1997 [DIRS 103038], 
Section 4) and by Simon (1998 [DIRS 160098]). 
The Exposure Factors Handbook recommends a mean soil ingestion rate of 100 mg/day for 
adults in residential and agricultural scenarios (EPA 1997 [DIRS 103038], p. 4-21). No 
recommendation is given for a distribution of rates. This handbook summarizes data on human 
behaviors and characteristics that affect exposure to environmental contaminants and 
recommends values to use for those factors (EPA 1997 [DIRS 103038], p. 1-1). The handbook 
summarizes relevant information and includes a discussion and review of data applicability and 
related issues. The handbook is intended to serve as a support document to the EPA Guidelines 
for Exposure Assessment (as cited in EPA 1997 [DIRS 103038], p. 1-1), which was developed to 
promote consistency among the various exposure assessment activities by providing a consistent 
set of exposure factors for calculating dose. As such, the scientific community recognizes this 
information as an authoritative source of exposure factors. 
Simon (1998 [DIRS 160098]) reviewed literature on soil ingestion and recommended 
distributions of soil ingestion rates for adults in various outdoor occupations and environments. 
The geometric means of the distributions representative of agricultural occupations and rural 
lifestyles used in this analysis ranged from 50 to 200 mg/d (Simon 1998 [DIRS 160098], 
Table 4). The following information was considered to evaluate whether confidence in the data 
development methods used in that publication are warranted and to determine whether the 
information used from that publication is suitable for use in this analysis. 
 
Reliability of the Data Source-Because there is no information available on soil 
ingestion rates for the specific conditions at Yucca Mountain, the recommended value 
must be based on a thorough review of data from a wide variety of conditions to be 
acceptable for the intended use in this analysis. Simon (1998 [DIRS 160098]) includes a 
comprehensive review of data on soil ingestion with an emphasis on risk assessments for 
soils contaminated with radionuclides. This article summarizes original research on soil 
ingestion, other published reviews of the topic, and distributions of ingestion rates used 
in risk assessment models. More than 175 references are cited. The article considers the 

influence of lifestyle, occupation, and environmental conditions on ingestion rates. In 
addition, different distributions are recommended for various occupations and 
conditions. Because this is a comprehensive review of soil ingestion rates, it is 
considered a reliable summary of information on soil ingestion rates. 
 
Qualifications of Personnel and Organizations Generating the Data-The article was 
published as a special review paper in Health Physics. Health Physics is a 
peer-reviewed technical journal, which is an official publication of the Health Physics 
Society. The journal adheres to high standards for published articles, which are subject 
to review by experts in the field. The author was affiliated with the Board on Radiation 
Effects Research of the National Research Council, National Academy of Sciences. 
Authorship by an individual associated with a respected organization and publication as 
a review article in a highly respected, peer-reviewed article raises the confidence that the 
data are suitable for the intended use. 
 
Extent to Which the Data Demonstrate the Properties of Interest-The geometric 
mean values recommended by Simon (1998 [DIRS 160098], Table 4) are used to 
develop the distribution range for inadvertent soil ingestion by adults in the Yucca 
Mountain region, a rural, arid area. The article reviews numerous estimates of soil 
ingestion by adults and considers the influence of lifestyle, occupation, and 
environmental conditions on ingestion rates. The data upon which the recommended 
values are based therefore demonstrate the properties of interest required for this 
analysis. 
 
Availability of Corroborating Data-There are few data available to corroborate the 
geometric standard deviation recommended by Simon (1998 [DIRS 160098]). The 
article includes a comprehensive review of available literature, and there have been few 
studies of soil ingestion published since 1998. The following three reports, which were 
not reviewed by Simon (1998 [DIRS 160098]), were examined. 
Stanek et al. (1997 [DIRS 160251]) report soil ingestion rates for 10 adults. Although 
the average ingestion rate is lower than reported in most other studies, they conclude that 
there is substantial uncertainty as to the best estimate of the rate (Stanek et al. 1997 
[DIRS 160251], p. 255). In a separate study of 64 children, Stanek and Calabrese (2000 
[DIRS 168391]) also report high uncertainty in soil ingestion rates. These studies 
corroborate that a large distribution range, as recommended by Simon 
(1998 [DIRS 160098]), is warranted. 
Binkowitz and Wartenberg (2001 [DIRS 168389]) reviewed distributions of soil 
ingestion rates and other input parameter distributions that have been used in risk 
assessment. All but one of the studies of soil ingestion rates listed by Binkowitz and 
Wartenberg (2001 [DIRS 168389], Table VII), and all but three of the models listed, also 
were reviewed by Simon (1998 [DIRS 160098]). The study not reviewed by Simon was 
a report of sources of lead ingested by children. The models not listed were a 
description of stochastic modeling methods, a study of the relationship between lead in 
soil and blood pressure, and a draft risk assessment model from Oregon. Thus, the 
report and models are not directly applicable to a review of soil ingestion. This 

comparison corroborates that Simon (1998 [DIRS 160098]) includes a thorough review 
of literature on soil ingestion rates. 
Because the distributions recommended by Simon (1998 [DIRS 160098]) are based on a 
thorough review of applicable information on soil ingestion, and because additional information 
corroborates the conclusion of Simon (1998 [DIRS 160098], p. 661) that there is large 
uncertainty in soil ingestion rates, these data are appropriately justified and suitable for the 
specific application in this analysis; therefore, the data are considered qualified for their intended 
use. Confidence that the data are appropriate is raised, because the data were published in a 
peer-reviewed article from a reputable journal, which was written by a person from a respected 
organization that is independent of the U.S. Department of Energy. 
4.1.9 Dose Conversion Factors, Dose Coefficients, and Properties of Nuclides 
Dose conversion factors (DCFs) and dose coefficients are expressions of specific dosimetric 
models and are used for converting radionuclide intake by inhalation and ingestion, as well as by 
exposure to sources external to the body, to radiation doses. The dose conversion factors (DCFs) 
and dose coefficients developed in this report are based on information from EPA Federal 
Guidance Report (FGR) No. 11 (Eckerman et al. 1988 [DIRS 101069]) and EPA FGR No. 12 
(Eckerman and Ryman 1993 [DIRS 107684]). The data used are identified and displayed in 
Tables 6-24, 6-25, and 6-26. Further discussion on the DCFs and dose coefficients can be found 
in Section 6.5.3 and 6.5.4. In addition, the dose coefficients from Eckerman and Ryman (1993 
[DIRS 107684]) for some radionuclides were used to determine the appropriate shielding factors 
(Section 6.6). 
These DCFs are considered established fact and appropriate for use in this analysis for the 
following reasons. DCFs tabulated in FGR No. 11, and dose coefficients tabulated in FGR 
No. 12, allow calculating total effective dose equivalent, as defined in 10 CFR 63.2 
[DIRS 156605]. The use of DCFs and dose coefficients from these sources is appropriate, 
because they are the authoritative source of dose coefficients for compliance with the NRC 
guidance on performance assessment methodology (NRC 2000 [DIRS 157704], 
Sections 3.3.7.3.1 and 3.3.7.3.2). In addition, the DCFs and dose coefficients developed in these 
reports are consistent with the individual protection standard defined in terms of total effective 
dose equivalent (TEDE) and the requirement in 10 CFR 63.312(e) (DIRS 156605) that the RMEI 
is an adult with metabolic and physiological considerations consistent with present knowledge of 
adults. 
DCFs for inhalation of radon decay products were developed based on ICRP 
Publication 32 (1981 [DIRS 163051]) and FGR No. 11 (Eckerman et al. 1988 [DIRS 101069]). 
The values from ICRP Publication 32 are consistent with the ICRP Publication 30 dose 
methodology (as described in pp. 1 and 2 of ICRP 1981 [DIRS 163051]), and thus with NRC 
guidance (NRC 2000 [DIRS 157704], Section 3.3.7.1.2). 
The data from FGR No. 12 (Eckerman and Ryman 1993 [DIRS 107684]) and the CRC 
Handbook of Chemistry and Physics (Lide and Frederikse 1997 [DIRS 103178]) were used as a 
source of information on properties of radioactive nuclei, such as the radioactive decay half-lives 
and branching fractions. These data are displayed in Table 6-23. 

4.1.10 Building Shielding Factors 
Shielding factors presented in the NCRP Report No. 129 (NCRP 1999 [DIRS 155894]) are used 
in Section 6.6 to select values of building shielding factors. These values are displayed in 
Table 6-28. 
These shielding factors are considered established fact and appropriate for use in this analysis for 
the following reasons. The NCRP was chartered by the U.S. Congress to collect, analyze, 
develop, and disseminate information and recommendations about radiation protection and 
measurements (NCRP 1997 [DIRS 160260], p. 226). The NCRP and ICRP (see Section 4.1.3) 
are independent non-governmental advisory bodies seeking to provide the quantitative scientific 
basis upon which radiation protection measures can be based. The NCRP work closely with 
international bodies, such as the ICRP, so that its recommendations reflect the consensus of 
leading scientific thinking. NCRP recommendations are considered for adoption by U.S. 
governmental organizations, including the NRC, the Public Health Service, the EPA, and state 
governments, to support specific advice, codes of practice, regulatory requirements, or other 
radiation protection activities. 
The NCRP reviewed literature on the shielding by dwellings of radiation from soil contaminated 
with radionuclides. It then formulated recommendations of the shielding factor values in Report 
No. 129 (NCRP 1999 [DIRS 155894]). This assessment, and the accompanying values of 
building shielding factors, are appropriate for evaluating exposure to contaminated soil in the 
biosphere model because of the similarities in the type and geometry of the dwellings and source 
of contamination considered in that report and in the biosphere model. 
4.1.11 Other Sources of Direct Inputs in this Analysis 
Other sources of inputs considered to be established fact and used in this analysis include the 
rules at 10 CFR Part 63 [DIRS 156605] and 10 CFR Part 20 [DIRS 104787]. 10 CFR Part 
63.312(d) [DIRS 156605] specifies the consumption rate of water (Section 6.4). 10 CFR Part 20 
[DIRS 104787] was used to support development of dose conversion factor for radon decay 
products (Section 6.5.4). In addition, information from the CRC Handbook of Chemistry and 
Physics (Lide and Frederikse 1997 [DIRS 103178]) was used as a source of information on 
half-lives and branching fractions of some radionuclides (values are displayed in Table 6-23), to 
calculate distributions of exposure times (Section 6.3.2.2), and to determine the appropriate 
shielding factor for 14C and 210Tl (Section 6.6). 
4.2 CRITERIA 
Table 4-2 lists requirements from the Project Requirements Document (Canori and Leitner 2003 
[DIRS 166275], Table 2-3) that are applicable to this analysis. These requirements are for 
compliance with applicable portions of 10 CFR Part 63 [DIRS 156605]. In addition to the 
requirements listed in Table 4-2, definition of terms in 10 CFR 63.2 [DIRS 156605] and 
description of concepts in 10 CFR 63.102 [DIRS 156605] that are relevant to biosphere 
modeling are also applicable to this analysis. 

Table 4-2. Requirements Applicable to This Analysis 
Requirement 
Number Requirement Title 
Related 
Regulation 
PRD-002/T-015 Requirements for Performance Assessment 10 CFR 63.114 
PRD-002/T-026 Required Characteristics of the Reference Biosphere 10 CFR 63.305 
PRD-002/T-028 Required Characteristics of the Reasonably Maximally Exposed Individual 10 CFR 63.312 
Source: Canori and Leitner 2003 (DIRS 166275), Table 2-3. 
Listed below are the acceptance criteria from the Yucca Mountain Review Plan, Final Report 
(NRC 2003 [DIRS 163274]) that are applicable to this analysis. The list is based on meeting the 
requirements of 10 CFR 63.114, 10 CFR 63.305, and 10 CFR 63.312 [DIRS 156605] that relate 
in whole or in part to this analysis. See section 7.2 for a summary of where these criteria are 
addressed in this report. 
2.2.1.3.14. BIOSPHERE CHARACTERISTICS 
14.1 System Description and Model Integration are Adequate 
14.1(3) Assumptions are consistent between the biosphere characteristics modeling and other 
abstractions. For example, the U.S. Department of Energy should ensure that the modeling of 
features, events, and processes, such as climate change, soil types, sorption coefficients, 
volcanic ash properties, and the physical and chemical properties of radionuclides are consistent 
with assumption in other total system performance assessment abstractions; and 
14.2 Data are Sufficient for Model Justification 
14.2(1) The parameter values used in the license application are adequately justified (e.g., 
behaviors and characteristics of the residents of the Town of Amargosa Valley, Nevada, 
characteristics of the reference biosphere, etc.) and consistent with the definition of the 
reasonably maximally exposed individual in 10 CFR Part 63. Adequate descriptions of how the 
data were used, interpreted, and appropriately synthesized into the parameters are provided; and 
14.2(2) Data are sufficient to assess the degree to which features, events, and processes related 
to biosphere characteristics modeling have been characterized and incorporated in the 
abstraction. As specified in 10 CFR Part 63, the U.S. Department of Energy should demonstrate 
that features, events, and processes, which describe the biosphere, are consistent with present 
knowledge of conditions in the region, surrounding Yucca Mountain. As appropriate, the U.S. 
Department of Energy sensitivity and uncertainty analyses (including consideration of alternative 
conceptual models) are adequate for determining additional data needs, and evaluating whether 
additional data would provide new information that could invalidate prior modeling results and 
affect the sensitivity of the performance of the system to the parameter value or model. 
14.3 Data Uncertainty is Characterized and Propagated Through the Model Abstraction 
14.3(1) Models use parameter values, assumed ranges, probability distributions, and bounding 
assumptions that are technically defensible, reasonably account for uncertainties and 
variabilities, do not result in an under-representation of the risk estimate, and are consistent with 
the definition of the reasonably maximally exposed individual in 10 CFR Part 63; 
14.3(2) The technical bases for the parameter values and ranges in the abstraction, such as 
consumption rates, plant and animal uptake factors, mass-loading factors, and biosphere dose 
conversion factors, are consistent with site characterization data, and are technically defensible; 
14.3(3) Process-level models used to determine parameter values for the biosphere 
characteristics modeling are consistent with site characterization data, laboratory experiments, 
field measurements, and natural analog research; 

14.3(4) Uncertainty is adequately represented in parameter development for conceptual models and 
process-level models considered in developing the biosphere characteristics modeling, either through 
sensitivity analyses, conservative limits, or bounding values supported by data, as necessary. 
Correlations between input values are appropriately established in the total system performance 
assessment, and the implementation of the abstraction does not inappropriately bias results to a 
significant degree. 
4.3 CODES, STANDARDS, AND REGULATIONS 
No codes, standards, or regulations other than those identified in the Project Requirements 
Document (Canori and Leitner 2003 [DIRS 166275], Table 2-3) and determined to be applicable 
(Table 4-2) were used in this analysis. 

5. ASSUMPTIONS 
In Section 6.3.1, two assumptions are used to estimate the proportion of the adult population in 
the Amargosa Valley that could be classified into four population groups (population groups are 
described in Section 6.2). 
5.1 PROPORTION OF POPULATIONCOMMUTERS 
For the groundwater exposure scenario, people who travel 10 minutes or more (one way) to work 
are classified as commuters and spend their working hours outside of the potentially 
contaminated area. For the volcanic ash exposure scenario, people who travel 35 minutes or 
more (one way) to work are classified as commuters. 
This assumption is based on 10 CFR Part 63 [DIRS 156605], which defines the location of the 
receptor and states that the RMEI should have a lifestyle representative of the people who reside 
in Amargosa Valley (10 CFR 63.312 [DIRS 156605]; see also Section 6.2) and the predicted 
depth of ash in northern Amargosa Valley after a volcanic eruption at Yucca Mountain. 
Groundwater Exposure ScenarioFor the groundwater exposure scenario, the receptor would 
only receive a dose from inhalation of, or exposure to, contaminated soil while commuting or 
working within areas where contaminated groundwater is used to irrigate crops or gardens. For 
this scenario, the amount of time it would take to drive out of the area contaminated by use of 
groundwater is determined based on the current conditions in the agricultural region of 
Amargosa Valley. That region is a maximum of about 13 km wide (along Farm Road); 
therefore, residents can leave the area where irrigated fields occur in less than 10 minutes of 
driving on the paved roads in the area. 
Volcanic Ash Exposure ScenarioFor this scenario, the receptor could receive a radiation dose 
from ash deposited on the ground surface in residential and work environments and from ash 
redistributed into those environments from aeolian and fluvial processes (calculation of dose 
during the volcanic eruption is addressed outside of the biosphere model and is not discussed 
here). Therefore, the amount of time required to travel out of the contaminated area is based on 
information about the distribution of ash following a volcanic eruption at Yucca Mountain. 
The amount of ash initially deposited at a location would depend primarily on characteristics of 
the volcano, wind direction, and distance from Yucca Mountain. Ash depths 18 km downwind 
from Yucca Mountain were predicted to range from 0.07 to 55 cm (based on 100 realizations of 
the ASHPLUME model; BSC 2004 [DIRS 170026], Table 6-4; with ash thickness calculated 
from ash concentration as described in the footnote to Table 6-5). About 35 percent of predicted 
depths were less than 1 cm, 75 percent were less than 5 cm, and 90 percent were less than 15 cm. 
Ash depths at the location of the RMEI (18 km south of Yucca Mountain) would be about 
2 orders of magnitude or more lower under normal, variable wind conditions (CRWMS M&O 
2000 [DIRS 153246], Section 3.10.5.1 and Figure 3.10-14) because the wind at Yucca Mountain 
blows to the south infrequently (BSC 2004 [DIRS 170026], Figure 8-1). Based on this 
information, it is likely that at least a thin layer of ash would be deposited throughout most or all 
of the Amargosa Valley and at many work areas on the Nevada Test Site. It is much less likely 

that ash would be deposited at more distant population and employment centers to the south 
(Pahrump), east (Las Vegas), and west (Beatty). 
Over time, some ash initially deposited at or near Yucca Mountain would be washed into the 
Amargosa Valley via Fortymile Wash. Ash may also be redistributed into the upper reaches of 
the Amargosa River near Beatty, Nevada, via Beatty Wash and other drainages that flow west 
from Yucca Mountain. Because they are outside the watersheds where substantial amounts of 
ash would be deposited initially, large amounts of ash probably would not be redistributed into 
Las Vegas and Pahrump. 
For the volcanic ash exposure scenario, it is assumed that, on average, people who commute to 
work less than 35 minutes (one way) remain in the contaminated area. Within 35 minutes, a 
person living in northern Amargosa Valley could travel to work sites in the Amargosa Valley, 
Beatty, and much of the Nevada Test Site. They probably could not travel to Pahrump or to 
other employment centers in Clark County (e.g., Indian Springs, Las Vegas) in only 35 minutes. 
The minimum value of the distribution of the proportion of the population classified as 
commuters is calculated as the average minus two standard errors (in contrast to  one standard 
error for other population groups) to account for uncertainty in the distribution of ash and the 
travel time required to leave contaminated areas (Section 6.3.1). 
5.2 PROPORTION OF POPULATIONLOCAL OUTDOOR WORKERS 
For both exposure scenarios, all residents working in agriculture, 25 percent of those working in 
construction, 10 percent of those working in the utilities industry, and 10 percent of miners are 
classified as local outdoor workers who spend their working hours outdoors in the potentially 
contaminated area. To account for uncertainty in the distribution of ash, the upper bound of the 
distribution of local outdoor workers is calculated as two times the standard error of the mean. 
All other distribution tails for both scenarios are calculated as one times the standard error of the 
mean. 
This assumption is based on information from the Bureau of the Census (2002 [DIRS 159728], 
Table P49) on the number of people working in various industries (Table 6-4). The population 
group local outdoor workers includes people who work outdoors and disturb (and therefore 
resuspend) contaminated soil. Because motor vehicle operators and others working in the 
transportation industry spend most of their time in enclosed cabs, they would not be exposed to 
substantial amounts of contaminated soil, and they are not considered local outdoor workers. 
All residents of the Amargosa Valley who work in agriculture, forestry, or fisheries are assumed 
to work outdoors in that valley. 
Many people in the construction and utilities industries also work outdoors. However, because 
many workers in Amargosa Valley have a long travel time to work (e.g., 20 percent had a travel 
time to work of more than 35 minutes in 2000; Table 6-3), and because there are few industries 
in Amargosa Valley that require construction and utility workers (Rasmuson 2004 
[DIRS 169506]), it is likely that only a few of these people work in the Amargosa Valley and 
conduct soil-disturbing activities. To account for these local workers, 25 percent of construction 

workers and 10 percent of utility workers are assumed to spend their work time outdoors in the 
Amargosa Valley. Because of the small number of workers in these industries, estimates of 
exposure times are insensitive to these percentages. 
One-hundred and nineteen people in Amargosa Valley are employed in the mining industry 
(Table 6-4). Of these, about 58 (Bureau of the Census 2002 [DIRS 159728], Table P50) list their 
occupation as extraction workers (i.e., miners). Many of these miners probably work in 
hard-rock or clay mines around Beatty (Nevada Department of Minerals et al. 1991 
[DIRS 160176], Section VI; Driesner and Coyner 2001 [DIRS 160175], Section VI]). In 1990, 
when gold and silver prices were relatively high (Driesner and Coyner 2001 [DIRS 160175], 
p. 
23), six of eight operational mines in southern Nye County were located around Beatty. The 
mines employed more than 400 people, with about 75 percent working at the Bullfrog Mine. 
The only mines in or near the Amargosa Valley in 1990 were a clay mine near the California 
border, employing 54 people, and a cinder mine at the Lathrop Wells Cone (at the north end of 
the Amargosa Valley), employing two people (Nevada Department of Minerals et al. 1991 
[DIRS 160176], Section VI). Because the Bullfrog Mine closed during the 1990s due to 
exhaustion of profitable ores and lower gold prices (Driesner and Coyner 2001 [DIRS 160175], 
p. 
23), few mines were operating in the region in 2000. According to Driesner and Coyner 
(2001 [DIRS 160175], Section VI), there were two operating mines near Beatty in 2000 
(employing about 50 people) and a clay mine in southern Amargosa Valley (employing 
33 people). Davis (2001 [DIRS 160096], p. 59) also lists the cinder mine at the Lathrop Wells 
Cone as operational and employing seven people in 2000. 
The only miners likely to work in or near an area potentially contaminated by water from a well 
or a substantial amount of volcanic ash are those working at the cinder mine or at temporary sand 
and gravel operations that could be developed in the northern part of the valley. The specialty 
clays mined in the Amargosa Valley are found only in the lacustrine sediments at the southern 
end of the valley (Castor 2001 [DIRS 160095], pp. 40 and 42). Even if ash were to fall at those 
clay mines or at hard-rock mines in the region, miners there would be exposed for a very short 
time because the ash would have to be removed before subsurface clay or rock could be mined. 
Estimates of activity budgets are relatively sensitive to the percentage of miners because miners 
are a substantial portion of the work force. To ensure that the number of miners working in a 
potentially contaminated area is not underestimated, it is assumed that 10 percent of the 
Amargosa Valley residents employed in the mining industry work outdoors in contaminated 
areas. 
This assumption is intended for use in the groundwater and volcanic ash exposure scenarios. 
However, there is a small possibility that contaminated ash would be deposited at some mines 
and other outdoor work locations in southern Amargosa Valley, Beatty, and elsewhere. To 
account for uncertainty in the distribution of ash and the subsequent exposure to additional 
miners and other outdoor workers following a volcanic eruption, the upper bound of the 
distribution of local outdoor workers is calculated as two times the standard error of the mean, as 
described in Section 6.3.1. 

INTENTIONALLY LEFT BLANK 

6. SCIENTIFIC ANALYSIS DISCUSSION 
The objective of this analysis is to develop values for the parameters used in the ERMYN that 
represent characteristics of the human receptor. The receptor considered in this analysis, the 
RMEI, is defined in Section 6.1. The methods and parameters used in the biosphere model to 
evaluate receptor exposure are presented in Section 6.2. 
Characteristics of the RMEI are based on regulations (10 CFR Part 63 [DIRS 156605]; see also 
Section 6.1) and on the range of conditions typical of the environment and population in the 
Amargosa Valley. Local lifestyle and dietary characteristics of the RMEI are considered in this 
report. Lifestyle parameters are discussed in Section 6.3 and Section 6.6, and include the type 
and location of employment and the associated population proportions, land use, activity budgets 
(i.e., amount of time spent conducting activities and the location where those activities occur), 
recreation, and characteristics of dwellings. Lifestyle characteristics are considered in the 
biosphere model for the parameters exposure time, fraction of houses with evaporative coolers, 
evaporative cooler use factor, inadvertent soil ingestion rate, and building shielding factor. 
Dietary parameters are discussed in Section 6.4. Dietary characteristics include the consumption 
rate of contaminated food and water. These characteristics are considered in the model 
parameters for consumption rate of water and consumption rates of locally produced leafy 
vegetables, other vegetables, fruit, grain, meat, poultry, milk, eggs, and fish. 
This analysis report also develops values for breathing rates, which are related to the physiology 
of the receptor (Section 6.3.3); describes the dosimetric methods used to convert internal and 
external exposure of the receptor to radiation doses; and selects dose coefficients for internal and 
external exposure (Section 6.5) and building shielding factors (Section 6.6). 
6.1 DEFINITION OF THE RECEPTOR 
In 2001, the EPA promulgated Public Health and Environmental Radiation Protection Standards 
for Yucca Mountain, Nevada (40 CFR 197 [DIRS 155238]). The EPA rule includes an 
Individual-Protection Standard (40 CFR 197.20 and 197.21 [DIRS 155238]) for the performance 
of the repository, expressed as the annual dose limit to the RMEI. The NRC incorporated these 
standards into licensing regulations in Disposal of High-level Radioactive Wastes in a Geologic 
Repository at Yucca Mountain, Nevada (10 CFR Part 63 [DIRS 156605]), consistent with 
requirements of the Energy Policy Act of 1992. 
Postclosure performance objectives include the requirement that radiological exposure to the 
RMEI are within specified limits (10 CFR 63.113 [DIRS 156605]). The limits for the individual 
protection standard, as in the EPA rule, are expressed in terms of an annual dose that includes all 
potential pathways of radionuclide transport and exposure (10 CFR 63.311 [DIRS 156605]). 

The RMEI is a hypothetical receptor who meets the following criteria (10 CFR 63.312 
[DIRS 156605]): 
 
Lives in the accessible environment above the highest concentration of radionuclides in 
the plume of contamination 
 
Has a diet and living style representative of people who now reside in the Town of 
Amargosa Valley, Nevada. DOE must use projections based on surveys of the people 
residing in the Town of Amargosa Valley, Nevada, to determine their current diets and 
living styles and use the mean values of these factors in the assessments conducted for 
10 CFR 63.311 and 10 CFR 63.321 (DIRS 156605) 
 
Uses well water with average concentrations of radionuclides based on an annual water 
demand of 3,000 acre-feet 
 
Drinks 2 liters of water per day from wells drilled into the groundwater from a point 
above the highest concentration of radionuclides in the plume of contamination 
 
Is an adult with metabolic and physiological considerations consistent with present 
knowledge of adults. 
The required characteristics of the RMEI include living in the accessible environment above the 
highest concentration of radionuclides in the plume of contamination (10 CFR 63.312(a) 
[DIRS 156605]). The location within the accessible environment with the highest concentrations 
likely would be above the contaminated groundwater plume at or near the southern edge of the 
controlled area (i.e., as close to Yucca Mountain as is accessible). The southern edge of the 
controlled area can extend no farther south than 36o40'13.6661" North latitude (10 CFR 63.302, 
definition of Controlled Area (1)(i) [DIRS 156605]), which is north of Highway 95 near the 
southern boundary of the Nevada Test Site. The approximate location of the contaminated 
plume has been predicted to be below Fortymile Wash (DOE 2001 [DIRS 153849], 
Figure 4-147). The exact location of the RMEI within this general area is not important for the 
parameters considered in this analysis, because the parameter values are independent of the exact 
location. 
Regulation 10 CFR 63.312(b) (DIRS 156605) refers to the Town of Amargosa Valley; 
however, there is no legally defined location associated with that name. The most applicable 
legally defined region is the Nye County unincorporated town and taxing district of Amargosa 
Valley (Figure 6-1). 
To meet the requirement in 10 CFR 63.312(b) (DIRS 156605) that mean values for factors 
related to dietary and lifestyle characteristics are used, all parameter distributions developed in 
this report are based on mean values for the population under consideration, and variation is 
calculated based on the standard error of the mean. Thus, the RMEI is a hypothetical composite 
individual with dietary and lifestyle characteristics represented by mean values of the people 
who reside in the unincorporated town of Amargosa Valley. 

To address other requirements of 10 CFR 63.312(b) (DIRS 156605), information from surveys 
of the people living in Amargosa Valley were used in this analysis to determine average values 
of current diets and living styles. A regional survey was conducted in 1997 to determine the 
frequency at which people in the Amargosa Valley consume locally produced food and to 
quantify other lifestyle characteristics (e.g., use of evaporative coolers) (DOE 1997 
[DIRS 100332]). Data from survey respondents having a telephone prefix of 372 were used in 
this analysis. This prefix covered the Amargosa Valley, Lathrop Wells, Ash Meadows, and 
Crystal areas (DOE 1997 [DIRS 100332], p. 3). Of 187 responses included in the analysis, two 
were from people who stated they lived in Crystal, one was from someone who stated she lived 
in Ash Meadows, and the remainder were from people who stated that they lived in Amargosa 
Valley (Appendix A). Thus, the information used in this analysis from that survey is 
representative of the people that reside in the unincorporated town of Amargosa Valley (Figure 
6-1), as required by 10 CFR 63.312(b) (DIRS 156605). 
Survey data from the 2000 census (Bureau of the Census 2002 [DIRS 159728]) were used to 
determine the proportion of the Amargosa Valley population in four population groups 
(Section 6.3.1) and to estimate the average amount of time the receptor spends in five 
environments (Section 6.3.2). Data from the Amargosa Valley census county division were used 
in this analysis. This area (Figure 6-1, Tract 980300 BG3) includes all residents of the 
unincorporated town of Amargosa Valley except for those living in about 10 residences in the 
western part of Crystal. Data from those residences could not be used because information about 
all people living in Crystal was included by the Census Bureau in the Pahrump census county 
division (Figure 6-1). Because the Amargosa Valley census county division includes almost all 
residents of the unincorporated town of Amargosa Valley, including those living in areas most 
likely to be affected by the Yucca Mountain repository, the data are a valid representation of the 
lifestyle characteristics of the people who now reside in the town of Amargosa Valley, Nevada. 
The RMEI is defined as an adult (10 CFR 63.312(e) [DIRS 156605]). For dose assessments, an 
adult is usually defined as an individual 18 or more years old (10 CFR 20.1003 [DIRS 104787]). 
Information on people 18 or more years old was used throughout this analysis with the following 
two exceptions. The Bureau of Census (2002 [DIRS 159728]) reports some data used in this 
analysis (e.g., number of hours worked per year; Tables 6-2 and 6-6) for residents 16 or more 
years old. Because there is no way to separate census information about 16- and 17-year-olds 
from information on older residents, some analyses in Section 6.3.1 and 6.3.2 were derived from 
residents 16 or more years old. This has little influence on the results of this analysis because 
only an estimated 3.7 percent (32 of 862; Table 6-10) of Amargosa Valley residents 16 or more 
years old were 16 or 17 years old. Average daily intake and frequency of consumption used in 
Section 6.4.2 (USDA 2000 [DIRS 154158]) to calculate consumption rates of locally produced 
foods were based on national survey results for males and females 20 or more years old. This 
was done because survey information for persons 18 and 19 years old could not be separated 
from younger age groups. This has little influence on the results of this analysis because 18- and 
19-year-olds only comprised 4.7 percent (39 of 830; Table 6-10) of the Amargosa Valley 
residents 18 or older in 2000. 
The characteristics of the RMEI and the individual protection standard of 0.15 mSv/year 
(15 mrem/year) (10 CFR 63.311 [DIRS 156605]) are considered protective of the general 
population. The general population includes individuals who are represented by the RMEI and 

all other individuals residing in the Yucca Mountain area. Because the community represented 
by the RMEI will have a higher estimated dose than the highest exposed individual who does not 
live in that community, an individual dose limit for the RMEI is protective of all individuals 
(66 FR 55732 [DIRS 156671], p. 55750). Because the location of the RMEI is directly above the 
path of the contamination plume and because the diet and lifestyle are representative of people 
living in the Amargosa Valley, the estimated dose to the RMEI bounds any doses received by 
other individuals in the population. 
Source: BSC 2003 [DIRS 168723], Figure 1.
Figure 6-1. South Central Nevada Census Geography 

6.2 METHODS FOR EVALUATING RECEPTOR RADIATION EXPOSURE, 
INTAKES, AND DOSES 
A person living in a contaminated environment can become exposed to radiation via many 
exposure pathways. The exposure pathways originate in the contaminated environmental 
medium, such as soil, air, or water. Contact with these media results in external exposure or 
intake of radionuclides by inhalation or ingestion. Exposure pathways included in the biosphere 
model, and the associated parameters related to characteristics of the receptor, are shown in 
Table 6-1. The exposure pathways for the volcanic ash exposure scenario are the same as those 
for the groundwater exposure scenario, except for the omission of pathways directly associated 
with contaminated water (e.g., water intake, consumption of freshwater fish, inhalation of 
aerosols generated by evaporative coolers) or associated with radionuclides that are not 
considered for volcanic releases (14C). 
Methods for calculating annual doses to the RMEI from the three major radiation exposure 
pathways (external exposure, inhalation, and ingestion) are described in this section. To estimate 
radiation doses, the biosphere model calculates radionuclide concentrations in the environmental 
media. Then the external exposure or radionuclide intake is evaluated considering the dietary 
and lifestyle characteristics of the receptor. The conversion of radionuclide intake or external 
exposure to dose is accomplished using DCFs or dose coefficients. 
Within the biosphere model, BDCFs (which differ from DCFs, as defined in Section 6.5), rather 
than total doses, are calculated. BDCFs are numerically equal to the dose per unit concentration 
of a radionuclide in a source media (e.g., groundwater or ash). These conversion factors are then 
used in the TSPA (where the concentrations of radionuclides in the source media are estimated) 
to calculate total dose. Therefore, in this report, descriptions and references to dose calculations 
in the biosphere model infer that the calculation uses a unit concentration of radionuclides in a 
medium. 
To account for variation and uncertainty in the characteristics of the RMEI and concentrations of 
radionuclides in the biosphere, the ERMYN uses a microenvironmental modeling approach to 
calculate inhalation and external exposure doses. For microenvironmental models, the total 
exposure environment (i.e., the biosphere) is divided into segments, or environments, with 
different concentrations of contaminants. The contaminant concentration, time spent exposed to 
the contaminant, and intake rate or exposure factor (e.g., breathing rate, shielding factor) are 
determined for each environment; the total dose is calculated as the sum of the dose within all 
environments (Mage 1985 [DIRS 162465], pp. 409 to 410). Micro-environmental models are 
commonly used to evaluate exposure to particulate matter and other contaminants (Duan 1982 
[DIRS 162466]; Mage 1985 [DIRS 162465]; Klepeis 1999 [DIRS 160094]). 
In the ERMYN model, the biosphere is divided into five environments. These mutually 
exclusive environments represent the behavioral and environmental combinations for which 
people may receive substantially different rates of exposure via inhalation or external exposure. 
Away from Potentially Contaminated AreaThis category includes time spent away from 
areas contaminated by groundwater or volcanic ash, including time spent working and 
commuting to work by people who work outside the contaminated areas. 

Table 6-1. Biosphere Model Exposure Pathways and Associated Parameters Related to Receptor 
Characteristics 
Environmental 
Medium 
Exposure 
Mode Exposure Pathwaysa 
Associated Parameters Related to the 
Receptor Characteristics 
WATER Ingestion Water intake * 
Consumption rate of water 
DCFs for ingestion 
Ingestion 
Inadvertent soil ingestion Inadvertent soil ingestion rate 
DCFs for ingestion 
SOIL 
External 
External radiation exposure Population proportion 
Exposure time 
Building shielding factor 
Dose coefficient for exposure to contaminated 
ground surface 
Dose coefficient for exposure to soil 
contaminated to an infinite depth 
AIR Inhalation 
Breathing of airborne 
particulates 
Breathing of gases (222Rn and 
decay products) 
Breathing of gases (14C)* 
Breathing of aerosols from 
evaporative coolers* 
Population proportion 
Exposure time 
Breathing rate 
Fraction of houses with evaporative coolers 
Evaporative cooler use factor 
DCFs for inhalation 
DCF for inhalation of radon decay products 
PLANTS Ingestion 
Consumption of locally 
produced crops: 
Leafy vegetables 
Other vegetables 
Fruit 
Grain 
Consumption rate of locally produced crops 
DCFs for ingestion 
ANIMALS Ingestion 
Consumption of locally 
produced animal products: 
Meat 
Poultry 
Milk 
Eggs 
Consumption rate of locally produced animal 
products 
DCFs for ingestion 
AQUATIC 
ORGANISMS Ingestion 
Consumption of locally 
produced freshwater fish* 
Consumption rate of locally produced fish 
DCFs for ingestion 
Source: Based on descriptions of exposure pathways in the Biosphere Model Report (BSC 2004 [DIRS 169460], 
Section 6.3). 
a 
All pathways are the same for the groundwater and volcanic ash exposure scenarios except those marked with 
an asterisk, which are not included in the volcanic ash exposure scenario. 
DCF=dose conversion factor 

Active OutdoorsTime spent active outdoors includes time spent outdoors in contaminated 
areas conducting activities that resuspend soil. This includes conducting dust-generating 
activities while working (e.g., plowing, excavating, and livestock operations) and recreating 
(e.g., gardening, landscaping, and riding horses or motorbikes) outdoors. Because dust 
concentrations decrease rapidly after dust-disturbing activities cease (e.g., Pinnick et al. 
1985 [DIRS 159577], pp. 103 to 104), this category is limited to the time when the activities are 
occurring. 
Inactive OutdoorsThis category represents the time spent commuting within contaminated 
areas and time spent outdoors in the contaminated area conducting activities that do not 
resuspend soil (e.g., sitting, swimming, walking, barbecuing, and equipment maintenance). 
Commuting time is included in this category, because major roads in the Amargosa Valley are 
paved. 
Asleep IndoorsThis category includes time spent sleeping indoors within contaminated areas. 
Active IndoorsThis category includes time spent awake, indoors within contaminated areas, 
including work time. In the model, this is calculated as the remainder of the day not spent in the 
other four environments. 
To account for variation and uncertainty in the amount of time the receptor spends in these 
environments, the model considers four mutually exclusive population groups (Section 6.3.1). 
The exposure times per environment for the RMEI are calculated as the weighted average of the 
exposure times per environment for all population groups (e.g., Equation 6.2-3). These groups 
represent the range of behaviors that most influence the amount of time people would be exposed 
to radionuclides via inhalation of resuspended soil, use of evaporative coolers, and external 
exposure. Variation among individuals in these exposure pathways is influenced primarily by 
the amount of time spent indoors and outdoors within contaminated areas and spent away from 
contaminated areas. For adults, variation among these time factors primarily is a function of 
occupational characteristics. People working out of a contaminated area generally would 
experience less exposure than people who remain within the area, and people who work outdoors 
would be exposed at a different level than those who remain indoors. Therefore, the categories 
are based on work location and type of occupation. Estimates of the proportion of the adult 
population of the Amargosa Valley in each group are given in Section 6.3.1. 
Non-WorkersResidents who are unemployed or not in the labor force, including retired 
persons. 
CommutersResidents who work in uncontaminated areas. 
Local Outdoor WorkersResidents who work outdoors, disturb and resuspend contaminated 
soil. 
Local Indoor WorkersResidents who work indoors (or outdoors in enclosed vehicles) in 
contaminated areas. The proportion of the population in this group is calculated as the 
proportion not in the other groups. 

6.2.1 Evaluation of External Exposure 
Doses received from external sources of radiation originate from radionuclides in the soil, air, 
and water. For external exposure, radiation emitters are external to the human body. Therefore, 
the exposure continues only as long as a person is in the immediate vicinity of, or in direct 
contact with, the contaminated medium, such as soil, air, or water. The doses from external 
exposure can be evaluated using radionuclide media concentrations and the duration of exposure 
to these media in combination with dose coefficients for external exposure to photons and 
electrons emitted by radionuclides distributed in the contaminated media. 
The annual individual dose to a receptor from external exposure to primary radionuclide i in 
contaminated soil may include contributions from other primary radionuclides formed in the soil 
as a result of radioactive decay of radionuclide i. The combined dose is estimated using the 
expression in Equation 6.2-1 (BSC 2004 [DIRS 169460], Section 6.4.7.1): 
.
..
.
... 
.
Csl
.
=
.
.
.
D 
D 
EDCi 
f 
PPm (3600

t )
,
.. 
= 
i ext 
,
l ext 
, 
soil , l l ext n
, 
m n 
d 
,
.
ll 
(Eq. 6.2-1) 
n 
m 
where 
Dext, i = annual dose from external exposure to primary radionuclide i in soil (Sv/yr) 
Dext, l = dose from external exposure to radionuclide l in a decay chain of a primary 
radionuclide i (Sv/yr) 
l = index of radionuclide in a decay chain; l = 0 for primary radionuclide 
EDCisoil, l = effective dose coefficient for exposure to soil contaminated to an infinite 
depth for a radionuclide l in a decay chain of a primary radionuclide i (Sv/s 
per Bq/m3) 
Cs l = saturation activity concentration in surface soil for a radionuclide l in a 
decay chain of a primary radionuclide i (Bq/m2) 
d = depth of surface soil (m) 
fext, l, n = building shielding factor for external exposure to radionuclide l in soil in 
environment n (dimensionless) 
n = environment index; n = 1 for active outdoors, 2 for inactive outdoors, 3 for 
active indoors, 4 for asleep indoors, and 5 for away from the contaminated 
area 
m = population group index; m = 1 for commuters, 2 for local outdoor workers, 
3 for local indoor workers, and 4 for non-workers 
PPm = population proportion (fraction of total population in population group m) 
t n, m = exposure time (number of hours a population group m spends in the 
environment n) (hr/yr) 
3600 = unit conversion factor, 3600 s/hr. 
This analysis develops values for the dose coefficients for individual radionuclides that are used 
to develop the effective dose coefficients for exposure to contaminated soil, EDCFsoil,l 
(Section 6.5); the building shielding factor for external exposure to radionuclides in soil, fext, l, n 
(Section 6.6); the amount of time population groups spend in defined environments, t n, m 

(Section 6.3); and the fraction of total population in specified population groups, PPm 
(Section 6.3). 
6.2.2 Evaluation of Inhalation Exposure 
External exposure, described in the previous section, results from emissions that arise outside the 
human body. This is in contrast to the intake of radionuclides by inhalation or ingestion, for 
which radiation is emitted inside the body and the exposure continues following the intake for as 
long as the radionuclides remain in the body. The inhalation dose is caused by inhalation of 
contaminated air. Three mechanisms of air contamination were included in the biosphere model: 
resuspension of contaminated soil, the use of evaporative coolers, and gaseous emission from 
soil (which includes exhalation of 222Rn, and 14C from soil). The total inhalation dose is the sum 
of inhalation doses resulting from these processes (BSC 2004 [DIRS 169460], Section 6.4.8) 
such that 
, ,, ,, ,, 
D
i inh =Di p inh + Di e inh + Di g inh (Eq. 6.2-2) 
where 
Dinh, i = annual dose from inhalation exposure to radionuclide i (Sv/yr) 
Dinh, p, i = annual dose from inhalation exposure to radionuclide i in resuspended 
particles (Sv/yr) 
Dinh, e, i = annual dose from inhalation exposure to radionuclide i in air resulting from 
operation of evaporative cooler (Sv/yr) 
Dinh, g, i = annual dose from inhalation exposure to radionuclides in air resulting from 
gaseous emission of radionuclide i from soil (Sv/yr). 
The last dose component (Equation 6.2-2) applies only to the inhalation of 222Rn decay products, 
and 14C. 
6.2.2.1 Inhalation of Airborne Particulates 
The annual dose to a receptor from inhalation exposure to primary radionuclide i in resuspended 
particles includes all radionuclides (l) in the decay chain of primary radionuclide i. The 
combined dose is estimated (BSC 2004 [DIRS 169460], Section 6.4.8.1) in Equation 6.2-3 as 
.
D
i p inh =. Dl p inh =. EDCFl inh ..Can l h BRn .(PPmt m n ) .. 
(Eq. 6.2-3) 
,,,, , . n 
, , , 
ll m . 
where 
Dinh, p, i = annual dose from inhalation exposure to primary radionuclide i in 
resuspended particles (Sv/yr) 
Dinh, p, l = annual dose from inhalation exposure to radionuclide l in a decay chain of 
primary radionuclide i in resuspended particles (Sv/yr) 

l 
= Radionuclide index for a decay chain, l = 0 for primary radionuclide, 1 for 
the 1st decay product, 2 for the 2nd decay product 
EDCFinh, l = effective DCF for inhalation of radionuclide l in a decay chain of primary 
radionuclide i (Sv/Bq) 
n = Environment index; n = 1 for active outdoors, 2 for inactive outdoors, 3 for 
active indoors, 4 for asleep indoors, and 5 for away from the contaminated 
area 
Cah, l, n = activity concentration of radionuclide l in a decay chain of primary 
radionuclide i in air for human (h) environment n (Bq/m3) 
BRn = breathing rate for environment n (m3/hr) 
m = population group index; m = 1 for commuters, 2 for local outdoor workers, 
t 
3 for local indoor workers, and 4 for non-workers 
PPm = population proportion (fraction of total population in population group m) 
n, m = exposure time (number of hours a population group m spends in 
environment n) (hr/yr). 
This analysis develops values for the inhalation DCFs for individual radionuclides that are used 
to develop the effective DCFs for inhalation, EDCFinh, l (Section 6.5); the 
environment-dependent breathing rate, BRn (Section 6.3); the amount of time population groups 
spend in defined environments, t n, m (Section 6.3); and the fraction of total population in 
specified population groups, PPm (Section 6.3). 
6.2.2.2 Inhalation of Aerosols Produced by Evaporative Coolers 
The inhalation dose attributable to the operation of evaporative coolers is estimated (BSC 2004 
[DIRS 169460], Section 6.4.8.2) in Equation 6.2-4 as 
4 
BR
n 
...
... 
(Eq. 6.2-4) 
.
.
D
EDCF
i inhCai e f f t PP 
m 
=
,
inh, i e ,, 
cooler 
use 
nm
, 
n
=
3 
m 
where 
Dinh, e, i = annual dose from inhalation of primary radionuclide i from evaporative 
cooler operation (Sv/yr) 
EDCFinh, i = effective DCF for inhalation of radionuclide i (Sv/Bq) 
Cae, i = activity concentration of radionuclide i in indoor air attributable to the 
evaporative cooler operation (Bq/m3) 
fcooler = fraction of houses with evaporative coolers (dimensionless) 
fuse = annual evaporative cooler use factor (dimensionless). 
This analysis develops values for the inhalation DCFs for individual radionuclides that are used 
to develop the effective DCFs for inhalation, EDCFinh, i (Section 6.5); the 
environment-dependent breathing rate, BRn (Section 6.3); the amount of time population groups 
spend in defined environments, tn, m (Section 6.3); the fraction of total population in specified 
population groups, PPm (Section 6.3), the fraction of houses with evaporative coolers, fcooler 
(Section 6.3); and the annual evaporative cooler use factor, fuse (Section 6.3). 

6.2.2.3 Inhalation of Carbon-14 
The inhalation dose from 14C is calculated using a method similar to that used for assessment of 
inhalation dose from resuspended particulates (BSC 2004 [DIRS 169460], Section 6.4.8.3), 
which is 
,, ,, 
D
C g inh -14 =. DC g inh -, 14 n
n
,, m m n 
= DCF
C inh -14 CaC g -14 . BRn ..
. t PP , 
.. 
(Eq. 6.2-5) 
n . m . 
where 
Dinh, g, C-14 = annual dose from inhalation of 14C in gaseous form (Sv/yr) 
Dinh, g, C-14, n = annual dose from inhalation of gaseous 14C for environment n (Sv/yr) 
Cag, C-14 = activity concentration of 14C in air (indoors and outdoors) (Bq/m3) 
DCFinh, C-14 = DCF for inhalation of 14C (Sv/Bq). 
This analysis develops values for the inhalation DCF for 14C, DCFinh, C-14 (Section 6.5); the 
environment-dependent breathing rate, BRn (Section 6.3); the amount of time population groups 
spend in defined environments, tn,m (Section 6.3); and the fraction of total population in specified 
population groups, PPm (Section 6.3). 
6.2.2.4 Inhalation of Radon Decay Products 
The dose due to inhalation of radon decay products is evaluated in the biosphere model 
(BSC 2004 [DIRS 169460], Section 6.4.8.4) as 
D
inh , g , Rn-222 =. Dinh, g , Rn-, 222 n
n
5 . =. Cag , Rn-, 222 n Fn DCFinh, Rn -, 222 n BRn .. PPmtm n 
.+ 
n=1 . m 
, . 
4 .. Cag, Rn-, 222 e f cooler f use DCFinh, Rn -, 222 n BRn .. PPmtm n 
. 
n=3 . m 
, . (Eq. 6.2-6) 
where 
Dinh, g, Rn-222 = annual dose from inhalation of 222Rn decay products (Sv/yr) 
Dinh, g,Rn-222, n = annual dose from inhalation of 222Rn decay products for 
environment n (Sv/yr) 
Cag, Rn-222, n = activity concentration of 222Rn in air for environment n (Bq/m3) 
Fn = correction factor to account for the use of evaporative coolers in 
indoor environment n (dimensionless), 1 for n =1 & 2, and 
(1 -fcooler  fuse) for n = 3 & 4 
DCFinh, Rn-222, n = DCF for inhalation of 222Rn decay products for environment n 
(Sv/Bq) 

Cag, Rn-222,e = activity concentration of 222Rn in indoor air at a high ventilation rate 
during evaporative cooler in operation (Bq/m3). 
This analysis develops values for the environment-dependent DCFs for inhalation of 222Rn decay 
products, DCFinh, Rn-222, n (Section 6.5); the environment-dependent breathing rate, BRn 
(Section 6.3); the amount of time population groups spend in defined environments, t n,m (Section 
6.3); and the fraction of total population in specified population groups, PPm (Section 6.3). 
6.2.3 Evaluation of Ingestion Exposure 
The total ingestion dose includes contributions from ingestion of water, crops, animal products, 
fish, and soil (BSC 2004 [DIRS 169460], Section 6.4.9) and is expressed as 
D
i ing =Di w ing + Di p ing + Di d ing + Di f ing + Di s ing (Eq. 6.2-7) 
, ,,,,,,,,,, 
where 
Ding, i = annual dose from ingestion of radionuclide i (Sv/yr) 
Ding, w, i = annual dose from ingestion of radionuclide i in drinking water (Sv/yr) 
Ding, p, i = annual dose from ingestion of radionuclide i in crops (Sv/yr) 
Ding, d, i = annual dose from ingestion of radionuclide i in animal products (Sv/yr) 
Ding, f, i = annual dose from ingestion of radionuclide i in fish (Sv/yr) 
Ding, s, i = annual dose from inadvertent ingestion of radionuclide i in surface soil 
(Sv/yr) 
Equation 6.2-7 can be further expressed (BSC 2004 [DIRS 169460]; Sections 6.4.9.1 through 
6.4.9.5) as 
.. .
D
i ing = EDCFi ing Uw Cw +... 
EDCFl ing .( Cp Upj ). +.. EDCF .( Cd Udk )
,, i , l, j l ing k l . 
l . j . l . 
, 
k 
, . (Eq. 6.2-8) 
+ EDCFi ing Uf Cf +.( EDCFl ing Csl m Us)
, i ,,
l
where 
EDCFing, i = effective DCF for ingestion of radionuclide i (Sv/Bq) 
Cwi = activity concentration of radionuclide i in groundwater (Bq/L)
Uw = annual consumption rate of drinking water for the receptor (L/yr) 
l = index of radionuclide decay chain member, l = 0 for primary radionuclide 
EDCFing, l = effective DCF for ingestion of radionuclide l in decay chain of primary 
radionuclide i (Sv/Bq) 
Cpl, j = activity concentration of a primary radionuclide l in crop type j (Bq/kg) 
j = index of crop type, j = 1 for leafy vegetables, 2 for other vegetables, 3 for 
fruit, and 4 for grain 
Upj = annual consumption rate of crop type j (kg/yr) 
Cdl, k = activity concentration of primary radionuclide l in animal product type k 

This analysis develops values for the ingestion DCFs for individual radionuclides which are used 
to develop the effective DCFs for ingestion, EDCFing,l (Section 6.5); the annual consumption 
rates of crops by crop type, Upj (Section 6.4); the annual consumption rates of animal products 
by animal product type, Udk (Section 6.4); annual consumption rates of fish, Uf (Section 6.4); 
and the annual consumption rate of soil, Us (Section 6.4). 
(Bq/kg) 
k = index of animal product, k = 1 for meat, 2 for poultry, 3 for milk, and 4 for 
eggs 
Udk = annual consumption rate of animal product type k (kg/yr) 
Cfi = activity concentration of primary radionuclide i in fish (Bq/kg) 
Uf = annual consumption rate of fish (kg/yr) 
Csm, l = mass-based activity concentration of a primary radionuclide l in the 
surface soil (Bq/kg) 
Us = annual consumption rate of soil (kg/yr) 
6.3 LIFESTYLE CHARACTERISTICS OF THE RECEPTOR 
In this section, distributions for parameters in the biosphere model related to the lifestyle and 
physiological characteristics of the RMEI are developed. These parameters include population 
proportions, annual exposure time, breathing rates, the fraction of houses with evaporative 
coolers, and the evaporative cooler use factor. 
6.3.1 Proportion of Population 
Estimates of the proportion of the adult population in the Amargosa Valley classified into the 
four population groups (described in Section 6.2; PPm, with m = population category) are used to 
estimate radiation exposure from inhalation and external exposure pathways. 
Estimates of the proportion of the adult population in the Amargosa Valley within each of the 
four categories were developed from 2000 census data (Bureau of the Census 2002 
[DIRS 159728]) on employment (Tables 6-2 and 6-4) and commuting time (Table 6-3) of people 
in the Amargosa Valley census county division. The standard error of the estimated proportions, 
SE(p), were calculated using methods recommended by the Bureau of the Census for calculating 
standard error of percentages (Bureau of the Census 2002 [DIRS 160179], pp. 8-6 and 8-21) as 
p SE 
(
)
=
DF
()..
.
..
.-ppN 
15 
(Eq. 6.3-1) 
where 
N = total population or population-group size 
p = estimated proportion of the population in a group 
DF = design factor. 
The design factor is a state and characteristic-specific correction factor determined from the 
percent of the population sampled. In the Amargosa Valley census county division, 11.1 percent 

of the population was sampled (Bureau of the Census 2002 [DIRS 159728], Table P4). The 
associated design factors for Nevada are 1.3 for usual hours worked per week and weeks worked 
in 1999 and 1.4 for travel time to work and industry of employment (Bureau of the Census 2002 
[DIRS 160179], Table C for Nevada). 
With two exceptions, uniform distributions with a minimum one standard error lower than the 
estimated proportion and a maximum one standard error higher than the estimate are to be used 
in the biosphere model to define the proportion of non-workers, commuters, and local outdoor 
workers (Table 6-5). To account for uncertainty in the distribution of ash following a volcanic 
eruption, the lower bound of the distribution of commuters and the upper bound of the 
distribution of local outdoor workers are calculated as the estimated proportion plus or minus 
two standard errors. The proportion of local indoor workers is calculated in the model as one 
minus the sum of the three other proportions; the estimated proportion and standard error for that 
group are presented below only for comparison. 
Non-WorkersNon-workers are adults who are unemployed or not in the labor force, including 
retired persons. The number of non-workers was estimated based on information from the 
2000 census on the work status during 1999 of Amargosa Valley residents 16 years or older. Of 
an estimated total of 862 residents 16 years of age or older, 338 (39.2 percent) were not in the 
work force in 1999 (Table 6-2). The standard error of this estimate is 4.8 percent (calculated as 
1.3 [(5/862) 0.392 0.608]1/2). The uniform distribution to be used in the biosphere model 
for this population group has minimum and maximum values of 34.4 percent and 44.0 percent, 
respectively (estimate proportion  one standard error). This distribution is to be used for the 
groundwater and volcanic ash exposure scenarios. 
The estimated number of Amargosa Valley residents that worked differs between 
Table 6-2 (524 working residents) and Tables 6-3 and 6-4 (449 working residents). Table 6-2 
summarizes employment status for all of 1999; the estimate of the total number of working 
residents includes people who worked part time. Tables 6-3 and 6-4 report information on 
commute time and industry of employment the week before survey forms were filled out (in 
April 2000), and therefore do not include information about people temporarily unemployed at 
that time. Because Table 6-2 includes information on part-time workers, and because 
information from that table is used in Section 6.3.2 to estimate the average number of hours 
worked, it is the more applicable source of information on the proportion of working (524 of 
862 = 60.8 percent) and non-working (338 of 862 = 39.2 percent) residents. Estimates of the 
proportion of commuters and local outdoor workers are derived from information in Tables 6-3 
and 6-4; therefore, these values must be multiplied by the percentage of the working population 
in 1999 (60.8 percent). To propagate errors from both estimates, the standard error, SE(p1p2), 
was calculated (using an equation modified from Knoll 1989 [DIRS 161052], p. 90; Bureau of 
the Census 2002 [DIRS 160179], p. 8-7) as 
2 
( () ()
12
p p SE )=p p p SE 2 
+p SE (Eq. 6.3-2) 
12122 2
pp
12 

where 
p1 = estimated proportion of the population in group 1 (the proportion of workers in 
the population) 
p2 = estimated proportion of the population in group 2 (the proportion of commuters 
or local outdoor workers) 
Table 6-2. Work Status of Amargosa Valley Residents in 1999 
Working Time 
Number of 
Males 
Number of 
Females Total 
Worked in 1999 296 228 524 
Usually worked =35 hours/week 
50-52 weeks 204 93 297 
48-49 weeks 8 21 29 
40-47 weeks 6 6 
27-39 weeks 11 3 14 
14-26 weeks 19 15 34 
1-13 weeks 29 29 
Usually worked 15-34 hours/week 
50-52 weeks 30 30 
48-49 weeks 8 8 16 
40-47 weeks 11 11 
27-39 weeks 12 12 
14-26 weeks 14 14 
1-13 weeks 10 15 25 
Usually worked 1-14 hours/week 
50-52 weeks 7 7 
48-49 weeks 
40-47 weeks 
27-39 weeks 
14-26 weeks 
1-13 weeks 
Did not Work in 1999 165 173 338 
Total 461 401 862 
Source: Bureau of the Census 2002 (DIRS 159728), Table P47. 
CommutersThis group includes employed people who would work in uncontaminated areas. 
For the groundwater exposure scenario, it is assumed that this group includes all employed adults 
in the Amargosa Valley who commute 10 minutes or more one way to work (Section 5.1). An 
estimated 64.4 percent (289 of 449) of Amargosa Valley residents 16 years or older that worked 
the week prior to census commuted 10 minutes or more (Table 6-3). The standard error of this 
estimate is 7.1 percent (calculated as 1.4  [(5/449)  0.644  0.356]1/2). This estimate must be 
multiplied by the proportion of the entire population 16 years or older that was employed in 
1999 (60.8 percent); thus, the estimate of adults in the Amargosa Valley that commute 
10 minutes or more is 39.2 percent (i.e., 0.608  0.644), with a standard error of 5.3 percent 

(calculated as (0.608x0.644)  [(0.0482/0.6082) + (0.0712/0.6442)]1/2 using Equation 6.3-2). 
The distribution of commuters for the groundwater exposure scenario is uniform with minimum 
and maximum values of 33.9 percent and 44.5 percent, respectively (estimated proportion  one 
standard error). 
Table 6-3. Travel Time to Work for Amargosa Valley Residents 
Travel Time (Minutes) a Number of Residents 
0 (Worked at home) 6 
Less than 5 84 
5 to 9 70 
10 to 14 98 
15 to 19 35 
20 to 24 64 
25 to 29 0 
30 to 34 0 
35 to 39 14 
40 to 44 23 
45 to 49 24 
60 to 89 9 
90 or more 22 
Total 449 
Source: Bureau of the Census 2002 (DIRS 159728), Table P31. 
a 
One-way commute time for employed residents 16 years or older 
during the week prior to the April 2000 census. 
For the volcanic ash exposure scenario, it is assumed that people who commute 35 minutes or 
more one way are not exposed to contaminated ash while at work (Section 5.1). An estimated 
20.5 percent (92 of 449) of Amargosa Valley residents 16 years or older that worked the week 
prior to the census commuted 35 minutes or more (Table 6-3). The standard error of this 
estimate is 6.0 percent (1.4  [(5/449)  0.205  0.795]1/2). The estimate of the total population 
of adults who commute 35 minutes or longer is 12.5 percent (i.e., 0.608  0.205), with a standard 
error of 3.8 percent (0.608  0.205)  [(0.0482/0.6082) + (0.0602/0.2052)]1/2). Because of 
uncertainty about where ash from a volcanic eruption at Yucca Mountain would fall 
(Section 5.1), the minimum value of the distribution of commuters is calculated as the estimated 
proportion minus two standard errors. Therefore, the distribution of commuters for the volcanic 
ash exposure scenario is uniform with minimum and maximum values of 4.9 percent and 
16.3 percent, respectively. 
Local Outdoor WorkersThis group includes people who work outdoors and disturb 
(and therefore resuspend) contaminated soil. It is assumed that local outdoor workers include all 
agricultural works, 25 percent of construction workers, 10 percent of utility workers, and 
10 percent of workers in the mining industry (Section 5.2). The estimated number of local 
outdoor workers in 2000 was 41 (26 agricultural workers, 2 of 7 construction workers, 1 of 
8 utility workers, and 12 of 119 miners [Table 6-4]). This is 9.1 percent of the 449 Amargosa 
Valley residents 16 years or older that worked the week prior to the census, with a standard error 
of 4.2 percent (1.4  ((5/449)  0.091  0.909)1/2). The estimate of the total population of 

local outdoor workers is 5.5 percent (i.e., 0.608  0.091), with a standard error of 2.6 percent 
((0.608  0.091)  [(0.0482/0.6082) + (0.0422/0.0912)]1/2). 
Table 6-4. Industry of Employed Amargosa Valley Residents in 2000 
Industry of Employment a 
Number of 
Males 
Number of 
Females Total 
Agriculture 26 26 
Mining 101 18 119 
Construction 7 7 
Retail trade 19 14 33 
Transportation and warehousing 23 26 49 
Utilities 8 8 
Educational services 47 47 
Health care and social assistance 20 8 28 
Arts, entertainment, recreation, accommodation, and food services 22 71 93 
Other services (except public administration) 6 15 21 
Public administration 18 18 
Total 232 217 449 
Source: Bureau of the Census 2002 (DIRS 159728), Table P49. 
a 
Industry of employed residents 16 years or older during the week prior to the April 2000 census. 
The distribution of local outdoor workers for the groundwater exposure scenario is uniform with 
a minimum of 2.9 percent and a maximum of 8.1 percent (estimated proportion  one standard 
error). Because of uncertainty about where ash from a volcanic eruption at Yucca Mountain 
would fall (Section 5.2), the maximum value of the distribution of this population group for the 
volcanic ash exposure scenario is calculated as the estimate plus two standard errors. Thus, the 
distribution of local outdoor workers for that exposure scenario is uniform with minimum and 
maximum values of 2.9 percent and 10.7 percent, respectively. 
Local Indoor WorkersThis group includes all people who work indoors (or outdoors in 
enclosed vehicles) in areas contaminated by groundwater or ash. In the biosphere model, the 
proportion of local indoor workers is calculated as one minus the sum of the other three 
population proportions. For the groundwater exposure scenario, the estimated proportion of 
local indoor workers is 16.1 percent (100 percent minus 39.2 percent non-workers, 39.2 percent 
commuters, and 5.5 percent local outdoor workers). For the volcanic ash exposure scenario, the 
estimated proportion in this group is 42.8 percent (100 percent minus 39.2 percent non-workers, 
12.5 percent commuters, and 5.5 percent local outdoor workers). 
The population proportion values are summarized in Table 6-5. 
6.3.2 Exposure Times 
To calculate exposure times for the five environments (Section 6.2), time spent conducting six 
activities (working, commuting, outdoors not working, active outdoors, sleeping, and away from 
the Amargosa Valley) is estimated in Section 6.3.2.1. The time estimates are then used to 
develop exposure times for each of the four population groups (Section 6.3.2.2). 

Table 6-5. Population Proportions 
Group 
Estimated 
Percentage Standard Errora 
Uniform Distributionb 
Minimum Maximum 
Groundwater Release Exposure Scenario 
Non-Workers 39.2% 4.8% 34.4% 44.0% 
Commuters 39.2% 5.3% 33.9% 44.5% 
Local Outdoor Workers 5.5% 2.6% 2.9% 8.1% 
Local Indoor Workers 16.1%c 
Volcanic Release Exposure Scenario 
Non-Workers 39.2% 4.8% 34.4% 44.0% 
Commuters 12.5% 3.8% 4.9% 16.3% 
Local Outdoor Workers 5.5% 2.6% 2.9% 10.7% 
Local Indoor Workers 42.8%c 
a 
Calculated using equations 6.3-1 and 6.3-2. 
b Calculated as estimated percentage  1 SE, except volcanic- commuters (minimum = estimated percentage  
2 SE) and volcanic- local outdoor workers (maximum = estimated percentage + 2 SE). 
Calculated in the biosphere model as 100 percent minus the sum of the other three percentages. 
6.3.2.1 Behavior Times 
Time Spent WorkingThe average amount of time people spent working (of those who 
worked), and the associated standard error, was calculated from census data on hours worked per 
week and weeks worked per year by Amargosa Valley residents 16 years or older in 
1999 (Table 6-6). The average of this categorical data set was calculated (using equations 
recommended by the Bureau of the Census 2002 [DIRS 160179], pp. 8-8 and 8-9) as 
c 
x=. j m p 
jj (Eq. 6.3-3) 
where 
c = number of categories into which the data is divided 
pj = portion of the total number of workers in category j 
mj = midpoint of each category j 
The Bureau of the Census (2002 [DIRS 159728], Table P47) presents time worked as a 
combination of hours worked per week and weeks worked per year. These distributions were 
combined to estimate the number of hours worked in 1999. The estimated mean of the combined 
distributions was used as mj in Equation 6.3-3, rather than the midpoint of each category. The 
mean was calculated as the product of the midpoints of hours per week and hours per year 
(Table 6-6) for each category, based on an equal probability of occurrence (i.e., uniform 
distribution) of each value within a category. This was done because the midpoint overestimates 
the average number of hours worked per year unless there is a correlation between number of 
hours worked per week and weeks worked per year. 

Table 6-6. Estimated Number of Hours Worked Per Year 
Weeks Worked/Year a Hours Worked/Week a 
mj 
b 
Number of 
Workers pj 
c pjmj pjmj 
2Range Midpoint Range Midpoint 
50-52 51 =35 52.5d 2,677.5 297 0.567 1,517.6 4,063,349.0 
48-49 48.5 =35 52.5 d 2,546.3 29 0.055 140.9 358,813.5 
40-47 43.5 =35 52.5 d 2,283.8 6 0.011 26.1 59,719.6 
27-39 33 =35 52.5 d 1,732.5 14 0.027 46.3 80,194.3 
14-26 20 =35 52.5 d 1,050.0 34 0.065 68.1 71,536.3 
1-13 7 =35 52.5 d 367.5 29 0.055 20.3 7,474.5 
50-52 51 15-34 24.5 1,249.5 30 0.057 71.5 89,384.6 
48-49 48.5 15-34 24.5 1,188.3 16 0.031 36.3 43,112.6 
40-47 43.5 15-34 24.5 1,065.8 11 0.021 22.4 23,843.6 
27-39 33 15-34 24.5 808.5 12 0.023 18.5 14,969.6 
14-26 20 15-34 24.5 490.0 14 0.027 13.1 6,414.9 
1-13 7 15-34 24.5 171.5 25 0.048 8.2 1,403.3 
50-52 51 1-14 7.5 382.5 7 0.013 5.1 1,954.5 
Sum 524 1.000 1,994.5 4,822,170.1 
Average e 1,994.5 
s2 f 844,117.0 
Standard error g 116.7 
Source: Bureau of the Census 2002 (DIRS 159728), Table P47). 
a 
Estimated number of hours worked in 1999 by employed residents of the Amargosa Valley. 
b 
mj = (midpoint of weeks worked per year) (midpoint of hours worked per week). 
c 
pj = portion of total workers (524) in category j. 
d Calculated as (3/2)  (lower limit of interval), as recommended by Bureau of the Census (2002 [DIRS 160179], p. 89). 
e 
Calculated using equation 6.3-3. 
f 
Calculated using equation 6.3-5. 
g Calculated using equation 6.3-4, with DF = 1.3 
The standard error [SE( x )] was calculated (Bureau of the Census 2002 [DIRS 160179], p. 8-8) 
as 
SE(x ) = 5 s 2 DFN (Eq. 6.3-4) 
with DF = 1.3 (Bureau of the Census 2002 [DIRS 160179], Table C for Nevada) and s2 
calculated as 
c 
22
s =.m p 
jj -(x)2 (Eq. 6.3-5) 
j =1 
The average number of hours worked in 1999 by employed residents of Amargosa Valley 
16 years or older was 1,994.5 hours per year, with a standard error of 116.7 hours (Table 6-6). 

This is an annual average of 5.5 hours per day (1,994.5 hours per year  365 days per year), with 
a standard error of 0.3 hours. Converted to hours worked per week (1,994.5  52 weeks = 38.4 
hours per week), this is similar to the national average number of hours worked by persons in all 
industries (39.7 hours; Bureau of the Census 2001 [DIRS 160177], Table 582). 
Time Spent CommutingThe average amount of time people that work spend commuting was 
calculated based on assumptions about how long it would take to drive out of the contaminated 
area (Section 5.1) and from census data on commuting time of 16-year and older residents of the 
Amargosa Valley the week prior to the 2000 census (Tables 6-7 and 6-8). Averages and 
standard error are calculated using equations 6.3-3, 6.3-4, and 6.3-5, with a DF = 1.4 (Bureau of 
the Census 2002 [DIRS 160179], Table C for Nevada). 
Table 6-7. Commute Time (minutes/day) for the Groundwater Exposure Scenario 
Travel 
Time a 
Non-Commuters Commuters 
N b mj 
c pj 
d pj mj pjmj 
2 N b mj 
e pj 
d pj mj pjmj 
2 
0 6 0 0.04 0.00 0.00 
<5 84 5 0.53 2.63 13.13 
5-9 70 14 0.44 6.13 85.75 
10-14 98 4 0.34 1.36 5.43 
15-19 35 14 0.12 1.70 23.74 
20-24 64 24 0.22 5.31 127.56 
25-29 0 34 0.00 0.00 0.00 
30-34 0 44 0.00 0.00 0.00 
35-39 14 54 0.05 2.62 141.26 
40-44 23 64 0.08 5.09 325.98 
45-59 24 84 0.08 6.98 585.97 
60-89 9 129 0.03 4.02 518.23 
>90 f 22 250 0.08 19.03 4,757.79 
Sum 160 1.00 8.75 98.88 289 1.00 46.10 6,485.94 
Average g 8.75 46.10 
s2 h 22.31 4,360.70 
Standard Error I 1.17 12.16 
Source: Bureau of the Census 2002 (DIRS 159728), Table P31. 
a 
One-way travel time to work in minutes. 
b N = number of workers =16 years old within each travel-time category the week before the 2000 census. 
c 
mj = midpoint of total daily travel time in areas contaminated by groundwater, calculated as twice the midpoint of 
dthe one-way travel time interval. 
pj = proportion of total workers in each category (160 non-commuters and 289 commuters). 
e 
mj = midpoint of total daily travel time in areas not contaminated by groundwater, calculated as twice the midpoint 
of the one-way travel time interval minus 20 minutes travel time in contaminated areas. 
f 
midpoint of one-way travel time calculated as (3/2)  (lower limit of interval), as recommended by Bureau of the 
Census (2002 [DIRS 160179], p. 8-9) 
g Calculated using equation 6.3-3. 
h Calculated using equation 6.3-5. 
I 
Calculated using equation 6.3-4, with DF = 1.4. 

Table 6-8. Commute Time (minutes/day) for the Volcanic Ash Exposure Scenario 
Travel 
Time a 
Non-Commuters Commuters 
N b mj 
c pj 
d pj mj pjmj 
2 N b mj 
e pj 
d pj mj pjmj 
2 
0 6 0 0.02 0.00 0.00 
<5 84 5 0.24 1.18 5.88 
5-9 70 14 0.20 2.75 38.43 
10-14 98 24 0.27 6.59 158.12 
15-19 35 34 0.10 3.33 113.33 
20-24 64 44 0.18 7.89 347.07 
25-29 0 54 0.00 0.00 0.00 
30-34 0 64 0.00 0.00 0.00 
35-39 14 4 0.15 0.61 2.43 
40-44 23 14 0.25 3.50 49.00 
45-59 24 34 0.26 8.87 301.57 
60-89 9 79 0.10 7.73 610.53 
>90 f 22 200 0.24 47.83 9,565.22 
Sum 357 1.00 21.73 662.83 92 1.00 68.53 10,528.75 
Average g 21.73 68.53 
s2 h 190.59 5,832.03 
Standard Error I 2.29 24.92 
Source: Bureau of the Census 2002 (DIRS 159728), Table P31. 
a 
One-way travel time to work in minutes. 
b N = number of workers =16 years old within each travel-time category the week before the 2000 census. 
c 
mj = midpoint of total daily travel time in areas contaminated by volcanic ash. 
d 
pj = proportion of total workers in each category (357 non-commuters and 92 commuters). 
e 
mj = midpoint of total daily travel time in areas not contaminated by volcanic ash, calculated as twice the midpoint of 
the one-way travel time interval minus 70 minutes travel time in contaminated areas. 
f 
midpoint of one-way travel time calculated as (3/2)  (lower limit of interval), as recommended by Bureau of the 
Census (2002 [DIRS 160179], p. 8-9) 
g Calculated using equation 6.3-3. 
h Calculated using equation 6.3-5. 
I 
Calculated using equation 6.3-4, with DF = 1.4. 
For the groundwater scenario, it is assumed that persons who commute 10 minutes or more 
one-way to work are employed outside of the area contaminated by groundwater (Section 5.1). 
The average round-trip commute time outside of contaminated areas for 289 Amargosa Valley 
residents 16 years or older that commuted 10 minutes or more the week prior to the 2000 census 
was 46 minutes, with a standard error of 12 minutes (Table 6-7). Based on an average workday 
of 8 hours (selected because 409 of 524 persons worked 35 hours or longer per week, Table 6-6), 
the average number of days worked per year is 249 (average of 1,995 hours worked per year 
[Table 6-6] divided by 8 hours per day). The total annual commute time outside of the 
contaminated area is 11,454 minutes per year (i.e., 46 minutes  249 days), or 31 minutes per 
day. The annualized standard error of this estimate is 8 minutes (i.e., [12 minutes per day 
worked]  [249 days worked per year]  [365 days per year]). For use in the model, this 
estimate is rounded to 0.5  0.1 hours per day. 
For commuters, the round-trip commute time inside the area contaminated by groundwater is 
20 minutes. This equals an annual average of 14 minutes per day, or 0.2 hours per day 

([20 minutes per day worked]  [249 days worked per year]  [365 days per year]). Because all 
commuters must travel at least that amount of time, no measure of variance is associated with 
this estimate. 
For non-commuters (i.e., those who commute less than 10 minutes one way), the average 
round-trip commute within the area contaminated by groundwater is 9 minutes, with an 
annualized standard error of about 1 minute (Table 6-7). This equals an annual average of 
6 minutes per day, or 0.1 hours per day ([9 minutes per day worked]  [249 days worked per 
year]  [365 days per year]). Because the standard error of this measure is small, no measure of 
variance is associated with this estimate. 
For the volcanic ash exposure scenario, it is assumed that all persons who commute 35 minutes 
or longer one-way work outside of the area contaminated by ash (Section 5.1). The average 
round-trip commute time outside of the contaminated area for 92 Amargosa Valley residents 
16 years or older that commuted 35 minutes or longer the week prior to the 2000 census was 
69 minutes, with a standard error of 25 minutes (Table 6-8). Based on an average workday of 
8 hours, the total annual commute time outside of the contaminated area is 17,181 minutes per 
year (i.e., 69 minutes  249 days), or 47 minutes per day. The standard error of this estimate is 
17 minutes (i.e., [25 minutes per day worked]  [249 days worked per year]  [365 days per 
year]). For use in the model, this estimate is rounded to 0.8  0.3 hours per day. 
For the volcanic ash scenario, commuters are assumed to spend 70 minutes per round trip 
traveling within the contaminated area (Section 5.1). Based on an average workday of 8 hours, 
this is 48 minutes, or 0.8 hours per day ([70 minutes per day worked]  [249 days worked per 
year] [365 days per year]). No variation is associated with this value, because it is assumed that 
commuters drive at least that long to their place of work. 
The average commute time for workers in the Amargosa Valley that commuted 35 minutes or 
less is 22 minutes, with a standard error of 2 minutes (Table 6-8). Based on an average workday 
of 8 hours, this is 15 minutes, or 0.3 hours per day ([22 minutes per day worked  [249 days 
worked per year]  [365 days per year]). Because the standard error of this estimate is small, it 
is not incorporated into calculations of activity budgets. 
Time Spent Outdoors Not WorkingIt is estimated that the average amount of time people in 
the Amargosa Valley spend outdoors in their community while not at work is 1.5 hours per day, 
with a standard error of 0.2 hours per day. This estimate is developed from a survey of the age 
distribution of the population in Amargosa Valley and from the NHAPS (Klepeis et al. 1996 
[DIRS 159299], EPA 1997 [DIRS 116135]). 
For the 1992 to 1994 NHAPS, more than 9,000 people nationwide recorded their activities and 
locations during a 24-hour period; 6,059 people surveyed were 18 through 64 years old, and 
1,349 were 65 years or older (Klepeis et al. 1996 [DIRS 159299], Table 3-9). Weighted 
percentages of time spent in various environments (Table 6-9) were calculated based on national 
population characteristics, season, day of week, and other factors (Klepeis et al. 1996 
[DIRS 159299], Table 6-1). Note that there is a mistake in the presentation of age groups in 
Chapter 6 of Klepeis et al. (1996 [DIRS 159299]). The tables incorrectly divide the population 

into the age groups 0-4, 5-7, 17-64, and 65+. The correct age groups, as used elsewhere in the 
report (e.g., Klepeis et al. 1996 [DIRS 159299], p. 4-4), are 0-4, 5-17, 18-64, and 65+. 
Table 6-9. Weighted Average Amount of Time Spent Per Day in Various Locations 
Location a 
18-64 Years Old =65 Years Old 
%b Minutes SE c n d %b Minutes SE c n d 
Residential Indoors 64.71 932 3.5 6022 80.84 1164 6.2 1348 
Residential Outdoors 2.93 42 3.6 1809 4.48 65 7.5 502 
In Vehicle 6.43 93 1.5 5286 4.17 60 3.1 907 
Travel/Near Vehicle 2.06 30 4.0 1787 0.99 14 4.6 342 
Other Outdoor 2.33 34 7.3 858 1.27 18 16.6 118 
Office/Factory 8.42 121 5.2 1749 1.18 17 16.9 132 
Mall/Other Store 2.77 40 3.6 1871 1.89 27 4.4 397 
Public Bldg. 5.19 75 5.4 1653 2.83 41 6.6 385 
Bar/Restaurant 2.43 35 3.4 1718 1.27 18 5.5 270 
Other Indoor 2.74 39 8.1 903 1.07 15 14.1 128 
Sources: Klepeis et al. (1996 [DIRS 159299], Table 6-1); EPA (1997 [DIRS 116135], Tables 15-131 through 
15-140). 
a 
b 
Locations defined in Klepeis et al. (1996 [DIRS 159299], Tables 5-2 and 5-3). 
Average percentage of time spend in an environment, weighted based on national population characteristics. 
SE (minutes) for those that spent time in the location on day surveyed, from EPA (1997 [DIRS 116135], Tables 
15-131 through 15-140); note that SE for entire population may be much smaller. 
d 
Sample size for SE calculation (i.e., number of people 18 to 64 years old and =65 years old surveyed that spent 
time in a location on the day surveyed; from EPA (1997 [DIRS 116135], Tables 15-131 through 15-140)). 
n=number; SE=standard error 
Klepeis et al. (1996 [DIRS 159299], Table 6-1) classified time spent outdoors per age group into 
three categories (residential outdoors, near a vehicle, and other outdoors). For this analysis, time 
spent in these categories was weighted by the percentage of Amargosa Valley residents in each 
age group during 2000 (721 people 18 through 64 years old, 109 people 65 years or older, 
Table 6-10). 
Table 6-10. Age (years) of Residents of the Amargosa Valley in 2000 
Number of Number of Number of 
Age People Age People Age People 
Under 1 13 17 13 45 to 49 108 
1 and 2 27 18 39 50 to 54 96 
3 and 4 17 19 0 55 to 59 67 
5 0 20 16 60 and 61 38 
6 8 21 0 62 to 64 22 
7 to 9 41 22 to 24 49 65 to 69 37 
10 and 11 72 25 to 29 8 70 to 74 36 
12 and 13 28 30 to 34 66 75 to 79 24 
14 9 35 to 39 127 80 to 84 6 
15 65 40 to 44 85 85 and over 6 
16 19 
Source: Bureau of the Census 2002 (DIRS 159728), Table P8. 

 
Residential OutdoorsThis category includes time spent at a pool, spa, yard, or other time 
outside ones own house or another house (Klepeis et al. 1996 [DIRS 159299], 
Tables 5-2 and 5-3). The weighted percentage of time spent in this environment for 
respondents 18 through 64 years old and 65 years or older was 2.93 percent and 4.48 percent, 
respectively (Table 6-9). Based on the proportion of people in the Amargosa Valley within 
each age group, the combined average time spent outdoors for all people 18 years or older is 
3.13 percent ([2.93%  721 + 4.48%  109]/830), or 0.75 hours per day. 
 
Traveling/Near Vehicle (Outdoors)This category includes time spent on a motorcycle, 
moped, or scooter; walking; on a bicycle or skateboard; in a stroller or carried by an adult; 
waiting for a bus, train, or other ride; on a sidewalk, street, or neighborhood; and at a parking 
lot, service station, or construction site (Klepeis et al. 1996 [DIRS 159299], Tables 5-2 and 
5-3). The weighted percentage of time spent in this environment for respondents 18 through 
64 years old and 65 years or older was 2.06 percent and 0.99 percent, respectively 
(Table 6-9). Based on the proportion of people in the Amargosa Valley within each age 
group, the combined average time spent outdoors for all people 18 years or older is 
1.92 percent ([2.06%  721 + 0.09%  109]/830), or 0.46 hours per day. 
 
Other OutdoorsThe other outdoor category includes time spent in a variety of places, such 
as school grounds, playgrounds, sports stadiums, parks, golf courses, pools, rivers, lakes, 
outdoor restaurants, picnic areas, and farms (Klepeis et al. 1996 [DIRS 159299], Tables 5-2 
and 5-3). The weighted percentage of time spent in these environments for respondents 
18 through 64 years old and 65 years or older was 2.33 percent and 1.27 percent, respectively 
(Table 6-9). Based on the proportion of people in the Amargosa Valley within each age 
group, the combined average time spent outdoors for all people 18 years or older is 
2.19 percent ([2.33%  721 + 1.27%  109]/830), or 0.53 hours per day. 
The total time spent in these three environments by people 18 years or older (weighted by the 
proportion of people in the Amargosa Valley 18-64 and 65 years or older) is 7.24 percent, or 
1.74 hours per day. A slightly lower value of 6.25 percent, or 1.5 hours per day, is selected for 
use in the biosphere model as the average time spent outdoors not working because some of the 
locations included in the environments are uncommon in the Amargosa Valley (e.g., bus and 
train stations, sports stadiums) and others are work sites included in other biosphere-model 
environments (e.g., construction sites and farms). 
There is uncertainty associated with the use of the data from the national survey in combination 
with information from the census survey of the people of Amargosa Valley. For example, 
people in the rural Amargosa Valley may spend more time outdoors than people in urban areas. 
In contrast, they may spend less time outdoors, especially during the summer, because of 
extreme temperatures. In addition, there are slight regional differences in the data that cannot be 
considered in this analysis because weighted, age-specific results are not presented by region 
(Klepeis et al. 1996 [DIRS 159299], Table 6-1). There also is uncertainty about whether these 
categories include all likely non-work time spent outdoors in the Amargosa Valley area. 
The only estimates of variation presented for the NHAPS data are for the subsamples of people 
who spent time in an environment, or doers (EPA 1997 [DIRS 116135], Table 15-131 through 
15-140). For example, the standard error of time spent at home in the residential outdoor 

environment, for those doers who spent time in that environment, was 3.6 minutes (n = 1,809) 
for ages 18 through 64 and 7.5 minutes (n = 502) for those 65 years or older (Table 6-9) 
(EPA 1997 [DIRS 116135], Table 15-132). The remaining approximately 5,100 people 
surveyed (total sample of 6,059 + 1,349 minus subsample sizes of 1,809 + 502, Klepeis et al. 
1996 [DIRS 159299], Table 3-9) spent no time in that environment on the day surveyed. The 
standard error for the entire sample would be at least a factor of two smaller because total sample 
sizes are about four times larger than subsample sizes (compare the square root of 1,801 to the 
square root of 6,059). Adding 5,100 more responses, all of which have the same value (zero), 
would further decrease the estimate of variation. Therefore, the standard errors calculated for 
doers are bounding or extreme estimates of variation around the mean time spent in an 
environment. The combined bounding estimate of standard error for the three environments for 
persons 18-64 years old, calculated as the square root of the sum of the squared standard error for 
each environment (Knoll 1989 [DIRS 161052], p. 88) is 9.1 minutes ([3.62 + 4.02 +7.32]), or 
0.15 hours. The combined estimates for persons 65 years or older is 18.8 minutes, or 0.31 hours. 
Weighted by the age of people in the Amargosa Valley, the estimate for all persons 18 years or 
older is 0.2 hours ([0.15  721 + 0.31  109]/830). 
The bounding estimate of standard error, 0.2 hours, based on variation among those who spent 
time in an environment, is selected for use in the biosphere model. This high value is selected to 
account for uncertainty in the use of national data on activity budgets with survey data from the 
residents of Amargosa Valley. See the discussion at the end of this section for additional 
information about the relative importance of this uncertainty in estimating activity budgets based 
upon surveys of the residents of Amargosa Valley. In summary, an average of 1.5 hours per day 
outdoors not working, with a standard error of 0.2 hours, is selected as the estimate of total time 
spent outdoors while not working. 
Time Spent Active OutdoorsIt is estimated that an average of 20 percent of time spent 
outdoors in contaminated areas is spent conducting dust-generating activities and that local 
outdoor workers spend an average of 50 percent of their work time conducting dust-generating 
activities. 
Table 6-11 shows the average amount of time that more than 5,000 people surveyed nationwide 
in 1985 (an early version of the NHAPS) spent in the physical/outdoor environment and the 
other/outdoor environment, when they spent time in those environments. The percent of total 
time outdoors spent in physical activity ranged from 10 to 33 percent per age group 
(from EPA 1997 [DIRS 116135], Table 15-10). Based on the proportion of people in the 
Amargosa Valley within each age group (Table 6-10), the combined average time spent 
conducting physical activity while outdoors is 20.1 percent. This value at least bounds, and most 
likely overestimates, the amount of time people spend conducting dust-generating activities 
outdoors because it includes time spent conducting activities that resuspend little or no excess 
soil (e.g., walking on turf or paved surfaces, golfing, and swimming) and it includes activities 
that would be conducted away from contaminated areas. A proportion of 20 percent, and a 
relatively large standard error of 0.1 hours (half of the standard error of the total time spent 
outdoors not working), is selected for the biosphere model to account for uncertainty in the 
application of this 1985 national data to conditions in the Amargosa Valley. Thus, an average 
time of 0.3  0.1 hours (20 percent of 1.5 hours spent outdoors while not at work) spent active 

outdoors and 1.2  0.2 hours spent inactive outdoors while not working is to be used for all 
population groups. 
Table 6-11. Average Minutes Spent Active and Inactive Outdoors by Age Groups in 1985 
Environment 18-24 Years 25-44 Years 45-64 Years = 65 Years 
Physical/Outdoors 17 19 7 15 
Other/Outdoors 34 48 60 82 
Total Outdoors 51 67 67 97 
% Outdoor Physical 33.3% 28.4% 10.4% 15.5% 
Number of Amargosa Valley Residents a 104 286 331 109 
Source: EPA 1997 (DIRS 116135), Table 15-10. 
a 
From Table 6-10. 
It is not reasonable to conclude that local outdoor workers would spend all of their work hours 
conducting dust-generating activities. Although some workers may spend the majority of their 
work time conducting dust-generating activities, others would spend little time doing so. For 
example, some agricultural workers may spend a substantial amount of their time irrigating, 
spraying pesticides, and conducting other activities that resuspend little soil. Because most fields 
in Amargosa Valley are planted in alfalfa and other hay (CRWMS M&O 1997 [DIRS 101090], 
Tables 3-12 and 3-13; YMP 1999 [DIRS 158212], Tables 10 and 11; Rasmuson 2004 
[DIRS 169506]), agricultural workers plow and conduct other soil disturbing activities in those 
fields infrequently. In addition, many miners and other outdoor workers would be involved in 
activities (e.g., miners conducting subsurface excavations) that do not resuspend surface soil. 
Therefore, a value of 50 percent was chosen as the percentage of time that outdoor workers 
spend conducting dust-generating activities. This is 2.8 hours of an annual average of 5.5 hours 
spent working per day. A standard error of 0.2 hours (more than half of the total standard error 
of time spent working) is selected to account for uncertainty in time spent conducting 
dust-disturbing activities. Local outdoor workers spend the remainder of their work time 
(2.7  0.2 hours) in the inactive outdoor environment. 
Time Spent SleepingThe average amount of time people in the Amargosa Valley spend 
sleeping is estimated to be 8.3 hours per day with a standard error of 0.1 hours. 
People 18 through 64 years old surveyed for NHAPS spent an average of 497 minutes 
(8.3 hours) sleeping or napping (standard error = 1.6 minutes or 0.03 hours) (EPA 1997 
[DIRS 116135], Table 15-83). People 65 years or older slept or napped an average of 
517 minutes (8.6 hours) (standard error = 3.2 minutes or 0.05 hours). These statistics were 
calculated using data from people who spent time sleeping or napping during the 24-hour period 
they were surveyed. However, because most people slept or napped at some time during the 
survey (6,041 of 6,059 people 18 through 64 years old and 1,347 of 1,349 people 65 years or 
older) (EPA 1997 [DIRS 116135], Table 15-83) the values do not need to be adjusted to account 
for those not sleeping or napping. Total sample sizes are from Klepeis et al. (1996 
[DIRS 159299], Table 3-9). 
Based on the proportion of people in the Amargosa Valley within each age group, the combined 
average time spent sleeping for all people 18 years or older is 8.3 hours 

([496.9  721 + 517.1  109]  830  60 minutes). A standard error of 0.1 hours, which is larger 
than those reported in the study, is selected to account for uncertainty in the application of this 
data to the population in the Amargosa Valley. 
Time Spent Away from the Amargosa ValleyPeople in the Amargosa Valley are estimated to 
spend an average of 2.0 hours per day, with a standard error of 0.4 hours per day, out of the 
Amargosa Valley shopping, on vacation, getting medical attention, or conducting other non-work 
activities. 
The Amargosa Valley is a small community with only a small medical clinic and a few stores, 
restaurants, entertainment opportunities, or other amenities (Rasmuson 2004 [DIRS 169506]). It 
is therefore reasonable to conclude that adults spend some time out of the Amargosa Valley 
obtaining goods and services and while on vacation. 
The combined, weighted average percentage of time people 18 through 64 and 65 years or older 
surveyed for the NHAPS spent in stores, public buildings (including schools, churches, medical 
facilities), bars and restaurants, and other indoor locations was 13.13 percent (3.2 hours) and 
7.06 percent (1.7 hours), respectively (Table 6-9). Although some facilities included in these 
categories are found in the Amargosa Valley (e.g., churches, small grocery stores, small medical 
clinic, and a few restaurants), many activities associated with these locations occur outside of the 
community. The nearest locations to find large shops and larger medical facilities are Pahrump 
and Las Vegas, which are 0.5 to more than 1 hour away; therefore, most trips will require 2 or 
more hours. 
It is likely that all residents spend some time outside the Amargosa Valley each year on vacation, 
recreating, or traveling for other reasons. A 7-day trip is about 1.9 percent of a year, or an 
average of 0.46 hours per day. 
To account for the time people spend out of the farming and residential community for 
entertainment; vacation; and to obtain medical attention, goods, and other services, it is estimated 
that residents would spend an average of 2 hours per day out of the potentially contaminated 
area, with a standard error of 0.4 hours. This relatively large standard error was selected to 
account for uncertainty in applying national data to the behavior of residents of the Amargosa 
Valley and to account for uncertainty in the size of the area contaminated by volcanic ash (and 
therefore the amount of time it would take to leave that area). 
6.3.2.2 Exposure Times Per Population Group 
The following is a summary of the exposure times per population group, based on the 
information in Sections 6.3.2.1. Lognormal distributions of exposure times are to be used, with 
minimum and maximum values equal to the upper and lower 99th percentile of the distributions. 
The arithmetic means and standard error of these distributions are described below, and the 
distributions are summarized in Table 6-12. 
Lognormal distributions are recommended because population distributions of exposure times 
generally are characterized by most people spending little time conducting an activity or in a 
location and a few people spending a large amount of time conducting that activity. For 

example, the average time spent outside the residence by 1,809 people ages 18 to 64 that spent 
time outside of a residence was 144 minutes, the median was 90 minutes, and the 75th, 90th, and 
95th percentiles were 199, 360, and 470 minutes, respectively (EPA 1997 [DIRS 116135], 
Table 15-132). About 4,000 other people surveyed spent no time outside of a residence. 
Table 6-12. Daily Exposure Times for Amargosa Valley Population Groups 
Population Group Groundwater Scenario (hours/day)a Volcanic Ash Scenario (hours/day)a 
Environment AM SE Min b Max b AM SE Min b Max b 
Non-Workers 
Away 2.0 0.4 1.2 3.3 2.0 0.4 1.2 3.3 
Active Outdoors 0.3 0.1 0.1 0.7 0.3 0.1 0.1 0.7 
Inactive Outdoors 1.2 0.2 0.8 1.8 1.2 0.2 0.8 1.8 
Asleep Indoors 8.3 0.1 8.0 8.6 8.3 0.1 8.0 8.6 
Active Indoors c 12.2 12.2 
Commuters 
Away 8.0 0.5 6.8 9.4 8.3 0.6 6.9 10.0 
Active Outdoors 0.3 0.1 0.1 0.7 0.3 0.1 0.1 0.7 
Inactive Outdoors 1.4 0.2 1.0 2.0 2.0 0.2 1.5 2.6 
Asleep Indoors 8.3 0.1 8.0 8.6 8.3 0.1 8.0 8.6 
Active Indoors c 6.0 5.1 
Local Outdoor Workers 
Away 2.0 0.4 1.2 3.3 2.0 0.4 1.2 3.3 
Active Outdoors 3.1 0.2 2.6 3.7 3.1 0.2 2.6 3.7 
Inactive Outdoors 4.0 0.3 3.3 4.8 4.2 0.3 3.5 5.0 
Asleep Indoors 8.3 0.1 8.0 8.6 8.3 0.1 8.0 8.6 
Active Indoors c 6.6 6.4 
Local Indoor Workers 
Away 2.0 0.4 1.2 3.3 2.0 0.4 1.2 3.3 
Active Outdoors 0.3 0.1 0.1 0.7 0.3 0.1 0.1 0.7 
Inactive Outdoors 1.3 0.2 0.9 1.9 1.5 0.2 1.1 2.1 
Asleep Indoors 8.3 0.1 8.0 8.6 8.3 0.1 8.0 8.6 
Active Indoors c 12.1 11.9 
a 
The statistics for the exposure scenario include arithmetic mean, SE, minimum, and maximum values defining the 
b 
lognormal distributions of exposure times. 
Calculated using equation 6.3-6. 
Calculated as 24 hours minus all other estimates for a population group; therefore, no SE or bounds are presented. 
AM = arithmetic mean; SE=standard error 
For the lognormal distribution, the lower and upper bounds of the 99 percent confidence interval 
of the mean are calculated using formulas based on LaPlante and Poor (1997 [DIRS 101079], 
p. 3-12), where the number of standard deviations for a 99 percent confidence interval is 
2.576 (Lide and Frederikse 1997 [DIRS 103178], p. A-104), such that 
GM
bound lower =
576.2 
GSD (Eq. 6.3-6) 
576.2 
bound upper = GM  GSD 

where 
GM = geometric mean 
GSD = geometric standard deviation 
The geometric mean and geometric standard deviation are calculated as 
e 
e 
..
= 
GM
=
GSD
with the variance of ln(x) for the lognormal distribution, ., given by Golder Associates (2000 
[DIRS 146973], p. B-3), as 
2
.
.
SE
X
... 
... 
2
=.
1 ln 
+... 
(Eq. 6.3-7) 
...
and the expected value of ln(x), ., is 
.
12
=
.
ln( X)
- 
(Eq. 6.3-8) 
2 
For cases in which more than one activity must be summed to obtain an average time (e.g., total 
time out of the contaminated environment includes commuting time and time spent away from 
the Amargosa Valley), the standard error of the total average time is calculated as the square root 
of the sum of squared standard error values per activity (Knoll 1989 [DIRS 161052], p. 88). 
Non-Workers-Non-workers spend an average of 2.0  0.4 hours per day out of the potentially 
contaminated area conducting non-work activities, 0.3  0.1 hours per day active outdoors, 
1.2 
 0.2 hours per day inactive outdoors conducting non-work activities, and 8.3  0.1 hours 
sleeping. The average time spent indoors by non-workers is 12.2 hours per day (24 hours minus 
2.0 
hours away, 0.3 hours active outdoors, 1.2 hours inactive outdoors, and 8.3 hours sleeping). 
Commuters-For the groundwater scenario, commuters spend an average of 8.0  0.5 hours per 
day out of the contaminated area, including time spent working (5.5  0.3 hours per day), 
commuting (0.5  0.1 hours per day), and conducting non-work activities (2.0  0.4 hour per 
day), with the standard error calculated as [0.32 + 0.12 + 0.42] = 0.51. Commuters spend an 
average of 0.3  0.1 hours per day active outdoors. They spend an average of 1.4  0.2 hours per 
day inactive in the outdoor environment, including 0.2 hours per day commuting within the area 
assumed to be contaminated by groundwater and an additional 1.2  0.2 hours inactive outdoors 
while not working. It is estimated that commuters spend 8.3  0.1 hours per day sleeping. The 
average time spent active indoors within the contaminated area is 6.0 hours per day 
(24 hours minus 8.0 hours away, 0.3 hours active outdoors, 1.4 hours inactive outdoors, and 
8.3 hours sleeping). 
For the volcanic ash scenario, commuters spend an average of 8.3  0.6 hours per day out of the 
contaminated area, including time spent working (5.5  0.3 hours per day), commuting (0.8  0.3 

hours per day), and conducting non-work activities (2.0  0.4 hour per day), with the standard 
error calculated as [0.32 + 0.32 + 0.42] = 0.58. They spend an average of 0.3  0.1 hours per day 
active outdoors. They spend an average of 2.0  0.2 hours per day inactive in the outdoor 
environment, including 0.8 hours per day commuting within the area assumed to be 
contaminated by ash, and an additional 1.2  0.2 hours inactive outdoors while not working. It is 
estimated that commuters spend 8.3  0.1 hours per day sleeping. The average time spent active 
indoors within the contaminated area is 5.1 hours per day (24 hours minus 8.3 hours away, 
0.3 hours active outdoors, 2.0 hours inactive outdoors, and 8.3 hours sleeping). 
Local Outdoor Workers-For the groundwater scenario, local outdoor workers spend an 
average of 2.0  0.4 hours per day out of the potentially contaminated area conducting non-work 
activities. They spend 3.1  0.2 hours per day active outdoors, including 2.8  0.2 hours active 
outdoors while working and 0.3  0.1 hours active outdoors conducting non-work activities. 
They spend an average of 4.0  0.3 hour per day in the inactive outdoor environment, including 
2.7 
 0.2 hours working, 0.1 hours commuting, and 1.2  0.2 hours conducting non-work 
activities. Local outdoor workers spend 8.3  0.1 hours per day sleeping. Thus, the average time 
spent active indoors by local outdoor workers is 6.6 hours per day (24 hours minus 2 hours away, 
3.1 
hours active outdoors, 4.0 hours inactive outdoors, and 8.3 hours sleeping). 
All exposure times are the same for the volcanic ash scenario except the time local outdoor 
workers commute (0.3 hours). Thus, they spend an average of 4.2  0.3 hour per day in the 
inactive outdoor environment, and an average of 6.4 hours per day active indoors. 
Local Indoor Workers-For the groundwater scenario, local indoor workers spend 2.0  0.4 
hours per day out of the contaminated area conducting non-work activities. They spend an 
average of 0.3  0.1 hours per day active outdoors. They spend 1.3  0.2 hour per day in the 
inactive outdoor environment, including 0.1 hours commuting and 1.2  0.2 hours conducting 
non-work activities. Average time spent active indoors by local indoor workers is 12.1 hours 
(24 hours minus 2.0 hours away, 0.3 hours active outdoors, 1.3 hours inactive outdoors, and 
8.3 hours sleeping). This estimate of 12.1 hours includes an average of 5.5 hours working 
indoors. 
All exposure times are the same for the volcanic ash scenario except for the time local indoor 
workers commute (0.3 hours). Thus, they spend an average of 1.5  0.2 hour per day in the 
inactive outdoor environment and an average of 11.9 hours per day active indoors. 
Information on time budgets of the people of Amargosa Valley was not collected because it 
would require very intrusive data collection and because the information that would be gathered 
would not contribute in an important way to the understanding of the lifestyle of the RMEI and 
would not result in underestimating risk. 
To meet the requirements of 10 CFR 63.312 that average values of lifestyle characteristics of the 
residents of Amargosa Valley be used in the TSPA dose assessments, the average exposure time 
per environment is calculated in the biosphere model as the average of exposure times per group 
weighted by the proportion of the population in each group (BSC 2004 [DIRS 169460], 
Section 6.4.7.1). This estimate of a lifestyle characteristic is based on a survey of the 
employment status, time worked, and commute time of the people of Amargosa Valley (Bureau 

of the Census 2002 [DIRS 159728]). This information on employment characteristics has the 
greatest influence on variation in activity budgets and exposure rates because work status and 
location determines what people will be doing and where they will be doing it during the time of 
day when most people are away from their home. During the remainder of the day most people 
will be conducting similar activities such as sleeping or remaining in or near their residences. 
Information from national surveys of activity budgets was used in combination with survey data 
from the people of Amargosa Valley to estimate time sleeping and time spent outdoors and 
away from potentially contaminated areas while not working. Surveys of the people of 
Amargosa Valley were not conducted to obtain this activity-budget information because it would 
not have contributed substantially to the measurement of uncertainty in this lifestyle 
characteristic and would have required a very intrusive investigation of Amargosa Valley 
residents. For example, the standard error of the average time spent sleeping measured in the 
NHAPS was about 3 minutes. This small amount of variation has no influence on estimates of 
time budgets. In addition, there is little variation in the average time that people spend sleeping 
and no reason to expect that people in Amargosa Valley have, on average, different sleep habits 
than people elsewhere in the United States. Times spent outdoors and away from the area are a 
relatively small part of a day (about 3.5 hours). Because most people in Amargosa Valley would 
spend at least some time in those environments, the uncertainty in the estimates used is a matter 
of minutes, not hours, and has little influence on estimates of time budgets. It is therefore 
concluded that the population proportions and activity budgets are based upon a survey of the 
residents of the town of Amargosa Valley. 
6.3.3 Breathing Rates 
Breathing rates used in the biosphere model represent the average values for each population 
group within the four potentially contaminated environments used in the ERMYN model 
(Section 6.2). The breathing rate for a population group in an environment is determined by 
considering the fraction of time people in that group are involved in various levels of activity and 
the breathing rate associated with those activity levels. Uncertainty in breathing rates is 
associated with the accuracy of estimates of activity levels for each population group and with 
the accuracy of measurements of breathing rates for these activity levels (ICRP 1994 
[DIRS 153705], p. 198). 
The expected values of breathing rates for the biosphere model were developed using values 
from ICRP Publication 66 (ICRP 1994 [DIRS 153705]). To comply with the requirement of 
10 CFR 63.312(e) that the RMEI be an adult, breathing rates representative of adults were 
selected for this analysis. The activity levels considered in this analysis correspond to activity 
levels used in ICRP Publication 66: sleep, sitting, light exercise, and heavy exercise (ICRP 1994 
[DIRS 153705], p. 192). Light exercise corresponds to working, for example, in workshops, 
active housecleaning, painting, or woodworking. Heavy exercise is considered appropriate for 
construction workers, farm workers, firemen, and athletes. ICRP Publication 66 assigns a 
standard combination of activity levels to the typical groups of people and typical environments 
(ICRP 1994 [DIRS 153705], p. 193). 
Four environments in the contaminated area are considered in the biosphere model: active 
outdoors, inactive outdoors, active indoors (i.e., not sleeping) and asleep (Section 6.3.2). People 

from all four groups (Section 6.3.1) could spent some of their time in any of these environments, 
either working, recreating, doing house work, resting, or involved in other activities. To develop 
expected values of breathing rates for the biosphere model, the amount of time spent in various 
equivalent environments was taken from the recent ICRP recommendations in the respiratory 
tract model (ICRP 1994 [DIRS 153705]), in which the nominal mix of activity levels associated 
with different environments is defined. These values were adopted for the environments used in 
the biosphere model as shown in Table 6-13. 
Table 6-13. Contributions of Activity Levels by Population Group and Environment 
Population 
Group, 
Environment Commuters 
Local Outdoor 
Workers 
Local Indoor 
Workers 
(Sedentary) Non-workers 
At work: At work: At work: At work: 
N/A 7/8 light exercise N/A N/A 
Active outdoors 
1/8 heavy exercise 
Recreation/Other: Recreation/Other: Recreation/Other: Recreation/Other: 
7/8 light exercise 7/8 light exercise 7/8 light exercise 7/8 light exercise 
1/8 heavy exercise 1/8 heavy exercise 1/8 heavy exercise 1/8 heavy exercise 
At work: At work: At work: At work: 
N/A 1/3 sitting N/A N/A 
Inactive outdoors 
2/3 light exercise 
Recreation/Other: Recreation/Other: Recreation/Other: Recreation/Other: 
1/3 sitting 1/3 sitting 1/3 sitting 1/3 sitting 
2/3 light exercise 2/3 light exercise 2/3 light exercise 2/3 light exercise 
At work: At work: At work: At work: 
Active indoors 
N/A N/A 1/3 sitting 
2/3 light exercise 
N/A 
At home: At home: At home: At home: 
1/3 sitting 1/3 sitting 1/3 sitting 1/3 sitting 
2/3 light exercise 2/3 light exercise 2/3 light exercise 2/3 light exercise 
Asleep indoors Sleeping Sleeping Sleeping Sleeping 
Source: ICRP 1994 (DIRS 153705), p. 193, Tables B.16B, and B.17. 
The breathing rates in ICRP Publication 66 (ICRP 1994 [DIRS 153705], p. 197) are calculated 
using the following mix of activity levels: 1/3 sitting + 2/3 light exercise for the time spent 
indoors not sleeping (corresponding to the active indoors environment of the biosphere model); 
1/2 sitting + 3/8 light exercise + 1/8 heavy exercise for travel and sports; and 7/8 light exercise + 
1/8 heavy exercise for outdoor workers. In the biosphere model, the time spent recreating 
outdoors is divided into two environments, active and inactive. Therefore, the activity mix that 
corresponds to the ICRP travel and sports category was not used. Rather, the breathing rate 
associated with the outdoor workers (7/8 light exercise + 1/8 heavy exercise) was used for active 
recreation outdoors and the breathing rate associated with the active indoor environment 
(1/3 sitting + 2/3 light exercise) was used for the inactive recreation outdoors. 
Activity-level dependent breathing rates for the biosphere model (Table 6-14) were calculated 
using data from ICRP Publication 66 (ICRP 1994 [DIRS 153705]) and gender weights consistent 

with the 2000 Census results; that is, 52.2 percent for males 18 years old or older and 
47.8 percent for females 18 years old or older (Bureau of the Census 2002 [DIRS 159728], 
Table P8). 
Table 6-14. Breathing Rates Per Level of Activity 
Gender 
Breathing Rate for a Given Exercise Level, m3/hr 
Sleep Sitting Light Exercise Heavy Exercise 
Adult woman 0.32 0.39 1.25 2.7 
Adult man 0.45 0.54 1.5 3.0 
Adult ICRPAmargosa Valley a 0.39 0.47 1.38 2.86 
Source: ICRP 1994 (DIRS 153705), p. 24. 
a 
Calculated by producing the weighted average of the breathing rates for males and females using the weights 
based on the fraction of males and females derived from the 2000 Census information (Bureau of the Census 2002 
[DIRS 159728], Table P8). 
When the activity level information (Table 6-13) is combined with the breathing rates for the 
Amargosa Valley population (Table 6-14), the expected values of effective breathing rates for 
the population groups and for the environments can be calculated (Table 6-15). 
The values of breathing rates shown in Table 6-15 are recommended for the use in the biosphere 
model. 
Table 6-15. Calculation of Expected Breathing Rates 
Environment Breathing Rate for All Population Groups a 
Active outdoors 7/8  1.38 m3/hr + 1/8  2.86 m3/hr = 1.57 m3/hr b 
Inactive outdoors 1/3  0.47 m3/hr + 2/3  1.38 m3/hr = 1.08 m3/hr b 
Active indoors 1/3  0.47 m3/hr + 2/3  1.38 m3/hr = 1.08 m3/hr b 
Asleep indoors 0.39 m3/hr 
NOTE: For the activity mix consisting of 1/2 (50%) time spent sitting, 3/8 (38%) in light exercise, and 1/8 (13%) in
heavy exercise, which is recommended by ICRP (ICRP 1994 [DIRS 153705], p. 197) for outdoor travel, 
sports, etc, the breathing rate would be 1.11 m3/hr, which is practically the same as that the value 
calculated for the biosphere model for the inactive outdoors and active indoors environments. 
a 
Commuters, local outdoor workers, local indoor workers, non-workers. 
b 
The results were rounded off to three significant figures. 
The remainder of this section presents an evaluation of how the breathing rates calculated using 
the ICRP-recommended mix of activity levels compare with the breathing rates that would be 
obtained if the national survey data were used instead. The fractional contributions of activity 
levels listed in Table 6-13 were compared with the aggregated results of the national survey 
(EPA 1997 [DIRS 116135], Table 15-9) listed in Table 6-16. The survey investigated the 
amount of time spent by people in various microenvironments. The time spent in various 
activities was divided among the environment-activity level categories as indicated in 
Table 6-16. The percentage of time spent in a given environment at a given activity level was 
then calculated by taking the weighted averages of the percent time spent on week days and on 
weekends with weighting factors corresponding to the number of week days and weekend days. 

Table 6-17 compares the percent of time spent in various environments at different activity levels 
calculated from the national survey data (Table 6-16) with the values adopted for the biosphere 
model calculated based on ICRP recommendations (Table 6-13). 
Table 6-16. Calculation of Aggregated Times Spent in Environments Per Activity Level 
ActivityAutoplaces 
Restaurant/barIn vehicle 
Physical/Outdoors 
Physical/Indoors 
Work/Study-Residence 
Work/Study-Other 
Cooking 
Other Activities/Kitchen 
Chores/Child 
Shop/Errand 
Other /Outdoors 
Social/CulturalLeisure-Eat/Indoors c 
Leisure-Eat/Indoors cSleep/Indoors 
Environment/Activity 
Level 
Indoor sitting 
Indoor light exercise 
Indoor heavy exercise 
Indoor total 
ActivityOutdoor sitting 
Outdoor light exercise 
Outdoor heavy exercise 
Outdoor total 
Sleep/Indoors 
Bin Codea Weekday Minutes/Day Weekend Minutes/Dayb 
Values for Individual Activities 
2 3 3 
1 20 23 
4 86 91 
6 15 23 
3 8 9 
1 16 15 
1 225 64 
2 35 34 
2 73 73 
2 124 120 
2 30 35 
5 51 67 
1 62 99 
1 105.5 128.5 
2 105.5 128.5 
481 525 
A g g r e g a t e d V a l u e s 
Total 
minutes/day 
Percent of 
Time 
Total 
minutes/day 
Percent of 
Time 
Total 
hours/dayd 
Percent of 
TimeBin 
Code Weekday Weekend Average for the Week 
1 428.5 53% 329.5 45% 6.67 51% 
2 370.5 46% 393.5 54% 6.28 48% 
3 8 1% 9 1% 0.14 1% 
807 732 13.09 
Bin Codea Weekday Minutes/Day Weekend Minutes/Dayb 
Values for Individual Activities 
4 86 57% 91 50% 1.46 55% 
5 51 34% 67 37% 0.93 35% 
6 15 10% 23 13% 0.29 11% 
152 181 2.67 
Aggregated Values 
481 100% 525 100% 8.23 100% 
Source: EPA 1997 (DIRS 116135), Table 15-9. 
NOTE: The data are for sample population ages 12 years and older. The biosphere model applies to adults 
(18 years and older). However, these data are presented here for comparison only (not used to develop 
the values of model parameters) and are considered to sufficiently represent times spent in various 
activities for adult population. 
a 
Bin code corresponds to the designation of activity level and environment used for aggregation. 
b 
Weekend minutes do not add up to 1440 minutes per day due to rounding. 
Leisure-Eat/Indoors time was split evenly between indoor sitting and indoor light exercise categories. 
d Weighted averages for a week. 

Table 6-17. Percent of Time Spent Outdoors and Indoors Per Activity Level 
Environment 
Activity Level 
Breathing 
rate a Reference Sitting 
Light 
Exercise 
Heavy 
Exercise 
Outdoors active 0% 87.5% 12.5 % 1.57 m3/hr 
Values adopted for the biosphere 
model based on ICRP 1994 
(DIRS 153705), pp. 24 and 197. 
Outdoors inactive 33% 67% 0% 1.08 m3/hr 
Values adopted for the biosphere 
model based on ICRP 1994 
(DIRS 153705), pp. 24 and 197. 
Outdoor active and 
inactive 55 % b 35 % 11 % 1.06 m3/hr 
Aggregated results based on Robin 
and Thomas 1991, as cited in EPA 
1997 (DIRS 116135), Table 15-9. 
Indoors active 
33 % 67 % 0% 1.08 m3/hr 
Values adopted for the biosphere 
model based on ICRP 1994 
(DIRS 153705), pp. 24 and 197. 
51 % 48 % 1 % 0.93 m3/hr Aggregated results based on EPA 
1997 (DIRS 116135), Table 15-9. 
Asleep Indoors N/A N/A N/A 0.39 m3/hr 
Values adopted for the biosphere 
model based on ICRP 1994 
(DIRS 153705), p. 24. 
a Calculated using the breathing rates for adults of both genders from Table 6-14. 
b 
Percentages do not total to 100 percent because of the rounding. 
Compared with the results of the national survey, the values adopted for the biosphere model for 
the outdoor and indoor environments are based on less time spent sitting and more time spent at 
light or higher levels of activity. However, the difference in breathing rates per environment is 
slight (Table 6-17). For the outdoor environment, the national survey results were combined into 
one environment, while the biosphere model uses two outdoor environments. The results 
(Table 6-17) indicate that the values of breathing rates selected for the biosphere model are 
slightly more conservative than what would be suggested by the results of the national survey. 
However, there is some degree of ambiguity in determining the breathing rates corresponding to 
the aggregated results of the national survey because the aggregation of activities listed in 
Table 6-16 involved categorizing the listed activities into the indoor and outdoor categories and 
activity levels. Therefore, it is concluded that the values of the environment-specific breathing 
rates selected for the biosphere model appropriately describe the expected combination of 
exercise levels. 
6.3.4 Evaporative Cooler Use 
There are two parameters in the biosphere model that quantify the use of evaporative coolers. 
These are the fraction of houses with evaporative coolers and the annual evaporative cooler use 
factor. For houses that are equipped with evaporative coolers, the evaporative cooler use factor 
is the fraction of a year that an evaporative cooler is used. The fraction of houses with 
evaporative coolers is representative of the living style of the residents of Amargosa Valley and 
therefore was developed based on a survey of those residents. The evaporative cooler use factor 
was developed based on a survey of the residents of Amargosa Valley and the present-day and 
predicted future climatic conditions in the Yucca Mountain region. 

6.3.4.1 Fraction of Houses with Evaporative Coolers 
One of the questions asked during the regional survey of Amargosa Valley residents (DOE 1997 
[DIRS 100332], p. B-12) was: Do you use a swamp cooler to cool your home during any part 
of the year? Of 187 full time adult residents of the Amargosa Valley who participated in the 
survey, 138 (73.8 percent) responded yes, and 49 responded no. Therefore, the estimated 
proportion of households that used evaporative coolers is 0.738. This proportion was calculated 
using the information from the data set DTN: MO0010SPANYE00.001 [DIRS 154976]. These 
calculations were performed using Excel (Appendix C, Consumption rates with 
uncertainties.xls). 
Because the applicable responses to this question were yes and no, the binomial distribution was 
selected to represent uncertainty in the sampling results. The binomial distribution is generally 
applied when the result is one of a small number of possible final states (Bevington and 
Robinson 1992 [DIRS 147076], p. 17), which fits the case of using an evaporative cooler. The 
biosphere model requires two inputs for a binomial distribution, the probability and a batch size. 
The probability is 0.738, based on 73.8 percent of people surveyed in Amargosa Valley having 
evaporative coolers) and the batch (sample) size is 187. The resulting distribution is presented in 
units of households, with a mean of 138 (187  0.738). Because the biosphere model uses the 
fraction of houses that used evaporative coolers rather than the number of houses, the sampled 
value must be divided by the batch size of 187. 
6.3.4.2 Evaporative Cooler Use Factor 
The evaporative cooler use factor was determined from a combination of local survey data and 
information on present-day and predicted future climatic conditions in the Yucca Mountain 
region. As part of the regional survey of Amargosa Valley residents, people who responded that 
they used a swamp cooler were asked how many months each year do you normally run your 
swamp cooler (DOE 1997 [DIRS 100332], p. B-12; DTN: MO0010SPANYE00.001 [DIRS 
154976]). Responses ranged from 1 to 12 months a year (Figure 6-2), with an average of 5.9 
months (49% of the year) and a standard error of 0.14 months (the figure and summary statistics 
are from the Excel spreadsheet Consumption rates with uncertainties.xls in Appendix C). Figure 
6-2 is based on 187 full time adult residents of the Amargosa Valley who participated in the 
survey. The standard error was calculated as the ratio of standard deviation and the square root of 
the number of surveyed households equipped with an evaporative cooler. 
An additional analysis was conducted using maximum daily temperatures because the survey 
data cannot be used to predict evaporative cooler use for the future climate. In addition, the 
survey results are not very precise because people were asked how many months, rather than 
days, a cooler was run, and the survey did not clarify whether respondents ran their cooler 
without water for part of the year. The fact that some respondents reported running their coolers 
for 10 to 12 months indicates that some respondents may have included the time that cooler fans 
were run with the water pump turned off to provide home ventilation. 
The evaporative cooler use factor was calculated as the proportion of days per year that the daily 
maximum outside temperature exceeded a threshold level above which people were likely to 
cool their homes. Three threshold levels were used to account for uncertainty in the range of 

temperatures over which people are likely to operate an evaporative cooler: 80oF (26.7oC), 85oF 
(29.4oC), and 90oF (32.2oC). The lower limit of the range corresponds to the upper limit of the 
comfort zone for a relative humidity of about 20 percent (Watt and Brown 1997 [DIRS 159497], 
p. 33). The relative humidity of 20 percent corresponds well to the mean values measured at 
Site 9 on the Nevada Test Site during the summer months (CRWMS M&O 1999 [DIRS 
102877], p. A-10). Therefore, when the outdoor temperature reaches 80oF (26.7oC) it is possible, 
but not likely that people would turn on their coolers. Also, they probably would not run them 
for the whole day because during most of the day the temperature would be lower than 80oF 
(26.7oC). The upper limit of the range is 10oF higher, which is approximately the width (range) 
of the temperature comfort zone (Watt and Brown 1997 [DIRS 159497], p. 33). It is assumed in 
the biosphere model (BSC 2004 [DIRS 169460], Section 5) that the indoor concentration of 
airborne contaminants resulting from operation of a cooler persists throughout the day, even for 
those days when the cooler is operated for only a portion of the day. 
For the present-day climate, the evaporative cooler use factor was calculated using temperatures 
measured at Yucca Mountain Meteorological Monitoring Site 9 (Section 4.1.6). Data from the 
four years preceding and including the survey year (1994 through 1997) were used to calculate 
the number of days per year that the daily maximum temperature exceeded threshold values 
(Table 6-18), as documented in BSC (2004 [DIRS 167055], Section 6.2). Based on these results, 
it is recommended that the evaporative cooler use factor for the present-day climate be 
represented by the uniform distribution in the range from 0.32 to 0.46. 
Data from a weather station at Spokane, Washington, were used to calculate the evaporative 
cooler use factor for the future climate. This site is representative of the upper bound (i.e., cooler 
and wetter) of the glacial-transition climate state predicted to occur at Yucca Mountain in the 
future (BSC 2004 [DIRS 170002], Table 6-1). The data were obtained from the National 
Climatic Data Center (NCDC [n.d.] [DIRS 161091]). Data from six years (1990-1995) were 
used to calculate the number of days per year that the daily maximum temperature exceeded 
threshold values (Table 6-19). The Excel data are listed in Appendix C, Spokane Hourly 
Temperatures and Daily Max Temperatures.xls. Based on this information, it is recommended 
that the evaporative cooler use factor for the glacial transition climate be represented by the 
uniform distribution in the range from 0.03 to 0.14. 
Table 6-18. Evaporative Cooler Use Factor for the Present-Day Climate 
> 80F (>26.7C) > 85F (>29.4C) > 90F (>32.2C) 
Year N days a Use Factor b N days a Use Factor b N days a Use Factor b 
1994 161 0.44 142 0.39 124 0.34 
1995 154 0.42 131 0.36 103 0.28 
1996 172 0.47 149 0.41 126 0.34 
1997 179 0.49 150 0.41 117 0.32 
Average 167 0.46  0.03 143 0.39  0.02 118 0.32  0.03 
Source: DTN: MO04019SUM9397.000 (DIRS 167054). 
a 
b 
Number of days per year that daily maximum temperature exceeded threshold temperature. 
Percentage of days per year that daily maximum temperatures exceeded threshold temperature. 
ANL-MGR-MD-000005 REV 03 6-37 September 2004 

Table 6-19. Evaporative Cooler Use Factor for the Upper Bound Glacial Transition Climate 
Year 
1990 
1991 
1992 
1993 
1994 
1995 
Average 
> 80F (>26.7C) 
N days a Use Factor b59 0.16 
48 0.13 
56 0.15 
32 0.09 
67 0.18 
47 0.13 
52 0.14  0.03 
> 85F (>29.4C) 
N days a Use Factor b40 0.11 
25 0.07 
40 0.11 
12 0.03 
41 0.11 
18 0.05 
29 0.08  0.04 
> 90F (>32.2C) 
N days a Use Factor b 
15 0.04 
12 0.03 
19 0.05 
1 0.00 
20 0.05 
3 0.01 
12 0.03  0.02 
Source: NCDC [n.d.] (DIRS 161091). 
a 
b 
Number of days per year that daily maximum temperatures exceeded threshold temperature. 
Percentage of days per year that daily maximum temperatures exceeded threshold temperature. 
The distribution developed from the analysis of current temperatures (0.32 to 0.46) is 
corroborated by the results of the regional survey (DTN: MO0010SPANYE00.001 
[DIRS 154976]; DOE 1997 [DIRS 100332]), and information from Phoenix, Arizona. Residents 
of Amargosa Valley used evaporative coolers from 1 to 12 months a year (Figure 6-2), with an 
average of 5.9 months (49% of the year). 
0 
5 
10 
15 
20 
25 
30 
35 
40 
45 
Number of users 
1234 5678 9101112 
Annual usage, months 
Source: DTN: MO0010SPANYE00.001 (DIRS 154976). 
Figure 6-2. Evaporative Cooler Use in the Amargosa Valley 
The average response to the survey question is about 10 percent higher than the average of the 
distribution based on daily maximum temperatures, and 3 percent higher than the maximum of 
that distribution (Table 6-18). It is expected that responses to the survey would result in a higher 
estimate of cooler use because the survey asked how many months per year an evaporative 
cooler was used. Coolers would be run for only a portion of the cooler months of early spring 
and late fall; therefore, an estimate based on days per year of operation should be lower than one 
based on months per year. Also, some survey respondents may have counted months during 
which they operated a cooler to ventilate their homes without running the water pump. 

Evaporative coolers were used for an average of 2,077 hours per year at about 40 houses in 
Phoenix, Arizona (Karpisak et al. 1998 [DIRS 160563], Table 1), which has comparable summer 
temperatures to southern Nevada. This is about 24 percent of the year (2077 hours / [365.25 
days x 24 hours]). This is lower than the distribution of 0.32 to 0.46 because the evaporative 
cooler use factor is based on the proportion of days (versus hours) that coolers would be run. 
6.4 DIETARY CHARACTERISTICS OF THE RECEPTOR 
This section describes the development of the parameters related to the dietary characteristics of 
the RMEI. Distributions of consumption rates for locally produced foods were developed based 
on the food consumption survey (DTN: MO0010SPANYE00.001 [DIRS 154976]) and 
information on daily food intake in the western United States (USDA 2000 [DIRS 154158]). 
Water consumption is defined at 10 CFR 63.312(d) [DIRS 156605], where it is stated that the 
RMEI drinks 2 liters of water per day (2 L/d  365.25 d/yr = 730.5 L/yr). 
Another dietary attribute of the RMEI is the inadvertent soil ingestion rate. A rate of soil 
ingestion consistent with the region and lifestyle of the Amargosa Valley population was 
developed based on a literature review. 
6.4.1 Food Consumption Survey 
10 C.F.R. 63.312(b) establishes the requirements for determining the diet of the RMEI. The 
NRC directed DOE to use projections based upon surveys of the people residing in the Town of 
Amargosa Valley, Nevada, to determine their current diets and living style and to use the mean 
values of these factors in the assessments conducted to determine compliance with dose limits. 
These directions were followed as described below to assess the mean value of the current diets 
of Amargosa Valleys population. 
Estimates of the amount of locally produced foods consumed by the RMEI are based upon a 
1997 survey of the residents of Amargosa Valley (DOE 1997 [DIRS 100332]) (see 
Section 4.1.5). As part of that survey, people were asked how often they consumed foods locally 
produced in Amargosa Valley. A substantial portion of the people surveyed stated that they 
consumed little or no locally produced foods (Figures 6-4 to 6-12, see below for a description of 
how those figures were developed), and the range in frequency of consumption among 
respondents was large. For example, residents surveyed consumed locally produced foods from 
zero to over 300 days per year (Appendix C, file Consumption rates with uncertainties.xls). 
These results are to be expected for a population living in an area where there are few 
commercially produced foodstuffs and most locally produced foodstuffs come from seasonal 
gardens and personally owned livestock, because those foodstuffs would only be available to part 
of the population for part of the year. 
To convert the consumption frequencies obtained from the survey into estimates of the amount 
of locally produced food consumed, as required in the ERMYN model to calculate ingestion 
exposure (BSC 2004 [DIRS 169460], Section 6.4.9), consumption frequencies were combined 
with estimates of daily intake of food by people in the western United States (see Section 6.4.2). 
Those estimates were obtained from the 1994-96 Continuing Survey of Food Intakes by 

Individuals conducted by the USDA (USDA 2000 [DIRS 154158]). As part of that survey, the 
daily food intake of about 16,000 people in the U.S. was measured, of which about 3,600 were 
from the western U.S. (USDA 2000 [DIRS 154158], Table 105). The estimates are appropriate 
for calculating the average daily consumption rates of the population of Amargosa Valley 
because they are based on a large sample of people and there is no reason to expect that the 
average amount of a food type consumed by those residents (on days when that food type is 
eaten) differs from the average of people in the western U.S. 
Changes since 1997 in the agricultural industry in Amargosa Valley, the proportion of homes 
with gardens, and food preferences could affect estimates of the current diet the residents of 
Amargosa Valley. The sensitivity of the biosphere model to changes in availability of gardens 
and changes in food preferences are addressed in other biosphere reports (BSC 2004 
[DIRS 170016]; changes in commercial agriculture are summarized here. During 1996 through 
1999, from 1,798 to 2,072 acres were planted in Amargosa Valley during spring surveys, 91 to 
93 percent of which was planted in alfalfa and other hay (CRWMS M&O 1997 [DIRS 101090], 
Tables 3-12 and 3-13; YMP 1999 [DIRS 158212], Tables 10 and 11). In the spring of 2004, 
2,392 acres of commercial fields identified in 1998 were revisited and most of the valley was 
surveyed for new agricultural fields. The 2,392 acres was about 85% of the total agricultural 
acreage in Amargosa Valley (including fallow fields) surveyed in 1998. About 1,978 acres 
surveyed in 2004 were planted in alfalfa and other hay (including 136 acres of previously 
uncultivated land), 45.3 acres had fruit or nut trees, 2.5 were to be planted, and 502.4 were 
fallow. In addition, 1,040 acres of previously non-cultivated land had been planted in pine tree 
seedlings (Rasmuson 2004 [DIRS 169506]). Thus, it is concluded that most agricultural fields in 
Amargosa Valley still are planted in crops that are not directly consumed by people. Other 
changes known to have occurred in the valley are that the commercial operation of the fish farm 
ceased after 1998 (Roe 2002 [DIRS 160674], p. 2) and a pistachio processing and packaging 
facility was opened some time after 2000 (based on personal observations of the authors of this 
analysis), which has increased the availability of locally produced nuts. Closure of the fish farm 
would not result in a substantial overestimate in the consumption rate of locally produced foods 
because few people surveyed consumed locally produced fish (Figure 12). Milk production at 
the Rockview Farms dairies in Amargosa Valley declined by about 2 percent and the average 
number of lactating cows per day decreased by around 9 percent (Rasmuson 2004 
[DIRS 169506]). It is concluded that there have been no changes in the agricultural industry that 
would have resulted in substantial changes in the amount of locally produced food available to 
residents of Amargosa Valley. 
Estimates of the amount of groundwater and locally produced foods consumed by residents of 
Amargosa Valley that were surveyed in 1997 are displayed in Figures 6-3 through 6-12. The 
food groups and methods used to calculate consumption rates are described in Section 6.4.2. The 
histograms were produced using the information in DTN MO0010SPANYE00.001 
[DIRS 154976]. The estimates of groundwater consumption (Figure 6-3) are included for 
completeness and are not used to develop output for use in the biosphere model. Development of 
these histograms is documented in the Excel worksheet (Consumption rates with 
uncertainties.xls) included in Appendix C. The first bar in the figures depicts the number of 
respondents who did not consume a food type, the second bar corresponds to a consumption rate 
from greater than zero to the value under the second bar, the third bar corresponds to 
consumption rates from the value under the second bar to that under the third bar, and so on. 

0 
10 
20 
30 
40 
50 
60 
Number of people 
0 1 00 30 0 60 0 9 50 1 260 156 0 
A n nua l c on s um pt ion r a te , L 
Source: DTN: MO0010SPANYE00.001 (DIRS 154976). 
Figure 6-3. Annual Consumption Rates of Groundwater 
0 
10 
20 
30 
40 
50 
60 
70 
80 
Number of people 
0 2.5 5 7.5 10 12.5 15 17.5 20 22.5 25 27.5 30 More 
Annual consumption rate, kg 
Source: DTN: MO0010SPANYE00.001 (DIRS 154976). 
Figure 6-4. Annual Consumption Rates of Locally Produced Leafy Vegetables 
0 
10 
20 
30 
40 
50 
60 
70 
80 
eNumber of peopl
0 2.5 5 7.5 10 12.5 15 17.5 20 22.5 25 27.5 30 More 
Annual consumption rate, kg 
Source: DTN: MO0010SPANYE00.001 (DIRS 154976). 
Figure 6-5. Annual Consumption Rates of Locally Produced Other Vegetables 
ANL-MGR-MD-000005 REV 03 6-41 September 2004 

0 
10 
20 
30 
40 
50 
60 
Number of people 
0 510152025303540455055606570More 
Annual consumption rate, kg 
Source: DTN: MO0010SPANYE00.001 (DIRS 154976). 
Locally produced fruit includes tomatoes. 
Figure 6-6. Annual Consumption Rates of Locally Produced Fruit 
0 
20 
40 
60 
80 
e 
100 
120 
140 
160 
180 
200 
Number of peopl
0 2.5 5 7.5 10 12.5 15 17.5 More 
Annual consumption rate, kg 
Source: DTN: MO0010SPANYE00.001 (DIRS 154976). 
Figure 6-7. Annual Consumption Rates of Locally Produced Grain 

0 
20 
40 
60 
80 
e 
100 
120 
140 
Number of peopl
0 2.5 5 7.5 10 12.5 15 17.5 20 22.5 25 27.5 30 More 
Annual consumption rate, kg 
Source: DTN: MO0010SPANYE00.001 (DIRS 154976). 
Figure 6-8. Annual Consumption Rates of Locally Produced Meat
0 
20 
40 
60 
80 
100 
120 
140 
160 
180 
Number of people 
0 1 2 3 4 5 6 7 8 91 0M o re 
A nnu a l c ons um p tion ra te , k g 
Source: DTN: MO0010SPANYE00.001 (DIRS 154976). 
Figure 6-9. Annual Consumption Rates of Locally Produced Poultry 
0 
20 
40 
60 
80Number of people10 0 
12 0 
14 0 
16 0 
18 0 
0 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 1 0 0M o re 
A nnua l c ons um ption ra te , k g 
Source: DTN: MO0010SPANYE00.001 (DIRS 154976). 
Figure 6-10. Annual Consumption Rates of Locally Produced Milk 
ANL-MGR-MD-000005 REV 03 6-43 September 2004 

0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
eNumber of peopl
0 5 10 15 20 25 30 35 40More 
Annual consumption rate, kg 
Source: DTN: MO0010SPANYE00.001 (DIRS 154976). 
Figure 6-11. Annual Consumption Rates of Locally Produced Eggs
0 
20 
40 
60 
80 
100 
120 
140 
160 
180 
eNumber of peopl
0 1 2 3 4 5 6 7 8 910More 
Annual consumption rate, kg 
Source: DTN: MO0010SPANYE00.001 (DIRS 154976). 
Figure 6-12. Annual Consumption Rates of Locally Produced Fish 
6.4.2 Calculation of Annual Consumption Rates of Locally Produced Food for the RMEI 
To include the consideration of uncertainty in the results of the food consumption survey, the 
annual consumption rates of locally produced food were recalculated from the frequency 
information and average daily food intake information. The frequency of consumption of locally 
produced food for the Amargosa Valley population was obtained from the 1997 survey of 
Amargosa Valley residents (DTN: MO0010SPANYE00.001 [DIRS 154976]). The average daily 
intake was obtained from the USDA 1994-96 Continuing Survey of Food Intakes by Individuals 
(USDA 2000 [DIRS 154158]). Table 6-20 contains the values of the average daily intakes, 
fraction of people consuming, and the respective standard error for the food groups included in 
the 1997 survey (BSC 2001 [DIRS 156016], p. 10). 
The frequency of consumption can be calculated using the individual responses to the regional 
food consumption survey questions. The following description of the survey questions related to 
the food consumption is paraphrased from DOE (1997 [DIRS 100332], p. 30-31). For every 
food group, a series of four questions was asked. The first question asked if the respondent ate 

any locally produced food in a food group during the past year. Those who answered yes 
proceeded to the second, third and fourth questions. Those who answered no skipped to the 
next series of questions. 
For a respondent who answered yes to the first question, the second question was how many 
months during the last year had some locally produced food in a food group been eaten. The 
response categories were 1-3 months, 4-6 months, 7-9 months, and 10-12 months. For 
calculating the food consumption rates, these responses were assigned the following values: 2, 5, 
8, and 11 months, respectively (BSC 2001 [DIRS 156016], p. 16). The third question was how 
many days per week had locally produced food been eaten (for those months when that 
locally-produced food had been eaten): less than 1 day per week, 1-2 days per week, 3-4, 5-6, or 
7 days per week. The corresponding values used in calculations were 0.5, 1.5, 3.5, 5.5, and 
7 days per week, respectively (BSC 2001 [DIRS 156016], p. 16). The fourth question was how 
much of the total amount of food consumed was locally produced (for the months when 
locally-produced food had been eaten): all, most, some, or very little. These responses were 
assigned the following values: 100 percent, 75 percent, 50 percent, and 25 percent, respectively 
(BSC 2001 [DIRS 156016], p. 17). 
Based on the responses to the survey questions and the value of the contingent average daily 
intake (CADI), annual food consumption rates were calculated as follows: 
25.365 d 1 wkUi, j = MPYi, j 12 mo 
DPWi, j 7 d 
Qi, j CADIi = EDPYi, j CADIi 
and 
25. 365 d 1 wkEDPYi, j =MPYi, j 12 mo 
DPWi, j 7 d 
Qi, j (Eq. 6.4-1) 
where 
Ui,j = annual consumption of locally produced food from food group i by 
individual j (kg/yr) 
MPYi,j = number of months per year that individual j consumed locally produced 
food from group i (mo/yr) 
DPWi,j = number of days per week that individual j consumed locally produced food 
from group i (d/wk) 
Qi,j = locally produced fraction of total consumption during the months in which 
respondent j consumed locally produced food from group i (dimensionless) 
CADIi = contingent average daily intake of food from group i (kg/d) 
EDPYi,j = effective number of days per year that individual j consumed locally 
produced food from group i (d/yr) 
The CADI is the quantity that can be calculated from the average daily intake by dividing it by 
the fraction of people consuming food from a given food group on a day of the survey. The 

CADI is the average amount of food from each group that is consumed by individuals on the 
days that they consumed some food from that group, so it applies to the doers. 
Consumption rates presented in this report are based on a 365.25-day year to match the number 
of days per year used in the biosphere model. This approach is valid because the responses to 
survey questions concerning consumption of locally produced food do not depend on the number 
of days per year (see paragraphs above). 
The last parameter in Equation 6.4-1, EDPYi,j, combines the results of the survey on 
consumption frequency of locally produced food for a given individual and a given food group. 
It is numerically equal to the number of days in a year at 100 percent consumption of locally 
produced food from a given food group by a given individual. 
The average consumption rate of locally produced food is calculated as 
U 
EDPY CADI PM
+
EDPY f i CADIf i PF (Eq. 6.4-2) 
,, 
=
,
m i 
i 
m i 
, 
where 
Ui = annual average consumption of locally produced food from food group i 
for Amargosa Valley adults (kg/yr) 
EDPY m i , = mean effective number of days per year that males from the Amargosa 
Valley population consumed locally produced food from group i (d/yr) 
CADIi,m = contingent average daily intake of food from food group i for males 
(kg/d) 
PM = percent adult males in the Amargosa Valley population 
EDPY f i , = mean effective number of days per year that females from the Amargosa 
Valley population consumed locally produced food from group i (d/yr) 
CADIi,f = contingent average daily intake of food from food group i for females 
(kg/d) 
PF = percent adult females in the Amargosa Valley population 
The standard error in the value of Ui can be evaluated using the general formula for propagating 
errors (based on Bevington and Robinson 1992 [DIRS 147076], Section 3.2, Equation 3.14, and 
examples in Section 3.3) as 
(
2 
SEM 
...
...
....
.
U 
,
m i 
+
)
2
.
U
(
. 
SEM 
CADI 
,
m i 
+
)
2
2 
. 
... 
i 
i
SEM
=
U
i 
EDPY 
CADI
.
EDPY
.
.
,
m i 
,
m i 
2
(
2 
SEM 
. 
..
+
)
2
.
(
...
SEM
.
...
.
U 
U
.
)
2 
CADI
. 
... 
i 
i 
(Eq. 6.4-3) 
+
FDPY 
CADI 
,
f i 
EDPY 
,
f i 
.
.
.
,
f i 
,
f i 

where 
SEM = Standard error of the mean effective number of days per year that 
EDPY m i 
, 
males from the Amargosa Valley population consumed locally 
produced food from group i (d/yr) 
= Standard error of the mean CADI of food from food group i for males 
SEM 
CADIm i 
, 
(kg/d) 
SEM = Standard error of the mean effective number of days per year that 
EDPY f i 
, 
females from the Amargosa Valley population consumed locally 
produced food from group i (d/yr) 
= Standard error of the mean CADI of food from food group i for
SEM 
CADI f i 
, 
females (kg/d) 
Using the expression for Ui (Equation 6.4-2), the standard error of the mean consumption rate of 
food from group i is calculated as 
2 2 222
SEMUi 
2 =((CADI m i )(SEM , ) +(EDPY m i )(SEM , ) )(PM )+ 
, EDPY m i 
, CADIm i 
(Eq. 6.4-4) 
2 2 222
((CADI f i )(SEM ) +(EDPY f i )(SEM , ) )(PF )
, CADIf i 
EDPY i , f 
, 
As noted above, the value of CADI is defined as the average amount of food from a given food 
group that is consumed during a one-day period by all individuals who consumed that food. In 
other words, the people who did not consume that food are not included in calculation of the 
CADI. The CADI (BSC 2001 [DIRS 156016], p. 7) is computed as 
CADIi =ADIi (Eq. 6.4-5) 
FPCi 
where 
CADIi = contingent average daily intake of food group i (kg/d) 
ADIi = average daily intake of food group i (kg/d) 
FPCi = fraction of people consuming food from food group i per day 
(dimensionless) 
The standard error of the CADI values can be calculated using the formula for error propagation 
(based on Bevington and Robinson 1992 [DIRS 147076], Equation 3.14 in Section 3.2 and 
examples in Section 3.3) as 

2 
2
...
SEM
(
...
...
SEM
(
...
CADI 
CADI
.
.
2 
ADI
)
2 
FPC
)
2 
i 
i
SEM
+
= 
=
CADI
i 
ADI 
FPCi
.
.
i 
i
.
.
.
.
i 
2 
2
...
. 
SEM
(
...
...
ADI
1 
2 
ADI
)
SEM
2
(
i 
2
=
)
... 
=
i
-
+
FPC
FPC 
(FPC )
i 
i
.
.
.
i 
2 
2
SEM
.
...
...
...
SEM ADI 
iADI 
FPCi
... 
=
i
+
2
FPCi 
(FPC )
i
.
.
.
2 
2 
2 
)(.. 
.
. 
.. 
.
. 
+.. 
.
. 
.. 
.
. 
i 
iFPCi 
i 
ADI 
FPCFPC 
SEM i SEM ADI 
SEM 
(Eq. 6.4-6) 
=
CADIi
where 
= Standard error of the mean CADI for food type i
SEM 
CADIi 
SEM ADIi 
= Standard error of the mean average daily intake, ADI, for food type i 
= Standard error of the mean fraction of people consuming, FPC, for
SEM 
FPCi
food type i
The standard errors of the CADIs calculated using Equation 6.4-6 are shown in Table 6-20. 
The effective number of days per year that individual members of the Amargosa Valley 
population consumed locally produced food from group i (d/yr) were calculated from the survey 
data using equation 6.4-1. The mean values, separately for the males and females, as well as the 
standard deviations, count, and standard errors of the means were calculated in an Excel 
spreadsheet (Appendix A). The Excel file, Consumption rates with uncertainties.xls, is included 
in Appendix C. The summary of the statistics is provided in Table 6-21. 
The mean consumption rates of locally produced food for both genders for the survey food 
groups were then calculated using Equation 6.4-2 and the standard error of the means were 
calculated using Equation 6.4-4. These calculations are summarized in Appendix A and the 
results are summarized in Table 6-21. 
The values of percent population (PM and PF in Equations 6.4-2 and 6.4-4) were based on the 
2000 Census data (Bureau of the Census 2002 [DIRS 159728], Table P8) rather than the food 
consumption survey data to correctly represent the proportions of genders for the current 
population (women were over-represented in the regional survey (DOE 1997 [DIRS 100332], 
Section 3.5 and Table 3.5.2)). The 2000 Census data indicated that there were fewer women 
then men among the population of the Amargosa Valley. 

The food types used in the biosphere model are not exactly the same as the food groups used in 
the regional survey. For the biosphere model some of the regional survey food groups were 
combined as shown below. 
Regional Survey Food Group Biosphere Model Food Type 
Leafy vegetables} Leafy vegetables 
Other vegetables .
. 
Other vegetables 
Fruit Fruit 
Tomatoes 
Grain . Grain 
Beef 
Pork 
Wild Game } . Meat 
Poultry . Poultry 
Milk . Milk 
Eggs . Eggs 
Fish . Fish 
The mean consumption rates for meat and fruit, which are composed of more than one food 
group used in the regional survey, were calculated by adding the mean consumption rates for the 
regional survey food groups. The calculation of the standard errors of the means was performed 
by taking the square root of the sum of squares of standard errors of the consumption rates for 
the regional survey (Appendix A). The results are also shown in Table 6-21. 
The analysis provided above uses data generated from local and national surveys and develops 
the expected (i.e., mean) value of annual consumption of each food type for the Amargosa 
Valley population. Being based upon sampling processes, the results are subject to statistical 
errors that have been quantified in terms of the standard error of the value developed (i.e., the 
expected standard deviation of the estimated mean). 
The biosphere model can accept stochastic input to propagate the effects of parametric variability 
and uncertainty (BSC 2004 [DIRS 169460], Section 6), and the question arises as to what 
approach to use to estimate the variability of each parameter around the calculated mean value. 
One approach would be to use the Student-t test for confidence testing (Bulmer 1979 
[DIRS 111961], p. 148) and establish a predetermined confidence limit (such as the 95 percent) 
into which the true mean should fall. It could then be stated that, to the predetermined 
confidence level, the true mean lies over this range with uniform probability. However, for 
several parameters where the standard error has a value similar to the calculated mean, this 
approach would lead to a sampled value corresponding to negative food consumption rates. If 
this condition were to be remedied by simple truncation at zero consumption, there would be a 
systematic bias in the mean value of the sampled parameter. 

Characteristics of the Receptor for the Biosphere Model 
ANL-MGR-MD-000005 REV 03 6-50 September 2004 
Table 6-20. Annual Daily Intake and Fraction of People Consuming for Respondents in the Western Region and the Calculated Contingent Annual 
Daily Consumption by Food Type 
1997 Food 
Consumption 
Survey Food 
Group 
94-96 USDA 
Food Group a Gender 
Average Daily Intake 
(g) b 
Fraction of People Consuming 
(dimensionless) b 
Contingent Average Daily Intake 
(g) c 
AM SE AM SE AM SE 
Leafy 
Vegetables 
Dark-green 
vegetables 
M 13 3 0.103 0.015 126.2 34.4 
F 16 3 0.133 0.014 120.3 25.9 
Other M 66 6 0.417 0.021 158.3 16.4 
vegetables White potatoes 
F 43 3 0.350 0.016 122.9 10.2 
Fruit Total fruits 
M 194 12 0.535 0.022 362.6 26.9 
F 181 15 0.603 0.025 300.2 27.8 
Tomatoes Tomatoes 
M 43 2 0.447 0.010 96.2 5.0 
F 27 2 0.398 0.022 67.8 6.3 
Grain Total grain 
products 
M 382 18 0.973 0.007 392.6 18.7 
F 266 12 0.968 0.005 274.8 12.5 
Beef Beef 
M 37 3 0.258 0.024 143.4 17.7 
F 17 2 0.194 0.014 87.6 12.1 
Pork Pork 
M 12 2 0.169 0.012 71.0 12.9 
F 6 1 0.132 0.014 45.5 9.0 
Wild Game Lamb, Veal, 
Game 
M 2 1 0.012 0.007 166.7 128.0 
F 1 1 0.010 0.004 100.0 107.7 
Poultry Total poultry 
M 29 3 0.215 0.012 134.9 15.9 
F 17 2 0.207 0.018 82.1 12.0 
Milk Total fluid milk 
M 193 9 0.496 0.020 389.1 24.0 
F 155 10 0.513 0.025 302.1 24.4 
Eggs Eggs 
M 29 3 0.239 0.019 121.3 15.8 
F 18 2 0.189 0.012 95.2 12.2 
Fish Fish and 
shellfish 
M 12 2 0.093 0.009 129.0 24.9 
F 9 2 0.078 0.012 115.4 31.2 
a 
bThe food groups were selected such that the resulting CADI is the most conservative (BSC 2001 [DIRS 156016], pp. 8-10). 
USDA 2000 [DIRS 154158], Tables 86A to 91A and 86Ase to 91Ase (average daily intake), 86B to 91B and 86Bse to 91Bse (fraction of people consuming). 
c Calculated using equations 6.4-5 and 6.4-6 in spreadsheet Consumption rates of the Excel file Consumption rates with uncertainties.xls (Appendix C), as 
explained in Appendix A. 
AM = arithmetic mean, SE = standard error. 

Characteristics of the Receptor for the Biosphere Model 
ANL-MGR-MD-000005 REV 03 6-51 September 2004 
Table 6-21. Effective Number of Days for Consumption of Locally Produced Food and Annual Consumption Rates by Survey Food Group and 
by Biosphere Model Food Type 
1997 Food 
Consumption 
Survey Food 
Group Gender 
Effective Number of Days per Year When Locally Produced 
Food is Consumed (d/yr) a 
Annual Consumption Rate (kg/yr) 
Biosphere 
Model Food 
Types 
Survey Food Groups 
Biosphere Model 
Food Types 
AM ASD Count SE % Popul. b AM c SE d AM SE 
Leafy 
vegetables 
M 30.70 60.15 70 7.19 0.522 3.78 0.88 3.78 0.88 Leafy 
vegetables F 30.53 60.36 108 5.81 0.478 
Other M 30.76 49.61 70 5.93 0.522 4.73 0.67 4.73 0.67 Other 
vegetables vegetables F 37.22 58.67 107 5.67 0.478 
Fruit M 22.16 38.03 70 4.55 0.522 9.35 1.28 
12.68 e 1.36 f FruitF 35.91 55.12 111 5.23 0.478 
Tomatoes M 33.25 47.35 53 6.50 0.522 3.33 0.48F 51.17 89.31 87 9.58 0.478 
Grain M 0.00 0.00 71 0.00 0.522 0.23 0.11 0.23 0.11 GrainF 1.76 8.85 106 0.86 0.478 
Beef M 19.34 61.11 71 7.25 0.522 2.18 0.62 
2.85 g 0.65 f Meat 
F 17.59 54.34 109 5.20 0.478 
Pork M 7.63 31.11 71 3.69 0.522 0.53 0.17F 11.59 37.30 112 3.52 0.478 
Wild game M 0.72 3.33 71 0.40 0.522 0.13 0.10F 1.50 7.76 112 0.73 0.478 
Poultry M 4.31 13.89 70 1.66 0.522 0.42 0.13 0.42 0.13 Poultry 
F 2.90 11.28 112 1.07 0.478 
Milk M 13.03 59.93 69 7.21 0.522 4.66 1.68 4.66 1.68 MilkF 13.97 56.27 108 5.41 0.478 
Eggs M 34.82 69.48 70 8.30 0.522 5.30 0.83 5.30 0.83 EggsF 67.86 94.66 111 8.98 0.478 
Fish M 1.72 8.87 70 1.06 0.522 0.23 0.10 0.23 0.10 Fish 
F 2.13 9.81 112 0.93 0.478 
a Calculated in Excel spreadsheet from the consumption frequency data (DTN: MO0010SPANYE00.001 [DIRS 154976]) as described in Appendix A. 
b Calculated based on Bureau of the Census (2002 [DIRS 159728], Table P8). Concerns adult population, i.e., more than 17 years old. 
d 
Calculated using equation 6.4-2. 
Calculated using equation 6.4-4. 
e 
Calculated as a sum of consumption rates for fruit and tomatoes. 
f Calculated by taking the square root of the sum of squares of the SEs of the consumption rates for the regional survey food groups. 
g Calculated as a sum of consumption rates for beef, pork, and game. The combined value was calculated in the spreadsheet. Therefore, it differs by 0.01 kg/yr 
from the sum of components presented in the table. 
AM = arithmetic mean; ASD = arithmetic standard deviation; SE=standard error 

A more realistic approach can be developed. The calculation of the mean value of a given 
consumption parameter involves taking the product of several factors, each of which is subject to 
uncertainty (Equations 6.4-1 and 6.4-2). By considering the logarithm of the parameter, the 
mathematical operation of taking the product of a number of factors is transformed to taking the 
sum of the logarithms of each of the factors. Based on the central limit theorem 
(Bulmer 1979 [DIRS 111961], p. 115), the distribution of the logarithm of that parameter will be 
approximately normal. Thus, a reasonable approximating distribution for the actual parameter is 
a lognormal distribution. A lognormal distribution possesses the beneficial attribute that it is 
limited to positive parameter values. The use of this distribution eliminates the artificial 
condition of negative food consumption as discussed above or as would arise by using the 
normal distribution. 
In the analysis to generate the consumption rates, the available data are only sufficient to 
calculate the first and second moments (the mean and the standard deviation). Any distribution 
used to approximate the variability of the derived parameters should only require the definition 
of two parameters to uniquely specify the proposed distribution. The lognormal distribution 
meets this requirement. 
6.4.3 Inadvertent Soil Ingestion 
Soil contains the largest inventory of radioactivity of all components of the biosphere system for 
both exposure scenarios. For the volcanic ash scenario, this is because the soil or the mixture of 
soil and ash is the source of contamination, and for the groundwater scenario, the soil receives 
the majority of the contamination from irrigation water. Direct intake of soil was included in the 
biosphere model. Contamination of surface soil occurs during crop irrigation with contaminated 
water or during deposition of contaminated volcanic ash on the soil surface. For the groundwater 
exposure scenario, it is assumed that irrigation continues sufficiently long for the buildup of 
radionuclides and their decay products in soil to occur and for radionuclide concentrations to 
reach equilibrium (BSC 2004 [DIRS 169460], Section 5) . 
Ingestion of soil by humans can be divided into two distinct phenomena: inadvertent and 
deliberate (geophagia). Deliberate soil ingestion is frequently referred to as soil pica (pica being 
defined as an eating disorder manifested by a craving to ingest any material unsuitable for food); 
thus geophagia is a special case of pica. Inadvertent ingestion of soil may be a result of 
swallowing dirt or dust accompanying mouth breathing, via food items contaminated with soil, 
as well as from mouthing of dirty hands or other contaminated non-food items, such as cigarettes 
(Simon 1998 [DIRS 160098], p. 648). Increased soil ingestion may be related to the living 
conditions or professions that bring people into close and continual contact with the soil 
(Simon 1998 [DIRS 160098], p. 647). Deliberate soil ingestion is considered to be relatively 
uncommon (EPA 1997 [DIRS 103038], p. 4-1). 
Purposeful ingestion of soil (i.e., geophagia) is not considered in the development of this 
parameter. Geophagia is a disorder characterized by purposeful eating of soil. This disorder is 
uncommon and is usually confined to infants and children (EPA 1997 [DIRS 103038], 
Section 4.5). To comply with 10 CFR 63.312, which states that projections of diet must be based 
on the average of the adults in the Amargosa Valley, geophagia is not considered in the estimate 
of soil ingestion. 

Soil ingestion rates for the biosphere model were developed based on inadvertent average daily 
intake of soil reported in the literature. The studies of soil ingestion among adults are limited in 
number compared with studies of pica in children (EPA 1997 [DIRS 103038], p. 4-1), and only a 
few studies involving the direct measurements of adult soil ingestion rates have been conducted. 
In most publications on the subject of inadvertent soil ingestion by adults, the ingestion rates are 
estimated partly based on existing measurements and partly on assumptions. Soil ingestion by 
humans was the subject of a comprehensive review by Simon (1998 [DIRS 160098], 
p. 647-672), which included applications of soil ingestion rate to risk assessment of radioactively 
contaminated soil. That review includes an evaluation of existing data and their sources as well 
as recommendations regarding soil ingestion values for different environments, populations, and 
exposure scenarios. 
A summary of the information on inadvertent soil ingestion rates for adults is given in 
Table 6-22, which lists the literature sources and the associated values, ranges, and distributions, 
where applicable. 
The measured and assessed values of inadvertent soil ingestion rates are in the range of less than 
1 mg/d for clean indoor environments to several hundred mg/d for dusty outdoor environments 
(Table 6-22). Most of the dose and risk assessment models use 100 mg/d as the default value for 
the rate of inadvertent soil ingestion (Table 6-22). The value of 100 mg/d is also recommended 
by the EPA for residential and agricultural scenarios (EPA 1997 [DIRS 103038], p. 4-21). 
Although the most recent measurements indicate that the soil ingestion rates are about an order 
of magnitude lower than this value (Stanek et al. 1997 [DIRS 160251], p. 249), consideration 
was given to site-specific conditions. The nature of the Amargosa Valley environment, 
especially the frequent wind, sparse vegetation, and arid climate, suggests that the average value 
of inadvertent soil ingestion rate of 100 mg/d recommended by the EPA for agricultural 
scenarios is appropriate for the use in the biosphere model. 
The uncertainty distributions recommended by Simon (1998 [DIRS 160098], p. 663) for the 
inadvertent soil ingestion rate are lognormal with the geometric standard deviation of 3.2. 
Because the RMEI represents the average adult in the Amargosa Valley population, the 
uncertainty distribution for the rate of inadvertent soil ingestion should be associated with the 
uncertainty of the mean rather than with the population variability. The geometric means of the 
uncertainty distributions recommended by Simon (1998 [DIRS 160098], p. 663) for the 
inadvertent soil ingestion rate for various agricultural scenarios and rural lifestyles range from 
50 to 200 mg/d. Therefore, it is recommended that the inadvertent soil ingestion for the RMEI 
be represented by a piece-wise cumulative distribution with the following characteristics: 
(50 mg/d, 0 percent), (100 mg/d, 50 percent), and (200 mg/d, 100 percent). The mean value is 
112.5 mg/d, which agrees well with the value of 100 mg/d recommended by the EPA and used in 
other assessment models (Table 6-22). The mean value of the distribution can be obtained by 
calculating the probability density function f(x) for the soil ingestion rate. It consists of the two 
uniform sections with the values of 0.5/(100 mg/d - 50 mg/d) = 0.01 d/mg for the range from 
50 to 100 mg/d and 0.5/(200 mg/d - 100 mg/d) = 0.005 d/mg for the range from 100 to 200 mg/d. 

Table 6-22. Inadvertent Soil Ingestion Rates Reported in the Literature 
Reference Soil Ingestion Rate Comments 
Direct Measurements 
Calabrese et al. (1990) 
as cited in EPA (1997 
[DIRS 103038], p. 4-21) and in 
Simon (1998 [DIRS 160098], 
p. 652) 
30-100 mg/d 
approximately 50 mg/d 
Based on soil trace element 
measurements in 6 adults; 
uncertainties due to small sample 
size and short duration of the study 
Stanek et al. (1997 Based on the soil trace element 
[DIRS 160251], p. 249) 10 mg/d average; SD = 94 mg/d; 95% measurements for 10 adults; lower 
value 331 mg/d level of soil ingestion in adults than 
estimated previously 
Assessments, Estimate, and Literature Reviews 
Calabrese (1987) as cited in Suggested values are conjectural 
EPA (1997 [DIRS 103038], 
p. 4-17) 1 to 100 mg/d and based on fractional estimates 
of earlier Center for Disease 
Control estimates. 
Finley and Paustenbach 
(1994) as cited in Simon (1998 
[DIRS 160098], p. 653) 
0.1 to 50 mg/d for people aged 13-30 
year 
Theoretical assessment 
calculations for exposure to dioxin 
contamination 
Hawley (1985) as cited in EPA 
(1997 [DIRS 103038], p. 4-17) 
and in Simon (1998 
[DIRS 160098], p. 652) 
480 mg/d for adults engaged in outdoor 
activities 
0.56 mg/d for ingesting house dust during 
typical living space activities 
110 mg/d for ingestion of house dust 
while working in attics 
60.5 mg/d estimated annual average soil 
intake rate 
Estimated values based on 
assumptions about soil and dust 
levels on hands and mouthing 
behavior. 
Kimbrough et al. (1984) as 
cited in Simon (1998 
[DIRS 160098], p. 652) 
100 mg/d for people aged more than 5 
years 
Theoretical assessment 
calculations for exposure to dioxin 
contamination 
Martin and Bloom (1975) as Theoretical assessment 
cited in Simon (1998 8-11 mg/d calculations for desert environment 
[DIRS 160098], p. 652) 
Sheppard (1995) as cited in 20 mg/d for adult gardener Based on literature review 
Simon (1998 [DIRS 160098], 
p. 654) 
0.4 mg/d for adult indoors 
Recommendations 
ATSDR (1992) as cited in 
Simon (1998 [DIRS 160098], 50 mg/d 
p. 653) 
EPA (1997 [DIRS 103038], p. 
4-21) 
50 mg/d for industrial settings; a 
reasonable central estimate of adult soil 
ingestion and the recommended generic 
value for soil ingestion 
100 mg/d for residential and agricultural 
scenarios 
Various dose/risk assessment The default value recommended for 
models as described in Simon 100 mg/d dose assessment models, such as 
(1998 [DIRS 160098], p. 664) GENII, and RESRAD 
Simon (1998 [DIRS 160098], Lognormal distribution Recommended distributions are for 
Table 4) GM from 50 to 200 mg/d depending on 
the environment 
occupations on sparsely to heavily 
vegetated pasture land and for rural 
GSD = 3.2 lifestyles on sparsely to heavily 
vegetated land. 
ATSDR = Agency for Toxic Substances and Disease Registry; EPA = Environmental Protection Agency; 
GM=geometric mean; GSD=geometric standard deviation 
ANL-MGR-MD-000005 REV 03 6-54 September 2004 

The mean value is calculated as 
100 200 
100 200
. 
01.0 dx x +. 005.0 dx x = 5.0 01.0 x 2 ]50 + 5.0 005.0 x 2 ]=
[[ 100 
50 100 
= 01.0  5.0 [10000- 2500]+ 005.0  5.0 [40000 - 10000]= 5.112 
Because there are few direct measurements of inadvertent soil ingestion by adults, EPA 
(1997 [DIRS 103038], p. 4-21) indicates that the recommended values of inadvertent soil 
ingestion are uncertain. Therefore it is recommended that the same distribution of soil ingestion 
rate be used for all population groups, all environments, both exposure scenarios, and for the 
present-day and future climates. The recommended uncertainty distribution sufficiently 
represents the range of possible values. 
6.5 DOSIMETRY CONSIDERATIONS 
The function of the biosphere model is to calculate doses resulting from the radiation exposure of 
the receptor. This is accomplished by evaluating radionuclide intake or external exposure of the 
receptor, which are subsequently converted to radiation doses. The conversion is based on 
radionuclide-specific DCFs for internal exposure (inhalation or ingestion) and dose coefficients 
for external exposure. This section develops or recommends the values of conversion factors for 
the use in the biosphere model. 
6.5.1 Radionuclides and Elements Included in the Analysis 
The biosphere model calculates BDCFs for 28 primary radionuclides (BSC 2004 
[DIRS 169460], Section 6.1.3). The list includes radionuclides that are potentially significant 
dose contributors during the compliance period (up to 10,000 years) and the period of up to 
1,000,000 years for both exposure scenarios. 
Some of the radionuclides included in the biosphere model are accompanied in the source 
(e.g., groundwater or volcanic ash) by long-lived decay products, which are not individually 
tracked in the TSPA model. The biosphere model accounts for exposures to these radionuclides. 
In the biosphere model, the decay products of primary radionuclides with half-lives less than 
180 days are assumed to be in secular equilibrium with the parent radionuclides, and their 
contributions to the BDCFs are included in the BDCF for the primary radionuclide (BSC 2004 
[DIRS 169460], Section 6.3.5). The decay products of primary radionuclides with half-lives 
longer than 180 days are treated like primary radionuclides (BSC 2004 [DIRS 169460], 
Section 6.3.5). Three such radionuclides, 228Th, 228Ra, and 235U were added to the list, resulting 
in a set of thirty-one radionuclides (Table 6-23). This table also lists the short-lived (half-life 
less than 180 days) decay products as well as the half-lives and branching fractions for the 
primary radionuclides and their decay products. Detailed discussion of the treatment of decay 
products in the biosphere model is presented in BSC (2004 [DIRS 169460], Sections 6.3.5 and 
6.4.1.2). 

Table 6-23. Primary Radionuclides and Their Decay Products Included in the Biosphere Model 
Primary Radionuclide 
Short-lived Decay 
Product Branching Fraction, % a Half-life a 
Carbon-14 (14C) 100 5.730E+03 yr 
Chlorine-36 (36Cl) 100 3.01E+05 yr 
Selenium-79 (79Se) 100 6.50E+04 yr 
Strontium-90 (90Sr) 100 2.912E+01 yr 
Yttrium-90 (90Y) 100 6.40E+01 hr 
Technetium-99 (99Tc) 100 2.13E+05 yr 
Tin-126 (126Sn) 100 1.0E+05 yr 
Antimony-126m (126mSb) 100 1.90E+01 min 
Antimony-126 (126Sb) 14 1.24E+01 d 
Iodine-129 (129I) 100 1.57E+07 yr 
Cesium-135 (135Cs) 100 2.3E+06 yr 
Cesium-137 (137Cs) 100 3.00E+01 yr 
Barium-137m (137mBa) 94.60 2.552E+00 min 
Thorium Series (4n) 
Plutonium-240 (240Pu) 100 6.537E+03 yr 
Uranium-236 (236U) 100 2.3415E+07 yr 
Thorium-232 (232Th) 100 1.405E+10 yr 
Radium-228 (228Ra) 100 5.75E+00 yr 
Actinium-228 (228Ac) 100 6.13E+00 hr 
Uranium-232 (232U) 100 7.2E+01 yr 
Thorium-228 (228Th) 100 1.9131E+00 yr 
Radium-224 (224Ra) 100 3.66E+00 d 
Radon-220 (220Rn) 100 5.56E+01 s 
Polonium-216 (216Po) 100 1.5E-01 s 
Lead-212 (212Pb) 100 1.064E+01 hr 
Bismuth-212 (212Bi) 100 6.055E+01 min 
Polonium-212 (212Po) 64.07 3.05E-07 s 
Thallium-208 (208Tl) 35.93 3.07E+00 min 
Neptunium Series (4n + 1) 
Americium-241 (241Am) 100 4.322E+02 yr 
Neptunium-237 (237Np) 100 2.14E+06 yr 
Protactinium-233 (233Pa) 100 2.70E+01 d 
Uranium-233 (233U) 100 1.585E+05 yr 
Thorium-229 (229Th) 100 7.340E+03 yr 
Radium-225 (225Ra) 100 1.48E+01 d 
Actinium-225 (225Ac) 100 1.00E+01 d 
Francium-221 (221Fr) 100 4.8E+00 min 
Astatine-217 (217At) 100 3.23E-02 s 
Bismuth-213 (213Bi) 100 4.565E+01 min 
Polonium-213 (213Po) 97.84 4.2E-06 s 
Thallium-209 (209Tl) 2.16 2.20E+00 min 
Lead-209 (209Pb) 100 3.253E+00 hr 

Table 6-23. Primary Radionuclides and Their Decay Products Included in the Biosphere Model 
(Continued) 
Primary Radionuclide Short-lived Decay 
Product Branching Fraction, % a Half-life a 
Uranium Series (4n + 2) 
Plutonium-242 (242Pu) 100 3.763E+05 yr 
Uranium-238 (238U) 100 4.468E+09 yr 
Thorium-234 (234Th) 100 2.410E+01 d 
Protactinium-234m 
(234mPa) 
99.80 1.17E+00 min 
Protactinium-234 (234Pa) 0.33 6.70E+00 hr 
Plutonium-238 (238Pu) 100 8.774E+01 yr 
Uranium-234 (234U) 100 2.445E+05 yr 
Thorium-230 (230Th) 100 7.7E+04 yr 
Radium-226 (226Ra) 100 1.600E+03 yr 
Radon-222 (222Rn) 100 3.8235E+00 d 
Polonium-218 (218Po) 100 3.05E+00 min 
Lead-214 (214Pb) 99.98 2.68E+01 min 
Astatine-218 (218At) 0.02 2.E+00 s 
Bismuth-214 (214Bi) 100 1.99E+01 min 
Polonium-214 (214Po) 99.98 1.643E-04 s 
Thallium-210 (210Tl) 0.02 1.3E+00 min b 
Lead-210 (210Pb) 100 2.23E+01 yr 
Bismuth-210 (210Bi) 100 5.012E+00 d 
Polonium-210 (210Po) 100 1.3838E+02 d 
Actinium Series (4n +3) 
Americium-243 (243Am) 100 7.380E+03 yr 
Neptunium-239 (239Np) 100 2.355E+00 d 
Plutonium-239 (239Pu) 100 2.4065E+04 yr 
Uranium-235 (235U) 100 7.038E+08 yr 
Thorium-231 (231Th) 100 2.552E+01 hr 
Protactinium-231 (231Pa) 100 3.276E+04 yr 
Actinium-227 (227Ac) 100 2.1773E+01 yr 
Thorium-227 (227Th) 98.62 1.8718E+01 d 
Francium-223 (223Fr) 1.38 2.18E+01 min 
Radium-223 (223Ra) 100 1.1434E+01 d 
Radon-219 (219Rn) 100 3.96E+00 s 
Polonium-215 (215Po) 100 1.78E-03 s 
Lead-211 (211Pb) 100 3.61E+01 min 
Bismuth-211 (211Bi) 100 2.14E+00 min 
Thallium-207 (207Tl) 99.72 4.77E+00 min 
Polonium-211 (211Po) 0.28 5.16E-01 s 
Sources: 
ab 
Eckerman and Ryman 1993 (DIRS 107684), Table A.1. 
Lide and Frederikse 1997 (DIRS 103178), p. 11-125. 
NOTE: Short-lived decay products of primary radionuclides are assumed to be in secular equilibrium with their 
parents. 
ANL-MGR-MD-000005 REV 03 6-57 September 2004 

6.5.2 Dosimetric Approaches 
To demonstrate compliance with licensing regulations (10 CFR 63.311 [DIRS 156605]), the 
results of performance assessment are compared with the individual protection standard 
expressed in terms of the annual dose. The annual dose in 10 CFR 63.311 [DIRS 156605] is 
equivalent to the TEDE from annual exposure (66 FR 55732 [DIRS 156671], pp. 55734 
to 55735). The TEDE is the quantity typically used to specify dose limits for occupational 
exposure and is defined in 10 CFR 20.1003 [DIRS 104787] as the sum of deep dose equivalent 
resulting from exposure to external radiation and the committed effective dose equivalent 
(CEDE) resulting from internal contamination. For assessing doses to the RMEI, the TEDE is 
the sum of the effective dose equivalent (EDE) for external exposures and the CEDE for internal 
exposures (10 CFR 63.2 [DIRS 156605]). The use of the EDE in place of the deep dose 
equivalent in dose assessment is consistent with NRC guidance (NRC 2003 [DIRS 163018]). 
The TEDE from annual exposure used in 10 CFR Part 63 [DIRS 156605] is also equivalent to 
the annual CEDE used by EPA in the individual protection standard (40 CFR 197.20 
[DIRS 155238]). The annual CEDE as defined by EPA is the sum of the CEDE from internal 
doses resulting from 1 year of intake of radioactive materials plus the EDE from external 
radiation exposure during the year. 
CEDE is defined by the NRC as the sum of the products of the weighting factors applicable to 
each of the body organs or tissues that are irradiated and the committed dose equivalent to those 
organs or tissues (10 CFR 20.1003 [DIRS 104787]). In determining annual TEDE for assessing 
doses to members of the public (10 CFR Part 63 [DIRS 156605]), the external dose component 
(EDE) also involves summing the products of organ doses and weighting factors (66 FR 55732 
[DIRS 156671], pp. 55734 to 55735). 
Calculating CEDE and EDE involves using exposure-to-dose conversion factors, more 
commonly referred to as DCFs or dose coefficients. The exposure-to-dose conversion factor is 
one of the fundamental representations of a dosimetric model used in assessing potential 
radiation dose. It allows an intake of, or exposure to, a radionuclide to be converted to radiation 
dose. The current approach uses dosimetric models based on the concepts recommended in 
ICRP Publication 26 (ICRP 1977 [DIRS 101075]) and the dosimetric methods outlined in 
ICRP Publication 30 (ICRP 1979 [DIRS 110386]; ICRP 1980 [DIRS 110351]; ICRP 1981 
[DIRS 110352]). This is consistent with the individual protection standard defined in terms of 
TEDE and with the NRC guidance on performance assessment methodology (NRC 2000 
[DIRS 157704], Section 3.3.7.1.2). The ICRP-26 and ICRP-30 concepts and methods were used 
by the EPA to calculate the exposure-to-dose conversion factors for inhalation and ingestion 
presented in FGR No. 11 (Eckerman et al. 1988 [DIRS 101069]) and also dose coefficients for 
external exposure in FGR No. 12 (Eckerman and Ryman 1993 [DIRS 107684]). Although the 
DCFs and dose coefficients may have considerable uncertainty due to variability in human 
physiological characteristics, in this analysis they are taken as fixed values, as given in 
FGR No. 11 and FGR No. 12. This approach is recommended by the NRC (2000 [DIRS 
157704], Sections 3.3.7.3.1 and 3.3.7.3.2) for performance assessments. The biokinetic and 
dosimetric models used to develop the values in FGR No. 11 and FGR No. 12 are based on the 
standard representation of adult persons (Eckerman et al. 1988 [DIRS 101069], p. 12; Eckerman 
and Ryman 1993 [DIRS 107684], p. 9) . 

After the incorporation of ICRP-26 and ICRP-30 methodology into various U.S. regulations, the 
ICRP introduced new recommendations and issued a new set of exposure-to-dose conversion 
factors in ICRP Publication 72 (ICRP 1996 [DIRS 152446]). This set is based on updated 
biokinetic data and models, and the revised method for computing radiation doses presented in 
ICRP Publication 60 (ICRP 1991 [DIRS 101836]). ICRP Publication 60 introduced a new 
dosimetric quantity, the effective dose, which considers an expanded list of tissues and organs, 
updated biokinetic data and models, and revised tissue and organ weighting factors. To date, the 
revised ICRP dosimetric methods and the new exposure-to-dose conversion factors have not 
been incorporated into United States regulations. Because the repository licensing rule uses the 
concept of TEDE for dose limits, the conversion factors must also be expressed in terms of 
CEDE and EDE, which are based on the ICRP-30 dosimetric methods. Therefore, the updated 
conversion factors were not used. 
6.5.3 Dose Coefficients for Internal and External Exposure 
The primary sources of DCFs for internal and external exposure are FGR No. 11 (Eckerman et 
al. 1988 [DIRS 101069]) and FGR No. 12 (Eckerman and Ryman 1993 [DIRS 107684]), 
respectively. 
6.5.3.1 Dose Conversion Factors for Inhalation and Ingestion 
The DCFs for radionuclide intake by inhalation and ingestion used in the biosphere model are 
based on the values from FGR No. 11 (Eckerman et al. 1988 [DIRS 101069]). The DCFs for 
inhalation are for particles with activity median aerodynamic diameter (AMAD) of 1 m. For 
many radionuclides, there is only one DCF value for inhalation and one for ingestion. For some 
radionuclides, FGR No. 11 gives more than one value of DCF corresponding to different 
chemical compounds. Different DCFs arise from different fractional uptakes of a radionuclide 
from the small intestine to the blood and different lung clearance classes (ICRP 1979 
[DIRS 110386], p. 24 and 30 to 31) for various chemical forms of the radionuclide. DCFs for 
radionuclide intake by inhalation and ingestion were selected such that they correspond to the 
most conservative conditions for radionuclides under consideration. For most of the 
radionuclides considered in the biosphere model, if a radionuclide has more than one DCF, the 
higher DCF is for more soluble compounds. One exception is uranium, for which inhalation 
DCFs are the highest for the lung clearance class Y (long retention, on the order of years, in the 
pulmonary region of the lung) and relatively low uptake to blood. In this case, the highest DCF 
for inhalation and ingestion correspond to different chemical forms of a radionuclide. Despite 
this inconsistency, selecting the highest DCF value for a radionuclide ensures that the doses from 
this radionuclide will not be underestimated regardless of the chemical form of the radionuclide 
in the environment. The NRC (NRC 2000 [DIRS 157704], Section 3.3.7.3.1) recommends using 
the most conservative internal DCFs for TEDE calculations for radionuclides that have multiple 
DCFs based on chemical form, unless a particular chemical form can be justified. 
The inhalation DCF for carbon dioxide was selected for 14C (Table 6-24). The value for carbon 
dioxide is not the highest DCF for carbon (the value for labeled organic compounds is higher), 
but was selected because carbon dioxide is the chemical form for 14C inhalation. 

For 90Sr, it is customary to not select the highest DCF for inhalation. The most conservative 
DCF value for inhalation of strontium is for SrTiO3, which is rare and is considered to be 
unattainable during transport through environmental media (Rittmann 1993 [DIRS 107744], 
p. 6). Therefore, the value for other, more common chemical forms of strontium are used for 
inhalation and ingestion. Table 6-24 contains a summary of the DCFs for inhalation and 
ingestion that are recommended for use in the biosphere model. 
It is customary in radiological assessments that the DCFs for inhalation and ingestion are 
represented by fixed values and the same approach is recommended for the biosphere model 
although there are many sources of uncertainty associated with the dosimetric models. These 
uncertainties are described in NCRP Commentary No. 15 (NCRP 1998 [DIRS 160160]). 
Specifically, the estimated reliability of the DCFs for inhalation and ingestion based on ICRP-30 
methodology can be found in the NCRP Commentary (NCRP 1998 [DIRS 160160], Table 8.2). 
The results of the NCRP evaluation indicate that for many radionuclides considered in this 
analysis, the DCFs are poorly known and that the true values for at least 90 percent of the 
population may be as much as a factor of 10 higher or lower than the values recommended by 
ICRP in Publication 30 (NCRP 1998 [DIRS 160160], Table 8.2). 
6.5.3.2 Dose Coefficients for Exposure to Contaminated Soil 
The source of dose coefficients for exposure to contaminated soil is FGR No. 12 (Eckerman and 
Ryman 1993 [DIRS 107684]). From this report, the biosphere model uses dose coefficients for 
exposure to contaminated ground surface and to soil contaminated to an infinite depth. These 
dose coefficients are listed in Table 6-25. 
6.5.3.3 Dose Coefficients for Air Submersion and Water Immersion 
Dose coefficients for external exposure to radionuclides in air (air submersion) and in water 
(water immersion) recommended for use in the biosphere model are listed in Table 6-26. The 
source of these dose coefficients is FGR No. 12 (Eckerman and Ryman 1993 [DIRS 107684]). 
These dose coefficients are used in the Biosphere Model Report (BSC 2004 [DIRS 169460], 
Section 7.4) to evaluate the consequences of air submersion and water immersion, but are not 
directly used in the ERMYN model. 

Table 6-24. Dose Conversion Factors for Inhalation and Ingestion of Radionuclides of Interest 
Primary Radionuclide 
Short-lived Decay 
Product 
Dose Conversion Factors (Sv/Bq) 
Inhalation Ingestion 
Carbon-14 (14C) (as CO2) 6.36E-12 5.64E-10 
Chlorine-36 (36Cl) 5.93E-09 8.18E-10 
Selenium-79 (79Se) 2.66E-09 2.35E-09 
Strontium-90 (90Sr) 6.47E-08 a 3.85E-08 
Yttrium-90 (90Y) 2.28E-09 2.91E-09 
Technetium-99 (99Tc) 2.25E-09 3.95E-10 
Tin-126 (126Sn) 2.69E-08 5.27E-09 
Antimony-126m (126mSb) 9.17E-12 2.54E-11 
Antimony-126 (126Sb) 3.17E-09 2.89E-09 
Iodine-129 (129I) 4.69E-08 7.46E-08 
Cesium-135 (135Cs) 1.23E-09 1.91E-09 
Cesium-137 (137Cs) 8.63E-09 1.35E-08 
Barium-137m (137mBa)  b  b 
Thorium Series (4n) 
Plutonium-240 (240Pu) 1.16E-04 9.56E-07 
Uranium-236 (236U) 3.39E-05 7.26E-08 
Thorium-232 (232Th) 4.43E-04 7.38E-07 
Radium-228 (228Ra) 1.29E-06 3.88E-07 
Actinium-228 (228Ac) 8.33E-08 5.85E-10 
Uranium-232 (232U) 1.78E-04 3.54E-07 
Thorium-228 (228Th) 9.23E-05 1.07E-07 
Radium-224 (224Ra) 8.53E-07 9.89E-08 
Radon-220 (220Rn)  b  b 
Polonium-216 (216Po)  b  b 
Lead-212 (212Pb) 4.56E-08 1.23E-08 
Bismuth-212 (212Bi) 5.83E-09 2.87E-10 
Polonium-212 (212Po)  b  b 
Thallium-208 (208Tl)  b  b 
Neptunium Series ( 4n + 1 ) 
Americium-241 (241Am) 1.20E-04 9.84E-07 
Neptunium-237 (237Np) 1.46E-04 1.20E-06 
Protactinium-233 (233Pa) 2.58E-09 9.81E-10 
Uranium-233 (233U) 3.66E-05 7.81E-08 
Thorium-229 (229Th) 5.80E-04 9.54E-07 
Radium-225 (225Ra) 2.10E-06 1.04E-07 
Actinium-225 (225Ac) 2.92E-06 3.00E-08 
Francium-221 (221Fr)  b  b 
Astatine-217 (217At)  b  b 
Bismuth-213 (213Bi) 4.63E-09 1.95E-10 
Polonium-213 (213Po)  b  b 
Thallium-209 (209Tl)  b  b 
Lead-209 (209Pb) 2.56E-11 5.75E-11 

Table 6-24. Dose Conversion Factors for Inhalation and Ingestion of Radionuclides of Interest 
(Continued) 
Primary Radionuclide 
Short-lived Decay 
Product Dose Conversion Factors (Sv/Bq) 
Inhalation Ingestion 
Uranium Series ( 4n + 2 ) 
Plutonium-242 (242Pu) 1.11E-04 9.08E-07 
Uranium-238 (238U) 3.20E-05 6.88E-08 
Thorium-234 (234Th) 9.47E-09 3.69E-09 
Protactinium-234m (234mPa)  b  b 
Protactinium-234 (234Pa) 2.20E-10 5.84E-10 
Plutonium-238 (238Pu) 1.06E-04 8.65E-07 
Uranium-234 (234U) 3.58E-05 7.66E-08 
Thorium-230 (230Th) 8.80E-05 1.48E-07 
Radium-226 (226Ra) 2.32E-06 3.58E-07 
Radon-222 (222Rn)  b  b 
Polonium-218 (218Po)  b  b 
Lead-214 (214Pb) 2.11E-09 1.69E-10 
Astatine-218 (218At)  b  b 
Bismuth-214 (214Bi) 1.78E-09 7.64E-11 
Polonium-214 (214Po)  b  b 
Thallium-210 (210Tl)  b  b 
Lead-210 (210Pb) 3.67E-06 1.45E-06 
Bismuth-210 (210Bi) 5.29E-08 1.73E-09 
Polonium-210 (210Po) 2.54E-06 5.14E-07 
Actinium Series ( 4n + 3 ) 
Americium-243 (243Am) 1.19E-04 9.79E-07 
Neptunium-239 (239Np) 6.78E-10 8.82E-10 
Plutonium-239 (239Pu) 1.16E-04 9.56E-07 
Uranium-235 (235U) 3.32E-05 7.19E-08 
Thorium-231 (231Th) 2.37E-10 3.65E-10 
Protactinium-231 (231Pa) 3.47E-04 2.86E-06 
Actinium-227 (227Ac) 1.81E-03 3.80E-06 
Thorium-227 (227Th) 4.37E-06 1.03E-08 
Francium-223 (223Fr) 1.68E-09 2.33E-09 
Radium-223 (223Ra) 2.12E-06 1.78E-07 
Radon-219 (219Rn)  b  b 
Polonium-215 (215Po)  b  b 
Lead-211 (211Pb) 2.35E-09 1.42E-10 
Bismuth-211 (211Bi)  b  b 
Actinium Series ( 4n + 3 ) 
Thallium-207 (207Tl)  b  b 
Polonium-211 (211Po)  b  b 

Table 6-24. Dose Conversion Factors for Inhalation and Ingestion of Radionuclides of Interest 
(Continued) 
Primary Radionuclide 
Short-lived Decay 
Product Dose Conversion Factors (Sv/Bq) 
Inhalation Ingestion 
Actinium Series ( 4n + 3 ) 
Thallium-207 (207Tl)  b  b 
Polonium-211 (211Po)  b  b 
Source: Eckerman et al. 1988 (DIRS 101069), Tables 2.1 and 2.2. 
DCFs are in units of Sv/Bq. 1 Sv = 100 rem; 1 Ci = 3.71010 Bq. 
a 
Two values of DCF for 90Sr are given in the source document: one for SrTiO3 and one for all other compounds. 
Because SrTiO3 is not a common compound and is unlikely to be present in the biosphere, the value for all other 
b 
compounds was used (Rittmann 1993 [DIRS 107744], p. 6). 
Eckerman et al. 1988 (DIRS 101069) does not include DCFs for the short-lived radionuclides. The contribution 
from the short-lived decay products resulting from the decay of a longer lived parent radionuclide in the human 
body is included together with the parent radionuclide DCF. For radon, the short-lived decay products are 
included in the DCF for the parent radionuclide, as described in Section 6.5.4. 

Table 6-25. Dose Coefficients for External Exposure to Contaminated Soil for Radionuclides of Interest 
Primary Radionuclide 
Short-lived Decay 
Product 
Dose Coefficient 
Ground Surface 
Sv/s per Bq/m2 
Infinite Depth 
Sv/s per Bq/m3 
Carbon-14 (14C) 1.61E-20 7.20E-23 
Chlorine-36 (36Cl) 6.73E-19 1.28E-20 
Selenium-79 (79Se) 2.07E-20 9.96E-23 
Strontium-90 (90Sr) 2.84E-19 3.77E-21 
Yttrium-90 (90Y) 5.32E-18 1.28E-19 
Technetium-99 (99Tc) 7.80E-20 6.72E-22 
Tin-126 (126Sn) 5.47E-17 7.89E-19 
Antimony-126m (126mSb) 1.52E-15 4.98E-17 
Antimony-126 (126Sb) 2.78E-15 9.16E-17 
Iodine-129 (129I) 2.58E-17 6.93E-20 
Cesium-135 (135Cs) 3.33E-20 2.05E-22 
Cesium-137 (137Cs) 2.85E-19 4.02E-21 
Barium-137m (137mBa) 5.86E-16 1.93E-17 
Thorium Series ( 4n ) 
Plutonium-240 (240Pu) 8.03E-19 7.85E-22 
Uranium-236 (236U) 6.50E-19 1.15E-21 
Thorium-232 (232Th) 5.51E-19 2.79E-21 
Radium-228 (228Ra) 0.00E+00 0.00E+00 
Actinium-228 (228Ac) 9.28E-16 3.20E-17 
Uranium-232 (232U) 1.01E-18 4.83E-21 
Thorium-228 (228Th) 2.35E-18 4.25E-20 
Radium-224 (224Ra) 9.57E-18 2.74E-19 
Radon-220 (220Rn) 3.81E-19 1.23E-20 
Polonium-216 (216Po) 1.65E-20 5.58E-22 
Lead-212 (212Pb) 1.43E-16 3.77E-18 
Bismuth-212 (212Bi) 1.79E-16 6.27E-18 
Polonium-212 (212Po) 0.00E+00 0.00E+00 
Thallium-208 (208Tl) 2.98E-15 1.23E-16 
Neptunium Series ( 4n + 1 ) 
Americium-241 (241Am) 2.75E-17 2.34E-19 
Neptunium-237 (237Np) 2.87E-17 4.17E-19 
Protactinium-233 (233Pa) 1.95E-16 5.46E-18 
Uranium-233 (233U) 7.16E-19 7.48E-21 
Thorium-229 (229Th) 8.54E-17 1.72E-18 
Radium-225 (225Ra) 1.33E-17 5.90E-20 
Actinium-225 (225Ac) 1.58E-17 3.41E-19 
Francium-221 (221Fr) 2.98E-17 8.22E-19 
Astatine-217 (217At) 3.03E-19 9.49E-21 
Bismuth-213 (213Bi) 1.32E-16 4.10E-18 
Polonium-213 (213Po) 0.00E+00 0.00E+00 
Thallium-209 (209Tl) 1.90E-15 6.92E-17 
Lead-209 (209Pb) 3.01E-19 4.14E-21 

Table 6-25. Dose Coefficients for External Exposure to Contaminated Soil for Radionuclides of 
Interest (Continued) 
Primary Radionuclide 
Short-lived Decay 
Product 
Dose Coefficient 
Ground Surface 
Sv/s per Bq/m2 
Infinite Depth 
Sv/s per Bq/m3 
Uranium Series ( 4n + 2 ) 
Plutonium-242 (242Pu) 6.67E-19 6.85E-22 
Uranium-238 (238U) 5.51E-19 5.52E-22 
Thorium-234 (234Th) 8.32E-18 1.29E-19 
Protactinium-234m (234mPa) 1.53E-17 4.80E-19 
Protactinium-234 (234Pa) 1.84E-15 6.18E-17 
Plutonium-238 (238Pu) 8.38E-19 8.10E-22 
Uranium-234 (234U) 7.48E-19 2.15E-21 
Thorium-230 (230Th) 7.50E-19 6.47E-21 
Radium-226 (226Ra) 6.44E-18 1.70E-19 
Radon-222 (222Rn) 3.95E-19 1.26E-20 
Polonium-218 (218Po) 8.88E-21 3.02E-22 
Lead-214 (214Pb) 2.44E-16 7.18E-18 
Astatine-218 (218At) 4.18E-18 3.13E-20 
Bismuth-214 (214Bi) 1.41E-15 5.25E-17 
Polonium-214 (214Po) 8.13E-20 2.75E-21 
Thallium-210 (210Tl) a a 
Lead-210 (210Pb) 2.48E-18 1.31E-20 
Bismuth-210 (210Bi) 1.05E-18 1.93E-20 
Polonium-210 (210Po) 8.29E-21 2.80E-22 
Actinium Series ( 4n + 3 ) 
Americium-243 (243Am) 5.35E-17 7.60E-19 
Neptunium-239 (239Np) 1.63E-16 4.03E-18 
Plutonium-239 (239Pu) 3.67E-19 1.58E-21 
Uranium-235 (235U) 1.48E-16 3.86E-18 
Thorium-231 (231Th) 1.85E-17 1.95E-19 
Protactinium-231 (231Pa) 4.07E-17 1.02E-18 
Actinium-227 (227Ac) 1.57E-19 2.65E-21 
Thorium-227 (227Th) 1.04E-16 2.79E-18 
Francium-223 (223Fr) 5.65E-17 1.06E-18 
Radium-223 (223Ra) 1.28E-16 3.23E-18 
Radon-219 (219Rn) 5.49E-17 1.65E-18 
Polonium-215 (215Po) 1.74E-19 5.44E-21 
Lead-211 (211Pb) 5.08E-17 1.64E-18 
Bismuth-211 (211Bi) 4.58E-17 1.37E-18 
Thallium-207 (207Tl) 3.76E-18 1.06E-19 
Polonium-211 (211Po) 7.61E-18 2.55E-19 
Source: Eckerman and Ryman 1993 (DIRS 107684), Tables III.3 and III.7. 
a 
not included. 

Table 6-26. Dose Coefficients for Air Submersion and Water Immersion for Radionuclides of Interest 
Primary Radionuclide 
Short-lived Decay 
Product 
Dose Coefficient 
Air Submersion 
Sv/s per Bq/m3 
Water Immersion 
Sv/s per Bq/m3 
Carbon-14 (14C) 2.24E-19 4.39E-22 
Chlorine-36 (36Cl) 2.23E-17 4.48E-20 
Selenium-79 (79Se) 3.03E-19 5.93E-22 
Strontium-90 (90Sr) 7.53E-18 1.46E-20 
Yttrium-90 (90Y) 1.90E-16 3.63E-19 
Technetium-99 (99Tc) 1.62E-18 3.14E-21 
Tin-126 (126Sn) 2.11E-15 4.76E-18 
Antimony-126m (126mSb) 7.50E-14 1.63E-16 
Antimony-126 (126Sb) 1.37E-13 2.99E-16 
Iodine-129 (129I) 3.80E-16 8.91E-19 
Cesium-135 (135Cs) 5.65E-19 1.10E-21 
Cesium-137 (137Cs) 7.74E-18 1.49E-20 
Barium-137m (137mBa) 2.88E-14 6.26E-17 
Thorium Series ( 4n ) 
Plutonium-240 (240Pu) 4.75E-18 1.11E-20 
Uranium-236 (236U) 5.01E-18 1.16E-20 
Thorium-232 (232Th) 8.72E-18 1.99E-20 
Radium-228 (228Ra) 0.00E+00 0.00E+00 
Actinium-228 (228Ac) 4.78E-14 1.04E-16 
Uranium-232 (232U) 1.42E-17 3.22E-20 
Thorium-228 (228Th) 9.20E-17 2.05E-19 
Radium-224 (224Ra) 4.71E-16 1.03E-18 
Radon-220 (220Rn) 1.85E-17 4.03E-20 
Polonium-216 (216Po) 8.29E-19 1.80E-21 
Lead-212 (212Pb) 6.87E-15 1.52E-17 
Bismuth-212 (212Bi) 9.24E-15 2.00E-17 
Polonium-212 (212Po) 0.00E+00 0.00E+00 
Thallium-208 (208Tl) 1.77E-13 3.84E-16 
Neptunium Series ( 4n + 1 ) 
Americium-241 (241Am) 8.18E-16 1.88E-18 
Neptunium-237 (237Np) 1.03E-15 2.32E-18 
Protactinium-233 (233Pa) 9.35E-15 2.05E-17 
Uranium-233 (233U) 1.63E-17 3.64E-20 
Thorium-229 (229Th) 3.83E-15 8.56E-18 
Radium-225 (225Ra) 2.79E-16 6.49E-19 
Actinium-225 (225Ac) 7.21E-16 1.61E-18 
Francium-221 (221Fr) 1.46E-15 3.22E-18 
Astatine-217 (217At) 1.48E-17 3.22E-20 
Bismuth-213 (213Bi) 6.39E-15 1.39E-17 
Polonium-213 (213Po) 0.00E+00 0.00E+00 
Thallium-209 (209Tl) 1.02E-13 2.22E-16 
Lead-209 (209Pb) 8.12E-18 1.57E-20 

Table 6-26. Dose Coefficients for Air Submersion and Water Immersion for Radionuclides of Interest 
(Continued) 
Primary Radionuclide 
Short-lived Decay 
Product 
Dose Coefficient 
Air Submersion 
Sv/s per Bq/m3 
Water Immersion 
Sv/s per Bq/m3 
Uranium Series ( 4n + 2 ) 
Plutonium-242 (242Pu) 4.01E-18 9.35E-21 
Uranium-238 (238U) 3.41E-18 7.95E-21 
Thorium-234 (234Th) 3.38E-16 7.64E-19 
Protactinium-234m (234mPa) 7.19E-16 1.52E-18 
Protactinium-234 (234Pa) 9.34E-14 2.03E-16 
Plutonium-238 (238Pu) 4.88E-18 1.14E-20 
Uranium-234 (234U) 7.63E-18 1.75E-20 
Thorium-230 (230Th) 1.74E-17 3.94E-20 
Radium-226 (226Ra) 3.15E-16 6.95E-19 
Radon-222 (222Rn) 1.91E-17 4.16E-20 
Polonium-218 (218Po) 4.48E-19 9.71E-22 
Lead-214 (214Pb) 1.18E-14 2.59E-17 
Astatine-218 (218At) 1.19E-16 2.75E-19 
Bismuth-214 (214Bi) 7.65E-14 1.66E-16 
Polonium-214 (214Po) 4.08E-18 8.85E-21 
Thallium-210 (210Tl)   
Lead-210 (210Pb) 5.64E-17 1.31E-19 
Bismuth-210 (210Bi) 3.29E-17 6.33E-20 
Polonium-210 (210Po) 4.16E-19 9.03E-22 
Actinium Series ( 4n + 3 ) 
Americium-243 (243Am) 2.18E-15 4.94E-18 
Neptunium-239 (239Np) 7.69E-15 1.70E-17 
Plutonium-239 (239Pu) 4.24E-18 9.60E-21 
Uranium-235 (235U) 7.20E-15 1.59E-17 
Thorium-231 (231Th) 5.22E-16 1.18E-18 
Protactinium-231 (231Pa) 1.72E-15 3.78E-18 
Actinium-227 (227Ac) 5.82E-18 1.30E-20 
Thorium-227 (227Th) 4.88E-15 1.07E-17 
Francium-223 (223Fr) 2.29E-15 5.11E-18 
Radium-223 (223Ra) 6.09E-15 1.35E-17 
Radon-219 (219Rn) 2.68E-15 5.85E-18 
Polonium-215 (215Po) 8.43E-18 1.84E-20 
Lead-211 (211Pb) 2.49E-15 5.41E-18 
Bismuth-211 (211Bi) 2.22E-15 4.85E-18 
Thallium-207 (207Tl) 1.62E-16 3.38E-19 
Polonium-211 (211Po) 3.81E-16 8.27E-19 
Source: Eckerman and Ryman 1993 (DIRS 107684), Tables III.1 and III.2. 

6.5.4 Radon Doses 
The DCF for inhalation of 222Rn decay products was calculated based on the data from 
FGR No. 11 (Eckerman et al. 1988 [DIRS 101069] and ICRP 1981 [DIRS 163051]). The 
function of the DCF for radon, DCFinh,Rn-222,n in the biosphere model is to convert the exposure to 
radon decay products to dose (CEDE) for a unit (1 Bq/m3) radon gas activity concentration in air 
and for a unit breathing rate (1 m3/hr) (BSC 2004 [DIRS 169460], Section 6.4.8.4). This DCF 
for inhalation of 222Rn decay products, can be derived based on the following: 
 
The potential alpha energy concentration (PAEC)-to-dose conversion factor for 222Rn 
decay products is 0.010 Sv (1 rem) per working level month (ICRP 1981 
[DIRS 163051], p. 15) 
 
One working level month (WLM) corresponds to an exposure to radon decay products 
whose PAEC is equal to 1 working level (WL) for a period of 1 working month 
(approximately 170 working hours) (10 CFR 20.1003 [DIRS 104787]). 
 
The PAEC of 1 WL corresponds to any combination of short-lived radon decay products 
in one liter of air that will result in the ultimate emission of 1.3  105 MeV of alpha 
energy (10 CFR 20.1003 [DIRS 104787]), which is approximately the alpha energy 
released from the decay of the short-lived decay products in equilibrium with 100 pCi of 
222Rn (ICRP 1981 [DIRS 163051], pp. 18-19). 
 
The conversion factor of (1 rem)/(1 WLM) was developed for workers whose breathing 
rate is equal to 1.2 m3/hr (ICRP 1981 [DIRS 163051], pp. 7 and 15, Eckerman et al. 
1988 [DIRS 101069], p. 10). Because the DCF for inhalation of 222Rn applies to a unit 
1
breathing rate, an additional correction factor of is used.
m 2.1 3/h 
The DCF for inhalation of 222Rn can thus be derived as follows: 
rem 1 WLM 11WL pCi/L 1 Sv 0.01 1 
= 
, = 3  EFRn-, 222 n
DCF
Rn inh -, 222 n WLM 1 h WL 170pCi/L 100 Bq/m 37 3 rem 1 /h m 2.1 
Sv
 
, 
= 10 1.33 8-EFRn-, 222 n Bq 
= DCFRn inh -222 EFRn-, 222 n 
where 
EFRn-222, n = equilibrium factor for 222Rn decay products for the environment n 
(dimensionless) 
DCFinh, Rn-222 = DCF for inhalation of 222Rn decay products in equilibrium with radon 
gas (1.33  10-8 Sv/Bq, rounded up to three significant digits) 
The equilibrium factor, EFRn-222, permits estimation of PAEC from the measurement of radon gas 
(here 222Rn). It is defined as the ratio of the actual PAEC to the PAEC that would prevail if all 
the decay products in the (222Rn) series were in equilibrium with the parent radon. The 

equilibrium factor depends on the environment and is typically higher for the outdoor 
environment than indoor (UNSCEAR 2000 [DIRS 158644], pp. 103-104). 
6.5.5 Dependence of Inhalation Dose Conversion Factors on Particle Sizes 
To estimate inhalation exposure to airborne particulates one needs to know the particle size 
distribution because the DCFs vary with the particle size. It is generally considered that the 
particles that may become resuspended are associated with the aerodynamic diameters of less 
than 100 m (Anspaugh et al. 1975 [DIRS 151548], p. 572). The smallest of these particles (less 
than about 10 m) may be suspended for a considerable amount of time (Nicholson 1988 
[DIRS 160116], p. 2642). 
6.5.5.1 Particle Size Distribution of Environmental Aerosols 
The size distribution of resuspended particles depends not only on the characteristic of the site 
but also on the activities that result in generation of airborne particulates. Shinn 
(1992 [DIRS 160115], p. 1190) indicates that average median aerodynamic diameter of particles 
produced by resuspension of material deposited on the ground is in the range between 2 and 
6 m. Dorrian (1997 [DIRS 159476], pp. 117, 129) concluded that the median value of AMAD 
for resuspended aerosols was 6 m. The measurements by Shinn (1992 [DIRS 160115]) include 
experiments performed at the Nevada Test Site. A coarse component (greater than about 2 m), 
with median diameter of about 15 m is sometimes also found when the soil is disturbed or when 
very strong winds are present (NCRP 1999 [DIRS 155894], p. 67). This coarse component 
should be considered transient because the gravitational settling velocities of the coarse particles 
are greater than the suspension velocities and their residence times in the atmosphere are short 
(NCRP 1999 [DIRS 155894], p. 67). In general, the ratio of total suspended particulates to the 
PM10 fraction (particulates with the median aerodynamic diameter less than 10 m) increases 
under disturbed conditions (NCRP 1999 [DIRS 155894], p. 67). The generic recommended 
particle size distribution is lognormal with a median diameter in the range of 2 to 6 m and a 
geometric standard deviation of about five (NCRP 1999 [DIRS 155894], p. 68). Such 
distribution applies to the long-term, average conditions. The particle size distribution of 
airborne activity may be different from the distribution of the suspended soil dust, particularly if 
the radioactive particles are preferentially bound to a specific size range of the soil particles. 
This may be the case for the volcanic ash exposure scenario, as described later in this section. 
Short-term particle size distributions may include a larger contribution from the coarse 
component, compared to the average conditions, especially during or immediately following a 
dust generating activity. For example, agricultural activities may involve generation of high 
levels of dust. In one study conducted in arid agricultural regions in California, it was observed 
that dust particles were relatively large and that the largest proportion of the dust belonged to the 
extrathoracic fraction (> 10 m) (Nieuwenhuijsen et al. 1998 [DIRS 150855], p. 36). The 
average mass median aerodynamic diameter measured during various agricultural operations was 
49 m (Nieuwenhuijsen et al. 1998 [DIRS 150855], p. 36). The proportion of small particles 
(less than 10 m) for most activities was less than 10 percent of the total mass and generally was 
lower for dustier activities. Another study of natural aerosols in the arid southwestern United 
States concluded that near-surface aerosol is comprised to two modes: a wind-derived 

supermicron component which is likely soil-derived and local in origin and a submicron 
component that is likely a product of long-range atmospheric transport (Pinnick et al. 1993 
[DIRS 160312], pp. 2651 and 2664). The supermicron component dominates the total aerosol 
mass while submicron mode contributes little to the aerosol mass. During the disturbed 
conditions, such as dust storm, there is an increase in concentration of supermicron aerosols 
(coarse mode with particle sizes up to 100 m) that consists almost exclusively of particles of the 
parent soil. The submicron aerosol concentration was nearly unaffected by the disturbed 
conditions (Pinnick et al. 1993 [DIRS 160312], p. 2659). Similar findings resulted from the 
study by Whitby as reported in EPA (1996 [DIRS 160121], p. 3-161, Figure 3-22), who 
concluded that the concentration of particles smaller than 2.5 m in diameter was not affected by 
the strong winds. The review of the available information on airborne particulates, with emphasis 
on the coarse mode, concluded that the coarse model could be reasonably well described by a 
lognormal distribution with a mass median aerodynamic diameter of 15 to 25 m and a 
geometric standard deviation of approximately two (EPA 1996 [DIRS 160121], p. 3-160). Thus 
for a freshly generated coarse model aerosol, only about 1 percent of the mass would be less than 
2.5 m and only about 0.1 percent would be less than 1.0 m in diameter (EPA 1996 
[DIRS 160121], pp. 3-160 to 3-161). Based on the reviewed literature (EPA 1996 
[DIRS 160121], Sections 3.7.5 - 3.7.8; Nieuwenhuijsen et al. 1998 [DIRS 150855]; Pinnick et al. 
1993 [DIRS 160312]), the airborne particles originating from the local soils range in size from 
about 0.1 m to about 100 m. 
Particle size distribution for the indoor environment differs from that characteristic of the 
outdoor environment. Under typical conditions, aerosols in the coarse mode (> 2 m) are only 
likely to give rise to exposures to people who are outdoors and close to the site of contamination 
(Dorrian 1997 [DIRS 159476], p. 129-130). In the indoor environment, concentration of large 
particles is significantly depleted in comparison to the outdoor environment and particles larger 
than 5 m would be decreasingly likely to penetrate indoors (Dorrian 1997 [DIRS 159476], 
p. 130). 
The volcanic ash exposure scenario involves generation of contaminated ash particles that can be 
transported in the atmosphere and subsequently deposited on the ground. Explosive eruptive 
styles of Quaternary volcanoes in the Yucca Mountain region include both strombolian and 
violent strombolian (BSC 2004 [DIRS 169980], Section 6.3.3.6.1). The distribution of the 
average size ash particles resulting from a volcanic eruption at Yucca Mountain is defined as 
logtriangular with a minimum of 0.01 mm (10 m), a mode of 0.1 mm (100) m, and a 
maximum of 1.0 mm (1,000 m). The distribution of mean ash particle standard deviation is 
uniform from 1-3 phi units (BSC 2004 [DIRS 169980], Section 6.3.3.6.1 and Table 7-1) 
(phi units are defined as a negative logarithm in base 2 of the particle diameter in millimeters, 
BSC 2004 [DIRS 169980], Section 6.1.3.5). This distribution is consistent with the particle size 
distributions for the analogue volcanoes (Tolbachik and Cerro Negro) of the violent strombolian 
type (BSC 2004 [DIRS 169980], Section 6.3.3.6.1). 
The distribution of the waste particle size has a minimum of 1 m, the mode of 16 m, and the 
maximum of 500 m (BSC 2004 [DIRS 170026], Section 6.5.2.16). Based on the particle size, 
only a small fraction of particles (the smallest predicted average ash sizes have a very low 
probability of occurrence) would be available for resuspension. 

During volcanic eruption intersecting the repository, the waste becomes incorporated into the ash 
with the incorporation ratio of 0.3 (BSC 2004 [DIRS 170026], Section 6.5.2.6). The 
incorporation ratio describes the ratio of ash/waste particle sizes that can be attached together. 
The waste mass is distributed among the ash mass based on relative particle sizes. Incorporation 
of waste particles requires ash particles of a certain size or larger. Thus, larger ash particles will 
carry a greater mass of radioactive waste particles than smaller ash particles (BSC 2004 
[DIRS 170026], Section 6.5.2.6). 
The model for atmospheric transport of contaminated volcanic ash (ASHPLUME) is appropriate 
for particles of mean diameter greater than 15-30 m (Jarzemba et al. 1997 [DIRS 100987], 
p. 2-2). Although the model is useful for calculating the distribution of the majority of ash 
(typical mean diameter of ash particle after an eruption is generally much greater than 15 m), it 
does not address well the particles in the respirable (less than 4 m) and thoracic (less than 
10 m) size range, which are more important for the evaluation of inhalation doses. Therefore, 
the information from the analog volcano was used to estimate the airborne particle sizes for the 
evaluation of inhalation exposure of the receptor. The measurements performed at about 21 km 
from the Cerro Negro volcano indicate that only about 20 percent of the deposited ash particles 
by mass are in the inhalable particle size range (less than 100 m) (Reamer and Williams 2000 
[DIRS 154597], Attachment 17 of Appendix 4). Particles in this size range can become airborne 
either due to natural processes or as the result of the human surface disturbing activities. 
The suspendibility of particles depends on their aerodynamic properties. Therefore it can be 
reasonably expected that the range of the aerodynamic diameters of the suspended ash particles 
will be similar to the range of suspended soil particles described above, although the mass 
particle size ranges may be different due to the differences in particle densities and shapes. The 
same range of particle sizes is also expected for the future climate considered within the 
applicability limits of the biosphere model. 
6.5.5.2 Dosimetric Considerations for Airborne Particulates 
From the human health perspective, particulates can be classified into inhalable, thoracic and 
respirable, according to their entrance and deposition in the various compartment of the 
respiratory system. Inhalable particles refer to those that enter the respiratory tract, including the 
head airways region (anterior and posterior nose, larynx, pharynx and mouth). Thoracic particles 
refer to particles that reach the lung airways and the gas-exchange region (bronchial, bronchiolar, 
and alveolar regions), and respirable particles are those that reach the gas-exchange region 
(alveolar region) (EPA 1996 [DIRS 160121], p. 3-11; ICRP 1994 [DIRS 153705], pp. 8-11). 
The term extrathoracic particles used later in this section refers to particles that do not reach the 
lung airways and the gas exchange region. 
The most important parameter determining the particles aerodynamic behavior and respiratory 
tract deposition is its aerodynamic equivalent diameter, which depends on particle density and 
shape (Dorrian 1997 [DIRS 159476], p. 117). The DCFs for inhalation of airborne contaminants 
depend on their aerodynamic diameter. To ensure consistent use, the inhalation DCFs are 
tabulated for particles with a given AMAD. AMAD is defined as the diameter of a unit-density 
sphere having the same terminal settling velocity in air as the aerosol particle whose activity is 
the median for the entire aerosol (Eckerman et al. 1988 [DIRS 101069], p. 219), i.e., 50 percent 

of an aerosols activity is associated with particles whose aerodynamic equivalent diameter is 
greater than the AMAD. Respiratory tract deposition of radioactive aerosols is related to the 
AMAD of the particle size distribution and is relatively insensitive to the geometric standard 
deviation of the distribution. 
The density of most of the environmental particles is greater than unity. Therefore such particles 
are aerodynamically equivalent to larger particles of unit density (aerodynamic diameter is 
directly proportional to the square root of the particle density) (EPA 1996 [DIRS 160121], 
p. 3-9). 
The size distribution of resuspended soil particles may be described as lognormal bimodal with 
one mode at 2-5 m and another mode at 30 to 60 m (EPA 1996 [DIRS 160121], p. 3-36) and 
the size range of the particles originating in local soil is typically between 0.1 and 100 m (see 
Section 6.5.5.1). The inhalation DCFs based on the ICRP-30 dosimetric methods are most 
commonly tabulated for particulates whose diameter is distributed lognormally with an AMAD 
of 1 m (ICRP 1979 [DIRS 110386], Eckerman et al. 1988 [DIRS 101069]). Using the 
respiratory tract model of ICRP Publication 30 (ICRP 1979 [DIRS 110386], pp. 23-29) the DCFs 
for 1-m particles can be converted to DCFs for other particle sizes, as described below. 
The conversion method is based on the formula (ICRP 1979 [DIRS 110386], Equation 5.8) that 
calculates the committed dose equivalent in an organ T for particles of a given AMAD, HT 
(AMAD), as a fraction of the committed dose equivalent in this organ for 1-m particles, HT 
(1 m): 
HT ( AMAD) DN -P ( AMAD) DT - B ( AMAD) + fP 
DP ( AMAD)
= fN -P + fT - B (Eq. 6.5-1) 
HT (1m) DN -P (1m) DT -B (1m) DP (1m) 
where 
fN-P = fraction of the committed dose equivalent in the reference tissue 
resulting from deposition in the naso-pharyngeal, N-P, region of the 
respiratory tract 
DN-P (AMAD) = deposition probability in the N-P region of the respiratory tract for a 
given AMAD (from ICRP 1979 [DIRS 110386], Figure 5.1) 
DN-P (1 m) = deposition probability in the N-P region of the respiratory tract for a 
given AMAD (from ICRP 1979 [DIRS 110386], Figure 5.1) 
fT-B = fraction of the committed dose equivalent in the reference tissue 
resulting from deposition in the tracheo-bronchial, T-B, region of the 
respiratory tract 
DT-B(AMAD) = deposition probability in the T-B region of the respiratory tract for a 
given AMAD (from ICRP 1979 [DIRS 110386], Figure 5.1) 
DT-B(1 m) = deposition probability in the T-B region of the respiratory tract for a 
m AMAD (from ICRP 1979 [DIRS 110386], Figure 5.1) 
fP = fraction of the committed dose equivalent in the reference tissue 
resulting from deposition in the pulmonary, P, region of the 
respiratory tract 

DP (AMAD) = deposition probability in the P region of the respiratory tract for a m 
AMAD (from ICRP 1979 [DIRS 110386], Figure 5.1) 
DP (1 m) = deposition probability in the P region of the respiratory tract for a m 
AMAD (from ICRP 1979 [DIRS 110386], Figure 5.1). 
The respiratory tract model of ICRP Publication 30 is intended for use with aerosol distributions 
with AMAD between 0.2 and 10 m and with geometric standard deviations of less than 4.5. 
Provisional estimates of deposition further extending the size range from 0.1 m to 20 m were 
provided. For distributions with an AMAD of greater than 20 m it is recommended that the 
complete deposition in the naso-pharyngeal region be assumed (ICRP 1979 [DIRS 110386], 
p. 24). The relationship between the values of DN-P, DT-B, and DP, representing the fractions of 
the inhaled particles that are estimated to deposit in the three regions of the respiratory tract, and 
the aerodynamic sizes of the particles were developed for an adult male involved in light work. 
The weighted committed dose equivalent in an organ per intake of unit activity for particles 
(here 1 Bq) of a given AMAD, wT HT,1(AMAD), can then be calculated by multiplying the ratio 
obtained using Equation 6.5-1 by the weighted committed dose equivalent in this organ per 
intake of unit activity for 1 m particles. 
HT ( AMAD)
wT HT 1 , ( AMAD) =wTH T 1 , (1m) (Eq. 6.5-2) 
HT (1m) 
where 
w
T = organ or tissue weighting factor 
The weighted committed dose equivalent for various organs per intake of unit activity for 1-m 
particles and the fractions of the committed dose equivalent in these organs or tissues resulting 
from deposition in various parts of the respiratory tract can be found in Supplements to Parts 1, 
2 and 3 of ICRP Publication 30 (ICRP 1978 [DIRS 101076], pp. 84-85, 192-193, 231-232, 
236-237, 289-290, 318, 322-323, 333-334, 356-357, 362, 364-365, 371, 378, 410-411, 414-415, 
418-419, 424-425, 456, 466-467; ICRP 1981 [DIRS 153056], pp. 19, 195, 660-661, 739; ICRP 
1982 [DIRS 153057], pp. 790, 827; ICRP 1982 [DIRS 163147], pp. 158-159). The committed 
EDE can then be calculated by summing up the organ-weighted committed dose equivalents. 
Their sum represents the effective (weighted) dose equivalent for a given AMAD per intake of 
unit activity by inhalation. This quantity can be compared to the corresponding DCF for 1-m 
particles by producing a following ratio of these two quantities: 
. wT HT 1 , ( AMAD) 
T
Ratio =. wT HT 1 , (1m) 
(Eq. 6.5-3) 
T 
The ratio identified in Equation 6.5-3 is a measure of how closely the DCFs for 1-m particles 
represent DCFs for other particle sizes, with the value of 1 meaning that the respective DCFs are 

equal. Such ratios were calculated for a range of particle sizes corresponding to the expected 
range of particle sizes for resuspended contaminated soil, i.e., from 0.1 to 100 m. As noted 
previously, the model is intended for use with aerosol distributions with AMAD between 0.2 and 
10 m and the values beyond this range are provisional. The results of comparison are 
summarized in Table 6-27. The same information is also presented graphically in Figure 6-13. 
The Excel spreadsheet calculations are shown in Appendix B. The Excel file (file name 
Inhalation of large particles.xls) is provided in Appendix C. 
Table 6-27. Comparison of Inhalation Dose Conversion Factors Between 1-m Particles and Other Size 
Particles 
Radionuclide 
DCF Ratio (DCF for a Given Size Particles to DCF for 1-m Particles)a 
0.1 m 0.2 m 0.5 m 1 m 2 m 5 m 10 m 20 m 100 m 
Chlorine-36 2.4 2.0 1.4 1.0 0.7 0.4 0.2 0.1 0.0 
Selenium-79 1.9 1.5 1.2 1.0 0.9 0.9 0.9 0.9 0.8 
Strontium-90 1.7 1.2 1.0 1.0 1.1 1.2 1.3 1.3 1.2 
Technetium-99 2.4 2.0 1.4 1.0 0.7 0.4 0.2 0.1 0.0 
Tin-126 2.3 1.9 1.4 1.0 0.7 0.5 0.3 0.2 0.1 
Iodine-129 1.4 1.0 1.0 1.0 1.2 1.4 1.6 1.6 1.6 
Cesium-135 1.5 1.0 1.0 1.0 1.1 1.4 1.6 1.5 1.5 
Cesium-137 1.5 1.0 1.0 1.0 1.1 1.4 1.6 1.6 1.5 
Lead-210 1.7 1.2 1.0 1.0 1.1 1.2 1.3 1.2 1.2 
Radium-226 2.3 1.9 1.4 1.0 0.7 0.5 0.3 0.2 0.1 
Actinium-227 1.8 1.3 1.1 1.0 1.0 1.1 1.2 1.1 1.1 
Thorium-229 1.9 1.2 1.1 1.0 1.0 1.1 1.1 0.9 0.8 
Thorium-230 1.9 1.2 1.1 1.0 1.0 1.1 1.1 0.9 0.8 
Thorium-232 1.9 1.2 1.1 1.0 1.0 1.1 1.1 0.9 0.8 
Protactinium-231 1.9 1.2 1.1 1.0 1.0 1.1 1.1 0.9 0.8 
Uranium-232 2.4 2.0 1.4 1.0 0.7 0.4 0.2 0.1 0.0 
Uranium-233 2.4 2.0 1.4 1.0 0.7 0.4 0.2 0.1 0.0 
Uranium-234 2.4 2.0 1.4 1.0 0.7 0.4 0.2 0.1 0.0 
Uranium-236 2.4 2.0 1.4 1.0 0.7 0.4 0.2 0.1 0.0 
Uranium-238 2.4 2.0 1.4 1.0 0.7 0.4 0.2 0.1 0.0 
Neptunium-237 1.9 1.2 1.1 1.0 1.0 1.1 1.2 1.0 0.9 
Plutonium-238 1.9 1.2 1.1 1.0 1.0 1.1 1.1 0.9 0.8 
Plutonium-239 1.9 1.2 1.1 1.0 1.0 1.1 1.1 0.9 0.8 
Plutonium-240 1.9 1.2 1.1 1.0 1.0 1.1 1.1 0.9 0.8 
Plutonium-242 1.9 1.2 1.1 1.0 1.0 1.1 1.1 0.9 0.8 
Americium-241 1.9 1.2 1.1 1.0 1.0 1.1 1.1 0.9 0.8 
Americium-243 1.9 1.2 1.1 1.0 1.0 1.1 1.1 0.9 0.8 
a 
Calculated in Excel file Inhalation of large particles.xls, explained in Appendix B, from Equations 6.5-1 to 6.5-3 
using values from ICRP 1978 (DIRS 101076), pp. 84-85, 192-193, 231-232, 236-237, 289-290, 318, 322-323, 
333-334, 356-357, 362, 364-365, 371, 378, 410-411, 414-415, 418-419, 424-425, 456, 466-467; ICRP 1981 
(DIRS 153056), pp. 19, 195, 660-661, 739; ICRP 1982 (DIRS 153057), pp. 790, 827; ICRP 1982 (DIRS 163147), 
pp. 158-159. 

Source: Based on the values shown in Table 6-27. 
Figure 6-13. The Ratio of Inhalation Dose Conversion Factors for Particulates of a Given AMAD to 
that of 1-m Particulates 
To determine the expected range of the inhalation DCF ratios, a comparison was made for 
primary radionuclides except 14C, which is inhaled as a gas (CO2). The decay products of the 
primary radionuclides were not included in this analysis because the majority of them are either 
isotopes of the elements already represented by the primary radionuclides (the DCF ratios for 
isotopes of the same element are the same, as shown in Table 6-27) or they are sufficiently 
short-lived such that their contribution is already accounted for in the DCF of the parent 
(DCF include contributions from decay products that are generated within the body). 
The DCF ratios for 0.1-m to 100-m particles range from 0.0 to 2.4. The DCFs are generally 
higher for the smallest particles. The radionuclides, such as isotopes of uranium, whose DCFs 
are the highest for small particles also have the lowest DCFs for large particles because of the 
whole or a large proportion of the dose originating in the lungs (large particles are deposited in 
the naso-pharyngial region and do not reach the lungs). The AMAD for the soil-derived airborne 
particulates for the long-term averages is expected to be in the 2-6 m range. However, it is 
anticipated that the majority of the inhalation exposure to the RMEI will occur in the dusty 
environments associated with relatively large particles. Therefore, the AMADs larger than 1 m 
are more appropriate to represent particle size distribution in various environments addressed in 
the biosphere model. For such particles, the DCF ratios do not exceed 1.6. The contribution to 
the dose from inhalation of particulates is high for the heavy radionuclides, such as isotopes of 
neptunium, plutonium, and americium (BSC 2004 [DIRS 169674], Section 6.2.5; BSC 2004 
[DIRS 167287], Section 6.2.5). Isotopes of these elements are also the highest contributors to 

the all-radionuclide dose for the igneous disruption scenario (DOE 2001 [DIRS 153849], 
Figure 4-194). For these radionuclides and AMADs between 0.5 and 100 m the DCF ratio is 
close to 1 and ranges from 0.8 to 1.2.The DCF ratios needs to be put into perspective considering 
uncertainties associated with the DCF values. The DCF uncertainties are not customarily 
included in radiological assessments. For instance, the internal dosimetry methods 
recommended for a performance assessment by the NRC (2000 [DIRS 157704], Section 
3.3.7.3.1) are based on FGR No. 11 (Eckerman et al. 1988 [DIRS 101069]), which does not 
include consideration of uncertainty in the DCF values. However, the DCFs are subject to 
uncertainty. The estimated uncertainties in inhalation DCFs for selected radionuclides were 
tabulated by NCRP (NCRP 1999 [DIRS 155894], p. 83). For heavy radionuclides, such as 210Pb,
210Po, 226Ra, 230Th, 234U, 237Np, 239Pu, and 241Am, the estimated uncertainty range is quantified as 
5 for adult males and up to 10 for other population groups, while for 90Sr and 137Cs, the 
uncertainty range is estimated at 3 and 2, respectively, for adult males and 5 for other groups 
(NCRP 1999 [DIRS 155894], p. 83). The uncertainty range can be interpreted as indicating that 
the DCF for some individuals may be as much as a given factor higher or lower than the dose 
factor recommended by ICRP. It also needs to be noted that these uncertainty estimates apply to 
the new ICRP respiratory tract model, which is considered more realistic than the older, 
ICRP-30-based model. 
The new respiratory tract model was also used to analyze the appropriateness of the 1-m 
AMAD DCFs recommended by the ICRP as a default for indoor or outdoor exposure of the 
general public (ICRP 1996 [DIRS 152446], p. 5). This recommendation is considered 
appropriate for estimating doses to members of the public when particle size distributions are 
unknown (Dorrian 1997 [DIRS 159476], p. 130). However, when the exposure is known to have 
resulted from inhalation of resuspended radioactive aerosols, the AMAD of 5 m appears to be 
more realistic for estimating the doses (Dorrian 1997 [DIRS 159476], p. 117). 
As noted previously, the respiratory tract model of ICRP Publication 30 was intended for use 
with aerosol distributions with AMADs between 0.2 and 10 m. The new respiratory tract 
models developed by NCRP (1997 [DIRS 160260]) and ICRP (1994 [DIRS 153705]) extended 
the range of particle sizes from 0.001 to 100 m. For the exposure to airborne particulates under 
disturbed conditions, the majority of particulates are associated with large particles. For such 
particles (>20 m), the ICRP model recommends that the complete deposition in the 
naso-pharyngeal region be assumed (ICRP 1979 [DIRS 110386], p. 24). The NCRP model, on 
the other hand, predicts a reduced deposition for very large particles in the upper airways due to 
the lower inspirability of such particles (NCRP 1998 [DIRS 160160], p. 37). Inspirability (also 
called inhalability) is the probability that particles with a particular aerodynamic diameter are 
able to follow the air stream from outside air into the respiratory tract. 
Considering the above, it was concluded that the application of DCFs for particles with AMAD 
of 1 m will not underestimate the doses from inhalation of resuspended material and that such 
DCFs are adequate for use in the biosphere model. 

6.6 BUILDING SHIELDING FACTORS 
The shielding offered by the floors and walls of the house varies widely depending on the type of 
construction, height above ground, and other factors. Even for lightly constructed houses 
(i.e., buildings such as mobile homes with thin walls and floors), the exposure rate from the 
high-energy gamma emitters is reduced to about 0.4 of the outside value (NCRP 1999 
[DIRS 155894], p. 52). The degree of reduction of indoor exposure relative to outdoor exposure 
is described by the building shielding factor, which is defined as ratio of dose indoors to dose 
outdoors. Shielding factors range from 0.001 to 0.5 (with higher values associated with buildings 
of light construction), with a mean of 0.2 (NCRP 1999 [DIRS 155894], p. 53). The shielding 
factors recommended by the NCRP for the use in screening models were calculated for a 
receptor population consisting of persons living in the most lightly constructed housing. Such 
shielding factors are appropriate for the Amargosa Valley population because 375 of 
422 (88.9 percent) occupied housing units in the 2000 Census were mobile homes (Bureau of the 
Census 2002 [DIRS 159728], Tables H30 and H31). In addition, the 2000 Census data indicated 
that 91.3 percent of the total Amargosa Valley population (1043 of 1142 people) lived in mobile 
homes (Bureau of the Census 2002 [DIRS 159728], Table H33). 
Four different shielding factor values were chosen for different radionuclides depending on the 
relative penetrability of their emissions (energy and type of radiation emitted) as follows 
(NCRP 1999 [DIRS 155894], p. 52). Relative penetrability was determined by comparing the 
dose coefficients for different geometries of the source and evaluating their differences with 
assumed radionuclide concentration profile in the soil. For radionuclides with highly penetrating 
radiations (gamma emitters of energy > 100 keV) a shielding factor of 0.4 was chosen. For low 
energy gamma (energy less than 100 keV) or high-energy beta (average energy > 100 keV) 
emitters, a shielding factor equal to 0.3 was chosen. For pure beta emitters with average energy 
less than 100 keV, and very low energy gamma emitters with energy less than 50 keV, a 
shielding factor of 0.2 was chosen. For low-energy x-ray emitters (energy less than 30 keV), the 
chosen value of shielding factor is 0.1. 
The default value of the shielding factor used in the RESRAD code is 0.7 (Yu et al. 2001 
[DIRS 159465], p. A-8). RESRAD is the code designed to estimate radiation doses and risks 
from residual radioactive materials in environmental media, including soil (Yu et al. 2001 
[DIRS 159465]). This value implies that the indoor levels of external radiation are only 
30 percent lower than the outdoor levels. The RESRAD authors state that this value is likely to 
be conservative when applied to scenarios involving low to moderate energy gamma emitters or 
when applied to well-shielded buildings. The review of the values of shielding factor reported in 
NCRP (1999 [DIRS 155894], p. 53) indicates that the shielding factor values are lower than the 
value of 0.7 used in RESRAD. Therefore, the shielding factors recommended for the use in 
screening models are considered appropriate for the biosphere model for evaluation of indoor 
exposures at home and at work. The list of shielding factors for the primary radionuclides and 
their decay products is shown in Table 6-28. Shielding factor for 14C, 210Tl, 212Po, 213Po, 222Rn,
223At, and 228Ra were not given in NCRP (1999 [DIRS 155894]). The dose coefficients for 
212Po, 213Po, and 228Ra are equal to 0 (Eckerman and Ryman 1993 [DIRS 107684], Table III.7); 
therefore, a shielding factor of 0 was selected. For the remaining radionuclides, the chosen value 
for the shielding factor was based on the type and energy of the radionuclide emissions and the 
criteria described above. 

In the biosphere model, some primary radionuclides are considered together with their 
short-lived decay products (see Table 6-28). For such radionuclides, the highest shielding factor 
for a primary radionuclide and its decay products was selected to ensure that the risk of external 
exposure was not underestimated. 

Characteristics of the Receptor for the Biosphere Model 
ANL-MGR-MD-000005 REV 03 6-79 September 2004 
Table 6-28. Shielding Factors for Primary Radionuclides and Their Decay Products 
Primary Radionuclide 
Short-lived Decay 
Products Shielding Factor Primary Radionuclide Decay Products 
Shielding 
Factor 
Carbon-14 (14C) 0.2 a 
Chlorine-36 (36Cl) 0.4 
Selenium-79 (79Se) 0.1 
Strontium-90 (90Sr) 0.3 (0.4) b 
Yttrium-90 (90Y) 0.4 
Technetium-99 (99Tc) 0.2 
Tin-126 (126Sn) 0.4 (0.4) b 
Antimony-126m (126mSb) 0.4 
Antimony-126 (126Sb) 0.4 
Iodine-129 (129I) 0.1 
Cesium-135 (135Cs) 0.1 
Cesium-137 (137Cs) 0.3 (0.4) b 
Barium-137m (137mBa) 0.4 
Thorium Series ( 4 n ) Neptunium Series ( 4 n + 1 ) 
Plutonium-240 (240Pu) 0.1 Americium-241 (241Am) 0.2 
Uranium-236 (236U) 0.1 Neptunium-237 (237Np) 0.3 (0.4) b 
Thorium-232 (232Th) 0.2 Protactinium-233 (233Pa) 0.4 
Radium-228 (228Ra) 0.0 a (0.4) b Uranium-233 (233U) 0.4 
Actinium-228 (228Ac) 0.4 Thorium-229 (229Th) 0.4 (0.4) b 
Uranium-232 (232U) 0.3 Radium-225 (225Ra) 0.1 
Thorium-228 (228Th) 0.4 (0.4) b Actinium-225 (225Ac) 0.4 
Radium-224 (224Ra) 0.4 Francium-221 (221Fr) 0.4 
Radon-220 (220Rn) 0.4 Astatine-217 (217At) 0.4 
Polonium-216 (216Po) 0.4 Bismuth-213 (213Bi) 0.4 
Lead-212 (212Pb) 0.4 Polonium-213 (213Po) 0.0 a 
Bismuth-212 (212Bi) 0.4 Thallium-209 (209Tl) 0.4 
Polonium-212 (212Po) 0.0 a Lead-209 (209Pb) 0.3 
Thallium-208 (208Tl) 0.3 

Characteristics of the Receptor for the Biosphere Model 
ANL-MGR-MD-000005 REV 03 6-80 September 2004 
Table 6-28. Shielding Factors for Primary Radionuclides and Their Decay Products (Continued) 
Primary Radionuclide 
Short-lived Decay 
Products Shielding Factor Primary Radionuclide Decay Products 
Shielding 
Factor 
Uranium Series ( 4 n + 2 ) Actinium Series ( 4 n + 3 ) 
Plutonium-242 (242Pu) 0.1 Americium-243 (243Am) 0.3 (0.4) b 
Uranium-238 (238U) 0.1 (0.4) b Neptunium-239 (239Np) 0.4 
Thorium-234 (234Th) 0.3 Plutonium-239 (239Pu) 0.3 
Protactinium-234m (234mPa) 0.4 Uranium-235 (235U) 0.4 
Protactinium-234 (234Pa) 0.4 Thorium-231 (231Th) 0.3 
Plutonium-238 (238Pu) 0.1 Protactinium-231 (231Pa) 0.4 
Uranium-234 (234U) 0.2 Actinium-227 (227Ac) 0.4 (0.4) b 
Thorium-230 (230Th) 0.3 Thorium-227 (227Th) 0.4 
Radium-226 (226Ra) 0.4 (0.4) b Francium-223 (223Fr) 0.3 
Radon-222 (222Rn) 0.0 a Radium-223 (223Ra) 0.4 
Polonium-218 (218Po) 0.4 Radon-219 (219Rn) 0.4 
Lead-214 (214Pb) 0.4 Polonium-215 (215Po) 0.4 
Astatine-218 (218At) 0.1 Lead-211 (211Pb) 0.4 
Bismuth-214 (214Bi) 0.4 Bismuth-211 (211Bi) 0.4 
Polonium-214 (214Po) 0.4 Thallium-207 (207Tl) 0.4 
Thallium-210 (210Tl) 0.4 a Polonium-211 (211Po) 0.4 
Lead-210 (210Pb) 0.1 (0.4) b 
Bismuth-210 (210Bi) 0.4 
Polonium-210 (210Po) 0.4 
Source: NCRP 1999 (DIRS 155894), Appendix C. 
a 
Shielding factor for 14C, 210Tl, 212Po, 213Po, 222Rn, and 228Ra were not given in the NCRP report (NCRP 1999 [DIRS 155894]). The dose coefficients for 212Po,
213Po, and 228Ra are equal to 0 (Eckerman and Ryman 1993 [DIRS 107684], Table III.7), so the value of the shielding factor equal to 0 was selected. For the 
remaining radionuclides, the value of the shielding factor was determined based on the type and energy of the radionuclide emissions and the criteria described 
above as follows: 
14C  beta emitter, average energy less than100 keV (Lide and Frederikse 1997 [DIRS 103178], p. 11-42); shielding factor = 0.2; 
210Tl  beta/gamma emitter, gamma energy greater than 100 keV (Lide and Frederikse 1997 [DIRS 103178], p. 11-125); shielding factor = 0.4; 
222
Rn  alpha emitter, no penetrating radiation (Eckerman and Ryman 1993 [DIRS 107684], Table A.1); shielding factor = 0.0. 
b For the primary radionuclides considered in the biosphere model together with their short-lived decay products, only one value of shielding factor was assigned, 
the highest of the values for individual radionuclides. This value is given in parentheses next to the shielding factor for the primary radionuclide. 

7. CONCLUSIONS 
This section provides a summary of the values of parameters pertaining to the characteristics of 
the receptor for the biosphere model. These data, which constitute an output of this analysis, are 
included in the data set identified by DTN: MO0407SPACRBSM.002. 
A restriction for subsequent use of the conclusions of this analysis is that the values of receptor 
characteristics were developed specifically for use in the biosphere model and to comply with the 
requirements of 10 CFR 63, and therefore may not be appropriate for other applications. 
Uncertainties in the parameter values are addressed in Section 6. 
7.1 PARAMETER VALUES 
7.1.1 Lifestyle Characteristics of the Receptor 
7.1.1.1 Proportion of Population 
Uniform distributions with minimum and maximum values shown in Table 7-1 are to be used in 
biosphere model for proportion of non-workers, commuters, and local outdoor workers. Different 
distributions are to be used for the groundwater and volcanic ash exposure scenarios. The 
summary of the values is presented in Table 7-1. 
Table 7-1. Proportion of the Amargosa Valley Population in Occupation Categories 
Group Estimated Proportion 
Uniform Distribution 
Minimum Maximum 
Groundwater Exposure Scenario 
Non-Workers 39.2% 34.4% 44.0% 
Commuters 39.2% 33.9% 44.5% 
Local Outdoor Workers 5.5% 2.9% 8.1% 
Local Indoor Workersa 16.1% 
Volcanic Ash Exposure Scenario 
Non-Workers 39.2% 34.4% 44.0% 
Commuters 12.5% 4.9% 16.3% 
Local Outdoor Workers 5.5% 2.9% 10.7% 
Local Indoor Workersa 42.8% 
a 
Calculated in the biosphere model as 100 percent minus the sum of the other three percentages; therefore, a 
standard error and distribution are not presented. 
7.1.1.2 Exposure Times by Population Group and Environment 
Lognormal distributions of exposure times, with arithmetic means, standard deviations, and 
bounds summarized in Table 7-2, are to be used to calculate time spent away from contaminated 
environments, and in the active outdoor, inactive outdoor, and asleep indoor environments. 
Different distributions are to be used for the groundwater and volcanic ash exposure scenarios. 

Table 7-2. Daily Exposure Times for Amargosa Valley Population Groups 
Population Group/ 
Environment 
Groundwater Scenario (hours/day) Volcanic Ash Scenario (hours/day) 
AM SE Min Max AM SE Min Max 
Non-Workers 
Away 2.0 0.4 1.2 3.3 2.0 0.4 1.2 3.3 
Active Outdoors 0.3 0.1 0.1 0.7 0.3 0.1 0.1 0.7 
Inactive Outdoors 1.2 0.2 0.8 1.8 1.2 0.2 0.8 1.8 
Asleep Indoors 8.3 0.1 8.0 8.6 8.3 0.1 8.0 8.6 
Active Indoorsa 12.2 12.2 
Commuters 
Away 8.0 0.5 6.8 9.4 8.3 0.6 6.9 10.0 
Active Outdoors 0.3 0.1 0.1 0.7 0.3 0.1 0.1 0.7 
Inactive Outdoors 1.4 0.2 1.0 2.0 2.0 0.2 1.5 2.6 
Asleep Indoors 8.3 0.1 8.0 8.6 8.3 0.1 8.0 8.6 
Active Indoorsa 6.0 5.1 
Local Outdoor Workers 
Away 2.0 0.4 1.2 3.3 2.0 0.4 1.2 3.3 
Active Outdoors 3.1 0.2 2.6 3.7 3.1 0.2 2.6 3.7 
Inactive Outdoors 4.0 0.3 3.3 4.8 4.2 0.3 3.5 5.0 
Asleep Indoors 8.3 0.1 8.0 8.6 8.3 0.1 8.0 8.6 
Active Indoorsa 6.6 6.4 
Local Indoor Workers 
Away 2.0 0.4 1.2 3.3 2.0 0.4 1.2 3.3 
Active Outdoors 0.3 0.1 0.1 0.7 0.3 0.1 0.1 0.7 
Inactive Outdoors 1.3 0.2 0.9 1.9 1.5 0.2 1.1 2.1 
Asleep Indoors 8.3 0.1 8.0 8.6 8.3 0.1 8.0 8.6 
Active Indoorsa 12.1 11.9 
a 
Calculated in the biosphere model as 24 hours minus the sum of the other times; therefore, a standard error and 
distribution are not presented. 
AM = arithmetic mean; SE=standard error 
7.1.1.3 Breathing Rates 
The summary of the breathing rates is presented in Table 7-3. The breathing rates are to be 
represented by fixed values. 
Table 7-3. Breathing Rates by Population Group and Environment 
Population Group Active Outdoors Inactive Outdoors Asleep Indoors Active Indoors 
Commuters 
Local Outdoor Workers 
Local Indoor Workers 
Non-Workers 
1.57 m3/hr 1.08 m3/hr 0.39 m3/hr 1.08 m3/hr 
The breathing rates for the adult Amargosa Valley population for different activity levels are 
summarized in Table 7-4. 
ANL-MGR-MD-000005 REV 03 7-2 September 2004 

Table 7-4. Breathing Rates Per Level of Activity 
Population Group Sleep Sitting Light Exercise Heavy Exercise 
Adult, Amargosa Valley 0.39 m3/hr 0.47 m3/hr 1.38 m3/hr 2.86 m3/hr 
7.1.1.4 Evaporative Cooler Use 
The fraction of houses with evaporative coolers is to be represented by a binomial distribution 
with the probability of 0.738 and the batch size of 187. The resulting distribution is presented in 
units of households. Because the biosphere model uses the fraction of the houses with 
evaporative coolers rather than the number of houses, the sampled value must be divided by the 
batch size of 187. 
The evaporative cooler use factor for the current (i.e., present-day) climate is to be represented 
by a uniform distribution in the range from 0.32 to 0.46. For the glacial transition climate, the 
use factor is to be represented by a uniform distribution with a range of from 0.03 to 0.14. 
7.1.2 Dietary Characteristics of the Receptor 
7.1.2.1 Consumption Rate of Water 
Consumption of water is defined at 10 CFR 63.312 (DIRS 156605) where it is stated that the 
RMEI drinks 2 liters of water per day, which corresponds to 730.5 liters per year. 
7.1.2.2 Consumption Rate of Locally Produced Food 
Consumption rates of locally produced food are to be represented by lognormal distributions 
with the means and standard deviations shown in Table 7-5. 
Table 7-5. Annual Consumption Rates of Locally Produced Food by Biosphere Model Food Type 
Food Type 
Annual consumption rate (kg/yr) 
Distribution Mean Standard Error 
Leafy vegetables 3.78 0.88 Lognormal 
Other vegetables 4.73 0.67 Lognormal 
Fruit 12.68 1.36 Lognormal 
Grain 0.23 0.11 Lognormal 
Meat 2.85 0.65 Lognormal 
Poultry 0.42 0.13 Lognormal 
Milk 4.66 1.68 Lognormal 
Eggs 5.30 0.83 Lognormal 
Fish 0.23 0.10 Lognormal 
7.1.2.3 Inadvertent Soil Ingestion 
It is recommended that the inadvertent soil ingestion for the RMEI be represented by a 
piece-wise cumulative probability distribution with the following characteristics: (50 mg/d, 
0 percent), (100 mg/d, 50 percent), and (200 mg/d, 100 percent). 
ANL-MGR-MD-000005 REV 03 7-3 September 2004 

7.1.3 Dosimetric Parameters 
7.1.3.1 Radionuclide Half-Lives and Branching Fractions 
The half-lives and branching fractions for radionuclides included in the biosphere model are 
listed in Table 6-23. 
7.1.3.2 Dose Conversion Factors and Dose Coefficients 
DCFs for inhalation and ingestion for use in the biosphere model are shown in Table 6-24; dose 
coefficients for exposure to contaminated soil are shown in Table 6-25; and dose coefficients for 
air submersion and water immersion are shown in Table 6-26. These parameters are to be 
represented by fixed values. 
The DCF for inhalation of 222Rn decay products in equilibrium with radon gas is equal to 
1.33  10-8 Sv/Bq. 
7.1.3.3 Building Shielding Factors 
Building shielding factors for primary radionuclides recommended for use in the biosphere 
model are listed in Table 7-6. 
7.2 HOW THE APPLICABLE ACCEPTANCE CRITERIA ARE ADDRESSED 
The following information describes how this analysis addresses the acceptance criteria in the 
Yucca Mountain Review Plan (NRC 2003 [DIRS 163274], Section 2.2.1.3.14). Only those 
acceptance criteria that are applicable to this report (see Section 4.2) are discussed. 
This analysis report is one of ten reports (Figure 1-1) that support biosphere modeling and 
describe how the acceptance criteria have been addressed by the biosphere model. A 
consideration of all ten reports is required to understand how all applicable acceptance criteria 
are satisfied by the biosphere model. 

Table 7-6. Building Shielding Factors for Primary Radionuclides 
Primary Radionuclide Shielding Factor Primary Radionuclide Shielding Factor 
Carbon-14 (14C) 0.2 
Chlorine-36 (36Cl) 0.4 
Selenium-79 (79Se) 0.1 
Strontium-90 (90Sr) 0.4 
Technetium-99 (99Tc) 0.2 
Tin-126 (126Sn) 0.4 
Iodine-129 (129I) 0.1 
Cesium-135 (135Cs) 0.1 
Cesium-137 (137Cs) 0.4 
Thorium Series ( 4 n ) Neptunium Series ( 4 n + 1 ) 
Plutonium-240 (240Pu) 0.1 Americium-241 (241Am) 0.2 
Uranium-236 (236U) 0.1 Neptunium-237 (237Np) 0.4 
Thorium-232 (232Th) 0.2 Uranium-233 (233U) 0.4 
Radium-228 (228Ra) 0.4 Thorium-229 (229Th) 0.4 
Uranium-232 (232U) 0.3 
Thorium-228 (228Th) 0.4 
Uranium Series ( 4 n + 2 ) Actinium Series ( 4 n + 3 ) 
Plutonium-242 (242Pu) 0.1 Americium-243 (243Am) 0.4 
Uranium-238 (238U) 0.4 Plutonium-239 (239Pu) 0.3 
Plutonium-238 (238Pu) 0.1 Uranium-235 (235U) 0.4 
Uranium-234 (234U) 0.2 Protactinium-231 (231Pa) 0.4 
Thorium-230 (230Th) 0.3 Actinium-227 (227Ac) 0.4 
Radium-226 (226Ra) 0.4 
Lead-210 (210Pb) 0.4 
Acceptance Criterion 1 System Description and Model Integration are Adequate. 
 Subcriterion (3): This analysis considers information and assumptions about climate change 
that are developed or also considered in other TSPA modeling abstractions. The analysis of 
the effects of climate change on the evaporative cooler use factor is described in 
Section 6.3.4.2 and is based on the climate states modeled in other TSPA abstractions 
(BSC 2003 [DIRS 166296], p. 79). 
Acceptance Criterion 2 Data are Sufficient for Model Justification. 
 
Subcriterion (1): The justification for the parameter distributions developed in this report, 
and the consistency of those distributions with the definition of the RMEI in 10 CFR 63, are 
described in Section 6, with additional justification for assumptions in Section 5. The data 
identified in Sections 4.1 were used, interpreted, and appropriately synthesized into the 
parameter distributions as described in Section 6. 
 
Subcriterion (2): The sufficiency of data used to develop parameter distributions used in the 
modeling of features, events, and processes related to biosphere characteristics modeling is 

described in Sections 4.1 and 6. Demonstration that the parameter distributions are 
consistent with present knowledge of the conditions in the Yucca Mountain region is in 
Section 6. Sensitivity and uncertainty analyses is addressed in other biosphere modeling 
reports listed in Figure 1-1. 
Acceptance Criterion 3 Data Uncertainty is Characterized and Propagated Through the 
Model Abstraction 
 
Subcriterion (1): The technical defensibility of assumptions used in this analysis is included 
in Section 5. The technical defensibility of the probability distribution developed for each 
parameter is described in Section 6. The identification of uncertainties and variabilities, and 
how those uncertainties and variabilities were accounted for in the development of parameter 
bounds that do not under-represent risk, is also described in Section 6. The consistency of 
parameter distributions and assumptions with the definition of the RMEI in 10 CFR 63 is 
described throughout Section 6. 
 
Subcriterion (2): The technical defensibility of the technical bases for the parameter 
distributions, and their consistency with site characterization data, is described in Section 6. 
 
Subcriterion (3): No process-level models were used to determine parameter values in this 
analysis. The consistency of the parameter distributions with site characterization data, 
laboratory experiments, field measurements, and natural analog research is described in 
Section 6. 
 
Subcriterion (4): The bounding values of the parameter distributions developed in this 
analysis were selected to adequately represent uncertainty, as described in Section 6. No 
correlations among biosphere model input parameters are identified in this analysis. 

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TIC: 252656. 

Knoll, G.F. 1989. Radiation Detection and Measurement. 2nd Edition. New York, 161052 
New York: John Wiley & Sons. TIC: 233703. 
LaPlante, P.A. and Poor, K. 1997. Information and Analyses to Support Selection of 101079 
Critical Groups and Reference Biospheres for Yucca Mountain Exposure Scenarios. 
CNWRA 97-009. San Antonio, Texas: Center for Nuclear Waste Regulatory 
Analyses. ACC: MOL.20010721.0035. 
Lide, D.R. and Frederikse, H.P.R., eds. 1997. CRC Handbook of Chemistry and 103178 
Physics. 78th Edition. Boca Raton, Florida: CRC Press. TIC: 243741. 
Mage, D.T. 1985. Concepts of Human Exposure Assessment for Airborne 162465 
Particulate Matter. Environment International, 11, 407-412. New York, New York: 
Pergamon Press. TIC: 250582. 
NCDC (National Climatic Data Center) [n.d.]. Hourly United States Weather 161091 
Observations 1990-1995. Washington, D.C.: U.S. Department of Commerce, 
National Oceanic and Atmospheric Administration. TIC: 253573. 
NCRP (National Council on Radiation Protection and Measurements) 1997. 160260 
Deposition, Retention and Dosimetry of Inhaled Radioactive Substances. NCRP 
Report No. 125. Bethesda, Maryland: National Council on Radiation Protection and 
Measurements. TIC: 232976. 
NCRP 1998. Evaluating the Reliability of Biokinetic and Dosimetric Models and 160160 
Parameters Used to Assess Individual Doses for Risk Assessment Purposes. NCRP 
Commentary No. 15. Bethesda, Maryland: National Council on Radiation Protection 
and Measurements. TIC: 252922. 
NCRP 1999. Recommended Screening Limits for Contaminated Surface Soil and 155894 
Review of Factors Relevant to Site-Specific Studies. NCRP Report No. 129. 
Bethesda, Maryland: National Council on Radiation Protection and Measurements. 
TIC: 250396. 
Nevada Department of Minerals; Nevada Bureau of Mines and Geology; and Mackay 160176 
School of Mines. 1991. Major Mines of Nevada, 1990. Nevada Bureau of Mines and 
Geology Special Publication 11. Reno, Nevada: University of Nevada Reno, Mackay 
School of Mines. TIC: 222736. 
Nicholson, K.W. 1988. A Review of Particle Resuspension. Atmospheric 160116 
Environment, 22, (12), 2639-2651. New York, New York: Pergamon Press. 
TIC 252279. 
Nieuwenhuijsen, M.J.; Kruize, H.; and Schenker, M.B. 1998. Exposure to Dust and 150855 
Its Particle Size Distribution in California Agriculture. American Industrial Hygiene 
Association Journal, 59, 34-38. Fairfax, Virginia: American Industrial Hygiene 
Association. TIC: 248134. 

NRC (U.S. Nuclear Regulatory Commission) 2003. Use of the Effective Dose 163018 
Equivalent in Place of the Deep Dose Equivalent in Dose Assessments. RIS 2003-04. 
Washington, D.C.: U.S. Nuclear Regulatory Commission. TIC: 254200. 
NRC 2003. Yucca Mountain Review Plan, Final Report. NUREG-1804, Rev. 2. 163274 
Washington, D.C.: U.S. Nuclear Regulatory Commission, Office of Nuclear Material 
Safety and Safeguards. TIC: 254568. 
NRC 2000. A Performance Assessment Methodology for Low-Level Radioactive 157704 
Waste Disposal Facilities, Recommendations of NRCs Performance Assessment 
Working Group. NUREG-1573. Washington, D.C.: U.S. Nuclear Regulatory 
Commission. TIC: 252174. 
Pinnick, R.G.; Fernandez, G.; Hinds, B.D.; Bruce, C.W.; Schaefer, R.W.; and 159577 
Pendleton, J.D. 1985. Dust Generated by Vehicular Traffic on Unpaved Roadways: 
Sizes and Infrared Extinction Characteristics. Aerosol Science and Technology, 4, 
(1), 99-121. New York, New York: Elsevier. TIC: 252364. 
Pinnick, R.G.; Fernandez, G.; Martinez-Andazola, E.; Hinds, B.D.; Hansen, A.D.A.; 160312 
and Fuller, K. 1993. Aerosol in the Arid Southwestern United States: Measurements 
of Mass Loading, Volatility, Size Distribution, Absorption Characteristics, Black 
Carbon Content, and Vertical Structure to 7 km Above Sea Level. Journal of 
Geophysical Research, 98, (D2), 2651-2666. Washington, D.C.: American 
Geophysical Union. TIC: 252365. 
Rasmuson, K.E. 2004. Summary of 2004 Agricultural Activities, Businesses, and 169506 
Community Services and Organizations in Amargosa Valley. Interoffice 
memorandum from K.E. Rasmuson (BSC) to K.R. Rautenstrauch, May 20, 2004, 
0520041667, with enclosures. ACC: MOL.20040519.0033. 
Reamer, C.W. and Williams, D.R. 2000. Summary Highlights of NRC/DOE 154597 
Technical Exchange and Management Meeting on Igneous Activity. Meeting held 
August 29-31, 2000, Las Vegas, Nevada, with attachments. Washington, D.C.: U.S. 
Nuclear Regulatory Commission. ACC: MOL.20001101.0105 through 
MOL.20001101.0128. 
Rittmann, P.D. 1993. Verification Tests for the July 1993 Revision to the GENII 107744 
Radionuclide and Dose Increment Libraries. WHC-SD-WM-TI-596. Richland, 
Washington: Westinghouse Hanford Company. TIC: 233965. 
Roe, L.K. 2002. Summary of RDA Investigation ID: 4/10/02 Fish Farming in 160674 
Amargosa Valley. Interoffice memorandum from L.K. Roe (BSC) to File, November 
5, 2002, 1105024986, with an attachment. ACC: MOL.20021107.0091; 
MOL.20020821.0002. 

Shinn, J.H. 1992. Enhancement Factors for Resuspended Aerosol Radioactivity: 160115 
Effects of Topsoil Disturbance. Proceedings of the Fifth International Conference 
on Precipitation Scavenging and Atmosphere-Surface Exchange Processes, Richland, 
Washington, 15-19 July 1991. 1183-1193. Washington, D.C.: Hemisphere. 
TIC: 252292. 
Simon, S.L. 1998. Soil Ingestion by Humans: A Review of History, Data, and 160098 
Etiology with Application to Risk Assessment of Radioactively Contaminated Soil. 
Health Physics, 74, (6), 647-672. Baltimore, Maryland: Williams & Wilkins. 
TIC: 253001. 
Stanek, E.J., III.; Calabrese, E.J.; Barnes, R.; and Pekow, P. 1997. Soil Ingestion in 160251 
AdultsResults of a Second Pilot Study. Ecotoxicology and Environmental Safety,
36, (3), 249-257. San Diego, California: Academic Press. TIC: 252381. 
Stanek, E.J. III; and Calabrese, E.J. 2000. Daily Soil Ingestion Estimates for 168391 
Children at a Superfund Site. Risk Analysis, 20, (5), 627-635. Malden, 
Massachusetts: Blackwell Publishers. TIC: 252382. 
UNSCEAR (United Nations Scientific Committee on the Effects of Atomic Radiation) 158644 
2000. Sources and Effects of Ionizing Radiation, United Nations Scientific Committee 
on the Effects of Atomic Radiation, UNSCEAR 2000 Report to the General Assembly, 
with Scientific Annexes. Two volumes. New York, New York: United Nations. 
TIC: 249863. 
USDA (U.S. Department of Agriculture) 2000. Food and Nutrient Intakes by 154158 
Individuals in the United States, 1994-1996. Nationwide Food Surveys Report 
No. 96-3. Two volumes. Washington, D.C.: U.S. Department of Agriculture. 
TIC: 249498. 
Watt, J.R. and Brown, W.K. 1997. Evaporative Air Conditioning Handbook. 3rd 159497 
Edition. Lilburn, Georgia: Fairmont Press. TIC: 252688. 
YMP (Yucca Mountain Site Characterization Project) 1999. Yucca Mountain Site 158212 
Characterization Project: Summary of Socioeconomic Data Analyses Conducted in 
Support of the Radiological Monitoring Program, April 1998 to April 1999. 
North Las Vegas, Nevada: Yucca Mountain Site Characterization Office. 
ACC: MOL.19991021.0188. 
Yu, C.; Zielen, A.J.; Cheng, J.-J.; LePoire, D.J.; Gnanapragasam, E.; Kamboj, S.; 159465 
Arnish, J.; Wallo, A., III.; Williams, W.A.; and Peterson, H. 2001. User's Manual for 
RESRAD Version 6. ANL/EAD-4. Argonne, Illinois: Argonne National Laboratory. 
TIC: 252702. 

8.2 CODES, STANDARDS, REGULATIONS, AND PROCEDURES 
10 CFR 20. Energy: Standards for Protection Against Radiation. Readily available. 104787 
10 CFR 63. Energy: Disposal of High-Level Radioactive Wastes in a Geologic 156605 
Repository at Yucca Mountain, Nevada. Readily available. 
40 CFR 197. 2001. Protection of Environment: Public Health and Environmental 155238 
Radiation Protection Standards for Yucca Mountain, Nevada. Readily available 
66 FR 55732. Disposal of High-Level Radioactive Wastes in a Proposed Geologic 156671 
Repository at Yucca Mountain, NV. Final Rule 10 CFR Part 63. Readily available. 
AP-2.22Q, Rev. 1, ICN 1. Classification Analyses and Maintenance of the Q-List. 
Washington, D.C.: U.S. Department of Energy, Office of Civilian Radioactive Waste 
Management. ACC: DOC.20040714.0002. 
AP-2.27Q, Rev. 1, ICN 4. Planning for Science Activities. Washington, D.C.: U.S. 
Department of Energy, Office of Civilian Radioactive Waste Management. ACC: 
DOC.20040610.0006. 
AP-SIII.9Q, Rev. 1, ICN 6. Scientific Analyses. Washington, D.C.: U.S. Department 
of Energy, Office of Civilian Radioactive Waste Management. 
ACC: DOC.20040805.0003. 
8.3 SOURCE DATA, LISTED BY DATA TRACKING NUMBERS 
MO0010SPANYE00.001. Cleaned Nye County Food Consumption Frequency 154976 
Survey. Submittal date: 10/10/2000. 
MO04019SUM9397.000. Summary of 1993-1997 Site 9 Meteorological Data. 167054 
Submittal date: 01/20/2004. 
MO0407SEPFEPLA.000. LA FEP List. Submittal date: 07/20/2004. 170760 
8.4 OUTPUT DATA, LISTED BY DATA TRACKING NUMBER 
MO0407SPACRBSM.002. Characteristics of the Receptor for the Biosphere Model. 
Submittal date: 07/19/2004. 

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APPENDIX A 
CALCULATION OF CONSUMPTION RATES OF LOCALLY PRODUCED FOOD 

CALCULATION OF CONSUMPTION RATES OF 
LOCALLY PRODUCED FOOD 
This appendix explains the spreadsheet calculations of consumption rates of locally produced 
food. The calculations were done using the standard function of Microsoft Excel 97 SR-2. The 
calculation method is described in Section 6.4.2. The calculations are done in the Excel 
workbook named Consumption rates with uncertainties.xls. The file is listed in Appendix C. 
The workbook consists of four worksheets: Histograms, Consumption rates, Survey data, and 
Consumption rate formulas. 
The data in the Excel workbook was extracted from the data set MO0106SPANYE00.001, which 
contains all data from the 1997 regional survey (see Section 4.1.5). Data from 195 survey 
respondents having a telephone prefix of 372 were extracted for this analysis. This prefix 
covered the Amargosa Valley, Lathrop Wells, Ash Meadows, and Crystal areas (DOE 1997 
[DIRS 100332], p. 3). Only data from respondents living in this region were extracted, to meet 
the requirement of 10 CFR 63.312(b) that DOE use projections based on surveys of the people 
residing in the town of Amargosa Valley. Of the 195 responses, eight were eliminated from 
further analyses because the respondents were seasonal or part-time residents, had resided in 
Amargosa Valley for less than 1 year, or refused to answer questions about residency. Of the 
remaining 187 responses, two were from respondents who stated that they lived in Crystal, one 
was from someone who stated that she lived in Ash Meadows, and the remainder were from 
people who stated that they lived in Amargosa Valley (MO0106SPANYE00.001). 
In the worksheet Survey data, the effective number of days per year (EDPY) that an individual 
consumed locally produced food from a given food group is calculated separately for males and 
females, together with the standard deviation, count, and the standard error of the mean. These 
calculations are done for 187 individuals residing in the region for at least one year prior to the 
survey and for 12 food groups that were included in the survey. Equation 6.4-1 was used to 
calculate EDPY as follows: 
jiEDPY , = jiMPY , mo 
d 
12 
25.365 
jiDPW , jid 
Qwk 
,7 
1 
The values of MPY, DPW, and Q for individual food groups are taken from the results of the 
regional survey residing in the Cleaned Nye County Food Consumption Frequency Survey data 
set, DTN: MO0010SPANYE00.001 [DIRS 154976]. The individual responses are coded in the 
data set (and the same coding is maintained in the worksheet) as: 
Q3A2-A, Q3A3-A, Q3A4-A for leafy vegetables 
Q3B2-A, Q3B3-A, Q3B4-A for root (other) vegetables
Q3C2-A, Q3C3-A, Q3C4-A for grain 
Q3D2-A, Q3D3-A, Q3D4-A for fruit 
Q3E2-A, Q3E3-A, Q3E4-A for poultry 
Q3F2-A, Q3F3-A, Q3F4-A for beef 
Q3G2-A, Q3G3-A, Q3G4-A for pork 
Q3H2-A, Q3D3-A, Q3D4-A for game
Q3I2-A, Q3I3-A, Q3I4-A for fish 

Q3J2-A, Q3J3-A, Q3J4-A for milk 
Q3K2-A, Q3K3-A, Q3K4-A for eggs 
Q3M2-A, Q3M3-A, Q3M4-A for tomatoes 
For every food group and gender, the mean value of the EDPY is calculated using the 
AVERAGE function of Excel for the defined range of values for the EDPY. The standard 
deviation of the EDPY is calculated using STDEV function of Excel for the defined range of 
cells. The count corresponds to the number of valid numerical EDPY results (DK or Refuse 
and Invalid are not included) for a given food group and gender and is calculated using the 
COUNT Excel function. The standard error of the mean EDPY is calculated by dividing the 
standard deviation by the square root of the count. 
.... 
The mean, standard deviation, count, standard error of the mean are carried to the Consumption 
rates worksheet. The mean and the standard error are subsequently used to calculate the 
consumption rates, while the standard deviation and the count are only shown to provide the 
convenient summary of values. 
.... 
+ 
The spreadsheet content is as follows: 
.... 
Column Description 
A Identification of food groups used in the regional survey 
.... 
B Gender designation (the value of average daily intake, ADI, of a specific food is 
gender-specific) 
C Mean value of ADI by food group and gender from the USDA Survey of Food 
Intake (USDA 2000 [DIRS 154158]) 
D Standard error of the mean ADIs by food group and gender from the USDA Survey 
of Food Intake (USDA 2000 [DIRS 154158]) 
E Mean value of the fraction of people consuming, FPC, food from a given food group 
by food group and gender from the USDA Survey of Food Intake (USDA 2000 
[DIRS 154158]) 
F Standard error of the mean value of FPC food from a given food group by food 
group and gender from the USDA Survey of Food Intake (USDA 2000 
[DIRS 154158]) 
G not used 
H Mean value of the CADI by food group and gender calculated as the ratio of ADI 
(column C) and FPC (column E) 
I Standard error of the mean CADI calculated using the following formula (Eq. 6.4-6): 
2SEM ADIi 
2 SEM ADI FPCi
i
SEM 
CADIi FPCi (FPC )2 
i 
=

Column Description 
Where: SEMADI is taken from column D 
FPC is taken from column E 
ADI is taken from column C 
SEMFPC is taken form column F 
J not used 
K Mean value of EDPY for the given food group and gender, which is calculated from 
the survey data in the Survey data worksheet as described above. 
L Standard deviation of EDPY for the given food group and gender, which is 
calculated from the survey data in the Survey data worksheet as described above. 
M Number of valid EDPY cells (count) for the given food group and gender, which is 
calculated from the survey data in the Survey data worksheet as described above. 
N Standard error of the mean EDPY for the given food group and gender, which is 
calculated from the survey data in the Survey data worksheet as described above. 
O Percent of the Amargosa Valley population for males (PM) and females (PF) from 
the 2000 Census data (Bureau of the Census (2002 [DIRS 159728]) for age groups 
18 and over. 
P not used 
Q Mean consumption rate of locally produced food calculated using Equation 6.4-2: 
Ui = EDPY m i CADI m i PM + EDPY f i CADIf i PF
, , 
,, 
where: EDPYm and EDPYf are taken from column K 
CADIm and CADIf are taken from column H 
PM and PF are taken from column O 
R Partial results for calculation of standard error of the mean consumption rate of 
locally produced food (Equation 6.4-4), representing the male and female 
contribution to the standard error, i.e., the terms that appear in the parentheses before 
they are multiplied by (PM)2 and (PF)2 respectively. 
2 2 222
SEMUi 
2 = ((CADIm i )(SEM , ) +(EDPY m i )(SEM , ) )(PM )+ 
, EDPY m i 
, CADIm i 
2 2 222
((CADIf i )(SEM ) +(EDPY f i )(SEM , ) )(PF )
, CADIf i 
EDPY i , f 
, 
where: CADIm and CADIf are taken from column H 
EDPYm and EDPYf are taken from column K 
SEMCADI m and SEMCADI f are taken from column I 
SEMEDPY m and SEMEDPY f are taken from column N 
S In this column calculation of the standard error of the mean is completed by 
2
multiplying the values from column R for males and females by (PM)2 an (PF)
(column O), respectively, adding the results, taking the square root of the sum and 
dividing it by 1,000 to convert the value from grams to kilograms. 
T not used 

Column Description 
U Mean consumption rate of locally produced food for the biosphere model food types 
(the regional survey food groups were combines as explained in Section 6.4.2). The 
values are calculated by either copying the content of cells in column R, if no 
grouping is involved, or adding the values in column R if the biosphere model food 
types include more than one regional survey food group. 
Standard error of the mean consumption rate for the biosphere model food types. It 
is calculated by either copying the content of cells in column S, if no grouping is 
involved, or taking the square root of the squared values in column S if the biosphere 
model food types include more than one regional survey food group. 
W not used 

APPENDIX B 
CALCULATION OF INHALATION DOSE CONVERSION FACTOR RATIOS FOR 
DIFFERENT SIZE PARTICLES 

CALCULATION OF INHALATION DOSE CONVERSION FACTOR 
RATIOS FOR DIFFERENT SIZE PARTICLES 
This appendix explains the spreadsheet calculations of inhalation dose conversion factors (DCF) 
ratios for particles with the activity median aerodynamic diameter (AMAD) in the range from 
0.1 to 100 m. The calculations were done using standard function of Microsoft Excel 97 SR-2. 
The calculation method is described in Section 6.5.5.2. The calculations were done in the Excel 
workbook named Inhalation of large particles.xls. The file is in Appendix C. The workbook 
consists of 29 worksheets. The first 27 worksheets contain calculations of the inhalation DCF 
ratio for individual primary radionuclides of interest (except C-14, which is considered to be 
present in the atmosphere in gaseous form). The names of the worksheets are the same as the 
radionuclide symbols; for example, the worksheet named Cl-36 contains calculations of 
inhalation DCF ratios for 36Cl. The 28th worksheet, named Summary, contains the summary of 
the DCF ratios (presented in the main body of the report in Table 6-27 and their graphical 
representation (Figure 6-13 in the report).. 
The last worksheet, named Np-237(2), contains an example of formulas used to calculate 
inhalation DCF ratios. The DCF ratios are calculated as follows. 
First, the deposition probabilities for particles of 0.1, 0.2, 0.5, 1.0, 2, 5, 10 20, and 100 m in the 
three regions (naso-pharyngeal, tracheo-bronchial, and pulmonary, of respiratory tract are read 
from Figure 5.1 in ICRP Publication 30 (ICRP 1979 [DIRS 110386]). These probabilities, 
denoted as D(0.1), D(0.2), and so on, are listed in rows 5 through 7, and columns A through I. In 
rows 10 through 12, columns A through I, the ratios of deposition probabilities for particles with 
a given AMAD and particles with AMAD = 1 m are calculated. 
In the next step, for every organ listed for a given radionuclide, fractions of dose originating in 
the naso-pharyngeal, tracheo-bronchial, and pulmonary regions are read from the tables given in 
ICRP-30 (ICRP 1978 [DIRS 101076], pp. 84-85, 192-193, 231-232, 236-237, 289-290, 318, 
322-323, 333-334, 356-357, 362, 364-365, 371, 378, 410-411, 414-415, 418-419, 424-425, 456, 
466-467; ICRP 1981 [DIRS 153056], pp. 19, 195, 660-661, 739; ICRP 1982 [DIRS 153057], 
pp. 790, 827; ICRP 1982 [DIRS 163147], pp. 158-159). These values are listed in column E 
under the header with a letter f. For every organ, these values are multiplied by the appropriate 
deposition probability ratios in the three regions of respiratory tract and added up (e.g., column G 
for 0.1 m AMAD; column L for 0.2 m AMAD). The organ DCF for a given AMAD is 
calculated as the product of the DCF in that organ for 1 m (column C) and the sum calculated in 
the previous step (e.g., column H for 0.1 m AMAD; column M for 0.2 m AMAD). The organ 
DCFs are added to get the CEDE for a given AMAD and divided by the CEDE for 1 m AMAD 
(e.g., column I for 0.1 m AMAD; column N for 0.2 m AMAD). 

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APPENDIX C 
FILES SUPPORTING THE ANALYSIS AND CD-ROM 

FILES SUPPORTING THE ANALYSIS AND CD-ROM 
The following Excel files were used in this analysis and are provided on the attached CD-ROM. 
Figure C-1. List of Files Included on CD-ROM 

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