Biosphere Dose Conversion Factor Importance and Sensitivity Analysis REV 00, ICN 00

ANL-NBS-MD-000014 

October 2004

1. PURPOSE 
This report presents importance and sensitivity analysis for the environmental radiation model 
for Yucca Mountain, Nevada (ERMYN). ERMYN is a biosphere model supporting the total 
system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain 
repository. This analysis concerns the output of the model, biosphere dose conversion factors 
(BDCFs) for the groundwater, and the volcanic ash exposure scenarios. It identifies important 
processes and parameters that influence the BDCF values and distributions, enhances 
understanding of the relative importance of the physical and environmental processes on the 
outcome of the biosphere model, includes a detailed pathway analysis for key radionuclides, and 
evaluates the appropriateness of selected parameter values that are not site-specific or have large 
uncertainty. 
The documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the 
interrelationships among the products (i.e., analysis and model reports) developed for biosphere 
modeling. The Biosphere Model Report (BSC 2004 [DIRS 169460]) describes in detail the 
ERMYN conceptual model and mathematical model. The input parameter reports (BSC 2004 
[DIRS 169671]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 
[DIRS 169458]; and BSC 2004 [DIRS 169459]) contain detailed descriptions of the model input 
parameters and their development. Outputs from these six reports are used in the Nominal 
Performance Biosphere Dose Conversion Factor Analysis (BSC 2004 [DIRS 169674]) and 
Disruptive Event Biosphere Dose Conversion Factor Analysis (BSC 2004 [DIRS 167287]) to 
generate the BDCFs, which are input parameters for the TSPA model. This report analyzes the 
output of these two BDCF reports. The analysis was performed in accordance with the technical 
work plan (BSC 2004 [DIRS 169573]). 
The biosphere model considers features, events, and processes (FEPs) applicable to the Yucca 
Mountain biosphere (DTN: MO0407SEPFEPLA.000 [DIRS 170760]). Consideration of the LA 
FEP List (DTN: MO0407SEPFEPLA.000 [DIRS 170760]) constitutes a deviation from the 
Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]), 
which referred to an earlier revision of the FEPs list (DTN: MO0307SEPFEPS4.000 
[DIRS 164527]). In addition, the list of Yucca Mountain Review Plan acceptance criteria (NRC 
2003 [DIRS 163274]) applicable to this analysis differs from the list provided in the technical 
work plan (BSC 2004 [DIRS 169573]). 
The disposition of these FEPs in the TSPA is through the BDCFs, which are direct inputs to the 
TSPA model. Table 1-1 lists FEPs that are included in the biosphere model (BSC 2004 
[DIRS 169460], Table 6.2-1). Relationships among the biosphere-related FEPs, the biosphere 
conceptual model, and the exposure scenarios are examined in Section 6.3 of the Biosphere 
Model Report. The disposition of the included FEPs within the mathematical model and their 
relationship to the model equations and input parameters are presented in Table 6.7-1 of the 
Biosphere Model Report (BSC 2004 [DIRS 169460]). 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 1-2 October 2004 
Figure 1-1. Biosphere Model Documentation and Total System Performance Assessment Feeds 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
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Table 1-1. Biosphere-Related Features, Events, and Processes Included in TSPA 
FEP Name LA FEP Number 
Ashfall 1.2.04.07.0A 
Climate change 1.3.01.00.0A 
Water table rise affects SZ 1.3.07.02.0A 
Water management activities 1.4.07.01.0A 
Wells 1.4.07.02.0A 
Chemical characteristics of groundwater in the SZ 2.2.08.01.0A 
Soil type 2.3.02.01.0A 
Radionuclide accumulation in soils 2.3.02.02.0A 
Soil and sediment transport in the biosphere 2.3.02.03.0A 
Surface water transport and mixing 2.3.04.01.0A 
Precipitation 2.3.11.01.0A 
Biosphere characteristics 2.3.13.01.0A 
Radionuclide alteration during biosphere transport 2.3.13.02.0A 
Human characteristics (physiology, metabolism) 2.4.01.00.0A 
Human lifestyle 2.4.04.01.0A 
Dwellings 2.4.07.00.0A 
Wild and natural land and water use 2.4.08.00.0A 
Agricultural land use and irrigation 2.4.09.01.0B 
Animal farms and fisheries 2.4.09.02.0A 
Urban and industrial land and water use 2.4.10.00.0A 
Radioactive decay and ingrowth 3.1.01.01.0A 
Atmospheric transport of contaminants 3.2.10.00.0A 
Contaminated drinking water, foodstuffs and drugs 3.3.01.00.0A 
Plant uptake 3.3.02.01.0A 
Animal uptake 3.3.02.02.0A 
Fish uptake 3.3.02.03.0A 
Contaminated non-food products and exposure 3.3.03.01.0A 
Ingestion 3.3.04.01.0A 
Inhalation 3.3.04.02.0A 
External exposure 3.3.04.03.0A 
Radiation doses 3.3.05.01.0A 
Radon and radon daughter exposure 3.3.08.00.0A 
Source: DTN: MO0407SEPFEPLA.000 [DIRS 170760]. 
FEP=feature, event, and process, SZ = saturated zone 

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2. QUALITY ASSURANCE 
Development of this report involved analysis of data that are used in the TSPA-LA and in the 
safety analysis report, as identified in the technical work plan (BSC 2004 [DIRS 169573]). 
Thus, it was a quality affecting activity in accordance with AP-2.27Q, Planning for Science 
Activities. Approved quality assurance (QA) procedures identified in Section 4 of the technical 
work plan were used to conduct and document the activities described in this report. Electronic 
data were controlled in accordance with methods specified in Section 8 of the technical work 
plan. The governing procedure for the development of this analysis was AP-SIII.9Q, Scientific 
Analyses. 
The natural barriers and items identified in the Q-List (BSC 2004 [DIRS 168361]) are not 
pertinent to this analysis. Furthermore, a Safety Category per AP-2.22Q, Classification Analyses 
and Maintenance of the Q-List, is not applicable. 

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3. USE OF SOFTWARE 
This analysis was performed using the output of the verified and validated ERMYN model, 
which is described in the Biosphere Model Report (BSC 2004 [DIRS 169460]). The model files 
were obtained from the Model Warehouse (DTNs: MO0407MWDGSBMF.000 [DIRS 170852]; 
MO0407MWDGSMFV.000 [DIRS 170856]). The model is implemented using the GoldSim 
Graphical Simulation Environment, a graphical, object-oriented computer program for carrying 
out dynamic, probabilistic simulations (GoldSim Technology Group 2003 [DIRS 166226]). 
The analysis was conducted using a version of the software qualified under the Office of Civilian 
Radioactive Waste Management, Quality Assurance program for use on the Yucca Mountain 
Project: GoldSim Version 8.01 Service Pack (SP) 4 (GoldSim V8.01, STN: 10344-8.01SP4-00) 
(BSC 2004 [DIRS 169695]). The software was appropriate for the intended use, because it is the 
program used to execute the model and create the results examined in this report. The software 
was used within the range of validation in accordance with procedure LP-SI.11Q-BSC, Software 
Management. GoldSim was installed by Software Configuration Management on a DELL 
Precision Workstation 530 computer and run under the Windows 2000 operating system. 
In addition, the commercial off-the-shelf product Microsoft Excel 2000 (Version 9.0.3821 SR-1) 
was used for data reduction. Standard functions of Excel were used to calculate values presented 
in Section 6. The use of these functions, including formulas or algorithms, inputs and outputs is 
included in the Excel files generated in this analysis shown in Appendix A. These results do not 
depend on the software program used. 

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4. INPUTS 
4.1 DIRECT INPUTS 
This analysis used the results of the biosphere model runs documented in Nominal Performance 
Biosphere Dose Conversion Factor Analysis (BSC 2004 [DIRS 169674]) and Disruptive Event 
Biosphere Dose Conversion Factor Analysis (BSC 2004 [DIRS 167287]) and included in the 
following two DTNs: 
MO0407MWDGSBMF.000 [DIRS 170852] GoldSim Biosphere Model Files for Calculating 
Biosphere Dose Conversion Factors for Groundwater Exposure Scenario 
MO0407MWDGSMFV.000 [DIRS 170856] GoldSim Biosphere Model Files for Calculating 
Biosphere Dose Conversion Factors for Volcanic Ash Exposure Scenario. 
From DTN: MO0407MWDGSBMF.000 [DIRS 170852], the GoldSim files for the groundwater 
exposure scenario for the present-day climate (ERMYN_GW_MC8_<radionuclide symbol>.gsm) 
and the future climate (ERMYN_GW_FC8_<radionuclide symbol>.gsm) were used. 
From DTN: MO0407MWDGSMFV.000 [DIRS 170856], the GoldSim files for the volcanic ash 
exposure scenario for the present-day climate (ERMYN_VA_MC8_<radionuclide symbol>.gsm) 
were used. 
In addition, deterministic analyses were performed by varying single parameters in the biosphere 
model. The deterministic parameters were usually included in the model input data files 
(DTNs: MO0403SPAAEIBM.002 [DIRS 169392]; MO0407SPAINEXI.002 [DIRS 170597]; 
MO0407SPASRPBM.002 [DIRS 170755]; MO0406SPAETPBM.002 [DIRS 170150]; 
MO0407SPACRBSM.002 [DIRS 170677]) as the mean (arithmetic or geometric) or median 
values of the distributions or were calculated as the mean value if a representative deterministic 
value could not be directly inferred from the distributions given. The input data for the 
deterministic analyses and their DTNs are listed in Tables 4.1-1 to 4.1-4. 
In addition, the consumption rates of locally produced food for an average member of the critical 
group (CRWMS M&O 2001 [DIRS 153342], Table 11) were used in Section 6.2.5.1 to 
determine the impact of change in the consumption rate on the BDCF values. These 
consumption rates are the product output of a superseded report. However, they were 
appropriately developed for the receptor previously used in the biosphere model. Because the 
aim of the comparison carried out in this report is to evaluate how the change in the consumption 
rates for the two receptorsa hypothetical person called the reasonably maximally exposed 
individual (RMEI) and an average member of the critical grouppropagates onto the model 
results, these data are suitable and considered qualified for the intended use. 
This analysis concerns the input parameters and the outputs of the biosphere model. The files 
listed in this section contain the input parameters and the modeling results for the biosphere 
model and are, therefore, appropriate for use in this analysis. 

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Table 4.1-1. Summary of Input Parameter Values Used in Deterministic Model Runs 
Parameter Name and Unit Value DTN/Reference 
S U R F A C E S O I L S U B M O D E L 
Concentration of a radionuclide in well water, Bq/m3 1 Source for groundwater scenario 
Radionuclide concentration in ash, Bq/m2 1 Source for volcanic ash scenario 
Annual average irrigation rate, present-day climate, m/yr 0.95 MO0403SPAAEIBM.002 [DIRS 169392] 
Radionuclide half-life and branching fraction Table 4.1-2 MO0407SPACRBSM.002 [DIRS 170677] 
Soil bulk density, kg/m3 1500 MO0407SPASRPBM.002 [DIRS 170755] 
Ash settled density, kg/m3 1000 MO0407SPASRPBM.002 [DIRS 170755] 
Surface soil depth (tillage depth), m 0.25 MO0403SPAAEIBM.002 [DIRS 169392] 
Surface soil erosion rate, kg/(m2 yr) 0.49 MO0407SPASRPBM.002 [DIRS 170755] 
Carbon 1.8E+01 
Chlorine 1.4E-01 
Selenium 1.5E+02 
Strontium 2.0E+01 
Technetium 1.4E-01 
Tin 4.5E+02 
Iodine 4.5E+00 
Cesium 4.4E+03 
Lead 1.6E+04 
Radium 3.6E+04 
Actinium 1.5E+03 
Thorium 3.0E+03 
Protactinium 1.8E+03 
Uranium 3.3E+01 
Neptunium 2.5E+01 
Plutonium 1.2E+03 
Soil solid/liquid partition 
coefficient, L/kg 
Americium 2.0E+03 
MO0407SPASRPBM.002 [DIRS 170755] 
Overwatering rate, m/yr Present-day climate 0.079 MO0403SPAAEIBM.002 [DIRS 169392] 
Volumetric water content 0.23 MO0407SPASRPBM.002 [DIRS 170755] 
A I R S U B M O D E L 
Mass loading for crops at nominal conditions, mg/m3 0.12 MO0407SPAINEXI.002 [DIRS 170597] 
Mass loading for crops at volcanic conditions, mg/m3 0.24 MO0407SPAINEXI.002 [DIRS 170597] 
Active outdoors 5.00 
Inactive outdoors 0.06 
Active indoors 0.10 
Mass loading for receptor 
environments at nominal 
conditions, mg/m3 
Asleep indoors 0.03 
MO0407SPAINEXI.002 [DIRS 170597] 
Active outdoors 2.50 
Inactive outdoors 0.06 
Active indoors 0.10 
Mass loading for ash for 
receptor environments, 
mg/m3 
Asleep indoors 0.03 
MO0407SPAINEXI.002 [DIRS 170597] 
Active outdoors 4.0 
Inactive outdoors 0.7 
Active indoors 0.7 
Enhancement factor at 
nominal conditions 
Asleep indoors 0.7 
MO0407SPASRPBM.002 [DIRS 170755] 
Active outdoors 4.4 
Inactive outdoors 0.7 
Active indoors 0.7 
Enhancement factor for 
volcanic scenario 
Asleep indoors 0.7 
MO0407SPASRPBM.002 [DIRS 170755] 

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Table 4.1-1. Summary of Input Parameter Values Used in Deterministic Model Runs (Continued) 
Parameter Name and Unit Value DTN/Reference 
Evaporative cooler water transfer fraction 0.5 
MO0406SPAETPBM.002 [DIRS 170150] 
(mean value) 
Evaporative cooler water use (evaporation) rate, 
L/hr 17 MO0406SPAETPBM.002 [DIRS 170150] 
Evaporative cooler air flow rate, m3/hr 8300 
MO0406SPAETPBM.002 [DIRS 170150] 
(median value) 
Radon release factor, (Bq/m3)/ (Bq/kg ) 0.25 MO0406SPAETPBM.002 [DIRS 170150] 
Average 1.0 
House ventilation rate, 1/hr 
Evaporative cooler on 
Mean 
(calculated by 
GoldSim from a 
distribution) 
MO0406SPAETPBM.002 [DIRS 170150] 
Fraction of radon from soil entering the house 
Mean 
(calculated by 
GoldSim from a 
distribution) 
MO0406SPAETPBM.002 [DIRS 170150] 
Ratio of Rn-222 concentration in air to flux density 
from soil, (Bq m-3)/ (Bq m-2 s-1) 300 MO0406SPAETPBM.002 [DIRS 170150] 
P L A N T S U B M O D E L 
Chlorine 6.4E+01 
Selenium 4.6E-02 
Strontium 1.7E+00 
Technetium 4.6E+01 
Tin 3.8E-02 
Iodine 2.6E-02 
Cesium 8.5E-02 
Lead 1.5E-02 
Radium 6.8E-02 
Actinium 4.3E-03 
Thorium 4.3E-03 
Protactinium 4.6E-03 
Uranium 1.1E-02 
Neptunium 5.9E-02 
Plutonium 2.9E-04 
Soil-to-plant transfer factor 
for leafy vegetables, 
(Bq/kgplant)/ (Bq/kgsoil) 
Americium 1.2E-03 
MO0406SPAETPBM.002 [DIRS 170150] 
Chlorine 6.4E+01 
Selenium 4.6E-02 
Strontium 7.9E-01 
Technetium 4.4E+00 
Tin 1.5E-02 
Iodine 3.2E-02 
Cesium 5.0E-02 
Lead 9.0E-03 
Radium 1.2E-02 
Actinium 1.1E-03 
Thorium 4.4E-04 
Soil-to-plant transfer factor 
for other vegetables, 
(Bq/kgplant)/ (Bq/kgsoil) 
Protactinium 1.1E-03 
MO0406SPAETPBM.002 [DIRS 170150] 

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Table 4.1-1. Summary of Input Parameter Values Used in Deterministic Model Runs (Continued) 
Parameter Name and Unit Value DTN/Reference 
Uranium 6.0E-03 
Neptunium 3.1E-02 
Plutonium 1.9E-04 
Soil-to-plant transfer factor 
for other vegetables, 
(Bq/kgplant)/ (Bq/kgsoil) 
Americium 4.0E-04 
MO0406SPAETPBM.002 [DIRS 170150] 
Chlorine 6.4E+01 
Selenium 4.6E-02 
Strontium 2.9E-01 
Technetium 4.3E+00 
Tin 1.5E-02 
Iodine 5.7E-02 
Cesium 5.6E-02 
Lead 1.2E-02 
Radium 7.3E-03 
Actinium 8.5E-04 
Thorium 2.9E-04 
Protactinium 1.1E-03 
Uranium 6.3E-03 
Neptunium 3.4E-02 
Plutonium 1.8E-04 
Soil-to-plant transfer factor 
for fruit, (Bq/kgplant)/ 
(Bq/kgsoil) 
Americium 5.4E-04 
MO0406SPAETPBM.002 [DIRS 170150] 
Chlorine 2.4E+01 
Selenium 2.9E-02 
Strontium 1.7E-01 
Technetium 1.6E+00 
Tin 9.2E-03 
Iodine 2.5E-02 
Cesium 2.0E-02 
Lead 5.5E-03 
Radium 3.1E-03 
Actinium 5.4E-04 
Thorium 1.7E-04 
Protactinium 9.5E-04 
Uranium 1.1E-03 
Neptunium 4.4E-03 
Plutonium 1.9E-05 
Soil-to-plant transfer factor 
for grain (Bq/kgplant)/ 
(Bq/kgsoil) 
Americium 7.5E-05 
MO0406SPAETPBM.002 [DIRS 170150] 
Chlorine 7.5E+01 
Selenium 1.5E-01 
Strontium 2.1E+00 
Technetium 2.7E+01 
Tin 1.6E-01 
Iodine 4.0E-02 
Cesium 1.3E-01 
Lead 1.8E-02 
Radium 8.2E-02 
Actinium 1.7E-02 
Thorium 1.0E-02 
Soil-to-plant transfer factor 
for forage crops, 
(Bq/kgplant)/ (Bq/kgsoil) 
Protactinium 1.9E-02 
MO0406SPAETPBM.002 [DIRS 170150] 

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Table 4.1-1. Summary of Input Parameter Values Used in Deterministic Model Runs (Continued) 
Parameter Name and Unit Value DTN/Reference 
Uranium 1.7E-02 
Neptunium 5.8E-02 
Plutonium 1.0E-03 
Soil-to-plant transfer factor 
for forage crops, 
(Bq/kgplant)/ (Bq/kgsoil) 
Americium 2.1E-03 
MO0406SPAETPBM.002 [DIRS 170150] 
Leafy vegetables 0.070 
Other vegetables 0.103 
Fruit 0.120 
Grain 0.903 
Dry-to-wet weight ratio, 
kgdry/kgwet 
Forage 0.220 
MO0403SPAAEIBM.002 [DIRS 169392] 
Leafy vegetables 1.0 
Other vegetables 0.1 
Fruit 0.1 
Grain 0.1 
Translocation factor 
Forage 1.0 
MO0406SPAETPBM.002 [DIRS 170150] 
Leafy vegetables 0.75 
Other vegetables 0.75 
Fruit 0.50 
Grain 0.90 
Fraction of overhead 
irrigation 
Forage 0.90 
MO0403SPAAEIBM.002 [DIRS 169392] 
Weathering half-life, d 14 MO0406SPAETPBM.002 [DIRS 170150] 
Leafy vegetables 75 
Other vegetables 80 
Fruit 160 
Grain 200 
Crop growing time, 
present-day climate, d 
Forage 75 
MO0403SPAAEIBM.002 [DIRS 169392] 
Leafy vegetables 3.30 
Other vegetables 4.13 
Fruit 2.75 
Grain 0.59 
Crop wet yield, kg/m2 
Forage 2.14 
MO0403SPAAEIBM.002 [DIRS 169392] 
Leafy vegetables 0.21 
Other vegetables 0.43 
Fruit 0.62 
Grain 1.13 
Crop dry biomass, kg/m2 
Forage 0.48 
MO0403SPAAEIBM.002 [DIRS 169392] 
Leafy vegetables 5.41 
Other vegetables 7.71 
Fruit 7.41 
Grain 4.64 
Daily average irrigation 
rate, present-day climate, 
mm/d 
Forage 6.55 
MO0403SPAAEIBM.002 [DIRS 169392] 
Leafy vegetables 14.7 
Other vegetables 26.0 
Fruit 33.9 
Grain 56.7 
Irrigation amount per 
application, present-day 
climate, mm 
Forage 57.8 
MO0403SPAAEIBM.002 [DIRS 169392] 

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Table 4.1-1. Summary of Input Parameter Values Used in Deterministic Model Runs (Continued) 
Parameter Name and Unit Value DTN/Reference 
Irrigation intensity, cm/hr 4.3 MO0403SPAAEIBM.002 [DIRS 169392] 
Dry deposition velocity, m/s 0.008 MO0406SPAETPBM.002 [DIRS 170150] 
A N I M A L S U B M O D E L 
Chlorine 4.6E-02 
Selenium 8.8E-02 
Strontium 1.4E-03 
Technetium 1.1E-03 
Tin 1.9E-02 
Iodine 1.0E-02 
Cesium 2.4E-02 
Lead 6.3E-04 
Radium 8.1E-04 
Actinium 7.9E-05 
Thorium 1.1E-04 
Protactinium 6.6E-05 
Uranium 4.8E-04 
Neptunium 3.4E-04 
Plutonium 1.3E-05 
Animal product transfer 
coefficients for meat, d/kg 
Americium 3.4E-05 
MO0406SPAETPBM.002 [DIRS 170150] 
Chlorine 1.8E-02 
Selenium 5.7E-03 
Strontium 1.7E-03 
Technetium 2.1E-03 
Tin 1.1E-03 
Iodine 9.1E-03 
Cesium 7.7E-03 
Lead 1.7E-04 
Radium 5.8E-04 
Actinium 7.6E-06 
Thorium 4.4E-06 
Protactinium 4.4E-06 
Uranium 4.9E-04 
Neptunium 6.3E-06 
Plutonium 2.3E-07 
Animal product transfer 
coefficients for milk, d/L 
Americium 1.6E-06 
MO0406SPAETPBM.002 [DIRS 170150] 
Chlorine 3.0E-02 
Selenium 5.1E+00 
Strontium 3.1E-02 
Technetium 6.3E-02 
Tin 3.5E-02 
Iodine 5.5E-02 
Cesium 2.6E+00 
Lead 2.5E-02 
Radium 1.7E-02 
Actinium 4.0E-03 
Thorium 5.9E-03 
Animal product transfer 
coefficients for poultry, d/kg 
Protactinium 3.0E-03 
MO0406SPAETPBM.002 [DIRS 170150] 

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Table 4.1-1. Summary of Input Parameter Values Used in Deterministic Model Runs (Continued) 
Parameter Name and Unit Value DTN/Reference 
Uranium 2.4E-01 
Neptunium 3.6E-03 
Plutonium 1.2E-03 
Animal product transfer 
coefficients for poultry, d/kg 
Americium 1.8E-03 
MO0406SPAETPBM.002 [DIRS 170150] 
Chlorine 4.4E-02 
Selenium 7.3E+00 
Strontium 2.7E-01 
Technetium 2.4E+00 
Tin 8.7E-02 
Iodine 2.6E+00 
Cesium 3.5E-01 
Lead 5.6E-02 
Radium 3.9E-04 
Actinium 2.9E-03 
Thorium 3.5E-03 
Protactinium 2.0E-03 
Uranium 6.3E-01 
Neptunium 3.4E-03 
Plutonium 1.7E-03 
Animal product transfer 
coefficients for eggs, d/kg 
Americium 4.9E-03 
MO0406SPAETPBM.002 [DIRS 170150] 
Beef cattle 
Mean 
(calculated by 
GoldSim from a 
distribution) 
Dairy cow 
Mean 
(calculated by 
GoldSim from a 
distribution) 
Poultry 
Mean 
(calculated by 
GoldSim from a 
distribution) 
Animal consumption rate of 
feed, kg/d 
Laying hen 
Mean 
(calculated by 
GoldSim from a 
distribution) 
MO0406SPAETPBM.002 [DIRS 170150] 
Beef cattle 60 
Dairy cow 
Mean 
(calculated by 
GoldSim from a 
distribution) 
Poultry 0.5 
Animal consumption rate of 
water, L/d 
Laying hen 0.5 
MO0406SPAETPBM.002 [DIRS 170150] 
Beef cattle 
Mean 
(calculated by 
GoldSim from a 
distribution) Animal consumption rate of 
soil, kg/d 
Dairy cow 
Mean 
(calculated by 
GoldSim from a 
distribution) 
MO0406SPAETPBM.002 [DIRS 170150] 

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Table 4.1-1. Summary of Input Parameter Values Used in Deterministic Model Runs (Continued) 
Parameter Name and Unit Value DTN/Reference 
Poultry 
Mean 
(calculated by 
GoldSim from a 
distribution) Animal consumption rate of 
soil, kg/d 
Laying hen 
Mean 
(calculated by 
GoldSim from a 
distribution) 
MO0406SPAETPBM.002 [DIRS 170150] 
F I S H S U B M O D E L 
Carbon 4.6E+03 
Chlorine 2.2E+02 
Selenium 2.3E+02 
Strontium 4.6E+01 
Technetium 2.0E+01 
Tin 2.5E+03 
Iodine 4.5E+01 
Cesium 3.5E+03 
Lead 2.9E+02 
Radium 6.7E+01 
Actinium 2.9E+01 
Thorium 1.1E+02 
Protactinium 1.2E+01 
Uranium 1.4E+01 
Neptunium 3.0E+01 
Plutonium 4.1E+01 
Bioaccumulation factor, 
L/kg 
Americium 5.2E+01 
MO0406SPAETPBM.002 [DIRS 170150] 
Carbon 1 
Water concentration 
modifying factor, presentday 
climate Other elements 
Mean 
(calculated by 
GoldSim from a 
distribution) 
MO0406SPAETPBM.002 [DIRS 170150] 
S P E C I A L C A R B O N  1 4 M O D E L 
C-14 emission rate, 1/yr 22 MO0406SPAETPBM.002 [DIRS 170150] 
Annual water demand, m3/yr 3,714,450 MO0406SPAETPBM.002 [DIRS 170150] 
Inhalation 
Mean 
(calculated by 
GoldSim from a 
distribution) Annual average wind 
speed, m/s 
Crops 
Mean 
(calculated by 
GoldSim from a 
distribution) 
MO0406SPAETPBM.002 [DIRS 170150] 
Inhalation 2 
C-14 mixing height, m 
Crops 1 
MO0406SPAETPBM.002 [DIRS 170150] 
Fraction of air-derived carbon in plants 0.98 MO0406SPAETPBM.002 [DIRS 170150] 
Fraction of soil-derived carbon in plants 0.02 MO0406SPAETPBM.002 [DIRS 170150] 
Leafy vegetables 0.09 
Other vegetables 0.09 Fraction of stable carbon in 
plants 
Fruit 0.09 
MO0406SPAETPBM.002 [DIRS 170150] 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 4-9 October 2004 
Table 4.1-1. Summary of Input Parameter Values Used in Deterministic Model Runs (Continued) 
Parameter Name and Unit Value DTN/Reference 
Grain 0.40 Fraction of stable carbon 
in plants Forage 0.09 MO0406SPAETPBM.002 [DIRS 170150] 
Fraction of stable carbon in soil 0.03 MO0406SPAETPBM.002 [DIRS 170150] 
Concentration of stable carbon in air 1.8E-04 MO0406SPAETPBM.002 [DIRS 170150] 
Concentration of stable carbon in water 2.0E-05 MO0406SPAETPBM.002 [DIRS 170150] 
Meat 0.24 
Milk 0.07 
Poultry 0.2 
Fraction of stable carbon 
in animal products 
Eggs 0.15 
MO0406SPAETPBM.002 [DIRS 170150] 
E X T E R N A L E X P O S U R E S U B M O D E L 
Outdoor workers 0.055 
Indoor workers GoldSim Calc. 
Commuters 0.392 
Population proportion, 
groundwater exposure 
scenario, % 
Non-workers 0.392 
Outdoor workers 0.055 
Indoor workers GoldSim Calc. 
Commuters 0.125 
Population proportion, 
volcanic ash exposure 
scenario, % 
Non-workers 0.392 
MO0407SPACRBSM.002 [DIRS 170677] 
Active outdoors 3.1 
Inactive outdoors 4.0 
Active indoors 6.6 
Asleep indoors 8.3 
Time spent by outdoor 
workers, groundwater 
exposure scenario, hr/d 
Away 2.0 
Active outdoors 3.1 
Inactive outdoors 4.2 
Active indoors 6.4 
Asleep indoors 8.3 
Time spent by outdoor 
workers, volcanic ash 
exposure scenario, hr/d 
Away 2.0 
Active outdoors 0.3 
Inactive outdoors 1.3 
Active indoors 12.1 
Asleep indoors 8.3 
Time spent by indoor 
workers, groundwater 
exposure scenario, hr/d 
Away 2.0 
Active outdoors 0.3 
Inactive outdoors 1.5 
Active indoors 11.9 
Asleep indoors 8.3 
Time spent by indoor 
workers, volcanic ash 
exposure scenario, hr/d 
Away 2.0 
Active outdoors 0.3 
Inactive outdoors 1.4 
Active indoors 6.0 
Asleep indoors 8.3 
Time spent by commuters, 
groundwater exposure 
scenario, hr/d 
Away 8.0 
Active outdoors 0.3 
Inactive outdoors 2.0 
Active indoors 5.1 
Asleep indoors 8.3 
Time spent by commuters, 
volcanic ash exposure 
scenario, hr/d 
Away 8.3 
MO0407SPACRBSM.002 [DIRS 170677] 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 4-10 October 2004 
Table 4.1-1. Summary of Input Parameter Values Used in Deterministic Model Runs (Continued) 
Parameter Name and Unit Value DTN/Reference 
Active outdoors 0.3 
Inactive outdoors 1.2 
Active indoors 12.2 
Asleep indoors 8.3 
Time spent by nonworkers, 
groundwater 
exposure scenario and 
volcanic exposure 
scenario, hr/d Away 2.0 
MO0407SPACRBSM.002 [DIRS 170677] 
Carbon-14 0.2 
Clorine-36 0.4 
Selenium-79 0.1 
Strontium-90 0.4 
Technetium-99 0.2 
Tin-126 0.4 
Iodine-129 0.1 
Cesium-135 0.1 
Cesium-137 0.4 
Plutonium-242 0.1 
Uranium-238 0.4 
Plutonium-238 0.1 
Uranium-234 0.2 
Thorium-230 0.3 
Radium-226 0.4 
Lead-210 0.4 
Plutonium-240 0.1 
Uranium-236 0.1 
Thorium-232 0.2 
Radium-228 0.4 
Uranium-232 0.3 
Thorium-228 0.4 
Americium-243 0.4 
Plutonium-239 0.3 
Uranium-235 0.4 
Protactinium-231 0.4 
Actinium-227 0.4 
Americium-241 0.2 
Neptinium-237 0.4 
Uranium-233 0.4 
Building shielding factor, 
continued 
Thorium-229 0.4 
MO0407SPACRBSM.002 [DIRS 170677] 
Dose coefficient for exposure to contaminated soil 
(infinite depth), (Sv/yr)/ (Bq/m3) See Table 4.1-4 MO0407SPACRBSM.002 [DIRS 170677] 
Dose coefficient for exposure to contaminated soil 
surface, (Sv/yr)/ (Bq/m2) See Table 4.1-4 MO0407SPACRBSM.002 [DIRS 170677] 
I N H A L A T I O N S U B M O D E L 
Active outdoors 1.57 
Inactive outdoors 1.08 
Active indoors 1.08 
Asleep indoors 0.39 
Breathing rate, m3/hr 
Away 1.08 
MO0407SPACRBSM.002 [DIRS 170677] 
Dose conversion factor for inhalation, Sv/Bq See Table 4.1-3 MO0407SPACRBSM.002 [DIRS 170677] 
Fraction of houses with evaporative coolers 0.738 MO0407SPACRBSM.002 [DIRS 170677] 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 4-11 October 2004 
Table 4.1-1. Summary of Input Parameter Values Used in Deterministic Model Runs (Continued) 
Parameter Name and Unit Value DTN/Reference 
Evaporative cooler use factor, present-day climate 
Mean 
(calculated in 
GoldSim) 
MO0407SPACRBSM.002 [DIRS 170677] 
Outdoors 0.6 Equilibrium factor for 
Radon-222 decay products Indoors 0.4 
MO0406SPAETPBM.002 [DIRS 170150] 
Dose coefficient for Radon-222 decay products, 
Sv/Bq 1.33E-8 MO0407SPACRBSM.002 [DIRS 170677] 
I N G E S T I O N S U B M O D E L 
Consumption rate of water, L/d 2.0 MO0407SPACRBSM.002 [DIRS 170677] 
Leafy vegetables 3.78 
Other vegetables 4.73 
Fruit 12.68 
Grain 0.23 
Meat 2.85 
Milk 4.66 
Poultry 0.42 
Eggs 5.30 
Consumption rate of locally 
produced food, kg/yr 
Fish 0.23 
MO0407SPACRBSM.002 [DIRS 170677] 
Inadvertent soil ingestion rate, mg/d 100 MO0407SPACRBSM.002 [DIRS 170677] 
Dose conversion factor for ingestion, Sv/Bq See Table 4.1-3 MO0407SPACRBSM.002 [DIRS 170677] 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 4-12 October 2004 
Table 4.1-2. Primary Radionuclides and Their Decay Products Included in the Biosphere Model 
Primary Radionuclide 
Short-lived Decay 
Product Branching Fraction, % Half-life 
Carbon-14 100 5.730E+3 yr 
Chlorine-36 100 3.01E+05 yr 
Selenium-79 100 6.50E+04 yr 
Strontium-90 100 2.912E+01 yr 
Yttrium-90 100 6.40E+01 hr 
Technetium-99 100 2.13E+05 yr 
Tin-126 100 1.0E+05 yr 
Antimony-126m 100 1.90E+01 min 
Antimony-126 14 1.24E+01 d 
Iodine-129 100 1.57E+07 yr 
Cesium-135 100 2.3E+06 yr 
Cesium-137 100 3.00E+01 yr 
Barium-137m 94.60 2.552E+00 min 
T h o r i u m S e r i e s ( 4n ) 
Plutonium-240 100 6.537E+03 yr 
Uranium-236 100 2.3415E+07 yr 
Thorium-232 100 1.405E+10 yr 
Radium-228 100 5.75E+00 yr 
Actinium-228 100 6.13E+00 hr 
Uranium-232 100 7.2E+01 yr 
Thorium-228 100 1.9131E+00 yr 
Radium-224 100 3.66E+00 d 
Radon-220 100 5.56E+01 s 
Polonium-216 100 1.5 E-01 s 
Lead-212 100 1.064E+01 hr 
Bismuth-212 100 6.055 E+01 min 
Polonium-212 64.07 3.05 E-07 s 
Thallium-208 35.93 3.07E+00 min 
N e p t u n i u m S e r i e s ( 4n + 1 ) 
Americium-241 100 4.322E+02 yr 
Neptunium-237 100 2.14E+06 yr 
Protactinium-233 100 2.70 E+01 d 
Uranium-233 100 1.585E+05 yr 
Thorium-229 100 7.340E+03 yr 
Radium-225 100 1.48E+01 d 
Actinium-225 100 1.00E+01 d 
Francium-221 100 4.8E+00 min 
Astatine-217 100 3.23E-02 s 
Bismuth-213 100 4.565E+01 min 
Polonium-213 97.84 4.2E-06 s 
Thallium-209 2.16 2.20 E+00 min 
Lead-209 100 3.253E+00 hr 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 4-13 October 2004 
Table 4.1-2. Primary Radionuclides and Their Decay Products Included in the Biosphere Model 
(Continued) 
Primary Radionuclide 
Short-lived Decay 
Product Branching Fraction, % Half-life 
U r a n i u m S e r i e s ( 4n + 2 ) 
Plutonium-242 100 3.763E+05 yr 
Uranium-238 100 4.468E+09 yr 
Thorium-234 100 2.410E+01 d 
Protactinium-234m 99.80 1.17E+00 min 
Protactinium-234 0.33 6.70E+00 hr 
Plutonium-238 100 8.774E+01 yr 
Uranium-234 100 2.445E+05 yr 
Thorium-230 100 7.7E+04 yr 
Radium-226 100 1.600E+03 yr 
Radon-222 100 3.8235E+00 d 
Polonium-218 100 3.05E+00 min 
Lead-214 99.98 2.68 E+01 min 
Astatine-218 0.02 2.E+00 s 
Bismuth-214 100 1.99E+01 min 
Polonium-214 99.98 1.643E-04 s 
Thallium-210 0.02 1.3E+00 min b 
Lead-210 100 2.23 E+01 yr 
Bismuth-210 100 5.012E+00 d 
Polonium-210 100 1.3838 E+02 d 
A c t i n i u m S e r i e s ( 4n + 3 ) 
Americium-243 100 7.380E+03 yr 
Neptunium-239 100 2.355E+00 d 
Plutonium-239 100 2.4065E+04 yr 
Uranium-235 100 7.038E+08 yr 
Thorium-231 100 2.552E+01 hr 
Protactinium-231 100 3.276E+04 yr 
Actinium-227 100 2.1773E+01 yr 
Thorium-227 98.62 1.8718E+01 d 
Francium-223 1.38 2.18E+01 min 
Radium-223 100 1.1434E+01 d 
Radon-219 100 3.96 E+00 s 
Polonium-215 100 1.78 E-03 s 
Lead-211 100 3.61 E+01 min 
Bismuth-211 100 2.14 E+00 min 
Thallium-207 99.72 4.77 E+00 min 
Polonium-211 0.28 5.16E-01 s 
Source: DTN: MO0407SPACRBSM.002 [DIRS 170677]. 
NOTE: Short-lived decay products of primary radionuclides are assumed to be in secular equilibrium with their 
parent. 
. 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 4-14 October 2004 
Table 4.1-3. Dose Conversion Factors for Inhalation and Ingestion of Radionuclides of Interest 
Dose Conversion Factors (Sv/Bq) 
Primary Radionuclide 
Short-lived Decay 
Product Inhalation Ingestion 
Carbon-14 (as CO2) 6.36E-12 5.64E-10 
Chlorine-36 5.93E-09 8.18E-10 
Selenium-79 2.66E-09 2.35E-09 
Strontium-90 6.47E-08 3.85E-08 
Yttrium-90 2.28E-09 2.91E-09 
Technetium-99 2.25E-09 3.95E-10 
Tin-126 2.69E-08 5.27E-09 
Antimony-126m 9.17E-12 2.54E-11 
Antimony-126 3.17E-09 2.89E-09 
Iodine-129 4.69E-08 7.46E-08 
Cesium-135 1.23E-09 1.91E-09 
Cesium-137 8.63E-09 1.35E-08 
Barium-137m   
T h o r i u m S e r i e s ( 4n ) 
Plutonium-240 1.16E-04 9.56E-07 
Uranium-236 3.39E-05 7.26E-08 
Thorium-232 4.43E-04 7.38E-07 
Radium-228 1.29E-06 3.88E-07 
Actinium-228 8.33E-08 5.85E-10 
Uranium-232 1.78E-04 3.54E-07 
Thorium-228 9.23E-05 1.07E-07 
Radium-224 8.53E-07 9.89E-08 
Radon-220   
Polonium-216   
Lead-212 4.56E-08 1.23E-08 
Bismuth-212 5.83E-09 2.87E-10 
Polonium-212   
Thallium-208   
N e p t u n i u m S e r i e s ( 4n + 1 ) 
Americium-241 1.20E-04 9.84E-07 
Neptunium-237 1.46E-04 1.20E-06 
Protactinium-233 2.58E-09 9.81E-10 
Uranium-233 3.66E-05 7.81E-08 
Thorium-229 5.80E-04 9.54E-07 
Radium-225 2.10E-06 1.04E-07 
Actinium-225 2.92E-06 3.00E-08 
Francium-221   
Astatine-217   
Bismuth-213 4.63E-09 1.95E-10 
Polonium-213   
Thallium-209   
Lead-209 2.56E-11 5.75E-11 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 4-15 October 2004 
Table 4.1-3. Dose Conversion Factors for Inhalation and Ingestion of Radionuclides of Interest 
(Continued) 
Dose Conversion Factors (Sv/Bq) 
Primary Radionuclide 
Short-lived Decay 
Product Inhalation Ingestion 
U r a n i u m S e r i e s ( 4n + 2 ) 
Plutonium-242 1.11E-04 9.08E-07 
Uranium-238 3.20E-05 6.88E-08 
Thorium-234 9.47E-09 3.69E-09 
Protactinium-234m   
Protactinium-234 2.20E-10 5.84E-10 
Plutonium-238 1.06E-04 8.65E-07 
Uranium-234 3.58E-05 7.66E-08 
Thorium-230 8.80E-05 1.48E-07 
Radium-226 2.32E-06 3.58E-07 
Radon-222   
Polonium-218   
Lead-214 2.11E-09 1.69E-10 
Astatine-218   
Bismuth-214 1.78E-09 7.64E-11 
Polonium-214   
Thallium-210   
Lead-210 3.67E-06 1.45E-06 
Bismuth-210 5.29E-08 1.73E-09 
Polonium-210 2.54E-06 5.14E-07 
A c t i n i u m S e r i e s ( 4n + 3 ) 
Americium-243 1.19E-04 9.79E-07 
Neptunium-239 6.78E-10 8.82E-10 
Plutonium-239 1.16E-04 9.56E-07 
Uranium-235 3.32E-05 7.19E-08 
Thorium-231 2.37E-10 3.65E-10 
Protactinium-231 3.47E-04 2.86E-06 
Actinium-227 1.81E-03 3.80E-06 
Thorium-227 4.37E-06 1.03E-08 
Francium-223 1.68E-09 2.33E-09 
Radium-223 2.12E-06 1.78E-07 
Radon-219   
Polonium-215   
Lead-211 2.35E-09 1.42E-10 
Bismuth-211   
Thallium-207   
Polonium-211   
Source: DTN: MO0407SPACRBSM.002 [DIRS 170677]. 
NOTES: 1 Sv = 100 rem 
1 Ci = 3.71010 Bq 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 4-16 October 2004 
Table 4.1-4. Dose Coefficients for Exposure to Contaminated Soil for Radionuclides of Interest 
Primary Radionuclide Short-lived Decay Product 
Dose Coefficient 
Infinite Depth 
Sv/s per Bq/m3 
Dose Coefficient 
Ground Surface 
Sv/s per Bq/m2 
Carbon-14 7.20E-23 1.61E-20 
Chlorine-36 1.28E-20 6.73E-19 
Selenium-79 9.96E-23 2.07E-20 
Strontium-90 3.77E-21 2.84E-19 
Yttrium-90 1.28E-19 5.32E-18 
Technetium-99 6.72E-22 7.80E-20 
Tin-126 7.89E-19 5.47E-17 
Antimony-126m 4.98E-17 1.52E-15 
Antimony-126 9.16E-17 2.78E-15 
Iodine-129 6.93E-20 2.58E-17 
Cesium-135 2.05E-22 3.33E-20 
Cesium-137 4.02E-21 2.85E-19 
Barium-137m 1.93E-17 5.86E-16 
T h o r i u m S e r i e s ( 4n ) 
Plutonium-240 7.85E-22 8.03E-19 
Uranium-236 1.15E-21 6.50E-19 
Thorium-232 2.79E-21 5.51E-19 
Radium-228 0.00E+00 0.00E+00 
Actinium-228 3.20E-17 9.28E-16 
Uranium-232 4.83E-21 1.01E-18 
Thorium-228 4.25E-20 2.35E-18 
Radium-224 2.74E-19 9.57E-18 
Radon-220 1.23E-20 3.81E-19 
Polonium-216 5.58E-22 1.65E-20 
Lead-212 3.77E-18 1.43E-16 
Bismuth-212 6.27E-18 1.79E-16 
Polonium-212 0.00E+00 0.00E+00 
Thallium-208 1.23E-16 2.98E-15 
N e p t u n i u m S e r i e s ( 4n + 1 ) 
Americium-241 2.34E-19 2.75E-17 
Neptunium-237 4.17E-19 2.87E-17 
Protactinium-233 5.46E-18 1.95E-16 
Uranium-233 7.48E-21 7.16E-19 
Thorium-229 1.72E-18 8.54E-17 
Radium-225 5.90E-20 1.33E-17 
Actinium-225 3.41E-19 1.58E-17 
Francium-221 8.22E-19 2.98E-17 
Astatine-217 9.49E-21 3.03E-19 
Bismuth-213 4.10E-18 1.32E-16 
Polonium-213 0.00E+00 0.00E+00 
Thallium-209 6.92E-17 3.01E-19 
Lead-209 4.14E-21 1.90E-15 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 4-17 October 2004 
Table 4.1-4. Dose Coefficients for Exposure to Contaminated Soil for Radionuclides of Interest 
(Continued) 
Primary Radionuclide Short-lived Decay Product 
Dose Coefficient 
Infinite Depth 
Sv/s per Bq/m3 
Dose Coefficient 
Ground Surface 
Sv/s per Bq/m2 
U r a n i u m S e r i e s ( 4n + 2 ) 
Plutonium-242 6.85E-22 6.67E-19 
Uranium-238 5.52E-22 5.51E-19 
Thorium-234 1.29E-19 8.32E-18 
Protactinium-234m 4.80E-19 1.53E-17 
Protactinium-234 6.18E-17 1.84E-15 
Plutonium-238 8.10E-22 8.38E-19 
Uranium-234 2.15E-21 7.48E-19 
Thorium-230 6.47E-21 7.50E-19 
Radium-226 1.70E-19 6.44E-18 
Radon-222 1.26E-20 3.95E-19 
Polonium-218 3.02E-22 8.88E-21 
Lead-214 7.18E-18 2.44E-16 
Astatine-218 3.13E-20 4.18E-18 
Bismuth-214 5.25E-17 1.41E-15 
Polonium-214 2.75E-21 8.13E-20 
Thallium-210   
Lead-210 1.31E-20 2.48E-18 
Bismuth-210 1.93E-20 1.05E-18 
Polonium-210 2.80E-22 8.29E-21 
A c t i n i u m S e r i e s ( 4n + 3 ) 
Americium-243 7.60E-19 5.35E-17 
Neptunium-239 4.03E-18 1.63E-16 
Plutonium-239 1.58E-21 3.67E-19 
Uranium-235 3.86E-18 1.48E-16 
Thorium-231 1.95E-19 1.85E-17 
Protactinium-231 1.02E-18 4.07E-17 
Actinium-227 2.65E-21 1.57E-19 
Thorium-227 2.79E-18 1.04E-16 
Francium-223 1.06E-18 5.65E-17 
Radium-223 3.23E-18 1.28E-16 
Radon-219 1.65E-18 5.49E-17 
Polonium-215 5.44E-21 1.74E-19 
Lead-211 1.64E-18 5.08E-17 
Bismuth-211 1.37E-18 4.58E-17 
Thallium-207 1.06E-19 3.76E-18 
Polonium-211 2.55E-19 7.61E-18 
Source: DTN: MO0407SPACRBSM.002 [DIRS 170677]. 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 4-18 October 2004 
4.2 CRITERIA 
The general requirements to be satisfied by the TSPA are stated in 10 CFR 63.114 
[DIRS 156605]. Technical requirements to be satisfied by the TSPA are identified in the Yucca 
Mountain Project Requirements Document (Canori and Leitner 2003 [DIRS 166275]). The 
acceptance criteria that will be used by the U.S. Nuclear Regulatory Commission (NRC) to 
determine whether the technical requirements have been met are identified in the Yucca 
Mountain Review Plan, Final Report (YMRP) (NRC 2003 [DIRS 163274]). The pertinent 
requirements and criteria for this report are summarized in Table 4.2-1. 
Table 4.2-1. Applicable Project Requirements and Acceptance Criteria 
Requirement 
Numbera Requirement Titlea 10 CFR 63 Link 
YMRP Acceptance 
Criteriab 
PRD -002/T-015 Requirements for Performance Assessment 10 CFR 63.114 (a) to 
(c) and (e) to (g) 
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 
2.2.1.3.14 
Criteria 1 to 3 
PRD -002/T-014 Performance Objectives for the Geologic 
Repository After Permanent Closure 10 CFR 63.113 (b) 
PRD -002/T-015 Requirements for Performance Assessment 10 CFR 63.114 
PRD-002/T-028 Required Characteristics of the Reasonably 
Maximally Exposed Individual 10 CFR 63.312 
2.2.1.4.1 
Criterion 2 
a from Canori and Leitner 2003 [DIRS 166275], Table 2-3. 
b from NRC 2003 [DIRS 163274]. 
In addition to the requirements listed in Table 4.2-1, definition of terms in 10 CFR 63.2 and 
description of concepts in 10 CFR 63.102 [DIRS 156605] that are relevant to biosphere 
modeling are also applicable to this analysis. 
The acceptance criteria identified in Sections 2.2.1.3.13, 2.2.1.3.14, and 2.2.1.4.1 of the YMRP 
(NRC 2003 [DIRS 163274] are included below. In cases where subsidiary criteria are listed in 
the YMRP for a given criterion, only the subsidiary criteria addressed by this scientific analysis 
are listed below. Where a subcriterion includes several components, only some of those 
components may be addressed. How these components are addressed is summarized in 
Section 7.2 of this report. 
The acceptance criteria considered in this analysis report differ from those listed in the technical 
work plan (BSC 2004 [DIRS 169573]). Some additional acceptance criteria were addressed 
while other criteria were determined to not apply to this analysis. 
Acceptance Criteria from Section 2.2.1.3.13, Redistribution of Radionuclides in Soil 
Acceptance Criterion 1, System Description and Model Integration Are Adequate. 
(1) Total system performance assessment adequately incorporates important features, physical 
phenomena and couplings between different models, and uses consistent and appropriate 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 4-19 October 2004 
assumptions throughout the abstraction of redistribution of radionuclides in the soil abstraction 
process; 
(2) The total system performance assessment model abstraction identifies and describes aspects 
of redistribution of radionuclides in soil that are important to repository performance, including 
the technical bases for these descriptions. For example, the abstraction should include modeling 
of the deposition of contaminated material in the soil and determination of the depth distribution 
of the deposited radionuclides; 
(3) Relevant site features, events, and processes have been appropriately modeled in the 
abstraction of redistribution of radionuclides, from surface processes, and sufficient technical 
bases are provided. 
Acceptance Criterion 2, Data Are Sufficient for Model Justification. 
(1) Behavioral, hydrological, and geochemical values used in the license application are 
adequately justified (e.g., irrigation and precipitation rates, erosion rates, radionuclide solubility 
values, etc.). Adequate descriptions of how the data were used, interpreted, and appropriately 
synthesized into the parameters are provided; and 
(2) Sufficient data (e.g., field, laboratory, and natural analog data) are available to adequately 
define relevant parameters and conceptual models necessary for developing the abstraction of 
redistribution of radionuclides in soil in the total system performance assessment. 
Acceptance Criterion 3, Data Uncertainty Is Characterized and Propagated Through the 
Model Abstraction. 
(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 characteristics of the reasonably maximally exposed individual in 10 CFR Part 63; 
(2) The technical bases for the parameter values and ranges in the total system performance 
assessment abstraction are consistent with data from the Yucca Mountain region, e.g., Amargosa 
Valley survey, studies of surface processes in the Fortymile Wash drainage basin, applicable 
laboratory testings, natural analogs, or other valid sources of data. For example, soil types, crop 
types, plow depths, and irrigation rates should be consistent with current farming practices, and 
data on the airborne particulate concentration should be based on the resuspension of appropriate 
material in a climate and level of disturbance similar to that which is expected to be found at the 
location of the reasonably maximally exposed individual, during the compliance time period; 
(3) Uncertainty is adequately represented in parameters for conceptual models, process models, 
and alternative conceptual models considered in developing the total system performance 
assessment abstraction of redistribution of radionuclides in soil, 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; 

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(4) Parameters or models that most influence repository performance based on the performance 
measure and time period of compliance, specified in 10 CFR Part 63, are identified. 
Acceptance Criteria from Section 2.2.1.3.14, Biosphere Characteristics 
Acceptance Criterion 1, System Description and Model Integration Are Adequate. 
(1) Total system performance assessment adequately incorporates important site features, 
physical phenomena, and couplings, and consistent and appropriate assumptions throughout the 
biosphere characteristics modeling abstraction process. 
(2) The total system performance assessment model abstraction identifies and describes aspects 
of the biosphere characteristics modeling that are important to repository performance, and 
includes the technical bases for these descriptions. For example, the reference biosphere should 
be consistent with the arid or semi-arid conditions in the vicinity of Yucca Mountain. 
(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 
assumptions in other total system performance assessment abstractions. 
Acceptance Criterion 2, Data Are Sufficient for Model Justification. 
(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. 
(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. 
Acceptance Criterion 3, Data Uncertainty Is Characterized and Propagated Through the 
Model Abstraction. 
(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. 

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ANL-NBS-MD-000014 REV 00 4-21 October 2004 
(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. 
(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. 
(6) Parameters or models that most influence repository performance, based on the performance 
measure and time period of compliance specified in 10 CFR Part 63, are identified. 
Acceptance Criteria from Section 2.2.1.4.1, Demonstration of Compliance with the 
Postclosure Public Health and Environmental Standards 
Acceptance Criterion 2, An Adequate Demonstration Is Provided That the Annual Dose to 
the Reasonably Maximally Exposed Individual in Any Year During the Compliance Period 
Does Not Exceed the Exposure Standard. 
(1) A sufficient number of realizations has been obtained, for each scenario class, using the total 
system performance assessment code, to ensure that the results of the calculations are statistically 
stable. 
(2) The annual dose curve includes confidence intervals (e.g., 95th and 5th percentile) to represent 
the uncertainty in the dose calculations. 
4.3 CODES, STANDARDS, AND REGULATIONS 
No codes or standards, other than those identified in the Project Requirements Document (Canori 
and Leitner 2003 [DIRS 166275], Table 2-3) and determined to be applicable, were used in this 
analysis. 

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5. ASSUMPTIONS 
No assumptions were used in this analysis. 

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6. SCIENTIFIC ANALYSIS DISCUSSION 
The objectives of this analysis are to evaluate the output of the biosphere model, BDCFs, from 
the perspective of parameter, process, and pathway importance and sensitivity. 
This section contains the description of the framework for the biosphere modeling (Section 6.1) 
and the discussion of important pathways, processes, and parameters for the groundwater 
(Section 6.2) and volcanic ash (Section 6.3) exposure scenarios. 
6.1 GENERAL CONSIDERATIONS 
6.1.1 Radionuclides Included in the Analysis 
The biosphere model was constructed for 28 radionuclides identified as important for the TSPA 
for scenario classes involving radionuclide releases to groundwater. These radionuclides are 
referred in this analysis as primary radionuclides, and include: carbon-14 (14C), chlorine-36 
(36Cl), selenium-79 (79Se), strontium-90 (90Sr), technetium-99 (99Tc), tin-126 (126Sn), iodine-129 
(129I), cesium-135 (135Cs), cesium-137 (137Cs), lead-210 (210Pb), radium-226 (226Ra), 
actinium-227 (227Ac), thorium-229 (229Th), thorium-230 (230Th), thorium-232 (232Th), 
protactinium-231 (231Pa), uranium-232 (232U), uranium-233 (233U), uranium-234 (234U), 
uranium-236 (236U), uranium-238 (238U), neptunium-237 (237Np), plutonium-238 (238Pu), 
plutonium-239 (239Pu), plutonium-240 (240Pu), plutonium-242 (242Pu), americium-241 (241Am), 
and americium-243 (243Am) (BSC 2004 [DIRS 169460], Section 6.1.3). 
The following 23 primary radionuclides were identified as important for the TSPA scenario 
classes involving radionuclide release during a volcanic eruption: 90Sr, 99Tc, 126Sn, 137Cs, 210Pb, 
226Ra, 227Ac, 229Th, 230Th, 232Th, 231Pa, 232U, 233U, 234U, 236U, 238U, 237Np, 238Pu, 239Pu, 240Pu, 
242Pu, 241Am, and 243Am (BSC 2004 [DIRS 169460], Section 6.1.3). Both lists include 
radionuclides that are of potential importance during the first 20,000 years and the period of up 
to 1 million years (BSC 2004 [DIRS 169460], Section 6.1.3). 
The biosphere model accounts for the decay products of the primary radionuclides. The 
short-lived decay products (half-lives less than 180 days) are considered to be in secular 
equilibrium with the parent radionuclide, and their contributions to the BDCFs are included in 
the BDCF for the long-lived radionuclide (either a primary radionuclide or its long-lived decay 
product) (BSC 2004 [DIRS 169460], Sections 6.3.1.4 and 6.3.5). The biosphere model also 
accounts for the decay and ingrowth of the long-lived decay products in the soil and adds BDCF 
contributions of the long-lived decay products to that of the parent primary radionuclide 
(BSC 2004 [DIRS 169460], Section 6.4.1.2). Two decay products of the primary radionuclides, 
228Th and 228Ra, have half-lives greater than 180 days and are not automatically included in the 
BDCFs of the parent when the biosphere model is executed. For biosphere modeling, 228Th and 
228Ra are treated like primary radionuclides. After BDCFs are calculated for these radionuclides, 
their BDCFs are added to the BDCF of the parent primary radionuclide. In the case of 232Th, the 
BDCF includes the contribution from 228Ra, 228Th, and their short-lived decay products. The 
BDCF for 232U includes the contribution from 228Th and its short-lived decay products. The list 
of primary radionuclides and the decay products included in the BDCF for a primary 
radionuclide is shown in Table 6.1-1. 

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Table 6.1-1. Primary Radionuclides and Decay Products Included in the Biosphere Dose 
Conversion Factors 
Primary Radionuclide Decay Products Included in BDCF 
C-14 
Cl-36 
Se-79 
Sr-90 Y-90 
Tc-99 
Sn-126 
I-129 
Cs-135 
Cs-137 Ba-137m 
Pb-210 Bi-210, Po-210 
Ra-226 Rn-222, Po-218, Pb-214, At-218, Bi-214, Po-214, Tl-210 
Ac-227 Th-227, Fr-223, Ra-223, Rn-219, Po-215, Pb-211, Bi-211, Tl-207, Po-211 
Th-229 Ra-225, Ac-225, Fr-221, At-223, Bi-213, Po-213, Tl-209, Pb-209 
Th-230 
Th-232 Ra-228, Ac-228, Th-228, Ra-224, Rn-220, Po-216, Pb-212, Bi-212, Po-212, Tl-208 
Pa-231 
U-232 Th-228, Ra-224, Rn-220, Po-216, Pb-212, Bi-212, Po-212, Tl-208 
U-233 
U-234 
U-236 
U-238 Th-234, Pa-234m, Pa-234 
Np-237 Pa-233 
Pu-238 
Pu-239 
Pu-240 
Pu-242 
Am-241 
Am-243 Np-239 
6.1.2 Description of the Exposure Scenarios 
Scenario classes considered for TSPA include the nominal scenario class and the disruptive 
scenario classes (BSC 2003 [DIRS 166296], pp. 51 to 52). The nominal scenario class 
represents the most likely evolution of the repository system and includes favorable and some 
potentially adverse future conditions. The disruptive event scenario classes consider 
combinations of FEPs that have a low probability of occurrence but may produce additional 
potentially adverse future conditions. The disruptive event scenario classes include the igneous 
(which includes the igneous intrusion and volcanic eruption cases) and seismic classes, as well as 
a special case analyzing the stylized intrusion of a human into the repository. TSPA scenarios 
consider radionuclide release from the repository in either groundwater or volcanic tephra. 
These two release modes match the two biosphere exposure scenarios and the associated 
biosphere models developed to support the TSPA analyses and described in the Biosphere Model 

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Report (BSC 2004 [DIRS 169460]). The biosphere exposure scenarios consider radiological 
consequences of radionuclide releases to the reference biosphere in groundwater or volcanic 
tephra. 
Groundwater Exposure Scenario 
BDCFs for the groundwater exposure scenario are used to calculate annual doses in the TSPA 
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 and human intrusion) may result in such a release. For this 
scenario, radionuclides enter the biosphere from wells that extract contaminated groundwater 
from an aquifer. Human exposure arises from using the contaminated water for domestic and 
agricultural purposes. 
A detailed description of the groundwater exposure scenario, including the associated conceptual 
and mathematical models, is presented in the Biosphere Model Report (BSC 2004 
[DIRS 169460], Sections 6.3.1 and 6.4). 
Volcanic Ash Exposure Scenario 
BDCFs for the volcanic ash exposure scenario are used for calculation of expected dose in the 
TSPA volcanic eruption modeling case. The initial source of radionuclides in the biosphere for 
the volcanic ash exposure scenario is contaminated volcanic ash deposited on the ground surface 
as the result of a volcanic eruption. 
After radionuclides enter the biosphere, radionuclide migration through the biosphere occurs due 
to a number of transport processes that lead to contamination and accumulation in the 
environmental media (e.g., soil, air, flora, and fauna). Human exposure to radionuclides in the 
environment arises when people come in contact with contaminated environmental media. 
A detailed description of the volcanic ash exposure scenario, including the associated conceptual 
and mathematical models, is presented in the Biosphere Model Report (BSC 2004 
[DIRS 169460], Sections 6.3.2 and 6.5). 
6.1.3 Receptor Used in the Biosphere Model 
The regulations for licensing the repository include a postclosure individual protection standard 
for the performance of the repository that has a reasonable expectation of being achieved. This 
standard is expressed as the annual dose limit to the RMEI (10 CFR 63.311 [DIRS 156605]). 
Analysis of annual dose includes all potential pathways of radionuclide transport and exposure 
(10 CFR 63.311 [DIRS 156605]). Changes in the reference biosphere, other than those due to a 
change in climate, are not included. 
To meet the requirements of 10 CFR 63.312(b) [DIRS 156605], the dietary and lifestyle 
characteristics of the RMEI were determined based on surveys of people living in the Amargosa 
Valley. 

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ANL-NBS-MD-000014 REV 00 6-4 October 2004 
6.1.4 Consideration of Climate Change 
For modeling climate change for TSPA, the climate shifts in a series of step changes between 
three climate states in the first 10,000 years: present-day climate, monsoon climate (warmer and 
much wetter than the present-day climate), and glacial transition climate (colder and wetter, but 
not substantially wetter, than the present-day climate) (BSC 2003 [DIRS 166296], p. 79, 
BSC 2004 [DIRS 170002], Section 7.1). Within the TSPA model, these shifts require 
coordinating the coupled submodels, because they must all simultaneously change to the 
appropriate climate state. To support climate change for the nominal exposure scenario, BDCFs 
are developed for three climate states (BSC 2004 [DIRS 169674], Section 6.2.2). For the 
volcanic release scenario, climate changes have been shown to have little effect on BDCFs, and 
TSPA is provided with a single but conservative set (BSC 2004 [DIRS 167287], Section 6.2.5). 
This analysis includes the discussion of climate influence on the BDCFs and input parameters. 
Two climates referred to throughout the analysis are the climate extremes for the compliance 
period, that is, the mean present-day climate and the upper bound of the glacial transition 
climate. These two climates constitute the average bounding cases for the climates expected 
during the period encompassed by the TSPA. The mean present-day climate is for brevity 
referred to thereafter as the present-day climate; the upper bound of the glacial transition climate 
is referred to as the future climate. 
6.1.5 Biosphere Model 
The ERMYN model (BSC 2004 [DIRS 169460]) is used to calculate BDCFs by modeling 
transport of radionuclides introduced into the biosphere and evaluating receptor exposure. The 
Biosphere Model Report (BSC 2004 [DIRS 169460]) describes the ERMYN model. Input 
parameters for the biosphere model were developed and documented in a series of five model 
parameter reports: BSC 2004 [DIRS 169673], BSC 2004 [DIRS 169671], BSC 2004 
[DIRS 169672], BSC 2004 [DIRS 169458], and BSC 2004 [DIRS 169459]. 
The biosphere model calculates radionuclide-specific BDCFs. For the groundwater exposure 
scenario, a BDCF is numerically equal to the all-pathway annual dose that the RMEI would 
receive if groundwater containing a unit activity concentration of a given radionuclide were 
extracted from wells and used for irrigation or domestic purposes. A radionuclide-specific 
BDCFs for the volcanic ash exposure scenario consist of a set of three components representing 
different exposure pathways and conditions and are developed for the unit activity deposited per 
unit area of the soil surface. 
BDCFs for groundwater and volcanic ash exposure scenarios were calculated, using probabilistic 
analysis, in a series of simulations for each primary radionuclide and two long-lived decay 
products, 228Th and 228Ra (Section 6.1.1). Each simulation resulted in 1,000 model realizations. 
A model realization is one of the possible model outcomes obtained as a result of a single round 
of sampling of the model input parameters. 
Uncertainty in the model outcome is represented by the probability distributions of the BDCFs 
and it arises from propagating input parameters uncertainty onto the modeling results. Input 

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ANL-NBS-MD-000014 REV 00 6-5 October 2004 
parameter values were sampled using latin hypercube sampling for consistency with the 
sampling technique to be used in the TSPA-LA (BSC 2003 [DIRS 166296], Section 7.3). 
6.2 IDENTIFICATION OF IMPORTANT PATHWAYS, PROCESSES AND 
PARAMETERS FOR THE GROUNDWATER EXPOSURE SCENARIO 
This section uses results of the runs of the biosphere model for the groundwater exposure 
scenario included in DTN: MO0407MWDGSBMF.000 [DIRS 170852] except for the 
deterministic runs. For the deterministic runs, the input was obtained from the model input data 
files (DTNs: MO0403SPAAEIBM.002 [DIRS 169392]; MO0407SPAINEXI.002 
[DIRS 170597]; MO0407SPASRPBM.002 [DIRS 170755]; MO0406SPAETPBM.002 
[DIRS 170150]; MO0407SPACRBSM.002 [DIRS 170677]), as described in Section 4.1. 
6.2.1 Distributions of Biosphere Dose Conversion Factors 
This section evaluates the distributions of all BDCFs and examines the trends in their values and 
their causes. Each run of the biosphere model for the groundwater exposure scenario for a given 
radionuclide produced 1,000 model realizations, that is, 1,000 BDCF values, each for a different 
set of input parameter values. BDCFs were calculated for three climate states, as described in 
Section 6.1.4. The BDCF statistics are summarized in the Nominal Performance Biosphere Dose 
Conversion Factor Analysis (BSC 2004 [DIRS 169674], Tables 6.2-5, 6.2-6, and 6.2-7 for the 
present-day, monsoon, and glacial transition climates, respectively). 
To calculate BDCFs for each climate state, BDCF values were first calculated for the 
present-day climate (which is also representative of the lower bound of the monsoon climate) 
and the upper bound of the glacial transition climate, using the full suite of variable input 
parameters, including those that have climate-specific values for those climates. These BDCFs 
incorporated variation and uncertainty in current conditions at Yucca Mountain and the analogue 
locations representative of the upper bound of the glacial transition climate. The BDCFs for the 
present-day climate were used in the TSPA for that climate state (BSC 2004 [DIRS 169674], 
Section 6.2.2). 
To incorporate variation in the predicted future climate states, BDCFs for the monsoon and 
glacial transition climates were calculated for each model realization by interpolation between 
the BDCFs for the climate extremes (i.e., the present-day and the upper bound of the glacial 
transition climates) for a realization using the annual average irrigation rate as a scaling factor. 
For the bounds of the monsoon and the glacial transition climate states, the value of this 
parameter was estimated from the analogue weather stations. The average minimum (0.52 m/yr) 
and maximum (0.94 m/yr) irrigation rates for the monsoon climate encompassed almost the 
entire range of average irrigation rates between the upper bound glacial transition (0.50 m/yr) 
and present-day (0.94 m/yr) climates (BSC 2004 [DIRS 169673], Section 6.5.2). Therefore, for 
each realization, the BDCF for the monsoon climate was a randomly selected value between the 
calculated BDCFs for the upper bound glacial transition and present-day climates. The range of 
irrigation rates for the glacial transition (0.50 to 0.88 m/yr) was about 86 percent of the range 
between the upper bound glacial transition and the present-day climate. Therefore, for each 
realization, the BDCF for the glacial transition climate was a randomly selected value between 
the calculated BDCF for the upper bound glacial transition and 86 percent of the calculated 

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ANL-NBS-MD-000014 REV 00 6-6 October 2004 
BDCF for the present-day climate. Interpolation between the bounds of each climate state based 
on differences in annual irrigation rate was valid because that parameter had the greatest 
influence on climate-dependent changes in BDCFs for most radionuclides and because BDCFs 
increased approximately linearly as annual irrigation rate increased (BSC 2004 [DIRS 169674], 
Section 6.2.2). 
Figure 6.2-1 shows the ranges of BDCFs for all primary radionuclides, including their mean and 
median values, minima and maxima, as well as the 5th and 95th percentiles. The variance in the 
BDCF values is a result of the input parameter variability and uncertainty that is propagated into 
the model output. A number of trends can be observed in the BDCF values. First, the mean 
BDCF values for non-actinides generally increase with increasing mass of a radionuclide. The 
mean BDCF values for the actinides are generally higher than those for the lighter radionuclides 
and are roughly within an order of magnitude of each other, with the values for 226Ra and 
isotopes of thorium being the highest. 
To better show the span of the BDCF values and identify radionuclides that have the lowest and 
the highest BDCF values, the BDCFs were sorted in ascending order by the value of the means 
(Figure 6.2-2). The BDCF values are the highest for the radionuclides with relatively high 
atomic numbers and generally tend to decrease with the decreasing atomic number. The lowest 
BDCF value is for 99Tc; the highest is for 231Pa and 226Ra. The high value for 226Ra is due to the 
contribution from inhalation of radon decay products. The high value for 231Pa arises from a 
tendency of protactinium to accumulate in the soil (relatively high partition coefficient, Kd) and 
its relatively high inhalation dose per unit activity intake. The difference between the highest 
and the lowest BDCFs is almost 5 orders of magnitude. 
Figures 6.2-1 and 6.2-2 show that the degree of variance in the BDCF values differs greatly 
among the radionuclides. The minimum-to-maximum range is much wider than the 5th to 95th 
percentile range of the BDCF values. The BDCF for 36Cl has the widest minimum-to-maximum 
range of BDCF values, extending over about 2.4 orders of magnitude; the range for 90Sr is only 
half an order of magnitude (a factor of about 3.1). The 5th to 95th percentile range is much 
narrower, spanning from a factor of 1.6 for 90Sr up to about 1.3 orders of magnitude for 233U. 
For calculations, see Excel file GW BDCF Variability Plots.xls (Appendix A). 

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ANL-NBS-MD-000014 REV 00 6-7 October 2004 
1.E-06 
1.E-05 
1.E-04 
1.E-03 
1.E-02 
1.E-01 
1.E+00 
C-14 
Cl-36 
Se-79 
Sr-90 
Tc-99 
Sn-126 
I-129 
Cs-135 
Cs-137 
Pb-210 
Ra-226 
Ac-227 
Th-229 
Th-230 
Th-232 
Pa-231 
U-232 
U-233 
U-234 
U-236 
U-238 
Np-237 
Pu-238 
Pu-239 
Pu-240 
Pu-242 
Am-241 
Am-243 
Radionuclide 
BDCF (rem/yr per pCi/L) 
Source: Excel file GW BDCF Variability Plots.xls (Appendix A). 
NOTE: Boxes represent 5th to 95th percentile range. The vertical solid line represents the range and the tick mark on the line is the median. Diamond represents 
BDCF contributions from drinking water; circle represents the mean BDCF. 
Figure 6.2-1. BDCF Distributions for the Groundwater Exposure Scenario and the Present-Day Climate 

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ANL-NBS-MD-000014 REV 00 6-8 October 2004 
1.E-06 
1.E-05 
1.E-04 
1.E-03 
1.E-02 
1.E-01 
1.E+00 
Tc-99 
C-14 
Cl-36 
Cs-135 
Se-79 
Sr-90 
I-129 
Cs-137 
U-238 
U-236 
U-234 
U-233 
Pu-238 
U-232 
Sn-126 
Am-241 
Np-237 
Pu-242 
Pu-240 
Pb-210 
Pu-239 
Am-243 
Th-230 
Ac-227 
Th-229 
Th-232 
Ra-226 
Pa-231 
Radionuclide 
BDCF (rem/yr per pCi/L) 
Source: Excel file GW BDCF Variability Plots.xls (Appendix A). 
NOTE: Boxes represent 5th to 95th percentile range. The vertical solid line represents the range. Circle represents the mean BDCF. 
Figure 6.2-2. BDCF Distributions for the Groundwater Exposure Scenario and the Present-Day Climate Sorted by the Mean BDCF Value 

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ANL-NBS-MD-000014 REV 00 6-9 October 2004 
The range in the BDCF values for a radionuclide can be better evaluated when the BDCFs are 
normalized to their mean value, as shown in Figure 6.2-3. This figure shows the distribution of 
BDCF values about the mean. The 5th percentile values are within a factor of 0.18 to 0.82 of the 
mean BDCF, depending on a radionuclide. The 95th percentiles are within a factor of 1.3 to 3.5 
of the mean (for calculations see Excel file GW BDCF Variability Plots.xls, worksheet BDCF 
Normalized to Mean). The minimum values are from 0.03 (126Sn and 226Ra) to 0.75 (90Sr) of the 
mean, and maximum values are from 2.3 (90Sr) to about 43 (36Cl) times greater than the mean. 
Per 10 CFR 63.312(d), the drinking water component in the biosphere model is fixed; therefore, 
the distribution of BDCFs results from variability and uncertainty in the contributions from all 
other pathways. As a result, the distribution of BDCFs tends to be narrow if drinking water is an 
important pathway (90Sr, 129I, 238Pu) and wider if the contribution of drinking water is less 
important. To show this, the drinking water contribution for individual radionuclides was 
subtracted from their BDCF statistics and the remainder normalized to its mean value 
(Figure 6.2-4). The variability (as measured by the 5th to 95th percentile levels) between 
normalized BDCF distributions, once the fixed drinking water component is removed, is more 
consistent among radionuclides than for the total normalized values. 

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1.E-02 
1.E-01 
1.E+00 
1.E+01 
1.E+02 
C-14 
Cl-36 
Se-79 
Sr-90 
Tc-99 
Sn-126 
I-129 
Cs-135 
Cs-137 
Pb-210 
Ra-226 
Ac-227 
Th-229 
Th-230 
Th-232 
Pa-231 
U-232 
U-233 
U-234 
U-236 
U-238 
Np-237 
Pu-238 
Pu-239 
Pu-240 
Pu-242 
Am-241 
Am-243 
Radionuclide 
BDCF (rem/yr per pCi/L) 
Source: Excel file GW BDCF Variability Plots.xls (Appendix A). 
NOTE: Boxes represent 5th to 95th percentile range. The vertical solid line represents the range and the tick mark on the line is the median. 
Figure 6.2-3. BDCF Distributions for Groundwater Exposure Scenario, Present-Day Climate, Normalized to the Mean Value 

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ANL-NBS-MD-000014 REV 00 6-11 October 2004 
1.E-02 
1.E-01 
1.E+00 
1.E+01 
1.E+02 
C-14 
Cl-36 
Se-79 
Sr-90 
Tc-99 
Sn-126 
I-129 
Cs-135 
Cs-137 
Pb-210 
Ra-226 
Ac-227 
Th-229 
Th-230 
Th-232 
Pa-231 
U-232 
U-233 
U-234 
U-236 
U-238 
Np-237 
Pu-238 
Pu-239 
Pu-240 
Pu-242 
Am-241 
Am-243 
Radionuclide 
BDCF (rem/yr per pCi/L) 
Source: Excel file GW BDCF Variability Plots.xls (Appendix A). 
NOTE: Boxes represent 5th to 95th percentile range. The vertical solid line represents the range. 
Figure 6.2-4. Distributions of the BDCFs (Exclusive of the Drinking Water Component) for Groundwater Exposure Scenario, Present-Day Climate, 
Normalized to the Mean Value 

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ANL-NBS-MD-000014 REV 00 6-12 October 2004 
6.2.2 Summary of Pathway Analysis Results 
The aim of the pathway analysis is to identify those pathways that are important contributors to 
the BDCFs, so further analyses can focus on their contributing environmental transport and 
exposure pathways and the corresponding input parameters. 
The biosphere model for the groundwater exposure scenario includes 15 exposure pathways. 
Pathway analysis was conducted, using the mean values of the BDCFs, to determine the relative 
importance of individual exposure pathways in terms of their contributions to BDCFs for various 
radionuclides (BSC 2004 [DIRS 169674], Section 6.2.5). The pathway contributions to the 
mean BDCF for the groundwater exposure scenario are reproduced in Tables 6.2-1 and 6.2-2. 
Pathway contributions differ among radionuclides, and the RMEIs ingestion of water is a 
dominant pathway for most radionuclides. Ingestion of locally produced food is important for 
most radionuclides with atomic numbers less than about 88. Inhalation of particulate matter 
tends to dominate doses for actinides (e.g., isotopes of thorium, uranium, plutonium, and 
americium). Inhalation of radioactive aerosols generated by evaporative coolers also is an 
important inhalation exposure pathway for some of these radionuclides. Other pathways are only 
important for a few radionuclides. For instance, external exposure is a dominant pathway for 
126Sn and 137Cs; inhalation of radon decay products is important for 226Ra and 230Th; and fish 
consumption is important for 14C, isotopes of cesium, and 210Pb (Table 6.2-1). 
For the future climate, the importance of the evaporative cooler pathway is greatly reduced, as is 
the importance of the pathways that are related to radionuclide concentration in the surface soil 
(the equilibrium activity concentration in the surface soil is less because of the decreased 
irrigation rate) (Table 6.2-2). This increases the relative importance of the water ingestion 
pathway, which is a dominant pathway for many radionuclides. Inhalation of particulate matter 
remains an important pathway for the actinides (Table 6.2-2). 
To visualize the results of the pathway analysis described above and to show the patterns in 
pathway importance for various radionuclides, Figures 6.2-5 and 6.2-6 show percent pathway 
contributions to the mean BDCF for several selected radionuclides for the present-day and future 
climates, respectively. The selected radionuclides include those radionuclides that were 
identified as important in previous performances assessments. The results of the TSPA for the 
supplemental science and performance analysis indicated that 14C, 99Tc, and 129I were the most 
important dose contributors for nominal performance during the first 20,000 years postclosure 
(CRWMS M&O 2000 [DIRS 153246], Figures 4.1-6 and 4.1-7). This coincides with the 
timeframe for the TSPA-LA (BSC 2003 [DIRS 166296], Section 1.3). Radionuclides important 
in the initial period are those that are relatively mobile in the environment. Transuranics tend to 
move more slowly in the environment because of their high sorption onto the solids. Three 
radionuclides, 233U, 237Np, and 239Pu were selected to represent this group. 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-13 October 2004 
Table 6.2-1. Exposure Pathway Contributions (Percent) for the Present-Day Climate Biosphere Dose Conversion Factors 
Inhalation Ingestion 
RN 
External 
exposure 
Particul. 
Matter 
Evap. 
Cooler Radon Water 
Leafy 
Veget. 
Other 
Veget. Fruit Grain Meat Milk Poultry Eggs Fish Soil 
C-14 0.0 0.0 0.0 0.0 16.8 2.8 5.0 13.0 0.6 7.0 3.3 0.6 5.5 45.3 0.0 
Cl-36 0.1 0.0 0.2 0.0 10.7 3.2 4.9 16.5 2.6 22.7 18.5 0.0 9.0 11.4 0.0 
Se-79 0.0 0.1 0.0 0.0 10.3 0.7 0.5 1.6 0.1 55.1 3.2 2.0 21.9 3.8 0.6 
Sr-90 0.5 0.1 0.3 0.0 68.2 6.6 3.7 6.2 0.6 3.0 3.7 0.0 1.6 5.1 0.4 
Tc-99 0.0 0.0 0.7 0.0 47.2 12.0 2.1 7.7 0.5 4.3 13.5 0.2 10.0 1.6 0.0 
Sn-126 98.2 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.4 0.0 0.0 0.1 1.0 0.0 
I-129 0.1 0.1 0.1 0.0 59.9 2.6 0.7 3.0 0.4 5.0 7.5 0.2 14.2 5.4 0.8 
Cs-135 0.0 0.1 0.0 0.0 9.3 1.4 0.9 4.2 0.2 10.3 5.8 7.3 5.5 54.0 1.1 
Cs-137 43.0 0.0 0.0 0.0 7.6 0.4 0.1 0.5 0.0 1.7 1.0 0.9 0.7 44.1 0.1 
Pb-210 0.0 0.2 0.5 0.0 58.8 2.6 0.6 2.3 0.3 0.3 0.2 0.1 1.4 32.4 0.4 
Ra-226 6.8 0.3 0.0 89.2 1.0 0.3 0.2 0.6 0.0 0.1 0.1 0.0 0.7 0.1 0.6 
Ac-227 0.3 16.8 42.6 0.0 34.7 1.4 0.3 1.2 0.1 0.1 0.0 0.0 0.0 2.2 0.2 
Th-229 3.0 71.9 12.5 0.0 8.6 0.5 0.1 0.4 0.0 0.1 0.0 0.0 0.0 1.8 0.9 
Th-230 5.7 13.6 2.2 74.5 1.4 0.3 0.1 0.6 0.0 0.1 0.1 0.0 0.6 0.3 0.6 
Th-232 25.0 53.9 8.8 0.0 8.2 0.7 0.2 0.6 0.1 0.1 0.1 0.0 0.0 1.5 0.9 
Pa-231 1.3 84.7 2.5 0.0 7.7 0.6 0.2 0.8 0.1 0.1 0.0 0.0 0.0 0.2 1.8 
U-232 12.3 20.6 33.9 0.0 26.6 1.1 0.3 0.9 0.1 0.1 0.1 0.2 0.8 2.7 0.3 
U-233 1.3 68.3 14.3 0.0 11.4 0.6 0.2 0.6 0.1 0.1 0.1 0.2 1.6 0.3 0.9 
U-234 0.4 52.3 20.4 4.9 16.2 0.8 0.2 0.7 0.1 0.1 0.1 0.3 2.2 0.5 0.7 
U-236 0.0 54.9 21.7 0.0 17.3 0.8 0.2 0.8 0.1 0.1 0.2 0.4 2.3 0.5 0.8 
U-238 3.7 52.1 20.6 0.0 17.3 0.8 0.2 0.8 0.1 0.1 0.2 0.4 2.4 0.5 0.8 
Np-237 2.6 22.5 15.2 0.0 46.5 2.6 1.0 4.3 0.2 0.9 0.0 0.0 0.0 3.0 1.2 
Pu-238 0.0 20.6 16.4 0.0 49.8 2.1 0.5 1.7 0.2 0.0 0.0 0.0 0.0 7.3 1.1 
Pu-239 0.0 52.5 9.1 0.0 27.9 1.5 0.3 1.3 0.2 0.0 0.0 0.0 0.1 4.1 2.9 
Pu-240 0.0 51.5 9.4 0.0 28.7 1.5 0.3 1.3 0.2 0.0 0.0 0.0 0.1 4.2 2.8 
Pu-242 0.0 53.1 9.1 0.0 27.5 1.5 0.3 1.3 0.2 0.0 0.0 0.0 0.1 4.1 2.9 
Am-241 0.1 38.2 12.8 0.0 39.0 1.8 0.4 1.6 0.2 0.1 0.0 0.0 0.0 3.7 2.1 
Am-243 5.6 49.0 9.1 0.0 27.7 1.5 0.3 1.3 0.1 0.1 0.0 0.0 0.0 2.6 2.7 
Source: BSC 2004 [DIRS 169674], Table 6.2-10. 

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ANL-NBS-MD-000014 REV 00 6-14 October 2004 
Table 6.2-2. Exposure Pathway Contributions (Percent) for the Future Climate Biosphere Dose Conversion Factors 
Inhalation Ingestion 
RN 
External 
exposure 
Particul. 
Matter 
Evap. 
Cooler Radon Water 
Leafy 
Veget. 
Other 
Veget. Fruit Grain Meat Milk Poultry Eggs Fish Soil 
C-14 0.0 0.0 0.0 0.0 18.0 2.9 3.7 10.1 0.7 6.4 3.1 0.7 6.2 48.6 0.0 
Cl-36 0.1 0.0 0.1 0.0 15.2 3.4 5.1 17.3 2.7 23.5 19.0 0.0 10.6 9.4 0.0 
Se-79 0.0 0.1 0.0 0.0 15.0 0.7 0.4 1.4 0.1 48.6 2.9 1.7 19.1 3.2 0.5 
Sr-90 0.3 0.1 0.1 0.0 78.4 4.8 2.4 3.9 0.4 2.1 2.6 0.0 1.2 3.4 0.2 
Tc-99 0.0 0.0 0.2 0.0 56.4 10.7 1.8 6.3 0.5 3.8 11.8 0.2 9.2 1.1 0.0 
Sn-126 97.7 0.0 0.0 0.0 0.4 0.0 0.0 0.0 0.0 0.4 0.0 0.0 0.1 1.0 0.0 
I-129 0.1 0.1 0.0 0.0 69.0 2.1 0.5 1.9 0.3 3.9 5.8 0.2 11.6 3.6 0.6 
Cs-135 0.0 0.1 0.0 0.0 15.1 1.3 0.8 3.7 0.2 9.4 5.2 6.6 5.0 51.1 1.0 
Cs-137 37.9 0.0 0.0 0.0 12.6 0.4 0.1 0.5 0.0 1.7 1.0 0.9 0.7 42.7 0.1 
Pb-210 0.0 0.1 0.1 0.0 71.1 2.2 0.4 1.4 0.2 0.2 0.1 0.0 1.2 22.6 0.3 
Ra-226 6.1 0.3 0.0 89.4 1.7 0.3 0.1 0.5 0.0 0.1 0.1 0.0 0.6 0.1 0.5 
Ac-227 0.3 15.8 16.4 0.0 61.6 1.8 0.3 1.0 0.2 0.1 0.0 0.0 0.0 2.3 0.2 
Th-229 3.0 72.2 5.1 0.0 16.1 0.6 0.1 0.4 0.1 0.1 0.0 0.0 0.1 2.0 0.9 
Th-230 5.3 12.6 0.8 77.6 2.4 0.3 0.1 0.5 0.0 0.1 0.1 0.0 0.5 0.3 0.6 
Th-232 24.5 52.9 3.5 0.0 14.9 0.8 0.2 0.5 0.1 0.1 0.1 0.0 0.0 1.6 0.9 
Pa-231 1.3 81.4 1.0 0.0 13.5 0.7 0.2 0.7 0.1 0.1 0.0 0.0 0.0 0.2 1.8 
U-232 12.1 20.3 13.2 0.0 47.5 1.4 0.2 0.9 0.2 0.1 0.1 0.2 1.0 2.8 0.3 
U-233 1.4 72.3 5.8 0.0 21.1 0.8 0.2 0.6 0.1 0.1 0.1 0.3 1.8 0.4 0.9 
U-234 0.4 54.0 8.1 5.8 29.7 1.0 0.2 0.7 0.1 0.1 0.2 0.4 2.4 0.5 0.8 
U-236 0.0 57.0 8.7 0.0 31.8 1.1 0.2 0.8 0.1 0.1 0.2 0.4 2.6 0.6 0.8 
U-238 3.8 53.6 8.2 0.0 31.7 1.0 0.2 0.8 0.1 0.1 0.2 0.4 2.6 0.6 0.8 
Np-237 2.2 18.9 4.5 0.0 63.7 2.4 0.8 3.6 0.2 0.8 0.0 0.0 0.0 2.4 1.0 
Pu-238 0.0 15.2 5.0 0.0 69.2 2.1 0.3 1.2 0.2 0.0 0.0 0.0 0.0 5.9 0.8 
Pu-239 0.0 44.4 3.1 0.0 43.5 1.6 0.3 1.0 0.2 0.0 0.0 0.0 0.1 3.7 2.5 
Pu-240 0.0 43.3 3.2 0.0 44.4 1.6 0.3 1.0 0.2 0.0 0.0 0.0 0.1 3.8 2.4 
Pu-242 0.0 45.0 3.1 0.0 43.0 1.6 0.3 1.0 0.2 0.0 0.0 0.0 0.1 3.7 2.5 
Am-241 0.1 30.3 4.1 0.0 57.4 1.9 0.3 1.2 0.2 0.1 0.0 0.0 0.0 3.1 1.7 
Am-243 4.8 41.6 3.1 0.0 43.5 1.5 0.3 1.0 0.2 0.1 0.0 0.0 0.0 2.4 2.3 
Source: BSC 2004 [DIRS 169674], Table 6.2-11. 

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0 
10 
20 
30 
40 
50 
60 
70 
Average Percent Pathway 
Contribution 
Water 
External 
Inhalation 
Evaporative Cooler 
Leafy Vegetables 
Other Vegetables 
Fruit 
Grain 
Meat 
Milk 
Poultry 
Eggs 
Fish 
Soil 
C-14
Tc-99 
I-129
U-233 
Np-237 
Pu-239 
Source: Excel file Detailed Pathway Analysis GW_MC.xls (Appendix A). 
Figure 6.2-5. Pathway Contributions for the Groundwater Exposure Scenario and Present-Day Climate 
0 
10 
20 
30 
40 
50 
60 
70 
80 
Average Percent Pathway 
Contribution 
Water 
External 
Inhalation 
Evaporative Cooler 
Leafy Vegetables 
Other Vegetables 
Fruit 
Grain 
Meat 
Milk 
Poultry 
Eggs 
Fish 
Soil 
C-14
Tc-99 
I-129 U-233 
Np-237 
Pu-239 
Source: Excel file Detailed Pathway Analysis GW_MC.xls (Appendix A). 
Figure 6.2-6. Pathway Contributions for the Groundwater Exposure Scenario and Future Climate 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-16 October 2004 
The variation associated with the major exposure pathways for the present-day climate for the 
radionuclides shown in Figure 6.2-5 is illustrated in Figure 6.2-7. 
Source: Excel file GW BDCF Variability Plots.xls (Appendix A). 
NOTE: Boxes represent 5th to 95th percentile range for the groundwater exposure scenario BDCFs for the 
present-day climate. Vertical solid line represents the range and the tick mark on the line is the median. 
Diamonds represent BDCF contributions from drinking water; circles represent the mean values. 
Figure 6.2-7. Uncertainty Associated with the Major Exposure Pathway BDCFs for Selected 
Radionuclides, Present-Day Climate 
Carbon-14 
1.E-13 
1.E-12 
1.E-11 
1.E-10 
1.E-09 
1.E-08 
1.E-07 
1.E-06 
1.E-05 
1.E-04 
1.E-03 
Total 
Water 
Ingestion 
Inhalation 
External 
BDCF (rem/yr per pCi/L) 
Technetium-99 
1.E-11 
1.E-10 
1.E-09 
1.E-08 
1.E-07 
1.E-06 
1.E-05 
1.E-04 
1.E-03 
Total 
Water 
Ingestion 
Inhalation 
External 
BDCF (rem/yr per pCi/L) 
Iodine-129 
1.E-10 
1.E-09 
1.E-08 
1.E-07 
1.E-06 
1.E-05 
1.E-04 
1.E-03 
1.E-02 
Total 
Water 
Ingestion 
Inhalation 
External 
BDCF (rem/yr per pCi/L) 
Uranium-233 
1.E-09 
1.E-08 
1.E-07 
1.E-06 
1.E-05 
1.E-04 
1.E-03 
1.E-02 
1.E-01 
Total 
Water 
Ingestion 
Inhalation 
External 
BDCF (rem/yr per pCi/L) 
Neptunium-237 
1.E-06 
1.E-05 
1.E-04 
1.E-03 
1.E-02 
1.E-01 
Total 
Water 
Ingestion 
Inhalation 
External 
BDCF (rem/yr per pCi/L) 
Plutonium-239 
1.E-08 
1.E-07 
1.E-06 
1.E-05 
1.E-04 
1.E-03 
1.E-02 
1.E-01 
Total 
Water 
Ingestion 
Inhalation 
External 
BDCF (rem/yr per pCi/L)

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6.2.3 Sources of Uncertainty in the Biosphere Dose Conversion Factors 
The source of variance in the BDCF values (see Figures 6.2-1 to 6.2-4) is the uncertainty and 
variability in the values of the input parameters for the biosphere model. The pathway 
importance and uncertainty contributions from the input parameters are not necessarily related. 
Frequently, the parameters that contribute the most to important pathways do not contribute to an 
appreciable degree, or even at all, to the variance in the BDCF. The obvious examples are 
parameters that are fixed, such as consumption of drinking water and the dose coefficients. 
This section discusses the degree to which individual input parameters influences the BDCFs. 
This was quantified by calculation of rank correlation coefficients. A correlation coefficient is a 
number between -1 and 1 that measures the degree to which two variables are linearly related. 
6.2.3.1 Correlation Statistics for the Selected Radionuclides 
Correlation coefficients for the stochastic model input parameters and BDCFs for the 
groundwater exposure scenario were calculated for the selected radionuclides (14C, 99Tc, 129I, 
233U, 237Np, and 239Pu) (see Excel file GW MC Correlations.xls in Appendix A). The results are 
presented in Table 6.2-3 for the present-day climate. Only those correlations that are non-zero at 
the 99 percent confidence interval (absolute value of the correlation coefficient equal or greater 
than 0.0812) are shown in the table, plus the next correlation that is below this threshold (see 
Section 6.2.3.2 for calculation of the statistically significant value). The list includes the false 
correlations that are above the threshold value, as explained in Section 6.2.3.2. 
Table 6.2-3. Correlation Coefficients for the Input Parameters and Biosphere Dose Conversion Factors 
for the Groundwater Exposure Scenario and the Present-Day Climate 
Radionuclide 
Parameter Name 
Correlation 
Coefficient 
Correlation 
Coefficient Squared 
Bioaccumulation factor for fish 0.886 0.786 
Fish Consumption rate 0.309 0.096 
Wind Speed for Crops -0.179 0.032 
Daily irrigation rate for other vegetables 0.108 0.012 
Protactinium partition coefficient (Kd) -0.097 0.009 
Milk consumption rate 0.089 0.008 
Protactinium transfer factor for other vegetables a 0.087 0.008 
Beef consumption rate 0.085 0.007 
Protactinium transfer factor for leafy vegetables a 0.083 0.007 
Carbon-14 
Leafy vegetable consumption rate 0.078 0.006 
Overwatering rate -0.637 0.406 
Technetium transfer coefficient for milk 0.265 0.070 
Technetium transfer factor for leafy vegetables 0.201 0.040 
Technetium transfer coefficient for meat 0.179 0.032 
Technetium transfer factor for fruit 0.174 0.030 
Technetium transfer coefficient for eggs 0.159 0.025 
Technetium-99 
Technetium transfer factor for grain 0.141 0.020 

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Table 6.2-3. Correlation Coefficients for the Input Parameters and Biosphere Dose Conversion Factors 
for the Groundwater Exposure Scenario and the Present-Day Climate (Continued) 
Radionuclide 
Parameter Name 
Correlation 
Coefficient 
Correlation 
Coefficient Squared 
Dry-to-wet weight ratio for fruit 0.141 0.020 
Technetium transfer factor for cattle forage 0.137 0.019 
Technetium transfer factor for other vegetables 0.131 0.017 
Weathering half-life 0.129 0.017 
Technetium partition coefficient (Kd) -0.125 0.016 
Irrigation amount for cattle forage -0.112 0.012 
Annual long-term irrigation rate 0.111 0.012 
Uranium bioaccumulation factor for fish a -0.106 0.011 
Translocation factor for other vegetables, fruits 
and grains 0.095 0.009 
Uranium transfer coefficient for eggs a -0.086 0.007 
Technetium-99 
(Continued) 
Neptunium transfer factor for cattle forage a 0.074 0.006 
Iodine partition coefficient (Kd) 0.325 0.106 
Weathering half-life 0.307 0.094 
Overwatering rate -0.273 0.075 
Iodine transfer factor for fruit -0.260 0.068 
Iodine transfer coefficient for eggs 0.251 0.063 
Iodine transfer factor for other vegetables -0.235 0.055 
Iodine transfer factor for leafy vegetables -0.228 0.052 
Iodine bioaccumulation factor for fish 0.207 0.043 
Iodine transfer factor for cattle forage -0.206 0.042 
Iodine transfer factor for grain -0.204 0.042 
Yield, forage -0.196 0.038 
Translocation factor for other vegetables, fruits 
and grains 0.183 0.034 
Irrigation intensity -0.163 0.027 
Iodine transfer coefficient for meat 0.157 0.025 
Iodine transfer coefficient for milk 0.153 0.023 
Dry biomass, forage 0.121 0.015 
Eggs consumption rate 0.110 0.012 
Fish consumption rate 0.095 0.009 
Mass loading in inactive outdoors environment 0.088 0.008 
Tin transfer coefficient for meat a 0.085 0.007 
Iodine-129 
Technetium transfer coefficient for poultry a 0.079 0.006 
Uranium partition coefficient (Kd) 0.822 0.676 
Uranium transfer factor for fruit -0.655 0.429 
Uranium transfer factor for cattle forage -0.651 0.423 
Uranium transfer factor for grain -0.645 0.416 
Uranium transfer factor for leafy vegetables -0.629 0.395 
Uranium-233 
Uranium transfer factor for other vegetables -0.612 0.375 

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Table 6.2-3. Correlation Coefficients for the Input Parameters and Biosphere Dose Conversion Factors 
for the Groundwater Exposure Scenario and the Present-Day Climate (Continued) 
Radionuclide 
Parameter Name 
Correlation 
Coefficient 
Correlation 
Coefficient Squared 
Overwatering rate -0.245 0.060 
Evaporative cooler water transfer fraction 0.212 0.045 
Erosion rate -0.184 0.034 
Enhancement factor for active outdoors 
environment 0.167 0.028 
Mass loading for active outdoors environment 0.136 0.019 
Deposition velocity 0.115 0.013 
Soil depth 0.109 0.012 
Fraction of non-workers -0.083 0.007 
Uranium-233 
(Continued) 
Time spent in active outdoors environment by 
commuters 0.070 0.005 
Overwatering rate -0.519 0.269 
Neptunium partition coefficient (Kd) 0.471 0.222 
Neptunium transfer factor for other vegetables -0.380 0.145 
Neptunium transfer factor for cattle forage -0.380 0.144 
Neptunium transfer factor for leafy vegetables -0.369 0.136 
Evaporative cooler water transfer fraction 0.362 0.131 
Neptunium transfer factor for grain -0.361 0.130 
Neptunium transfer factor for fruit -0.277 0.077 
Enhancement factor for active outdoors 
environment 0.217 0.047 
Mass loading for active outdoors environment 0.183 0.033 
Neptunium bioaccumulation factor for fish 0.117 0.014 
Deposition velocity 0.099 0.010 
Time spent in active outdoors environment by 
non-workers 0.095 0.009 
Erosion rate -0.093 0.009 
Thorium transfer factor for grain a -0.087 0.008 
Strontium transfer coefficient for milk a 0.085 0.007 
Water usage in evaporative coolers 0.085 0.007 
Long-term irrigation 0.084 0.007 
Poultry consumption rate -0.083 0.007 
Weathering half-life 0.083 0.007 
Cesium transfer coefficient for eggs a 0.081 0.007 
Neptunium-237 
Ventilation rate for evaporative coolers 0.078 0.006 
Erosion rate -0.534 0.285 
Mass loading for active outdoors environment 0.475 0.226 
Enhancement factor for active outdoors 
environment 0.368 0.135 
Plutonium partition coefficient (Kd) 0.265 0.070 
Plutonium-239 
Plutonium transfer factor for leafy vegetables -0.220 0.048 

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Table 6.2-3. Correlation Coefficients for the Input Parameters and Biosphere Dose Conversion Factors 
for the Groundwater Exposure Scenario and the Present-Day Climate (Continued) 
Radionuclide 
Parameter Name 
Correlation 
Coefficient 
Correlation 
Coefficient Squared 
Plutonium transfer factor for cattle forage -0.213 0.045 
Plutonium transfer factor for fruit -0.209 0.043 
Evaporative cooler water transfer fraction 0.199 0.040 
Plutonium transfer factor for other vegetables -0.191 0.036 
Plutonium transfer factor for grain -0.188 0.035 
Overwatering rate -0.166 0.028 
Time spent in active outdoors environment by 
commuters 0.142 0.020 
Plutonium bioaccumulation factor for fish 0.119 0.014 
Time spent in active outdoors environment by 
non-workers 0.111 0.012 
Fraction of outdoor workers 0.109 0.012 
Actinium bioaccumulation factor for fish a -0.107 0.011 
Weathering half-life 0.106 0.011 
Tin bioaccumulation factor for fish a -0.099 0.010 
Daily irrigation rate for other vegetables 0.096 0.009 
Uranium transfer coefficient for poultry a -0.086 0.007 
Plutonium-239 
(Continued) 
Deposition velocity 0.074 0.005 
Source: Excel file GW MC Correlations.xls (Appendix A). 
a False correlations, as explained in Section 6.2.3.2. 
For 14C, the greatest correlations are with the bioaccumulation factor in fish and the consumption 
rate of fish. Fish consumption is also the most important pathway (see Table 6.2-1). The other 
high correlation for the 14C BDCF is a negative correlation with wind speed, which controls the 
activity concentration in the mixing cell for carbon dioxide released from the soil and thus crop 
uptake of 14C through photosynthesis. 
For 99Tc, the greatest correlation is with the overwatering rate. Overwatering rate is used to 
calculate the leaching removal constant (Section 6.2.4.1), which, in turn, affects the activity 
concentration in the soil and thus root uptake. BDCFs for 99Tc are also correlated with the 
animal transfer coefficients, soil-to-plant transfer factors, weathering half-life, irrigation rates, 
and partition coefficient (Kd). 
Parameters that influence the BDCF for 129I are related to radionuclide transport to soil, crops, 
and animal products. The weathering half life and the translocation factor that control the 
amount of activity externally deposited on a plant remaining in an edible product have higher 
correlation coefficients than those for 99Tc, indicating that this transport mechanism is more 
important for 129I than it is for 99Tc. 
The variance in the BDCF for 233U has its source primarily in the Kd value followed by the 
transfer factors for crops. Other parameters that influence the level of radionuclides in the soil, 
such as the overwatering rate and erosion rate, are also important. In addition, some parameters 

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ANL-NBS-MD-000014 REV 00 6-21 October 2004 
in the calculation of the inhalation dose from airborne particulate matter and aerosols generated 
by evaporative coolers contribute to a lesser degree to variance in the BDCF. 
For 237Np and 239Pu, air mass loading for the active outdoors environment and the enhancement 
factor for the same environment are among the input parameters with high correlation 
coefficients. The parameters that control the equilibrium level of activity concentration in the 
soil, such as the Kds and overwatering rate also tend to appear near the top of the list. 
Soil-to-plant transfer factors also have high correlation coefficients for these radionuclides 
because of the negative correlation between Kds and transfer factors built into the biosphere 
model. 
6.2.3.2 Calculation of Correlation Statistics for Stochastic Input Parameters and 
Biosphere Dose Conversion Factors 
The GoldSim code used to generate the stochastic BDCF distributions provides the user with the 
capability to calculate correlation coefficients between any two or more distributions. This 
capability is used to provide a convenient indication of those input parameters that have a 
significant effect on the model results (i.e., the BDCFs). For example, for the BDCFs for 99Tc 
presented in Table 6.2-3, the parameters with the absolute value of the correlation coefficient 
greater than or equal to 0.125 are provided in Table 6.2-4. 
Table 6.2-4. Correlation Coefficients between BDCF Values for 99Tc and Input Parameters with Absolute 
Values Greater than 0.125 
GoldSim Input Parameter Correlation Coefficient 
Overwatering rate -0.637 
Technetium transfer coefficient for milk 0.265 
Technetium transfer factor for leafy vegetables 0.201 
Technetium transfer coefficient for meat 0.179 
Technetium transfer factor for fruit 0.174 
Technetium transfer coefficient for eggs 0.159 
Technetium transfer factor for grain 0.141 
Dry-to-wet weight ratio for fruit 0.141 
Technetium transfer factor for cattle forage 0.137 
Technetium transfer factor for other vegetables 0.131 
Weathering half-life 0.129 
Technetium partition coefficient (Kd) -0.125 
Source: Excel file GW MC Correlations.xls (Appendix A). 
Kd=partition coefficient 
As there are almost 300 stochastic input parameters for the groundwater exposure scenario, it is 
of interest to determine a value for the correlation coefficient below which there is no statistical 
significance, in order to identify those parameters that are inconsequential in determining the 
BDCFs. The details of such an approach is presented in Steel and Torrie (1980 [DIRS 150857] 
p. 279) where to test the null hypothesis of the true correlation coefficient (.) being zero, the 
measured correlation coefficient (r) is used to calculate t from Equation 6.2-1. The value of t is 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-22 October 2004 
then compared with Students t for n-2 degrees of freedom (n = the number of data points used to 
derive r) for the required confidence interval. 
) 2 /( ) 1 ( 2 - - 
= 
n r 
r t (Eq. 6.2-1) 
For generating the BDCFs, the number of realizations (n) was 1,000. For a large number of 
degrees of freedom, the Students t distribution is closely approximated by the normal 
distribution, so the 95 percent confidence interval for the absolute value of t is 1.96. Substituting 
these values into Equation 6.2-1 results in an absolute value of r, below which the null 
hypothesis would not be rejected, as 0.062. The corresponding absolute value at the 99 percent 
confidence limit for rejecting the null hypothesis is 0.0812. 
When setting up GoldSim to conduct correlation coefficient calculations, the user selects the 
parameter against which the correlation will be made. In this case, the parameter is the output 
BDCF array. The user either can select, on a one-by-one basis, the input parameter distributions 
to use for the correlation or nominate to do the correlation matrix for all stochastic parameters. 
Without any prior sensitivity analysis, there is no basis to select any particular set of parameters 
for the correlation analysis; the normal default is to use all stochastic inputs to generate the 
matrix. In following this path, GoldSim automatically includes the radionuclide specific 
parameters for all radionuclides and not just the set for the radionuclide under consideration. In 
the case of 99Tc, some of these additional parameters are determined to be potentially significant, 
as shown in Table 6.2-5. 
Table 6.2-5. Observed Correlation Coefficients between 99Tc BDCF Values and Input Parameters for 
Other Radionuclides 
GoldSim Input Parameter Correlation Coefficient 
Irrigation amount for cattle forage -0.112 
Long-term irrigation rate 0.111 
Uranium bioaccumulation factor for fish -0.106 
Translocation factor for other vegetables, fruits and grains 0.095 
Uranium transfer coefficient for eggs -0.086 
Source: Excel file GW MC Correlations.xls (Appendix A). 
From the previous discussion on the significance of the parametric correlation, Table 6.2-5 
appears to indicate some unexpected parameter correlation being generated by the GoldSim 
approach. Further investigation illustrates that the results in Table 6.2-5 are predictable. 
In the 99Tc example, there are 172 stochastic parameters included in the biosphere model that are 
not associated with 99Tc but are associated with all the other radionuclides included in the model. 
GoldSim, once set up for a scenario, keeps track of all parameters whether or not they are 
radionuclide specific. Thus, by selecting to generate the correlation matrix for all stochastic 
parameters, these (redundant) 172 parameters are automatically included. The alternative, but 
tedious and error prone, approach is to individually select, one by one, the 100+ parameters that 
are used for the radionuclide being evaluated. 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-23 October 2004 
When the statistical approach is used to test the null hypothesis that the actual correlation is not 
significantly different from zero, it is necessary to establish a confidence interval for 
accepting/rejecting the hypothesis. At the 95 percent confidence interval, a value is established 
for the measured correlation coefficient; if the correlation coefficient is less than this value, it is 
postulated that there are no underlying correlation between variables. If random tests (i.e., the 
GoldSim model run with a new random number seed) were performed a large number of times, 
in only 5 percent of cases would the observed value of the correlation lead to the rejection of the 
null hypothesis (i.e., exceed the cut-off value). 
In the reported case, although GoldSim was run only once, the random test applies to each of the 
172 parameters for which there is no 99Tc dependency. The analysis of calculating the measured 
and expected number of significant non-zero correlation values is relatively simple and is 
reported in Table 6.2-6 for the 172 independent (i.e., not correlated) parameters. The data in 
Excel file GW MC Correlations.xls (Appendix A) show that the observed number of false 
correlation events is in line with the expected number. Consequently, GoldSim is behaving in a 
logical and consistent manner. 
Table 6.2-6. The Number of Expected and Observed False Correlation Values for Independent Input 
Parameters as a Function of Confidence Level 
Confidence Level t a 
Correlation 
Coefficient b Expected Number c Observed Number d 
5.0% 1.96 0.062 8.6 7 
2.0% 2.33 0.074 3.4 4 
1.0% 2.58 0.081 1.7 2 
0.2% 3.10 0.098 0.3 1 
a Value of t (see Equation 6.2-1) corresponding to the confidence level shown in the first column (from Steel and 
Torrie 1980 [DIRS 150857], Table A.4) 
b Correlation coefficient corresponding to the value of t (see Excel file GW MC Correlations.xls (Appendix A) 
c Calculated as a product of the confidence level (first column) and 172 parameters. 
d From Excel file GW MC Correlations.xls (Appendix A) 
6.2.4 Analysis of the Environmental Transport Pathways and Radionuclide 
Accumulation in the Environmental Media 
The dose to the receptor from radionuclides in well water arises from the transport of 
radionuclides from water to environmental media (environmental transport pathways) and from 
human exposure to these media (receptor exposure pathways). 
For many radionuclides, especially non-actinides, consumption of locally produced food is an 
important contributor to BDCFs. The doses from consumption of locally produced food depend 
on the radionuclide concentration in these foods and on their respective consumption rates. The 
relative importance of transport processes that contribute to radionuclide concentration in locally 
produced foods is discussed in this section. 
Environmental transport pathways lead to radionuclide accumulation in the environmental 
media. The environmental media included in the biosphere model for the groundwater exposure 
scenario include well water (groundwater), surface soil, air, plants, animals, and fish. For the 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-24 October 2004 
groundwater exposure scenario, water is the source of contamination in the biosphere. Surface 
soil becomes contaminated when well water is used for irrigation. Airborne contamination is a 
result of resuspension of contaminated soil and operation of evaporative coolers. Radionuclide 
accumulation in plants occurs as a result of transport from water, soil, and air. The source of 
radionuclide intake by animals is water, fodder crops, and soil. 
6.2.4.1 Radionuclide Accumulation in Surface Soil 
In the groundwater exposure scenario, surface soil is an environmental medium that can be 
considered a secondary source of contamination for many environmental transport and receptor 
exposure pathways (groundwater is a primary source). These pathways include resuspension of 
soil particles with the subsequent deposition on crops or inhalation by humans, external 
exposure, radionuclide uptake by crops through their roots, emission of radioactive gasses and 
their transport to crops and humans, and soil ingestion by humans and animals. In fact, there are 
only a few transport processes and pathways in the biosphere model that do not originate in the 
soil, namely the deposition of contaminated water on crop surfaces, water ingestion by humans 
and animals, and radionuclide bioaccumulation in fish. For the remaining pathways, activity 
concentration in soil has a direct effect on the outcome of the relevant submodels. 
The source of radionuclides in the surface soil is from groundwater used for irrigation. The 
buildup of radionuclides in soil from this input is offset by the processes that remove 
radionuclides from the soil. Removal processes include leaching, surface soil erosion, and 
radioactive decay (a removal mechanism for the parent radionuclide, but a source for the decay 
product). Radionuclide concentrations in surface soil are calculated for equilibrium conditions. 
Generally, the change in radionuclide concentration in soil is equal to the rate of radionuclide 
input (irrigation), minus the rate of radionuclide loss. For equilibrium conditions, the rate of 
radionuclide addition is equal to the rate of radionuclide removal, with concentrations in the 
surface soil remaining constant. The biosphere model uses equilibrium radionuclide 
concentrations in surface soil for predicting root uptake of activity, for calculating radionuclide 
concentration in the atmosphere from resuspension of soil particles (for inhalation and 
attachment to foliage), and for inadvertent soil ingestion. The radionuclide concentration in 
surface soil is calculated in the biosphere model as (adapted from BSC 2004 [DIRS 169460], 
Equation 6.4.1-4): 
eff e l d 
IR Cw IR Cw Cs 
. . . . 
= 
+ + 
= (Eq. 6.2-2) 
where 
Cs = equilibrium activity concentration of the radionuclide in surface soil per unit 
area (Bq m-2) 
Cw = activity concentration of the radionuclide in the groundwater (Bq m-3) 
IR = annual average irrigation rate on land (annual irrigation rate) (m yr-1) 
.d 
= radioactive decay constant for the radionuclide (yr-1) 
.l 
= average annual leaching removal constant for the radionuclide (yr-1) 
.e = average annual surface soil erosion removal constant (yr-1). 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-25 October 2004 
.eff = effective removal constant 
Equation 6.2-2 shows that the equilibrium radionuclide concentration in soil is directly 
proportional to the irrigation rate. The typical range of irrigation rates is from 0.5 to 1.0 m/yr 
(BSC 2004 [DIRS 169673], Section 6.5.2). The average irrigation rate is time-dependent 
because of climate changes predicted for the Yucca Mountain region over the period of interest. 
However, because stochastic BDCFs are defined for each climate state predicted to occur to 
10,000 years in the future, the average irrigation rate for a given climate is not a function of time. 
Annual average irrigation rates were developed using Food and Agriculture Organization 
methods based on determination of crop water requirements, which are calculated from 
evapotranspiration of a grass reference surface and adjusted with a crop-specific coefficient 
(BSC 2004 [DIRS 169673], Section 6.5.2). Parameter inputs were growing season lengths, 
average monthly weather data for the climate states under consideration, as well as salinity of 
irrigation water. These parameters are site-specific. The probability distribution of irrigation 
rate that is representative of long-term averages was developed such that the range of values 
extends from the 1st to 99th percentile of the irrigation rate values for representative crops. The 
dependence of the BDCFs on the value of annual average irrigation rate is shown in Figure 6.2-8 
for selected radionuclides (see Excel file Dependence of GW BDCFs on Inputs.xls in 
Appendix A). 
The graphs were plotted using averaged values of the independent and dependent variables. If 
the unsorted data for individual realizations are plotted, the stochastic variability among BDCFs 
from the multiple random inputs results in plots that show little discernable trend. To generate a 
graph illustrating the effects of an input parameter on BDCFs, averaging over realizations was 
required to minimize the impact of other variables. The results of model realizations were sorted 
by the value of the independent variable (here the annual average irrigation rate). Then the 
irrigation rates and the corresponding BDCFs were averaged in blocks of 100 values. The 
calculations were performed and the graph generated in an Excel spreadsheet (Dependence of 
GW BDCFs on Inputs.xls, Appendix A). The triangle symbols in the graph represent the mean 
of 100 values. The error bars represent the uncertainty range for the mean at the 95 percent 
uncertainty interval, calculated as 1.96 times the standard error of the mean. The standard error 
was calculated as standard deviation of the BDCF values in a block of 100 values divided by a 
square root of the number of results in a block, that is, 10 100 = . 
There is one data point in the 99Tc graph (Figure 6.2-8) that is an outlier with a high BDCF 
value. If included in the plots, this outlier results in large error bars for the point that includes 
this value in the corresponding bin with 100 BDCF values. To better show the relationship 
between the input parameter and the BDCFs, this point was removed from the graphs for 99Tc 
presented further in this analysis report. 

ANL-NBS-MD-000014 REV 00 6-26 October 2004 
Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
Source: Excel file Dependence of GW BDCFs on Inputs.xls (Appendix A). 
NOTE: The triangles represent the mean of 100 values. The error bars represent the uncertainty range for the mean at the 95 percent uncertainty interval, 
calculated as 1.96 times the standard error of the mean. The outlier point with a high BDCF value for 99Tc was removed to better show the trend in the 
BDCFs for this radionuclide as a function of the irrigation rate. 
Figure 6.2-8. Dependence of BDCF for the Groundwater Exposure Scenario and Present-Day Climate on Annual Average Irrigation Rate 
Technetium-99 
1.4E-06 
1.6E-06 
1.8E-06 
2.0E-06 
2.2E-06 
2.4E-06 
2.6E-06 
2.8E-06 
3.0E-06
0.80 0.85 0.90 0.95 1.00 1.05 1.10 
Annual average irrigation rate (m/yr) 
BDCF (rem/yr per pCi/L) Uranium-233 
1.0E-03 
1.4E-03 
1.8E-03 
2.2E-03 
2.6E-03 
3.0E-03
0.80 0.85 0.90 0.95 1.00 1.05 1.10 
Annual average irrigation rate (m/yr) 
BDCF (rem/yr per pCi/L) 
Neptunium-237 
6.0E-03 
6.5E-03 
7.0E-03 
7.5E-03 
8.0E-03 
8.5E-03 
9.0E-03 
9.5E-03 
1.0E-02
0.80 0.85 0.90 0.95 1.00 1.05 1.10 
Annual average irrigation rate (m/yr) 
BDCF (rem/yr per pCi/L) 
Plutonium-239 
6.0E-03 
7.0E-03 
8.0E-03 
9.0E-03 
1.0E-02 
1.1E-02 
1.2E-02
0.80 0.85 0.90 0.95 1.00 1.05 1.10 
Annual average irrigation rate (m/yr) BDCF (rem/yr per pCi/L)

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-27 October 2004 
The graphs in Figure 6.2-8 show that there is a positive relationship between BDCFs and 
irrigation rate in the upper part of the range of irrigation rates used in the model (annual average 
irrigation rate greater than about 1 m/yr). This dependence is stronger for the radionuclides that 
strongly adsorb to soil particles (i.e., have high Kd values), such as 237Np and 239Pu. For these 
radionuclides, the difference between the average BDCF value using the minimum of the 
irrigation rate range and the BDCF value calculated using the maximum was assessed in 
deterministic runs of the biosphere model. The input parameter values used in the model were 
presented in Tables 4.1-1 to 4.1-4. For the stochastic model parameters, these values are either 
the distribution means or the values that best represent a distribution, such as the mode. The 
results are summarized in Table 6.2-7. 
Table 6.2-7. BDCF and Percent Change from Average for Different Levels of Annual Average 
Irrigation Rate 
Neptunium-237 Plutonium-239 
Irrigation 
Conditions Irrigation, m/yr BDCF 
Percent Change 
from Average BDCF 
Percent Change 
from Average 
Average 0.95 5.35E-03 N/A 7.68E-03 N/A 
Minimum 0.74 5.12E-03 -4.2 6.75E-03 -12.1 
Maximum 1.16 5.58E-03 4.2 8.61E-03 12.1 
Alfalfa 1.94 6.42E-03 19.9 1.21E-02 57.0 
NOTE: BDCFs were calculated in deterministic runs of ERMYN_GW_MC8_Det_Base.gsm by changing the 
radionuclide selection and the value of annual average irrigation rate. The percent change for the BDCFs 
was calculated in the Excel spreadsheet Dependence of GW BDCFs on Inputs.xls (Appendix A). 
The results of the BDCF calculations using different irrigation rates indicate that the BDCFs for 
237Np are relatively insensitive to the value of the annual average irrigation rate and that the 
value varies by only about  4 percent over the variability range of this parameter. If a higher 
value of the irrigation rate is used, which is typical of alfalfa, the BDCF for 237Np is about 
20 percent greater than the average. For 239Pu, the differences are greater: about  12 percent 
over the variability range and up to 57 percent higher for the irrigation rate of alfalfa. 
Offsetting radionuclide addition from irrigation are the processes that remove radionuclides from 
surface soil. These processes are collectively represented in the model by the effective removal 
constant in Equation 6.2-2. The biosphere model includes removal of radionuclides from surface 
soil by radioactive decay, leaching to the deep soil, and soil erosion. 
The surface soil erosion removal constant, .e 
, represents the rate of radionuclide loss from the 
surface soil due to wind (dominant for the present-day climate) as well as surface erosion from 
occasional heavy precipitation (an important contributor to erosion in the future climate). This 
parameter is calculated in the biosphere model (BSC 2004 [DIRS 169460], Equation 6.4.1-11) 
using the annual average erosion rate for the surface soil, representing the removal of soil mass 
per unit area per unit time, and the surface soil depth and density. The value of annual average 
erosion rate is a radionuclide-independent parameter that is strongly site-specific and depends on 
environmental characteristics and land use. The range of the soil erosion rate is from 0.19 to 
1.1 kg/(m2 yr), which, when divided by the density of surface soil (65 to 510 kg/m2), gives the 
erosion rate constant range from about 0.0004 to about 0.017 per year (from the modeling results 
included in the Excel file Dependence of GW BDCFs on Inputs.xls, Appendix A). The soil 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-28 October 2004 
erosion rate was developed from the information include in the U.S. Department of Agriculture 
Natural Resources Conservation Service database and from other literature sources. The values 
were selected such that they are representative of the types of soils, climate, and land use 
conditions in Amargosa Valley (BSC 2004 [DIRS 169459]). 
To illustrate the dependence of BDCFs on the values of erosion rate, graphs were produced, 
similar to those shown in Figure 6.2-8 for irrigation rates. These graphs show the BDCF 
dependence on the value of erosion rate used in the biosphere model for 99Tc, 233U, 237Np, and 
239Pu. The graphs were plotted using averaged values of the independent and dependent variables 
in blocks of 100 data pairs, as explained before, and are shown in Figure 6.2-9. 
A few observations can be made based on Figure 6.2-9. First, the BDCFs for 99Tc are 
independent of erosion rate. This is because technetium is an element that has a relatively low 
Kd and thus leaching is a much more important radionuclide removal mechanism than soil 
erosion. Second, soil erosion is important for those radionuclides that have a moderate (233U and 
237Np) and high value of Kd (239Pu). For these radionuclides, a strong dependence on the erosion 
rate can be observed, especially in the lower region of the parameter range. In this region of the 
parameter range, the effectiveness of soil erosion as a mechanism of radionuclide removal from 
surface soil is diminished and radionuclides build up in surface soil. For the higher erosion rate, 
the BDCFs for these radionuclides seem to asymptotically converge to a constant BDCF value, 
which is consistent with the functional relationship of the equilibrium activity concentration in 
the soil and the erosion rate constant, which is of the 
x 
x f 1 ) ( = type. In this region, the removal 
processes effectively reduce the activity concentration in the soil and the BDCF is controlled by 
other pathways that are not related to radionuclide concentration in the surface soil, such as 
consumption of water, or ingestion of crops contaminated by deposition of water on the foliage. 
In fact, for the highly sorbing radionuclides, their uptake by crops from soil is a less important 
mechanism than the radionuclide deposition on plant surfaces from irrigation as discussed in 
Section 6.2.4.3. 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-29 October 2004 
Source: Excel file Dependence of GW BDCFs on Inputs.xls (Appendix A). 
NOTE: The triangles represent the mean of 100 values. The error bars represent the uncertainty range for the mean at the 95 percent uncertainty interval, 
calculated as 1.96 times the standard error of the mean. The outlier point with a high BDCF value for 99Tc was removed to better show the trend in the 
BDCFs for this radionuclide as a function of the erosion rate. 
Figure 6.2-9. Dependence of BDCF for the Groundwater Exposure Scenario and Present-Day Climate on Soil Erosion Rate 
Technetium-99 
1.0E-06 
1.5E-06 
2.0E-06 
2.5E-06 
3.0E-06 
3.5E-06 
4.0E-06 
0.2 0.4 0.6 0.8 1.0 
Erosion rate (kg/(m2 yr)) 
BDCF (rem/yr per pCi/L) 
Uranium-233 
0.0E+00 
1.0E-03 
2.0E-03 
3.0E-03 
4.0E-03 
5.0E-03 
0.2 0.4 0.6 0.8 1.0 
Erosion rate (kg/(m2 yr)) 
BDCF (rem/yr per pCi/L) 
Neptunium-237 
6.0E-03 
7.0E-03 
8.0E-03 
9.0E-03 
0.2 0.4 0.6 0.8 1.0 
Erosion rate (kg/(m2 yr)) 
BDCF (rem/yr per pCi/L) 
Plutonium-239 
6.0E-03 
8.0E-03 
1.0E-02 
1.2E-02 
1.4E-02 
1.6E-02 
0.2 0.4 0.6 0.8 1.0 
Erosion rate (kg/(m2 yr)) 
BDCF (rem/yr per pCi/L)

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-30 October 2004 
Another process that results in radionuclide removal from surface soil is leaching. The process 
of leaching radionuclides from the surface soil is evaluated using element-specific leaching 
removal constants (BSC 2004 [DIRS 169460], Section 6.4.1.3). The leaching removal constant 
for each radionuclide (.l) is calculated using a relationship (adopted from BSC 2004 
[DIRS 169460], Equation 6.4.1-10) 
.. 
. 
.. 
. 
.
. 
+ .  
= . 
d 
l 
K d 
OW 
1 
(Eq. 6.2-3) 
where 
OW = crop overwatering rate (m/yr) 
d = depth of surface soil (m) 
. 
= bulk density of surface soil (kg/m3) 
. = volumetric water content of soil (dimensionless) 
Kd = solid-liquid partition coefficient for the radionuclide in surface soil 
(Bq/kg solid)/(Bq/m3 
liquid) = (m3 
liquid /kg solid) 
The value of the leaching removal constant is influenced by the overwatering rate, OW, 
soil-liquid partition coefficient, Kd, and other parameters that characterize soil properties. 
Soil-specific parameters were taken from the U.S. Department of Agriculture Natural Resources 
Conservation Service database and from other literature sources. The values were selected such 
that they are representative of the types of soils, climate, and land use conditions in Amargosa 
Valley (BSC 2004 [DIRS 169459], Section 4.1). The volumetric water content of soil is defined 
as the fraction of the soil volume representing water-filled porosity. The value of this parameter 
depends on soil texture and ranges from less than 0.1 (dry soils) to between 0.4 and 0.5 
(water-saturated soils) for the soil types in Amargosa Valley, with typical values of about 
0.2 to 0.3. 
The value of the overwatering rate was developed for representative crops based on the crop 
leaching fraction (the amount of water applied in addition to crop water requirements to remove 
excess salts from the root zone) or the deep percolation of precipitation below the crop root zone. 
As shown in Table 6.2-3, the overwatering rate has a high correlation coefficient with BDCFs for 
most radionuclides. In arid regions, the overwatering rate usually is determined by calculating 
the amount of water required to transport accumulated salts out of the surface soil to maintain 
productivity. The value of this parameter is on the order of 10 cm/yr (BSC 2004 [DIRS 169673], 
Section 6.9). 
The dependence of BDCFs for selected radionuclides on the value of the overwatering rate is 
shown in Figure 6.2-10 (see Excel file Dependence of GW BDCFs on Inputs.xls, Appendix A). 
It can be seen that the BDCFs decrease as overwatering increases for all radionuclides. This is 
because overwatering causes leaching of radionuclides out of the surface soil thus decreasing the 
level of equilibrium radionuclide concentration in the soil. Decreased activity concentration in 
the soil results in less activity available for plant root uptake and leads to a reduced ingestion 
dose as well as reduced inhalation and external exposures. The strength of the correlation with 
the overwatering rate can be seen by the range of the error bars for the radionuclides shown in 
Figure 6.2-10. 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-31 October 2004 
Source: Excel file Dependence of GW BDCFs on Inputs.xls (Appendix A). 
NOTE: The triangles represent the mean of 100 values. The error bars represent the uncertainty range for the mean at the 95 percent uncertainty interval, 
calculated as 1.96 times the standard error of the mean. The outlier point with a high BDCF value for 99Tc was removed to better show the trend in the 
BDCFs for this radionuclide as a function of the overwatering rate. 
Figure 6.2-10. Dependence of BDCF for the Groundwater Exposure Scenario and Present-Day Climate on Overwatering Rate 
Uranium-233 
5.0E-04 
1.0E-03 
1.5E-03 
2.0E-03 
2.5E-03 
3.0E-03 
3.5E-03
0.00 0.05 0.10 0.15 0.20 0.25 
Overwatering rate (m/yr) 
BDCF (rem/yr per pCi/L) 
Neptunium-237 
4.0E-03 
6.0E-03 
8.0E-03 
1.0E-02 
1.2E-02
0.00 0.05 0.10 0.15 0.20 0.25 
Overwatering rate (m/yr) 
BDCF (rem/yr per pCi/L) 
Plutonium-239 
7.0E-03 
8.0E-03 
9.0E-03 
1.0E-02 
1.1E-02 
1.2E-02
0.00 0.05 0.10 0.15 0.20 0.25 
Overwatering rate (m/yr) 
BDCF (rem/yr per pCi/L) 
Technetium-99 
1.0E-06 
2.0E-06 
3.0E-06 
4.0E-06 
5.0E-06
0.00 0.05 0.10 0.15 0.20 0.25 
Overwatering rate (m/yr) 
BDCF (rem/yr per pCi/L)

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-32 October 2004 
The leaching removal constant also depends on the value of Kd. The Kds, in turn, depend on soil 
characteristics, with values spanning several orders of magnitude (with geometric means from 
0.14 L/kg for technetium to 3.6  104 L/kg for radium) (BSC 2004 [DIRS 169459], 
Section 7.1.2). The overall uncertainty in the Kd values is the greatest of all biosphere model 
parameters. To illustrate the overall effect of the uncertainty in the Kd values on the biosphere 
modeling results, plots were generated that show the dependence of BDCFs on Kd values. The 
plots (Figure 6.2-11) were constructed for the same four radionuclides as for the preceding plots. 
These radionuclides represent distributions with high (239Pu), moderate (237Np and 233U), and low 
(99Tc) mean values of Kds. 
Figure 6.2-11 shows that although the range of Kd values covers several orders of magnitude, the 
impact of these large changes in Kd values on BDCF values is less than a factor of 2 about the 
mean value for most radionuclides. For 237Np and 233U, elements with a moderate value of Kd, 
there is little change in BDCF values for Kd values at the low end of the range. In this region, 
leaching is efficient and little buildup is expected. At higher Kd values, the BDCFs increase due 
to radionuclide retention in the soil. BDCF values for a radionuclide with a high Kd (239Pu) 
gradually increases as Kd increases (due to low leaching and thus greater buildup in soil), but 
converge to a fixed value at high Kd values. In this region of high Kd values, BDCFs no longer 
increase as Kds increase because the equilibrium radionuclide concentration in surface soil is 
controlled by soil erosion. 
Technetium has the lowest mean Kd of those considered for TSPA (a geometric mean of 
0.14 L/kg compared to the next lowest of 4.5 L/kg for iodine). The BDCFs for 99Tc show the 
effect of increased plant uptake at low Kd values resulting from the inverse correlation between 
the soil-to-plant transfer factor and Kd (Figure 6.2-11). For a low Kd, leaching is an efficient 
radionuclide removal mechanism keeping the equilibrium concentration of this element in 
surface soil at a relatively low level, but, for such low Kd values, increased plant uptake due to 
availability of the radionuclide in the solution drives the BDCF to higher values. As the Kd 
increases, the BDCF passes through a minimum and, for the Kds in the upper region of their 
range, increases as leaching becomes less efficient as a removal mechanism. This process causes 
increased radionuclide buildup in surface soil and, consequently, causes an increase in the BDCF 
components that depend on radionuclide concentration in the soil. The range of the Kd values 
was selected such that it encompasses all values reported in the literature. Therefore, it is 
unlikely that additional data on Kd would result in higher BDCF values. For the higher Kd 
values, the BDCFs reach an asymptote, as shown in Figure 6.2-11 graphs for 233U and 239Pu; in 
this range of Kd values, soil erosion controls the level of equilibrium concentration in surface 
soil. 
The relative insensitivity of the BDCF value to order-of-magnitude changes in the Kd value, 
along with the conservative approach of using the equilibrium radionuclide concentration in the 
soil, adds confidence that the selection of the Kd values for the biosphere model is justified, and 
that additional data on Kd values in Amargosa Valley would not invalidate biosphere modeling 
results or affect the sensitivity of those results to the parameter values. 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-33 October 2004 
Source: Excel file Dependence of GW BDCFs on Inputs.xls (Appendix A). 
NOTE: The triangles represent the mean of 100 values. The error bars represent the uncertainty range for the mean at the 95 percent uncertainty interval, 
calculated as 1.96 times the standard error of the mean. The outlier point with a high BDCF value for 99Tc was removed to better show the trend in the 
BDCFs for this radionuclide as a function of the Kd. 
Figure 6.2-11. Dependence of BDCF for the Groundwater Exposure Scenario and Present-Day Climate on Kds 
Technetium-99 
1.0E-06 
2.0E-06 
3.0E-06 
4.0E-06 
5.0E-06
1.E-03 1.E-02 1.E-01 1.E+00 1.E+01 
Kd (L/kg) 
BDCF (rem/yr per pCi/L)
Uranium-233 
0.0E+00 
1.0E-03 
2.0E-03 
3.0E-03 
4.0E-03 
5.0E-03 
6.0E-03
1.E-01 1.E+00 1.E+01 1.E+02 1.E+03 1.E+04 1.E+05 
Kd (L/kg) 
BDCF (rem/yr per pCi/L) 
Neptunium-237 
4.0E-03 
5.0E-03 
6.0E-03 
7.0E-03 
8.0E-03 
9.0E-03 
1.0E-02 
1.1E-02 
1.E+00 1.E+01 1.E+02 1.E+03 
Kd (L/kg) 
BDCF (rem/yr per pCi/L) 
Plutonium-239 
6.0E-03 
7.0E-03 
8.0E-03 
9.0E-03 
1.0E-02 
1.1E-02 
1.2E-02 
1.E+02 1.E+03 1.E+04 1.E+05 
Kd (L/kg) 
BDCF (rem/yr per pCi/L)

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-34 October 2004 
6.2.4.2 Radionuclide Transport to Air 
Radionuclides transported to the atmosphere originate in two environmental media: water and 
soil. Radionuclide transport from water to air is only considered in the case of aerosols 
generated by operation of evaporative coolers. Radionuclide transport from soil to air occurs via 
resuspension of surface soil and exhalation of gasses from the soil. 
6.2.4.2.1 Operation of Evaporative Coolers 
Inhalation of particulate matter and inhalation of aerosols generated by evaporative coolers are 
important pathways for actinides (see Tables 6.2-1 and 6.2-2), the latter depending on climate 
conditions. Inhalation of aerosols generated by evaporative cooler contributes on average from 0 
to 43 percent for the present-day climate BDCFs and from 0 to about 16 percent for the future 
climate BDCFs for the groundwater exposure scenario, depending on a radionuclide. 
Radionuclide concentration in indoor air when evaporative coolers are in operation is calculated 
in the biosphere model as (based on BSC 2004 [DIRS 169460], Equation 6.4.2-3) 
Cw 
F 
M 
f Ca 
air 
water 
evap e = (Eq. 6.2-4) 
where 
Cae = activity concentration of a radionuclide in the air resulting from the operation 
of an evaporative cooler (Bq/m3) 
fevap = fraction of radionuclides in water transferred to indoor air (dimensionless) 
Mwater = water evaporation rate (water use rate) for an evaporative cooler (m3/hr) 
Fair = air flow rate for an evaporative cooler (m3/hr) 
Cw = activity concentration of the radionuclide in the groundwater (Bq/m3). 
The parameters in Equation 6.2-4 that are related to evaporative cooler operation, such as the 
water use rate and the air flow rate, were developed based on the technical specifications of 
evaporative coolers that would be suitable for the type of houses in Amargosa Valley. A search 
of the scientific literature did not find environmental assessments that considered the evaporative 
cooler transport process, so there is a lack of experimental measurements of the transfer of 
radionuclides from water to air. Therefore, a maximum range from zero to unity was used in the 
model. This was done to evaluate the importance of this parameter in the biosphere model and to 
determine if a further investigation leading to a more accurate value was warranted. 
The dependence of BDCFs on the value of the water transfer fraction for evaporative coolers is 
shown in Figures 6.2-12 and 6.2-13 for the present-day and future climates, respectively for 99Tc, 
233U, 237Np, and 239Pu. As can be seen, this parameter does not have a strong influence on the 
BDCF values. Changing the water transfer fraction from a mean of 0.5 to a minimum of zero or 
a maximum of one causes a change of less than 15 percent in the BDCF for 237Np for the present 
day climate. These results were obtained from deterministic runs of the model. The BDCF 
values were 4.57  10-3, 5.35  10-3, and 6.13  10-3 rem/yr per pCi/L, for fevap = 0, 0.5, and 1, 
respectively. 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-35 October 2004 
Source: Excel file Dependence of GW BDCFs on Inputs.xls (Appendix A). 
NOTE: The triangles represent the mean of 100 values. The error bars represent the uncertainty range for the mean at the 95 percent uncertainty interval, 
calculated as 1.96 times the standard error of the mean. The outlier point with a high BDCF value for 99Tc was removed to better show the trend in the 
BDCFs for this radionuclide as a function of the evaporative cooler water transfer fraction. 
Figure 6.2-12. Dependence of BDCF for the Groundwater Exposure Scenario and the Present-Day Climate on the Water Transfer Fraction for 
Evaporative Coolers 
Technetium-99 
1.5E-06 
2.0E-06 
2.5E-06 
3.0E-06 
0.0 0.2 0.4 0.6 0.8 1.0 
Evaporative cooler water transfer fraction 
BDCF (rem/yr per pCi/L) Uranium-233 
5.0E-04 
1.0E-03 
1.5E-03 
2.0E-03 
2.5E-03 
3.0E-03 
0.0 0.2 0.4 0.6 0.8 1.0 
Evaporative cooler water transfer fraction 
BDCF (rem/yr per pCi/L) 
Neptunium-237 
5.0E-03 
5.5E-03 
6.0E-03 
6.5E-03 
7.0E-03 
7.5E-03 
8.0E-03 
8.5E-03 
9.0E-03 
0.0 0.2 0.4 0.6 0.8 1.0 
Evaporative cooler water transfer fraction 
BDCF (rem/yr per pCi/L) 
Plutonium-239 
6.0E-03 
7.0E-03 
8.0E-03 
9.0E-03 
1.0E-02 
1.1E-02 
1.2E-02 
0.0 0.2 0.4 0.6 0.8 1.0 
Evaporative cooler water transfer fraction BDCF (rem/yr per pCi/L)

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-36 October 2004 
Source: Excel file Dependence of GW BDCFs on Inputs.xls (Appendix A). 
NOTE: The triangles represent the mean of 100 values. The error bars represent the uncertainty range for the mean at the 95 percent uncertainty interval, 
calculated as 1.96 times the standard error of the mean. The outlier point with a high BDCF value for 99Tc was removed to better show the trend in the 
BDCFs for this radionuclide as a function of the evaporative cooler water transfer fraction. 
Figure 6.2-13. Dependence of BDCF for the Groundwater Exposure Scenario and the Future Climate on the Water Transfer Fraction for 
Evaporative Coolers 
Technetium-99 
1.2E-06 
1.4E-06 
1.6E-06 
1.8E-06 
2.0E-06 
2.2E-06 
2.4E-06 
2.6E-06 
0.0 0.2 0.4 0.6 0.8 1.0 
Evaporative cooler water transfer fraction 
BDCF (rem/yr per pCi/L) 
Uranium-233 
5.0E-04 
1.0E-03 
1.5E-03 
2.0E-03 
0.0 0.2 0.4 0.6 0.8 1.0 
Evaporative cooler water transfer fraction 
BDCF (rem/yr per pCi/L) 
Neptunium-237 
4.0E-03 
4.5E-03 
5.0E-03 
5.5E-03 
6.0E-03 
0.0 0.2 0.4 0.6 0.8 1.0 
Evaporative cooler water transfer fraction 
BDCF (rem/yr per pCi/L) 
Plutonium-239 
5.0E-03 
5.5E-03 
6.0E-03 
6.5E-03 
7.0E-03 
0.0 0.2 0.4 0.6 0.8 1.0 
Evaporative cooler water transfer fraction BDCF (rem/yr per pCi/L)

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-37 October 2004 
The difference between the mean BDCF value obtained in a deterministic run and the mean of 
the BDCF distribution from a stochastic realization of the model results from the selection of 
representative (fixed) input parameter values for the deterministic runs. Some of these 
representative values are not the mean of the distribution used in the stochastic realizations. 
The importance of the evaporative cooler pathway decreases for the future climate, which is 
expected to be cooler and wetter than the present-day climate. The present-day climate is 
predicted to last for only 400-600 years post-closure followed by the monsoon and the glacial 
transition climate (BSC 2004 [DIRS 170002], Table 6-1). 
The increase in the mean BDCF of 237Np as the results of the evaporative cooler water transfer 
fraction change from fevap = 0 to fevap = 1 is about 35 percent for the present-day climate and still 
less for the future climate. Considering that the upper bound of the BDCF range for 237Np differs 
from the lower bound by a factor of nearly 7, the uncertainty introduced by the evaporative 
cooler component is not significant. 
The influence of activity concentration in air caused by the operation of evaporative coolers on 
BDCFs for five radionuclides was estimated in a series of deterministic model runs. The 
calculations were done for the average value of activity concentration in indoor air from 
operation of evaporative coolers and for twice that value. The results are presented in 
Table 6.2-8. 
Table 6.2-8. BDCFs and Percent Change for a Doubling in the Average Activity Concentration in Air 
from Operation of Evaporative Coolers 
Activity Concentration in Air BDCF 
Radionuclide Level Bq/m3 rem/yr per pCi/L 
Percent Change 
Relative to Average 
Average 1.024E-06 1.380E-06 Technetium-99 
2 x Average 2.048E-06 1.392E-06 0.9 
Average 1.024E-06 2.588E-04 Iodine-129 
2 x Average 2.048E-06 2.591E-04 0.1 
Average 1.024E-06 9.529E-04 Uranium-233 
2 x Average 2.048E-06 1.149E-03 20.6 
Average 1.024E-06 5.350E-03 Neptunium-237 
2 x Average 2.048E-06 6.132E-03 14.6 
Average 1.024E-06 7.677E-03 Plutonium-239 
2 x Average 2.048E-06 8.298E-03 8.1 
NOTE: BDCFs were calculated in deterministic runs of ERMYN_GW_MC8_Det_Base.gsm by changing the 
radionuclide selection and the value of mass loading. The percent change for the BDCFs was calculated in 
the Excel spreadsheet Dependence of GW BDCFs on Inputs.xls (Appendix A). 
Doubling the activity concentration in air from operation of evaporative coolers results, on 
average, in an increase in the BDCF from about 21 percent for 233U to less than one percent for 
99Tc and 129I. 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-38 October 2004 
6.2.4.2.2 Resuspension of Surface Soil 
Radionuclide concentrations in the air from the resuspension of contaminated surface soil are 
calculated as (BSC 2004 [DIRS 169460], Equation 6.4.2-2) 
n m n enhance n h S Cs f Ca , , = (Eq. 6.2-5) 
where 
Cah,n = activity concentration of a radionuclide in the air from soil resuspension for 
the assessment of human inhalation exposure in environment n (Bq/m3) 
fenhance,n = enhancement factor for the activity concentration of resuspended particulates 
in environment n (dimensionless) 
Sn = concentration of total resuspended particulates (atmospheric mass loading) 
for evaluation of inhalation exposure for environment n (kg/m3) 
Csm = mass activity concentration of a radionuclide in soil (Bq/kg) 
n = index of the environments (see below) 
Five receptor environments associated with different human activities are considered in the 
biosphere model, four in the contaminated area: active outdoors (n = 1), inactive outdoors 
(n = 2), active indoors (n = 3), asleep indoors (n = 4), and one outside of the contaminated area 
(n = 5) (see BSC 2004 [DIRS 169671], Section 6.2 for detailed discussion of receptor 
environments). Activity concentration in the air outside the contaminated area is zero. These 
mutually exclusive environments represent behavioral and environmental combinations for 
which the receptor would receive a substantially different rate of exposure via inhalation or 
external exposure. 
The average radionuclide concentrations in air in the five environments for 99Tc, 233U, 237Np, and 
239Pu are shown in Figure 6.2-14. The activity concentration in soil for 99Tc is much lower than 
that for the remaining three radionuclides because 99Tc does not build up in surface soil as much 
as the actinides do. This is due to a higher leaching removal constant for this element. It can 
also be seen that the radionuclide concentration in air for the active outdoor environment is much 
higher than that in any of the remaining environments. From Equation 6.2-5, the radionuclide 
concentration in air depends on the radionuclide concentration in surface soil (discussed in 
Section 6.2.4.1), atmospheric mass loading, and the enhancement factor. The radionuclide 
concentration in the outdoor active environment is high because both atmospheric mass loading 
and the enhancement factor are high for this environment, as shown in Figures 6.2-15 and 
6.2-16, respectively. 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-39 October 2004 
0.0E+00 
1.0E-05 
2.0E-05 
3.0E-05 
4.0E-05 
5.0E-05 
Concentration in air 
(Bq/m3) 
Active 
Outdoors 
Inactive 
Outdoors 
Active 
Indoors 
Asleep 
Indoors 
Away 
Tc-99 
U-233 
Np-237 
Pu-239 
Source: Excel file Detailed Pathway Analysis GW_MC.xls (Appendix A). 
Figure 6.2-14. Average Radionuclide Concentration in Air from Resuspension of Soil by Radionuclide 
and Environment 
0.0E+00 
1.0E-06 
2.0E-06 
3.0E-06 
4.0E-06 
5.0E-06 
6.0E-06 
Mass loading (kg/m 3) 
Active 
Outdoors 
Inactive 
Outdoors 
Active 
Indoors 
Asleep 
Indoors 
Away 
Source: Excel file Detailed Pathway Analysis GW_MC.xls (Appendix A). 
Figure 6.2-15. Average Particulate Concentration in Air (Mass Loading) in the Receptor Environments 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-40 October 2004 
0.0 
0.5 
1.0 
1.5 
2.0 
2.5 
3.0 
3.5 
4.0 
4.5 
Enhancement factor 
Active 
Outdoors 
Inactive 
Outdoors 
Active 
Indoors 
Asleep 
Indoors 
Away 
Source: Excel file Detailed Pathway Analysis GW_MC.xls (Appendix A). 
Figure 6.2-16. Average Enhancement Factor in the Receptor Environments 
Because mass loading in the outdoor active environment is an important parameter, graphs were 
produced that show the dependence of the BDCFs on this parameter. The graphs produced for 
99Tc, 233U, 237Np, and 239Pu are shown in Figure 6.2-17. The BDCFs for 99Tc are, as expected, 
unaffected by mass loading. The BDCFs for the remaining radionuclides depend strongly on 
mass loading. 
The influence of mass loading in the active outdoor environment on the BDCFs for 237Np and 
239Pu was estimated in a series of deterministic model runs. The mass loading parameters used 
in the runs and the corresponding BDCF values are presented in Table 6.2-9. 
Table 6.2-9. BDCF and Percent Change for Different Levels of Mass Loading for the Active Outdoors 
Environment 
Neptunium-237 Plutonium-239 Mass Loading 
Conditions 
Mass Loading 
mg/m3 BDCF Percent change BDCF Percent change 
Average 5.00 5.35E-03 N/A 7.68E-03 N/A 
Minimum 1.00 4.76E-03 -11.0 4.68E-03 -39.0 
Maximum 10.00 6.09E-03 13.8 1.14E-02 48.8 
NOTE: BDCFs were calculated in deterministic runs of ERMYN_GW_MC8_Det_Base.gsm by changing the 
radionuclide selection and the value of mass loading. The percent change for the BDCFs was calculated in 
the Excel spreadsheet Dependence of GW BDCFs on Inputs.xls (Appendix A). 
The results of the BDCF calculations using different values of mass loading in the active 
outdoors environment indicate that the BDCFs for 237Np are less sensitive to the value of the 
mass loading than the BDCFs for 239Pu. This is because the inhalation of particulate matter is a 
more important pathway for 239Pu than it is for 237Np. For 237Np the BDCF value varies by up to 
about 14 percent over the variability range of this parameter. For 239Pu, the difference is greater, 
up to about 49 percent when the mass loading value is doubled. 
For comparison, the dependence of BDCFs for the selected radionuclides on mass loading for the 
inactive outdoors environment is shown in Figure 6.2-18. 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis ____________________________ 
ANL-NBS-MD-000014 REV 00 6-41 October 2004 
Source: Excel file Dependence of GW BDCFs on Inputs.xls (Appendix A). 
NOTE: The triangles represent the mean of 100 values. The error bars represent the uncertainty range for the mean at the 95 percent uncertainty interval, 
calculated as 1.96 times the standard error of the mean. The outlier point with a high BDCF value for 99Tc was removed to better show the trend in the 
BDCFs for this radionuclide as a function of the mass loading. 
Figure 6.2-17. Dependence of BDCF for the Groundwater Exposure Scenario and the Present-Day Climate on the Atmospheric Mass Loading 
for the Active Outdoors Environment 
Technetium-99 
1.6E-06 
1.8E-06 
2.0E-06 
2.2E-06 
2.4E-06 
2.6E-06 
2.8E-06
2.E-06 3.E-06 4.E-06 5.E-06 6.E-06 7.E-06 8.E-06 9.E-06 
Mass loading, active outdoors environment (kg/m3) 
BDCF (rem/yr per pCi/L) 
Uranium-233 
5.0E-04 
1.0E-03 
1.5E-03 
2.0E-03 
2.5E-03 
3.0E-03 
3.5E-03
2.E-06 3.E-06 4.E-06 5.E-06 6.E-06 7.E-06 8.E-06 9.E-06 
Mass loading, active outdoors environment (kg/m3) 
BDCF (rem/yr per pCi/L) 
Neptunium-237 
5.0E-03 
5.5E-03 
6.0E-03 
6.5E-03 
7.0E-03 
7.5E-03 
8.0E-03 
8.5E-03 
9.0E-03
2.E-06 3.E-06 4.E-06 5.E-06 6.E-06 7.E-06 8.E-06 9.E-06 
Mass loading, active outdoors environment (kg/m3) 
BDCF (rem/yr per pCi/L) 
Plutonium-239 
4.0E-03 
6.0E-03 
8.0E-03 
1.0E-02 
1.2E-02 
1.4E-02
2.E-06 3.E-06 4.E-06 5.E-06 6.E-06 7.E-06 8.E-06 9.E-06 
Mass loading, active outdoors environment (kg/m3) BDCF (rem/yr per pCi/L)

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis ____________________________ 
ANL-NBS-MD-000014 REV 00 6-42 October 2004 
Source: Excel file Dependence of GW BDCFs on Inputs.xls (Appendix A). 
NOTE: The triangles represent the mean of 100 values. The error bars represent the uncertainty range for the mean at the 95 percent uncertainty interval, 
calculated as 1.96 times the standard error of the mean. The outlier point with a high BDCF value for 99Tc was removed to better show the trend in the 
BDCFs for this radionuclide as a function of the mass loading. 
Figure 6.2-18. Dependence of BDCF for the Groundwater Exposure Scenario and the Present-Day Climate on the Atmospheric Mass Loading 
for the Inactive Outdoors Environment 
Technetium-99 
1.5E-06 
1.7E-06 
1.9E-06 
2.1E-06 
2.3E-06 
2.5E-06 
2.7E-06 
2.9E-06 
3.1E-06
3.E-08 4.E-08 5.E-08 6.E-08 7.E-08 8.E-08 9.E-08 
Mass loading, inactive outdoors environment (kg/m3) 
BDCF (rem/yr per pCi/L) 
Uranium-233 
5.0E-04 
1.0E-03 
1.5E-03 
2.0E-03 
2.5E-03 
3.0E-03
3.E-08 4.E-08 5.E-08 6.E-08 7.E-08 8.E-08 9.E-08 
Mass loading, inactive outdoors environment (kg/m3) 
BDCF (rem/yr per pCi/L) 
Neptunium-237 
6.0E-03 
6.5E-03 
7.0E-03 
7.5E-03 
8.0E-03
3.E-08 4.E-08 5.E-08 6.E-08 7.E-08 8.E-08 9.E-08 
Mass loading, inactive outdoors environment (kg/m3) 
BDCF (rem/yr per pCi/L) 
Plutonium-239 
7.0E-03 
8.0E-03 
9.0E-03 
1.0E-02 
1.1E-02
3.E-08 4.E-08 5.E-08 6.E-08 7.E-08 8.E-08 9.E-08 
Mass loading, inactive outdoors environment (kg/m3) BDCF (rem/yr per pCi/L)

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-43 October 2004 
As shown in Figure 6.2-18, the BDCFs are insensitive to mass loading in the inactive outdoors 
environment. For example, based on a deterministic run of the model, tripling the mass loading 
value for this environment from 0.06 mg/m3 to 0.18 mg/m3 resulted in a change in the BDCF for 
239Pu from 7.68  10-3 rem/yr per pCi/L to 7.71  10-3 rem/yr per pCi/L, that is, by 0.5 percent. 
BDCFs were calculated in a deterministic run of ERMYN_GW_MC8_Det_Base.gsm by changing 
the radionuclide selection and the value of mass loading. The percent change for the BDCFs was 
calculated in the Excel spreadsheet Dependence of GW BDCFs on Inputs.xls (Appendix A). 
6.2.4.3 Radionuclide Transport to Crops 
Environmental transport pathways considered in the biosphere model for the groundwater 
exposure scenario that result in radionuclide transport to crops are: 
 Deposition of contaminated water on crop surfaces 
 Deposition of resuspended contaminated soil in crop surfaces 
 Root uptakes of radionuclides present in surface soil 
The relative contributions of these pathways to the overall activity concentration in a crop type is 
pathway and crop-type dependent. Table 6.2-10 summarizes the fractions of radionuclide 
concentration in the crop types considered in the biosphere model by transport process for a few 
selected radionuclides. The fractions for the present-day climate were calculated in the Excel 
file Detailed Pathway Analysis GW_MC.xls (Appendix A). 
Table 6.2-10. Fractions of Activity in Crop Types from Considered Environmental Transport Pathways 
for Groundwater Exposure Scenario for Present-Day Climate 
Crop Type 
Radionuclide 
Transport Process 
Leafy 
Vegetables 
Other 
Vegetables 
Fruits 
Grains 
Forage 
Average 
Irrigation water deposition 0.307 0.363 0.373 0.492 0.349 0.377 
Dust deposition 0.000 0.001 0.001 0.001 0.000 0.001 Tc-99 
Root uptake 0.693 0.636 0.626 0.507 0.651 0.623 
Irrigation water deposition 0.914 0.759 0.665 0.720 0.867 0.785 
Dust deposition 0.027 0.018 0.020 0.024 0.026 0.023 I-129 
Root uptake 0.060 0.222 0.314 0.256 0.107 0.192 
Irrigation water deposition 0.865 0.770 0.738 0.862 0.821 0.811 
Dust deposition 0.069 0.056 0.070 0.076 0.067 0.068 U-233 
Root uptake 0.066 0.175 0.192 0.062 0.112 0.121 
Irrigation water deposition 0.737 0.536 0.506 0.755 0.693 0.646 
Dust deposition 0.044 0.032 0.042 0.051 0.042 0.042 Np-237 
Root uptake 0.218 0.432 0.452 0.194 0.265 0.312 
Irrigation water deposition 0.846 0.829 0.782 0.836 0.767 0.812 
Dust deposition 0.146 0.133 0.166 0.155 0.133 0.147 Pu-239 
Root uptake 0.008 0.038 0.052 0.010 0.099 0.041 
Source: Excel file Detailed Pathway Analysis GW_MC.xls (Appendix A). 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-44 October 2004 
Because there is a trend regarding the importance of environmental transport pathways for each 
radionuclide, regardless of crop type, the fractions of radionuclide concentrations for a 
radionuclide were averaged over all crop types included in the analysis. The results are shown in 
Table 6.2-10 and Figure 6.2-19 (see Excel file Detailed Pathway Analysis GW_MC.xls in 
Appendix A). This averaging was justified because the differences among the crop types were 
usually less than the differences between the mechanisms of radionuclide transport to a crop. 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
Fraction of radionuclide 
concentration 
Tc-99 I-129 Np-237 U-233 Pu-239 
Dust R
oot uptake 
Irrigation water 
Source: Excel file Detailed Pathway Analysis GW_MC.xls (Appendix A). 
Figure 6.2-19. Environmental Transport Pathway Contributions for Groundwater Exposure Scenario and 
Present-Day Climate Averaged for All Crop Types 
Figure 6.2-19 shows that radionuclide deposition on plant surfaces from irrigation water is the 
dominant mechanism of activity transport to crops for all radionuclides except 99Tc. Root uptake 
is dominant for 99Tc and a significant contributor for 129I and 237Np. Root uptake decreases as 
the atomic number increases and is relatively insignificant for 239Pu because of its low uptake 
from the liquid phase, which is due to the high sorption properties of this element (it is preferably 
present in the solid phase). Particulate deposition is relatively unimportant, regardless of 
radionuclide, although it is greater for transuranics, which tend to accumulate in the soil to a 
greater degree than poorly sorbing elements such as technetium. 
Not shown in Figure 6.2-19 is the relative importance of the environmental transport pathways 
leading to accumulation of 14C in the plants. This is because the environmental transport of 14C 
in the environment is evaluated in the biosphere model using a special submodel (BSC 2004 
[DIRS 169460], Section 6.4.6), which is different than the plant submodel used for the other 
radionuclides (BSC 2004 [DIRS 169460], Section 6.4.3). This special submodel includes 
different mechanisms of carbon migration though the environment. Concentration of 14C in 
crops and animal products is calculated based on the ratios of 14C to stable carbon in the media 
that are the source of carbon for plants (air and soil) and for animals (feed, water, and soil), on 
the fraction of total carbon in plants or animal products that originates from these media, and on 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-45 October 2004 
the carbon content of these media. The concentration of 14C in crops and animal products thus 
reflects the relative abundance of 14C and stable carbon in the environment. Pathway 
contributions for crops and animal products correspond to the consumption of these foodstuffs. 
In the case of 14C transport to plants, almost 100 percent of 14C in crops is from the air (carbon 
absorption during photosynthesis). The fraction of 14C concentration in crops from root uptake is 
negligible (Excel file Detailed Pathway Analysis GW_MC.xls in Appendix A). 
Similar calculations were performed for the future climate. The fractions of radionuclide 
concentration in various crop types for five selected radionuclides are presented in Table 6.2-11 
(see Excel file Detailed Pathway Analysis GW_FC.xls in Appendix A). The differences between 
the proportions for the present-day climate and the future climate are a few percent or less. 
Thus, the conclusions for the present-day climate also apply to the future climate. 
Table 6.2-11. Fractions of Activity in Crop Types from Considered Environmental Transport Processes for 
Groundwater Exposure Scenario for Future Climate 
Crop Type 
Radionuclide 
Transport Process 
Leafy 
Vegetables 
Other 
Vegetables 
Fruits 
Grains 
Forage 
Average 
Irrigation water deposition 0.320 0.323 0.334 0.523 0.348 0.370 
Dust deposition 0.000 0.001 0.001 0.001 0.000 0.001 Tc-99 
Root uptake 0.680 0.676 0.665 0.476 0.651 0.630 
Irrigation water deposition 0.918 0.726 0.629 0.746 0.866 0.777 
Dust deposition 0.024 0.021 0.022 0.021 0.025 0.023 I-129 
Root uptake 0.057 0.253 0.349 0.233 0.109 0.200 
Irrigation water deposition 0.881 0.749 0.717 0.887 0.830 0.813 
Dust deposition 0.061 0.060 0.074 0.062 0.063 0.064 Np-237 
Root uptake 0.058 0.191 0.209 0.050 0.108 0.123 
Irrigation water deposition 0.756 0.500 0.473 0.785 0.700 0.643 
Dust deposition 0.040 0.035 0.045 0.044 0.041 0.041 Pu-239 
Root uptake 0.203 0.465 0.482 0.171 0.260 0.316 
Irrigation water deposition 0.868 0.819 0.775 0.868 0.787 0.823 
Dust deposition 0.125 0.140 0.170 0.125 0.122 0.136 Am-241 
Root uptake 0.007 0.041 0.055 0.007 0.091 0.040 
Source: Excel file Detailed Pathway Analysis GW_FC.xls (Appendix A). 
Irrigation with contaminated water is an important environmental transport pathway for all 
radionuclides. Radionuclide concentrations in crops due to leaf uptake from contaminated 
irrigation water sprayed on plants is expressed as (adapted from BSC 2004 [DIRS 169460], 
Equation 6.4.3-3) 
( ) j g w t 
j w 
j j j o j 
j water e 
Y 
T Rw f Dw 
Cp , , 
, 1 
. 
. 
- - = (Eq. 6.2-6) 
where 
Cpwater,j = radionuclide concentration in crop type j due to application of irrigation 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-46 October 2004 
water (Bq/kgwet weight) 
Dwj = deposition rate of a radionuclide due to application of irrigation water on 
crop type j (Bq/(m2 d)) 
fo,j = fraction of irrigation applied using overhead methods for plant type j 
(dimensionless) 
Rwj = interception fraction of irrigation water for crop type j (dimensionless) 
Tj = translocation factor for crop type j (dimensionless) 
.w = weathering constant (per d), which can be calculated from weathering 
half-life (Tw in units of day) by .w = ln(2) / Tw 
tg, j = crop growing time for crop type j (d) 
Yj = crop yield or wet biomass for crop type j (kg wet weight/m2). 
For overhead irrigation (i.e., sprinkler or spray), the rate of radionuclide deposition onto crops, 
Dwj, is the product of irrigation rate and radionuclide concentration in water. In this submodel, 
the radionuclide deposition rate from irrigation water is estimated as (adapted form BSC 2004 
[DIRS 169460], Equation 6.4.3-4) 
j j IRD Cw Dw = (Eq. 6.2-7) 
where 
IRDj = daily average irrigation rate for crop type j during the growing season (m/d) 
The result calculated using Equation 6.2-6 is relatively insensitive to the value of the term in the 
parentheses, containing an exponential function. This is because the weathering time is much 
shorter than the crop growing time (the weathering rate constant is relatively large), so the 
exponential term approaches values that are close to zero. The weathering half-life influences 
the BDCF values, especially for those radionuclides that have a significant fraction of their 
BDCF due to ingestion of locally produced food, as can be seen in Table 6.2-3. 
For the remaining parameters, the radionuclide concentration in crops is directly proportional to 
the deposition rate, fraction of irrigation applied using overhead methods, interception fraction, 
and translocation, and inversely proportional to the weathering constant and crop yield. These 
parameters influence the radionuclide concentration in crops from irrigation, making this 
environmental transport pathway the most important transport mechanisms for contamination of 
crops, but they do not contribute to an appreciable degree to the uncertainty in the all-pathway 
BDCF (Table 6.2-3). One reason is that many agricultural parameters that are used for this 
pathway were developed based on representative crops and with consideration of site-specific 
conditions and, as the result, the level of uncertainty associated with these parameters is 
relatively low. 
A parameter that received some attention in the past was the interception fraction for irrigation 
water. This parameter quantifies the amount of contaminated water intercepted by crop surfaces. 
The histograms of water interception fraction for all crop types used in the biosphere model are 
shown in Figure 6.2-20. The biosphere model is relatively insensitive to the value of this 
parameter, as illustrated in Figure 6.2-21 for 99Tc, a radionuclide that has a high BDCF 
contribution from the ingestion of locally produced food. The water interception pathway is 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-47 October 2004 
more important as a transport pathway for elements that are poorly taken up from the soil 
through their roots, as indicated in Figure 6.2-19. However, for these elements, ingestion of 
locally produced food is, overall, not a very important pathway, so the influence of the water 
interception fraction on the BDCFs for these radionuclides is expected to be even less. 
Leafy Vegetables 
0 
100 
200 
300 
400 
0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9
1 
Frequency (N = 1,000) 
Other Vegetables 
0 
100 
200 
300 
400 
0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9
1 
Frequency (N = 1,000) 
Fruits 
0 
100 
200 
300 
0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9
1 
Frequency (N = 1,000) 
Grains 
0 
50 
100 
150 
200 
0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9
1 
Frequency (N = 1,000) 
Cattle Forage 
0 
100 
200 
300 
400 
500 
0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9
1 
Water Interception Fraction 
Frequency (N = 
1,000) 
Source: Excel file Water Interception Fraction.xls (Appendix A). 
Figure 6.2-20. Water Interception Fraction Histograms by Crop Type Resulting from 1,000 Realizations 
of the Biosphere Model 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis _____________________________ 
ANL-NBS-MD-000014 REV 00 6-48 October 2004 
Source: Excel file Dependence of GW BDCFs on Inputs.xls (Appendix A). 
NOTE: The triangles represent the mean of 100 values. The error bars represent the uncertainty range for the mean at the 95 percent uncertainty interval, 
calculated as 1.96 times the standard error of the mean. The outlier point with a high BDCF value for 99Tc was removed to better show the trend in the 
BDCFs for this radionuclide as a function of water interception fraction. 
Figure 6.2-21. Dependence of 99Tc BDCF for the Groundwater Exposure Scenario and Present-Day Climate on Water Interception Fraction by 
Type of Crops for Human Consumption 
Leafy Vegetables 
1.5E-06 
2.0E-06 
2.5E-06 
3.0E-06 
3.5E-06
0.10 0.20 0.30 0.40 0.50 
Water interception fraction 
BDCF (rem/yr per pCi/L) Other Vegetables 
1.5E-06 
2.0E-06 
2.5E-06 
3.0E-06 
3.5E-06
0.20 0.30 0.40 0.50 0.60 
Water interception fraction 
BDCF (rem/yr per pCi/L) 
Fruits 
1.5E-06 
2.0E-06 
2.5E-06 
3.0E-06 
3.5E-06
0.20 0.30 0.40 0.50 0.60 0.70 
Water interception fraction 
BDCF (rem/yr per pCi/L) 
Grains 
1.5E-06 
2.0E-06 
2.5E-06 
3.0E-06 
3.5E-06
0.30 0.40 0.50 0.60 0.70 0.80 0.90 
Water interception fraction 
BDCF (rem/yr per pCi/L

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-49 October 2004 
The influence of irrigation interception fraction on BDCFs for five radionuclides was estimated 
in a series of deterministic model runs. The calculations were done for average and doubled 
irrigation interception fractions for all crops. The irrigation interception values used in the 
calculations are listed in Table 6.2-12 and the results are presented in Table 6.2-13. 
Table 6.2-12 Irrigation Interception Fractions Used in Calculations 
Irrigation Interception 
Fraction 
Leafy 
Vegetables 
Other 
Vegetables Fruit Grain Forage 
Average for all crops 0.216 0.301 0.360 0.470 0.258 
2 x Average for all crops 0.432 0.602 0.719 0.940 0.516 
Table 6.2-13. BDCFs and Percent Change for Different Irrigation Interception Fractions 
Radionuclide Irrigation interception fraction 
BDCF 
rem/yr per pCi/L 
Percent Change 
Relative to Average 
Average for all crops 1.380E-06 
Technetium-99 2 x Average for all crops 1.483E-06 7.5 
Average for all crops 2.588E-04 
Iodine-129 2 x Average for all crops 2.913E-04 12.5 
Average for all crops 9.529E-04 
Uranium-233 2 x Average for all crops 9.663E-04 1.4 
Average for all crops 5.350E-03 
Neptunium-237 2 x Average for all crops 5.521E-03 3.2 
Average for all crops 7.677E-03 
Plutonium-239 2 x Average for all crops 7.811E-03 1.7 
NOTE: BDCFs were calculated in deterministic runs of ERMYN_GW_MC8_Det_Base.gsm by changing the 
radionuclide selection and the value of mass loading. The percent change for the BDCFs was calculated in 
the Excel spreadsheet Dependence of GW BDCFs on Inputs.xls (Appendix A). 
Doubling the irrigation interception fraction results, on average, in an increase in the BDCF of 
from about two percent for 239Pu to about 13 percent for 129I. 
Root uptake is the second most important environmental transport pathway that gives rise to 
radionuclide concentration in crops (Figure 6.2-19 and Table 6.2-11). The activity concentration 
of radionuclides in crops from root uptake is estimated as (adapted from BSC 2004 
[DIRS 169460], Equation 6.4.3-2) 
j j p s m j root DW F Cs Cp , , . = (Eq. 6.2-8) 
where 
Csm = activity concentration of the radionuclide in surface soil (Bq/kg dry soil) 
Fs .p,j = soil-to-plant transfer factor for the radionuclide and crop type j (Bq/kg dry plant 
per Bq/kg dry soil) 
DWj = dry-to-wet weight ratio for edible part of plant (kg dry-plant /kg 
wet-plant). 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-50 October 2004 
The dry-to-wet weight ratio was developed from measurements of reference crops and has a low 
degree of uncertainty. The soil-to-plant transfer factor, in contrast, was developed based on 
literature data for many elements and crop types and has a relatively wide distribution. This 
uncertainty is transferred to the biosphere model results, as indicated by the results of the 
correlation analysis, which indicated that the soil-to-plant transfer factors are statistically 
significant contributors to the overall BDCF variance (see Table 6.2-3). 
Of the radionuclides shown in Figure 6.2-19 and in Table 6.2-11, 99Tc and 237Np have the highest 
fraction of activity in crops that is attributable to the root uptake. The dependence of the BDCFs 
for these two radionuclides on the transfer factors for the crop types considered in the biosphere 
model is presented in Figures 6.2-22 and 6.2-23, respectively. 
The dependence of the BDCF for 99Tc and 237Np on the soil-to-plant transfer factor corresponds 
to the BDCF dependence on the partition coefficients for these radionuclides (Figure 6.2-11) 
because these two parameters are correlated in the model. The correlation is negative because a 
high Kd reduces the amount of an element present in solution and thus its availability for root 
uptake. This results in low transfer factors for high values of Kds. Thus, the trends shown in 
Figures 6.2-22 and 6.2-23 for transfer factors reflect the opposite of trends shown in Figure 
6.2-11 for the Kds. 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis ______________________________ 
ANL-NBS-MD-000014 REV 00 6-51 October 2004 
Source: Excel file Dependence of GW BDCFs on Inputs.xls (Appendix A). 
NOTE: The triangles represent the mean of 100 values. The error bars represent the uncertainty range for the mean at the 95 percent uncertainty interval, 
calculated as 1.96 times the standard error of the mean. The outlier point with a high BDCF value for 99Tc was removed to better show the trend in the 
BDCFs for this radionuclide as a function of transfer factor. 
Figure 6.2-22. Dependence of BDCFs for 99Tc for the Groundwater Exposure Scenario and the Present-Day Climate on Transfer Factors by 
Crop Type 
Leafy Vegetables 
1.0E-06 
1.5E-06 
2.0E-06 
2.5E-06 
3.0E-06 
3.5E-06 
4.0E-06 
1.E+00 1.E+01 1.E+02 1.E+03 
Transfer Factor 
BDCF (rem/yr per pCi/L) 
Other Vegetables 
1.0E-06 
1.5E-06 
2.0E-06 
2.5E-06 
3.0E-06 
3.5E-06 
4.0E-06
1.E-01 1.E+00 1.E+01 1.E+02 
Transfer Factor 
BDCF (rem/yr per pCi/L) 
Fruits 
1.0E-06 
1.5E-06 
2.0E-06 
2.5E-06 
3.0E-06 
3.5E-06
1.E-01 1.E+00 1.E+01 1.E+02 
Transfer Factor 
BDCF (rem/yr per pCi/L) 
Grains 
1.0E-06 
1.5E-06 
2.0E-06 
2.5E-06 
3.0E-06 
3.5E-06 
4.0E-06
1.E-01 1.E+00 1.E+01 1.E+02 
Transfer Factor 
BDCF (rem/yr per pCi/L

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis ______________________________ 
ANL-NBS-MD-000014 REV 00 6-52 October 2004 
Source: Excel file Dependence of GW BDCFs on Inputs.xls (Appendix A). 
NOTE: The triangles represent the mean of 100 values. The error bars represent the uncertainty range for the mean at the 95 percent uncertainty interval, 
calculated as 1.96 times the standard error of the mean. The outlier point with a high BDCF value for 99Tc was removed to better show the trend in the 
BDCFs for this radionuclide as a function of transfer factor. 
Figure 6.2-23. Dependence of BDCFs for 237Np for the Groundwater Exposure Scenario and the Present-Day Climate on Transfer Factors by 
Crop Type. 
Leafy Vegetables 
5.0E-03 
6.0E-03 
7.0E-03 
8.0E-03 
9.0E-03 
1.0E-02
1.E-03 1.E-02 1.E-01 1.E+00 
Transfer Factor 
BDCF (rem/yr per pCi/L) 
Other Vegetables 
5.0E-03 
6.0E-03 
7.0E-03 
8.0E-03 
9.0E-03 
1.0E-02
1.E-03 1.E-02 1.E-01 1.E+00 
Transfer Factor 
BDCF (rem/yr per pCi/L) 
Fruits 
5.0E-03 
6.0E-03 
7.0E-03 
8.0E-03 
9.0E-03 
1.0E-02
1.E-03 1.E-02 1.E-01 1.E+00 1.E+01 
Transfer Factor 
BDCF (rem/yr per pCi/L) 
Grains 
5.0E-03 
6.0E-03 
7.0E-03 
8.0E-03 
9.0E-03 
1.0E-02
1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 
Transfer Factor BDCF (rem/yr per pCi/L

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-53 October 2004` 
6.2.4.4 Radionuclide Transport to Animal Products 
Environmental transport pathways considered in the biosphere model that result in radionuclide 
transport to animal products are animal consumption of feed; water; and soil; and, indirectly, 
environmental transport pathways leading to radionuclide accumulation in forage plants and in 
the surface soil. 
The relative contributions of these pathways to the overall activity concentration in an animal 
product is pathway and animal-product dependent. Table 6.2-14 summarizes the fractions of 
radionuclide concentration in the animal products considered in the biosphere model by transport 
process for selected radionuclides. The fractions for the present-day climate were calculated in 
the Excel file Detailed Pathway Analysis GW_MC.xls (Appendix A). 
Table 6.2-14. Fractions of Activity in Animal Products from Environmental Transport Pathways for 
Groundwater Exposure Scenario for Present-Day Climate 
Animal Product 
Radionuclide Transport Process Meat Milk Poultry Eggs 
Average 
Meat and 
Milk 
Average 
Poultry and 
Eggs 
Feed Consumption 0.968 0.968 0.851 0.850 0.968 0.851 
Water Consumption 0.030 0.030 0.108 0.107 0.030 0.107 Tc-99 
Soil Consumption 0.003 0.003 0.041 0.042 0.003 0.042 
Feed Consumption 0.794 0.789 0.560 0.561 0.792 0.560 
Water Consumption 0.078 0.078 0.102 0.102 0.078 0.102 I-129 
Soil Consumption 0.128 0.132 0.338 0.338 0.130 0.338 
Feed Consumption 0.668 0.659 0.341 0.344 0.664 0.342 
Water Consumption 0.061 0.061 0.081 0.080 0.061 0.081 U-233 
Soil Consumption 0.271 0.280 0.577 0.577 0.276 0.577 
Feed Consumption 0.743 0.734 0.359 0.360 0.739 0.359 
Water Consumption 0.052 0.052 0.062 0.062 0.052 0.062 Np-237 
Soil Consumption 0.205 0.213 0.579 0.578 0.209 0.579 
Feed Consumption 0.448 0.433 0.109 0.110 0.440 0.109 
Water Consumption 0.029 0.029 0.016 0.016 0.029 0.016 Pu-239 
Soil Consumption 0.523 0.538 0.875 0.874 0.531 0.875 
Source: Excel file Detailed Pathway Analysis GW_MC.xls (Appendix A). 
To show trends regarding the importance of environmental transport processes for a given 
radionuclide, the fractions of radionuclide concentrations for a radionuclide were averaged over 
animal products of bovine origin (meat and milk) and poultry origin (poultry and eggs) included 
in the analysis. The results are shown in Table 6.2-14, and Figures 6.2-24 and 6.2-25, for meat 
and milk and for poultry and eggs, respectively. This averaging was justified because the 
differences between individual animal products (milk and meat as well as poultry and eggs) were 
usually much less than the differences between the mechanisms of radionuclide transport to these 
products. 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-54 October 2004` 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0 
Fraction of radionuclide concentration 
Tc-99 I-129 U-233 Np-237 Pu-239 
Water 
Soil
Feed 
Source: Excel file Detailed Pathway Analysis GW_MC.xls (Appendix A). 
Figure 6.2-24. Average Contributions of Environmental Transport Pathways to Radionuclide Transport 
to Meat and Milk 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
Fraction of radionuclide concentration 
Tc-99 I-129 U-233 Np-237 Pu-239 
Water 
Soil
Feed 
Source: Excel file Detailed Pathway Analysis GW_MC.xls (Appendix A). 
Figure 6.2-25. Average Contributions of Environmental Transport Pathways to Radionuclide Transport 
to Poultry and Eggs 
Figures 6.2-24 and 6.2-25 show that for meat and milk, the contribution from animal feed is 
dominant for all radionuclides except 239Pu; for poultry and eggs, animal feed contributes the 
most for 99Tc and 129I. The contribution from ingestion of soil generally increases with atomic 
number and especially dominates for 239Pu. This is due to the buildup of these radionuclides in 
surface soil that is irrigated with contaminated water over a long period of time and to the 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-55 October 2004` 
relatively high soil intake by chickens. Ingestion of water is relatively unimportant regardless of 
the radionuclide and the animal product. 
Not shown is the relative importance of the environmental transport pathways leading to 
accumulation of 14C in animal products. This is because the environmental transport of 14C in 
the environment is evaluated in the biosphere model using a special submodel (BSC 2004 
[DIRS 169460], Section 6.4.6), which is different than the animal submodel used for the other 
radionuclides (BSC 2004 [DIRS 169460], Section 6.4.4). This special submodel includes 
different mechanisms of carbon migration though the environment. In the case of 14C transport 
to animal products, the fraction of 14C intake from feed is 97-98 percent, 2-3 percent from water, 
and less than 0.02 percent from soil. 
Similar calculations were performed for the future climate. The fractions of radionuclide 
concentration in animal products for five radionuclides are presented in Table 6.2-15. The 
differences between the proportions for the present-day climate and the future climate are a few 
percent or less. Thus, the conclusions for the present-day climate also apply to the future 
climate. 
Table 6.2-15. Fractions of Activity in Animal Products from Environmental Transport Pathways for 
Groundwater Exposure Scenario for the Future Climate 
Animal Product 
Radionuclide Transport Process Meat Milk Poultry Eggs 
Average 
Meat and 
Milk 
Average 
Poultry and 
Eggs 
Feed Consumption 0.953 0.953 0.824 0.824 0.953 0.824 
Water Consumption 0.044 0.044 0.139 0.138 0.044 0.138 Tc-99 
Soil Consumption 0.003 0.003 0.037 0.038 0.003 0.038 
Feed Consumption 0.766 0.762 0.559 0.559 0.764 0.559 
Water Consumption 0.112 0.113 0.132 0.132 0.113 0.132 I-129 
Soil Consumption 0.121 0.125 0.309 0.309 0.123 0.309 
Feed Consumption 0.657 0.648 0.355 0.357 0.652 0.356 
Water Consumption 0.090 0.090 0.106 0.104 0.090 0.105 U-233 
Soil Consumption 0.253 0.262 0.540 0.539 0.258 0.539 
Feed Consumption 0.729 0.720 0.377 0.379 0.725 0.378 
Water Consumption 0.078 0.078 0.086 0.086 0.078 0.086 Np-237 
Soil Consumption 0.193 0.202 0.537 0.536 0.197 0.536 
Feed Consumption 0.467 0.453 0.136 0.136 0.460 0.136 
Water Consumption 0.049 0.048 0.027 0.027 0.049 0.027 Pu-239 
Soil Consumption 0.484 0.499 0.837 0.837 0.491 0.837 
Source: Excel file Detailed Pathway Analysis GW_FC.xls (Appendix A). 
99Tc and 129I are examples of radionuclides that have a higher proportion of BDCF that is due to 
consumption of locally produced animal products than most other radionuclides. For most 
radionuclides, especially actinides, ingestion of animal products is not an important exposure 
pathway (see Tables 6.2-1 and 6.2-2). 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-56 October 2004` 
For 14C, 97 to 98 percent of this radionuclide in animal products is from ingestion of feed, and 2 
to 3 percent from ingestion of water. Ingestion of soil is a negligible source of 14C in animal 
products. 
The concentration of a radionuclide in a specific animal product (Cdk) (BSC 2004 
[DIRS 169460], Section 6.4.4) is calculated in the biosphere model as (adapted from BSC 2004 
[DIRS 169460], Sections 6.4.4.1 through 6.4.4.4): 
( ) k m k k j k k Qs Cs Qw Cw Qf Cp Fm Cd + + = (Eq. 6.2-9) 
where 
Cdk = activity concentration of a radionuclide in animal product k (Bq/kg fresh weight 
or Bq/L for milk) 
k = animal product index; k = 1 for beef, 2 for milk, 3 for poultry, 4 for eggs 
Fmk = animal intake-to-animal product transfer coefficient for the radionuclide and 
animal product k (d/kg fresh weight or d/L for milk) 
Cpj = activity concentration of the radionuclide in animal feed j (Bq/kg fresh weight) 
Qfk = animal consumption rate of feed (kg/d) 
Cw = activity concentration of the radionuclide in groundwater (Bq/L) 
Qwk = animal consumption rate of water (L/d) 
Cs m = equilibrium activity concentration of the radionuclide in surface soil per unit 
mass (Bq/kg) 
Qsk = animal consumption rate of soil (kg/d) 
The radionuclide concentration in animal products is the product of the animal intake of a 
radionuclide and the animal intake-to-animal product transfer coefficient. Animal intake, in turn 
is a product of a radionuclide concentration in the ingested medium (feed, water, and soil) and 
the animal consumption rate of this medium. The environmental transport pathways for the soil 
and animal feed are described in Sections 6.2.4.1 and 6.2.4.3, respectively. As noted previously, 
only the intake of feed and soil are significant contributors to radionuclide concentrations in 
animal products. 
The dependence of BDCFs for 99Tc on the value of the transfer coefficient for animal products is 
shown in Figure 6.2-26. This radionuclide was chosen because it has a relatively high BDCF 
contribution from the consumption of locally produced animal products. The BDCFs tend to 
increase as the transfer coefficients for meat, milk and eggs increase but only in the upper region 
of the range of transfer coefficients. The variability in the BDCF does not depend strongly on 
the variability in animal consumption rates appearing in Equation 6.2-9, as shown in 
Figure 6.2-27 for 99Tc and also in Table 6.2-3. This is because these parameters tend to have 
relatively narrow distributions. 

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ANL-NBS-MD-000014 REV 00 6-57 October 2004 
Source: Excel file Dependence of GW BDCFs on Inputs.xls (Appendix A). 
NOTE: The triangles represent the mean of 100 values. The error bars represent the uncertainty range for the mean at the 95 percent uncertainty interval, 
calculated as 1.96 times the standard error of the mean. The outlier point with a high BDCF value for 99Tc was removed to better show the trend in the 
BDCFs for this radionuclide as a function of transfer coefficient. 
Figure 6.2-26. Dependence of BDCF for 99Tc for the Groundwater Exposure Scenario and the Present-Day Climate on Transfer Coefficients by 
Animal Product 
Meat 
1.5E-06 
2.0E-06 
2.5E-06 
3.0E-06 
3.5E-06
1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 
Transfer coefficient, d/kg 
BDCF (rem/yr per pCi/L) 
Milk 
1.0E-06 
2.0E-06 
3.0E-06 
4.0E-06 
5.0E-06
1.E-04 1.E-03 1.E-02 1.E-01 
Transfer coefficient, d/L 
BDCF (rem/yr per pCi/L) 
Poultry 
1.0E-06 
1.5E-06 
2.0E-06 
2.5E-06 
3.0E-06 
3.5E-06
1.E-03 1.E-02 1.E-01 1.E+00 1.E+01 
Transfer coefficient, d/kg 
BDCF (rem/yr per pCi/L) 
Eggs 
1.0E-06 
1.5E-06 
2.0E-06 
2.5E-06 
3.0E-06 
3.5E-06
1.E-01 1.E+00 1.E+01 
Transfer coefficient, d/kg 
BDCF (rem/yr per pCi/L

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ANL-NBS-MD-000014 REV 00 6-58 October 2004 
Source: Excel file Dependence of GW BDCFs on Inputs.xls (Appendix A). 
NOTE: The triangles represent the mean of 100 values. The error bars represent the uncertainty range for the mean at the 95 percent uncertainty interval, 
calculated as 1.96 times the standard error of the mean. The outlier point with a high BDCF value for 99Tc was removed to better show the trend in the 
BDCFs for this radionuclide as a function of feed consumption rates. 
Figure 6.2-27. Dependence of BDCF for 99Tc for the Groundwater Exposure Scenario and the Present-Day Climate on Animal Feed 
Consumption Rates by Animal Product 
Meat 
1.5E-06 
1.8E-06 
2.1E-06 
2.4E-06 
2.7E-06 
3.0E-06 
30 40 50 60 70 
Feed consumption rate, kg/d 
BDCF (rem/yr per pCi/L) Milk 
1.5E-06 
1.8E-06 
2.1E-06 
2.4E-06 
2.7E-06 
3.0E-06 
50 55 60 65 70 75 
Feed consumption rate, kg/d 
BDCF (rem/yr per pCi/L) 
Poultry 
1.5E-06 
1.8E-06 
2.1E-06 
2.4E-06 
2.7E-06 
3.0E-06 
0.1 0.2 0.3 0.4 
Feed consumption rate, kg/d 
BDCF (rem/yr per pCi/L) 
Eggs 
1.5E-06 
1.8E-06 
2.1E-06 
2.4E-06 
2.7E-06 
3.0E-06 
0.1 0.2 0.3 0.4 
Feed consumption rate, kg/d 
BDCF (rem/yr per pCi/L

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ANL-NBS-MD-000014 REV 00 6-59 October 2004 
6.2.4.5 Radionuclide Transport to Aquatic Food 
The activity concentration in fish is calculated as (adapted from BSC 2004 [DIRS 169460], 
Equation 6.4.5-2) 
BF MF Cw Cf = (Eq. 6.2-10) 
where 
Cf = activity concentration of a radionuclide in fish (Bq/kg wet) 
BF = bioaccumulation factor for the radionuclide in freshwater fish (L/kg) 
Cw = activity concentration of the radionuclide in groundwater (Bq/L) 
MF = water concentration modifying factor for the radionuclide (dimensionless) 
The water concentration modifying factor accounts for water evaporation from fish ponds and is 
developed using site-specific conditions. It has a small range of uncertainty relative to the 
distribution of the bioaccumulation factor, which was developed from a literature review. The 
bioaccumulation of radionuclides in fish is element specific and the fish consumption pathway is 
important for only a few radionuclides that have high values of bioaccumulation factor (carbon, 
cesium, and lead). The bioaccumulation of these elements in fish is overestimated, especially for 
carbon, because farmed fish in Amargosa Valley received uncontaminated commercially 
produced feed (BSC 2004 [DIRS 169672], Sections 6.4.2 and 6.4.3). Bioaccumulation factors 
reported in literature and used in the biosphere model were measured in natural systems and 
include the influence of contaminated food. 
6.2.5 Analysis of the Receptor Exposure Pathways 
The dose to the receptor is influenced by radionuclide levels in the environmental media 
(Section 6.2.4). It is also influenced by the factors that control the intake of these media for 
ingestion and inhalation and by the duration of exposure to radionuclides in media that are 
external to the receptor. These factors are discussed in this section. 
6.2.5.1 Ingestion 
The ingestion dose to the receptor arises from consumption of contaminated water and locally 
produced food. The dose from consumption of a given food type is calculated in the biosphere 
model as the product of radionuclide concentrations in the foodstuff, the consumption rate, and 
the dose coefficient converting radionuclide intake by ingestion to dose. 
Ingestion of contaminated water is an important pathway for almost all radionuclides, as shown 
in Tables 6.2-1 and 6.2-2. This component of the annual dose to the receptor is defined by the 
rule at 10 CFR 63.312(d) [DIRS 156605], which requires that the RMEIs consumption of water 
is 2 L/d; it is not evaluated in this section. 
The pathway contributions from consumption of locally produced food (Tables 6.2-1 and 6.2-2) 
are directly proportional to consumption rates of these foods. The consumption rates of locally 
produced food were developed based on the dietary characteristics of Amargosa Valley 
residents. Because food consumption rates are represented in the model by the distribution of 

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ANL-NBS-MD-000014 REV 00 6-60 October 2004 
their averages, as required in 10 CFR 63.312(b) [DIRS 156605], the variance in their values is 
relatively small. 
To evaluate the sensitivity of BDCFs to consumption rates, deterministic model runs using the 
mean or best estimate input parameter values were performed for selected radionuclides at 
different levels of consumption rates. First, the baseline BDCF levels were established by 
using the mean values of the current consumption rates for the RMEI. Then, BDCFs for the 
same radionuclides were calculated using doubled consumption rates of locally produced food. 
Finally, the consumption rates for an average member of the critical group were used. The 
average member of the critical group was a receptor that was used to calculate BDCFs for the 
TSPA for the site recommendation (CRWMS M&O 2001 [DIRS 152539]). Regarding the 
dietary characteristics, the critical group consisted of those Amargosa Valley residents that 
consumed locally produced food and had vegetable gardens (CRWMS M&O 2001 
[DIRS 153342], Section 7). The dietary characteristics of the RMEI reflect averages for the 
adult Amargosa Valley population. The consumption rates of locally produced food for these 
three receptors are presented in Table 6.2-16. 
Table 6.2-16. Annual Consumption Rates of Locally Produced Food Used in the Evaluation 
Consumption Rate by Food Type (kg/yr) 
Receptor 
Water 
Leafy 
Vegetables 
Other 
Vegetables 
Fruit 
Grain 
Meat 
Milk 
Poultry 
Eggs 
Fish 
RMEI a 730.5 3.78 4.73 12.68 0.23 2.85 4.66 0.42 5.3 0.23 
2  RMEI 
consumption 730.5 7.56 9.46 25.36 0.46 5.7 9.32 0.84 10.6 0.46 
Critical group b 730.5 c 15.14 7.81 15.57 0.48 2.93 4.14 0.8 6.68 0.47 
Sources: a DTN: MO0407SPACRBSM.002. 
b CRWMS M&O 2001 [DIRS 153342], Table 11. 
c The actual average consumption rate for an average member of the critical group was 752.85 L/yr, but 
this parameter was not changed in this analysis. 
The BDCFs calculated using the consumption rates shown in Table 6.2-16 are summarized in 
Table 6.2-17. Table 6.2-17 also includes the percent change in the BDCF for a given 
consumption rate relative to the BDCF for the RMEI. 

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ANL-NBS-MD-000014 REV 00 6-61 October 2004 
Table 6.2-17. BDCFs for Different Levels of Consumption of Locally Produced Food 
RMEI Double RMEI Consumption Critical Group 
Radionuclide BDCF BDCF 
Percent Change 
Relative to the 
RMEI BDCF 
Percent Change 
Relative to the 
RMEI 
Carbon-14 7.14E-06 1.28E-05 78.6 1.10E-05 53.8 
Technetium-99 1.38E-06 1.68E-06 21.7 1.73E-06 25.1 
Iodine-129 2.59E-04 3.15E-04 21.7 2.93E-04 13.2 
Uranium-233 9.53E-04 9.80E-04 2.8 9.81E-04 2.9 
Neptunium-237 5.35E-03 5.75E-03 7.5 5.86E-03 9.6 
Plutonium-239 7.68E-03 7.96E-03 3.7 8.08E-03 5.2 
NOTE: BDCFs were calculated in deterministic runs of ERMYN_GW_MC8_Det_Base.gsm by changing the 
radionuclide selection and the values of food consumption rates. The percent change for the BDCFs was 
calculated in the Excel spreadsheet Dependence of GW BDCFs on Inputs.xls (Appendix A). 
The values in Table 6.2-14 indicate that the BDCFs for actinides are relatively unaffected by 
changes in the consumption rates of locally produced food. The BDCFs for these radionuclides 
increase no more than about 10 percent. The BDCF for 99Tc increases by about 22 percent when 
food consumption is doubled. The greatest difference is for 14C because of the large proportion 
of the BDCF arising from consumption of food, especially fish. However, as noted in Section 
6.2.4.5, the dose from the fish consumption is overestimated for carbon because of the use of 
uncontaminated feed in the fishery (fish get their carbon primarily from their food, not from the 
water). 
The other part of the analysis of the ingestion pathway was an evaluation of the effects of the 
receptor change from an average member of the critical group to the RMEI, in terms of their 
consumption rates. Because the critical group consisted of those Amargosa Valley residents that 
had a vegetable garden, their consumption rate of locally grown food, especially crops, was 
higher than average (i.e., higher than that of the RMEI). The differences between the 
consumption rates of the RMEI and an average member of the critical group also result from 
recategorizing tomatoes from the leafy vegetable crop type to the fruit crop type. 
The BDCFs for the critical group consumption rate were 54 percent higher for 14C and 25 
percent higher or less for the other radionuclides. The difference was smallest for actinides 
because food consumption is not an important pathway for these radionuclides (Table 6.2-1). 
6.2.5.2 Inhalation 
The following components of the inhalation pathway are included in the biosphere model: 
 Inhalation of particulate matter 
 Inhalation of aerosols generated by an evaporative cooler 
 Inhalation of radon decay products 
 Inhalation of 14CO2. 
Inhalation of radon decay products is the most important pathway for 226Ra and 230Th, because 
these radionuclides include 222Rn in their decay chain. The dose from inhalation of radon decay 

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ANL-NBS-MD-000014 REV 00 6-62 October 2004 
products depends on the level of radon gas in the air, degree of equilibrium with its decay 
products and the breathing rate. Inhalation of 14C in the gaseous form as 14CO2 is a negligible 
contributor to the BDCF for 14C. Inhalation of particulate matter and aerosols generated by 
evaporative coolers is further discussed in this section. 
6.2.5.2.1 Inhalation of Particulate Matter 
Inhalation exposure is calculated in the biosphere model by using a time-budget method, where a 
receptors time is spent in several mutually exclusive environments. Inhalation of particulate 
matter arising from resuspension of contaminated soil occurs in all receptor environments except 
when away from the contaminated area. A short summary of the environments and their 
characteristics with regard to the receptor follow: 
 Active outdoors  receptor is outdoors conducting dust generating activities 
 Inactive outdoors  receptor is outdoors conducting activities that do not resuspend soil 
 Active indoors  receptor is awake indoors 
 Asleep  receptor is sleeping 
 Away  receptor is away from contaminated area. 
Figure 6.2-28 shows the fractional contributions from these environments to the BDCF 
component that results from inhalation of airborne particulates. Inhalation exposure accrued in 
the active outdoors environment is by far a dominant contributor (the Excel file Detailed 
Pathway Analysis GW_MC.xls is the source of this and other figures in this section). 
0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9
1 
Fraction of Particulate Inhalation 
BDCF 
Active 
Outdoors 
Inactive 
Outdoors 
Active 
Indoors 
Asleep 
Indoors 
Away 
U-233
Np-237 
Pu-239 
Source: Excel file Detailed Pathway Analysis GW_MC.xls (Appendix A). 
Figure 6.2-28. Average Fraction of Dose from Particulate Inhalation by Radionuclide and Environment 
To explain the reasons behind the high inhalation exposure in the active outdoor environment 
and discuss the sources of uncertainty, the mathematical representation of the particulate 
inhalation submodel is described below. The inhalation dose from airborne particulates is 
calculated as (adopted from BSC 2004 [DIRS 169460], Equation 6.4.8-2) 

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ANL-NBS-MD-000014 REV 00 6-63 October 2004 
( ) . . = 
n m 
m n m n n inh p inh t PP BR Ca DCF D , , (Eq. 6.2-11) 
where 
Dinh,p = annual dose from inhalation exposure to a radionuclide in resuspended 
particulates (Sv/yr) 
DCFinh = dose conversion factor for inhalation (Sv/Bq) 
Can = activity concentration of a radionuclide in air for environment n (Bq/m3) 
BRn = breathing rate for environment n (m3/hr) 
PPm = fraction of total population in population group m 
tn,m = annual number of hours a population group m spends in environment n 
(hr/yr) 
The dose from inhalation of particulate matter in a given receptor environment is calculated as a 
product of radionuclide concentration in air, breathing rate, and time spent in that environment. 
The activity concentration in air, Can, is an environment-specific quantity that depends on the 
level of soil-disturbing and dust-generating activities that are conducted in an environment and 
on the level of increase of mass activity concentration of resuspended material relative to the 
mass activity concentration of the surface soil. These parameters were discussed in Section 
6.2.4.2. Mass loading was developed based on measurements of resuspended particulate 
concentrations in environments or conditions analogous to those considered in the biosphere 
model (BSC 2004 [DIRS 169458], Section 6.1). The active outdoors environment is 
characterized by the highest mass loading levels of all receptor environment. 
Inhalation exposure for an environment depends on the time spent in this environment by the 
receptor. Since the receptor for the biosphere model is a hypothetical individual representative 
of different population groups living in Amargosa Valley, the time spent in an environment is 
weighted by the population proportions for individual population group. Population groups are 
mutually exclusive fractions of the Amargosa Valley population that constitute the hypothetical 
receptor and are described in detail in the Characteristics of the Receptor for the Biosphere 
Model (BSC 2004 [DIRS 169671], Section 6.3.1). In Equation 6.2-11, the weighted time spent 
in an environment is represented by the product of PPm and tn,m. Population proportions, PPm, 
were developed from 2000 census data (BSC 2004 [DIRS 169671], Section 6.3.1). Time spent 
in an environment by a population group, tn,m, was calculated based on 2000 census data for the 
residents of Amargosa Valley (BSC 2004 [DIRS 169671], Section 6.3.2). 
Figure 6.2-29 shows the weighted time for all receptor environments. The receptor spends 
relatively few hours per day in the active outdoors environment and most time indoors. Despite 
this receptor behavior pattern, inhalation exposure in the active outdoor environment is dominant 
because of the high level of airborne particulates in that environment. 

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0.0 
1.0 
2.0 
3.0 
4.0 
5.0 
6.0 
7.0 
8.0 
9.0 
10.0 
Weighted time in environment 
(h/d) 
Active 
Outdoors 
Inactive 
Outdoors 
Active 
Indoors 
Asleep 
Indoors 
Away 
Source: Excel file Detailed Pathway Analysis GW_FC.xls (Appendix A). 
Figure 6.2-29. Average Weighted Time Spent in the Receptor Environments for the Groundwater 
Exposure Scenario 
Another factor affecting radionuclide intake by inhalation, and thus inhalation dose, is the 
breathing rate. Breathing rate in the biosphere model is also environment-dependent and is 
highest in the active outdoor environment, as illustrated in Figure 6.2-30. 
0.0 
0.2 
0.4 
0.6 
0.8 
1.0 
1.2 
1.4 
1.6 
Breathing rate (m 3/h) 
Active 
Outdoors 
Inactive 
Outdoors 
Active 
Indoors 
Asleep 
Indoors 
Away 
Source: Excel file Detailed Pathway Analysis GW_FC.xls (Appendix A). 
Figure 6.2-30. Breathing Rates in the Receptor Environments 
Breathing rates for the receptor environments correspond to the activities and exercise levels 
expected in an environment and were adopted from the reference values reported in the 
International Commission on Radiological Protection Publication 66 (ICRP 1994 
[DIRS 153705]), as described in Characteristics of the Receptor for the Biosphere Model 
(BSC 2004 [DIRS 169671], Section 6.3.3). 

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ANL-NBS-MD-000014 REV 00 6-65 October 2004 
The correlation statistics presented in Table 6.2-3 indicate that there are only a few receptor 
related parameters used in the calculation of the inhalation dose that affect the variance in 
BDCFs. One of these parameters is the time spent in the active outdoors environment by 
non-workers and commuters. These two group are by far the most common among Amargosa 
Valley residents, accounting, on average, for over 78 percent of the population (see Excel file 
Detailed Pathway Analysis GW_MC.xls in Appendix A). The times spent outdoors by these two 
groups are included in the calculation of the weighted time (PPm  tn,m in Equation 6.2-11) and 
significantly influence its value. The dependence of the BDCFs for actinides on the value of the 
weighted time in the active outdoors environment is graphically shown in Figure 6.2-31. The 
BDCFs for 233U, 237Np, and 239Pu, used here as examples, depend relatively strongly on the value 
of this parameter, especially 239Pu. 
6.2.5.2.2 Inhalation of Aerosols Generated by Evaporative Coolers 
Inhalation of aerosols generated by evaporative coolers is another pathway leading to inhalation 
exposure. This type of inhalation exposure occurs only in the indoor environments, that is, 
active indoors and asleep, and only while evaporative coolers are being used. The importance if 
this pathway is greatly reduced for the future climate (Table 6.2-2). 
The inhalation dose from airborne aerosols generated by evaporative coolers is calculated as 
(adopted from BSC 2004 [DIRS 169460], Equation 6.4.8-3) 
. . .. 
. 
.. 
. 
= 
.) ( 
, , 
env indoor n m 
m n m n use cooler e inh e inh t PP BR f f Ca DCF D (Eq. 6.2-12) 
where 
Cae = activity concentration of a radionuclide 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) 
The fraction of houses with evaporative coolers is a site-specific parameter that was developed 
from the results of a survey of Amargosa Valley residents. The value of the annual evaporative 
cooler use factor was based on local temperatures. The distributions of these parameters 
represent realistic, site-specific conditions (BSC 2004 [DIRS 169671, Section 6.3.4). 
The parameters used to calculate the inhalation dose from aerosols generated by evaporative 
coolers contribute to the variance in the BDCFs for some radionuclides, particularly actinides. 
The parameter that account for the largest fraction of the BDCF variance is the evaporative 
cooler water transfer fraction, which was discussed in Section 6.2.4.2.1. Parameters that depend 
on the receptor behaviors, such as time spent indoors where exposure occurs, are not significant 
contributors to the BDCF variance (Table 6.2-3). 

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ANL-NBS-MD-000014 REV 00 6-66 October 2004 
Source: Excel file Dependence of GW BDCFs on Inputs.xls (Appendix A). 
NOTE: The triangles represent the mean of 100 values. The error bars represent the uncertainty range for the mean at the 95 percent uncertainty interval, 
calculated as 1.96 times the standard error of the mean. The outlier point with a high BDCF value for 99Tc was removed to better show the trend in the 
BDCFs for this radionuclide as a function of time spent in an environment. 
Figure 6.2-31. Dependence of the BDCFs for Selected Actinides on the Population Weighted Time Spent in the Active Outdoors Environment 
Technetium-99 
1.6E-06 
1.8E-06 
2.0E-06 
2.2E-06 
2.4E-06 
2.6E-06 
2.8E-06 
3.0E-06
0.30 0.35 0.40 0.45 0.50 0.55 0.60 
Weighted time in active outdoors environment (hr/d) 
BDCF (rem/yr per pCi/L) 
Uranium-233 
1.0E-03 
1.5E-03 
2.0E-03 
2.5E-03 
3.0E-03
0.30 0.35 0.40 0.45 0.50 0.55 0.60 
Weighted time in active outdoors environment (hr/d) 
BDCF (rem/yr per pCi/L 
Neptunium-237 
5.5E-03 
6.0E-03 
6.5E-03 
7.0E-03 
7.5E-03 
8.0E-03 
8.5E-03
0.30 0.35 0.40 0.45 0.50 0.55 0.60 
Weighted time in active outdoors environment (hr/d) 
BDCF (rem/yr per pCi/L 
Plutonium-239 
6.0E-03 
8.0E-03 
1.0E-02 
1.2E-02 
1.4E-02
0.30 0.35 0.40 0.45 0.50 0.55 0.60 
Weighted time in active outdoors environment (hr/d) BDCF (rem/yr per pCi/L

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ANL-NBS-MD-000014 REV 00 6-67 October 2004 
6.2.5.3 External Exposure 
External exposure is an important pathway for only a few radionuclides (see Table 6.2-1 and 
6.2-2). The dose from external exposure depends on radionuclide concentrations in the soil 
(discussed in Section 6.2.4.1) and the duration of receptor exposure to the soil, modified by the 
building shielding factor, while indoors (BSC 2004 [DIRS 169460], Equation 6.4.7-1). There is 
little variability in this component because the receptor is assumed to be exposed to 
contaminated soil at all times, except for the time spent away by commuters (an average of 8 
hours per day), and an average of 2 hours per day spent away by the other population groups. 
6.3 IDENTIFICATION OF IMPORTANT PATHWAYS, PROCESSES AND 
PARAMETERS FOR THE VOLCANIC ASH EXPOSURE SCENARIO 
This section uses results of the runs of the biosphere model for the groundwater exposure 
scenario included in DTN: MO0407MWDGSMFV.000 [DIRS 170856]. For deterministic 
calculations the input was obtained from the model input data files 
(DTNs: MO0403SPAAEIBM.002 [DIRS 169392]; MO0407SPAINEXI.002 [DIRS 170597]; 
MO0407SPASRPBM.002 [DIRS 170755]; MO0406SPAETPBM.002 [DIRS 170150]; 
MO0407SPACRBSM.002 [DIRS 170677]), as described in Section 4.1. 
6.3.1 Distributions of Biosphere Dose Conversion Factors 
This section evaluates the distributions of the BDCF components for the volcanic ash exposure 
scenario for radionuclides included in the biosphere model for this scenario, examines trends in 
the BDCFs, and evaluates the cause of these trends. Each run of the biosphere model for the 
volcanic ash exposure scenario for a given radionuclide produced 1,000 model realizations, with 
the realization results in the form of three BDCF components and the value of the critical 
thickness. These components are incorporated into the TSPA model using the following 
expression (adapted from BSC 2004 [DIRS 169460], Equation 6.5.8-2) 
( ) ) ( ) ( ) , ( , , , , a p inh v inh Rn ing ext a d g BDCF t f BDCF BDCF t d BDCF + + = (Eq. 6.3-1) 
where 
BDCF(da, t) = BDCF for the primary radionuclide for an ash depth da at time t 
following a volcanic eruption (Sv/yr per Bq/m2) 
BDCFext,ing,Rn = BDCF for the primary radionuclide for non-inhalation pathways, 
that is, external exposure, ingestion, and inhalation of radon decay 
products (Sv/yr per Bq/m2) 
BDCFinh,v = BDCF for the primary radionuclide for short-term inhalation at 
post-volcanic level of mass loading in excess of nominal mass 
loading (Sv/yr per Bq/m2) 
BDCFinh,p = BDCF for the primary radionuclide for long-term inhalation at 
nominal level of mass loading (Sv/yr per Bq/m2) 
f(t) = decay function describing reduction of mass loading with time 
da = thickness of ash (m) 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-68 October 2004 
g(da) = function of ash thickness, da, representing the fraction of total 
activity that is available for resuspension. 
The function of time, f(t) in Equation 6.3-1, accounts for the reduction of mass loading in the 
years immediately following volcanic eruption and is expressed as (modified from BSC 2004 
[DIRS 169458], Equation 6.3-1) 
t e t f . - = ) ( (Eq. 6.3-2) 
where 
. = mass loading decrease constant (1/yr) 
t = time (yr); t = 0 is the first year after a volcanic eruption. 
The function of ash thickness (BSC 2004 [DIRS 169460], Section 6.5.1.2), g(da), is expressed as 
.. 
.. 
. 
=
< 
= when 
when 1 
) ( 
c a 
a
c 
c a 
a d d 
d
d 
d d 
d g (Eq. 6.3-3) 
where dc is the critical thickness of the ash layer. The critical thickness is defined as the 
thickness of the surface soil (ash) layer that is available for resuspension 
Each model realization used a different set of input parameter values. The three BDCF 
components generated by the biosphere model are the ingestion-radon-external exposure 
component, the short-term inhalation component, and the long-term inhalation component. The 
ingestion-external-radon component accounts for contributions from all ingestion pathways, 
including ingestion of locally produced food and inadvertent soil ingestion; external exposure; 
and inhalation exposure to radon decay products. The short-term inhalation component 
represents exposure to airborne particulate matter during the period of increased concentrations 
of resuspended particulates following volcanic eruption. This component is multiplied by the 
time-dependent function in the TSPA because mass loading will decrease after a volcanic 
eruption. The long-term inhalation component represents inhalation of resuspended particulates 
under nominal conditions (i.e., when mass loading is not elevated as the result of a volcanic 
eruption). One set of BDCFs was calculated for all climates. The BDCF statistics are 
summarized in the Disruptive Event Biosphere Dose Conversion Factor Analysis (BSC 2004 
[DIRS 167287], Tables 6.2-1 to 6.2-3 for the external-ingestion-radon component, short-term 
inhalation component, and the long-term inhalation component, respectively). 
Figures 6.3-1 to 6.3-3 show the ranges of BDCF components for all primary radionuclides 
included in the biosphere model for the volcanic ash scenario, including their mean and median 
values, minima and maxima, and the 5th and 95th percentiles. The figures were generated in the 
Excel workbook VA BDCF Variability Plots.xls (Appendix A). The variance in the BDCFs is a 
result of the input parameter variability and uncertainty that is propagated into the model output. 

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ANL-NBS-MD-000014 REV 00 6-69 October 2004 
1.E-11 
1.E-10 
1.E-09 
1.E-08 
1.E-07 
1.E-06 
Sr-90 
Tc-99 
Sn-126 
Cs-137 
Pb-210 
Ra-226 
Ac-227 
Th-229 
Th-230 
Th-232 
Pa-231 
U-232 
U-233 
U-234 
U-236 
U-238 
Np-237 
Pu-238 
Pu-239 
Pu-240 
Pu-242 
Am-241 
Am-243 
Radionuclide 
BDCF (rem/yr per pCi/m2) 
Source: Excel file VA BDCF Variability Plots.xls (Appendix A). 
NOTE: Boxes represent 5th to 95th percentile range. The vertical solid line represents the range and the tick mark on the line is the median. Circle represents 
the mean BDCF. 
Figure 6.3-1. Distributions of the Ingestion-Radon-External Exposure Component of the BDCFs for the Volcanic Ash Exposure Scenario 

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1.E-12 
1.E-11 
1.E-10 
1.E-09 
1.E-08 
1.E-07 
1.E-06 
1.E-05 
1.E-04 
Sr-90 
Tc-99 
Sn-126 
Cs-137 
Pb-210 
Ra-226 
Ac-227 
Th-229 
Th-230 
Th-232 
Pa-231 
U-232 
U-233 
U-234 
U-236 
U-238 
Np-237 
Pu-238 
Pu-239 
Pu-240 
Pu-242 
Am-241 
Am-243 
Radionuclide 
BDCF (rem/yr per pCi/m2) 
Source: Excel file VA BDCF Variability Plots.xls (Appendix A). 
NOTE: Boxes represent 5th to 95th percentile range. The vertical solid line represents the range and the tick mark on the line is the median. Circle represents the 
mean BDCF. 
Figure 6.3-2. Distributions of the Short-Term Inhalation Component of the BDCFs for the Volcanic Ash Exposure Scenario 

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1.E-12 
1.E-11 
1.E-10 
1.E-09 
1.E-08 
1.E-07 
1.E-06 
1.E-05 
1.E-04 
1.E-03 
Sr-90 
Tc-99 
Sn-126 
Cs-137 
Pb-210 
Ra-226 
Ac-227 
Th-229 
Th-230 
Th-232 
Pa-231 
U-232 
U-233 
U-234 
U-236 
U-238 
Np-237 
Pu-238 
Pu-239 
Pu-240 
Pu-242 
Am-241 
Am-243 
Radionuclide 
BDCF (rem/yr per pCi/m2) 
Source: Excel file VA BDCF Variability Plots.xls described in Appendix A. 
NOTE: Boxes represent 5th to 95th percentile range. The vertical solid line represents the range and the tick mark on the line is the median. Circle represents the 
mean BDCF. 
Figure 6.3-3. Distributions of the Long-Term Inhalation Component of the BDCFs for the Volcanic Ash Exposure Scenario 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
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A number of trends can be observed in the BDCF values. The variability in the 
ingestion-radon-external exposure BDCF component differs greatly among radionuclides. The 
95th to 5th percentile ratio vary from 1.1 to 13.7 except for 99Tc (the ratio for this radionuclide is 
42.3). The maximum values are higher than the minima by less than two orders of magnitude, 
except for 99Tc and 210Pb. There are a few radionuclides that have a very narrow distribution for 
the ingestion-radon-external exposure BDCF component. These are the radionuclides, such as 
126Sn, 137Cs, 232Th, and 232U, that have a large fraction of the BDCFs attributable to the external 
exposure pathway. External exposure may be due to the decay products of these radionuclides. 
For the short-term and long term inhalation components, BDCF distributions differ among 
radionuclides only by the value of the inhalation dose conversion factor, which is a fixed 
parameter, and functions here as a scaling factor. For all short-term BDCF components, the ratio 
of the 95th to 5th percentile is 8.4 and the maximum to minimum ratio is 58.5. The corresponding 
values for the long-term inhalation component are 6.7 and 34.3, respectively. 
6.3.2 Summary of Pathway Analysis 
The pathway contributions to the mean BDCF for the volcanic ash exposure scenario and the 
present-day climate are summarized in the Disruptive Event Biosphere Dose Conversion Factor 
Analysis (BSC 2004 [DIRS 167287], Table 6.2-7). These results are reproduced in Table 6.3-1. 
The differences between the volcanic ash scenario BDCFs for the present-day and future 
climates are insignificant (BSC 2004 [DIRS 167287], Section 6.2.5). 
To calculate the annual dose, the BDCF components are combined in the TSPA model with the 
time dependent source term and ash thickness information. Therefore, the BDCF pathway 
contributions listed in Table 6.3-1 refer to specific conditions. Here they are presented for the 
point-in-time and ash-layer-thickness conditions, when the values of parameters t and da in 
Equations 6.3-1 to 6.3-3 are constant. From Equations 6.3-1 to 6.3-3, when t = 0 (i.e., for the 
initial values of ash deposition and before the mass loading decrease occurs) and da = dc (i.e., all 
deposited activity can become resuspended), then 
p inh v inh Rn ing ext a BDCF BDCF BDCF t d BDCF , , , , ) , ( + + = (Eq. 6.3-4) 
The biosphere model for the volcanic ash exposure scenario explicitly addresses 12 exposure 
pathways. The pathways related to groundwater contaminationsuch as water consumption, 
consumption of aquatic food, and inhalation of aerosols from evaporative coolersare not 
included because contamination of water in modeled in the groundwater exposure scenario. 
Pathway analysis was conducted to determine the relative importance of individual exposure 
pathways in terms of their contributions to BDCFs for various radionuclides. Percent 
contributions to the BDCF were calculated using the mean values of the BDCFs. 

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Table 6.3-1. Exposure Pathway Contributions (Percent) for the Mean Volcanic Ash Exposure Scenario BDCFs for the Present-Day Climate 
Inhalation Ingestion 
Radionuclide 
External Short Long Radon 
Leafy 
Veget. 
Other 
Veget. Fruit Grain Meat Milk Poultry Eggs Soil 
Sr-90 7.2 14.4 28.7 0.0 11.7 9.0 12.2 0.9 5.6 6.9 0.1 2.7 0.8 
Tc-99 0.3 2.6 5.1 0.0 20.1 4.4 17.2 0.9 7.0 25.7 0.2 16.4 0.0 
Sn-126 99.1 0.2 0.5 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 
Cs-137 98.1 0.3 0.5 0.0 0.0 0.0 0.1 0.0 0.3 0.2 0.2 0.2 0.0 
Pb-210 0.1 31.9 63.6 0.0 0.5 0.2 1.0 0.1 0.1 0.1 0.0 1.5 0.9 
Ra-226 36.5 8.5 17.0 37.5 0.1 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.1 
Ac-227 0.0 33.4 66.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 
Th-229 0.1 33.3 66.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 
Th-230 0.0 33.4 66.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 
Th-232 0.9 33.1 66.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 
Pa-231 0.0 33.4 66.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 
U-232 1.0 33.0 65.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 
U-233 0.0 33.4 66.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 
U-234 0.0 33.4 66.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 
U-235 0.0 33.4 66.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 
U-236 0.2 33.3 66.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 
Np-237 0.3 33.2 66.2 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 
Pu-238 0.0 33.4 66.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 
Pu-239 0.0 33.4 66.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 
Pu-240 0.0 33.4 66.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 
Pu242 0.0 33.4 66.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 
Am-241 0.0 33.4 66.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 
Am-243 0.4 33.2 66.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 
Source: BSC 2004 [DIRS 167287], Table 6.2-7. 
NOTE: The pathway contributions are for the conditions when t = 0 (i.e., for the initial values of ash deposition and before the mass loading decrease occurs) and 
da = dc (i.e., all deposited activity can become resuspended). 

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Figure 6.3-4 shows the average pathway contributions from Table 6.3-1 for several selected 
radionuclides (Excel file Detailed Pathway Analysis VA.xls in Appendix A). The selection 
includes the radionuclides that were identified as important in previous TSPA efforts, such as 
90Sr, 137Cs, 237Np, 239Pu, and 241Am (CRWMS M&O 2000 [DIRS 153246], Figure 4.2-2). 
Radon-226 was added to the list as an example of a radionuclide with a notably different 
composition of pathway contributions. 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100 
Average Percent Pathway Contribution 
External 
Inhalation Short 
Inhalation Long 
Radon 
Leafy Vegetables 
Other Vegetables 
Fruit 
Grain 
Meat 
Milk 
Poultry 
Eggs 
Soil Sr-90 
Cs-137 
Ra-226 
Np-237 
Pu-239 
Am-241 
Figure 6.3-4. Average Percent BDCF Pathway Contributions for the Volcanic Ash Exposure Scenario for 
Time = 0 and Ash Thickness Equal to or Less than Critical Thickness for Selected 
Radionuclides 
If the ash thickness is greater than the critical thickness, the pathway composition changes from 
that shown in Table 6.3-1. If the ash thickness is 10 times that of the critical thickness, then the 
contribution of the inhalation BDCF components is reduced in proportion to dc/ds, that is, by a 
factor of 10. The pathway contributions for t = 0 are illustrated in Figure 6.3-5. Even though the 
activity available for resuspension is 10 times less, the inhalation pathway still dominates for the 
actinides. When the level of dust in air returns to the pre-eruption level, the short-term inhalation 
component no longer contributes to the all-pathway dose. 

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0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100 
Average Percent Pathway Contribution 
External 
Inhalation Short 
Inhalation Long 
Radon 
Leafy Vegetables 
Other Vegetables 
Fruit 
Grain 
Meat 
Milk 
Poultry 
Eggs 
Soil 
Sr-90 
Cs-137 
Ra-226 
Np-237 
Pu-239 
Am-241 
Source of both figures on this page: Excel file Detailed Pathway Analysis VA.xls (Appendix A). 
Figure 6.3-5. Average Percent BDCF Pathway Contributions for the Volcanic Ash Exposure Scenario for 
Time = 0 and Ash Thickness 10 Times Greater Than Critical Thickness for Selected 
Radionuclides 
The pathway contributions for 90Sr and 99Tc are diverse, and there is not a dominant contributor. 
The ingestion pathways are, overall, more important for 99Tc-99 than they are for 90Sr. For 137Cs, 
external exposure accounts for 98 percent of the dose. The BDCF for 226Ra includes a large 
contribution from exposure to radon decay products (37.5 percent), as well as from inhalation 
(25.5 percent) and external exposure (36.5 percent). Ingestion is an unimportant exposure 
pathway for 226Ra. The dose for primary radionuclides with atomic numbers greater than 88 
arises from the short- and long-term inhalation. The other pathways are negligible (Table 6.3-1). 
The results of previous TSPA assessments indicate that, except for the initial few hundred years 
postclosure, the expected dose from a volcanic eruption is primarily due to the transuranics 
(CRWMS M&O 2000 [DIRS 153246], Figure 4.2-2). The following analysis concentrates on a 
few selected transuranics: 241Am, 239Pu, 240Pu and 237Np. For these and other transuranics, BDCF 
pathway contributions are nearly identical (Table 6.3-1), with the short-term inhalation 
accounting for about one-third and the long-term inhalation accounting for about two-thirds of 
the BDCF the first year following an eruption. 
6.3.3 Sources of Uncertainty in the Biosphere Dose Conversion Factors 
The source of variance in the BDCF values (see Figures 6.3-1 to 6.3-3) is the uncertainty and 
variability in the values of the input parameters for the biosphere model. This section discusses 
the degree to which selected input parameters influence the BDCFs. This was quantified by 
calculating rank correlation coefficients. A correlation coefficient is a number between -1 and 1 
that measures the degree to which two variables are linearly related. 

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Correlation coefficients for the stochastic model input parameters and BDCF components for the 
volcanic ash exposure scenario were calculated for the selected radionuclides (see Excel file VA 
Correlations.xls in Appendix A). Of the selected radionuclides considered in Section 6.3.2, 90Sr, 
99Tc, and 137Cs have a significant BDCF component from the pathways other than the inhalation 
of particulate matter. Therefore, the correlation coefficients for the ingestion-radon-external 
exposure pathways were calculated for these radionuclides only and are presented in Table 6.3-2 
(see Excel file VA Correlations.xls in Appendix A). Only those correlations that are non-zero at 
the 99 percent confidence interval (absolute value of the correlation coefficient equal or greater 
than 0.0812) are shown in the table, plus the next correlation that is below this threshold (see 
Section 6.2.3.2 for calculation of the statistically significant value). The list includes the false 
correlations that were above the threshold value (marked with an a), as explained in 
Section 6.2.3.2. 
Table 6.3-2 Correlation Coefficients for Input Parameters and the Ingestion-Radon-External Exposure 
Component of Biosphere Dose Conversion Factors for the Volcanic Ash Exposure 
Scenario 
Radionuclide Parameter 
Correlation 
Coefficient 
Correlation 
Coefficient Squared 
Strontium partition coefficient (Kd) -0.672 0.451 
Strontium transfer factor for leafy vegetables 0.631 0.398 
Strontium transfer factor for forage 0.628 0.394 
Strontium transfer factor for fruit 0.616 0.379 
Strontium transfer factor for other vegetables 0.583 0.340 
Strontium transfer factor for grain 0.544 0.296 
Surface soil depth -0.529 0.280 
Strontium transfer coefficient for meat 0.153 0.024 
Dry to wet ratio for leafy vegetables 0.117 0.014 
Soil density -0.116 0.013 
Dry to wet ratio for fruit 0.115 0.013 
Strontium transfer coefficient for eggs 0.113 0.013 
Critical thickness 0.092 0.009 
Dry to wet ratio for other vegetables 0.086 0.007 
Neptunium transfer coefficient for milk a -0.082 0.007 
Strontium-90 
Population fraction, commuters 0.080 0.006 
Technetium partition coefficient (Kd) -0.764 0.584 
Technetium transfer factor for leafy vegetables 0.696 0.485 
Technetium transfer facto for forage 0.683 0.466 
Technetium transfer factor for grain 0.675 0.455 
Technetium transfer factor for fruit 0.674 0.454 
Technetium transfer factor for other vegetables 0.596 0.355 
Soil depth -0.390 0.152 
Technetium transfer coefficient for milk 0.178 0.032 
Dry to wet ratio for leafy vegetables 0.086 0.007 
Technetium-99 
Cesium transfer factor for leafy vegetables a 0.079 0.006 

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Table 6.3-2 Correlation Coefficients for the Input Parameters and Ingestion-Radon-External Exposure 
Component of Biosphere Dose Conversion Factors for the Volcanic Ash Exposure 
Scenario (Continued) 
Radionuclide Parameter 
Correlation 
Coefficient 
Correlation 
Coefficient Squared 
Population fraction, outdoor workers 0.372 0.139 
Time spent away, indoor workers -0.350 0.123 
Time spent away, non-workers -0.320 0.102 
Population fraction, commuters -0.312 0.097 
Time spend in inactive outdoors environment, 
indoor workers 0.278 0.078 
Time spend in inactive outdoors environment, nonworkers 
0.203 0.041 
Soil depth -0.197 0.039 
Cesium transfer factor for forage 0.185 0.034 
Cesium partition coefficient (Kd) -0.171 0.029 
Cesium transfer factor for grain 0.165 0.027 
Time spend in active outdoors environment, nonworkers 
0.155 0.024 
Cesium transfer factor for fruit 0.152 0.023 
Cesium transfer coefficient for poultry 0.149 0.022 
Time spend in active outdoors environment, indoor 
workers 0.143 0.021 
Cesium transfer factor for leafy vegetables 0.134 0.018 
Deposition velocity 0.115 0.013 
Protactinium transfer coefficient for milk a -0.109 0.012 
Time spent away, commuters -0.104 0.011 
Cesium transfer factor for other vegetables 0.101 0.010 
Cesium transfer coefficient for eggs 0.095 0.009 
Cesium transfer coefficient for meat 0.092 0.008 
Time spend in inactive outdoors environment, 
commuters 0.086 0.007 
Enhancement factor for inactive outdoors 
environments -0.086 0.007 
Cesium-137 
Cesium transfer coefficient for milk 0.078 0.006 
Source: Excel file VA Correlations.xls (Appendix A). 
a false correlation 
For 90Sr and 99Tc, the highest correlations for the ingestion-radon-external exposure BDCF 
component are with the parameters that control transfer of radioactivity to crops and retention of 
radionuclides in the surface soil. For these radionuclides, there is a strong a positive correlation 
of BDCFs with the soil-to-pant transfer factors and a negative correlation with Kds. Correlation 
with the Kd is an artifact of having Kds and transfer factors negatively correlated in the model 
because leaching is not a radionuclide removal mechanism that is included in the model for the 
volcanic ash exposure scenario. 

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The variance in the ingestion-radon-external exposure BDCF component for 137Cs is influenced 
primarily by the weighted time spent in the receptor environments, which depends on the 
population proportions and time spent in the receptor environments by the population groups. A 
very small fraction of the BDCF variance for 137Cs is due to the parameters related to the 
ingestion pathways. Although consumption of crops is an unimportant pathway for 137Cs, 
soil-to-depth transfer factors, soil depth, and the partition coefficient were correlated with the 
BDCF component for ingestion, inhalation of radon decay products, and external exposure. This 
is because the variation in those input parameters is large relative to variation in the input 
parameters used to calculate external exposure. 
The correlation coefficients for both inhalation components for all radionuclides are presented in 
Table 6.3-3. Only those correlations that are non-zero at the 99 percent confidence interval 
(absolute value of the correlation coefficient equal or greater than 0.0812) are shown in the table, 
plus the next correlation that is below this threshold. Table 6.3-3 includes false correlations 
(marked with an a) that were above the threshold value, as explained in Section 6.2.3.2. The 
correlation coefficients are the same for all radionuclides because the stochastic parameters that 
are used to calculate these BDCF components are radionuclide-independent. 
Table 6.3-3. Correlation Coefficients for the Input Parameters and Inhalation Components of Biosphere 
Dose Conversion Factors for the Volcanic Ash Exposure Scenario 
Short-term Inhalation Component Long-term Inhalation Component 
Parameter CC CC2 Parameter CC CC2 
Ash mass loading, active 
outdoors environment 0.641 0.411 
Dust mass loading, active 
outdoors 0.555 0.308 
Enhancement factor, active 
outdoors environment 0.494 0.244 Critical thickness -0.496 0.246 
Critical thickness -0.447 0.200 
Enhancement factor, active 
outdoors 0.491 0.241 
Population proportion, outdoor 
workers 0.251 0.063 
Population proportion, outdoor 
workers 0.294 0.087 
Time spent active outdoors, 
non-workers 0.154 0.024 
Time spent active outdoors, 
non-workers 0.176 0.031 
Time spent active outdoors, 
indoor workers 0.138 0.019 
Time spent active outdoors, 
indoor workers 0.146 0.021 
Lead transfer factor for leafy 
vegetables a 0.093 0.009 
Thorium transfer factor for 
leafy vegetables a -0.096 0.009 
Time spent in inactive outdoors 
environment, outdoor workers -0.092 0.009 
Chlorine transfer factor for 
leafy vegetables a 0.089 0.008 
Tin transfer coefficient for meat 
a -0.088 0.008 
Chlorine transfer factor for 
fruits a 0.084 0.007 
Enhancement factor, active 
indoor environment 0.083 0.007 
Protactinium transfer factor for 
other vegetables a 0.078 0.006 
Neptunium transfer factor for 
forage a 0.081 0.007 
Dry biomass for other 
vegetables 0.080 0.006 
Source: Excel file VA Correlations.xls (Appendix A). 
a false correlation; CC= correlation coefficient 

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For both inhalation components, air mass loading for the active outdoors environment and the 
enhancement factor for the same environment are among the input parameters with large 
contributions to the BDCF variance. Critical thickness is also important, as it controls the level 
of activity concentration in the resuspendable layer of surface soil that, in turn, influences 
inhalation dose. These three parameters account for a significant fraction of the BDCF variance. 
Population proportion of outdoor workers is a less important contributor to the BDCF variance 
(Table 6.3-3). 
6.3.4 Analysis of the Environmental Transport Pathways and Radionuclide 
Accumulation in the Environmental Media 
The dose to the receptor from deposition of contaminated volcanic ash on the soil surface arises 
from the intake of and exposure to contaminated soil and other environmental media that become 
contaminated as a result of environmental transport of radionuclides from the soil. The 
environmental media included in the biosphere model for the volcanic ash exposure scenario 
include surface soil, air, plants, and animals. For the volcanic ash exposure scenario, water is 
assumed uncontaminated. Surface soil becomes contaminated from the deposition of volcanic 
ash. Airborne contamination is a result of resuspension of contaminated soil. Radionuclide 
accumulation in plants occurs as a result of transport from soil and air. Feed and soil are sources 
of radionuclide intake by animals. 
This section discusses calculation of radionuclide concentrations in the environmental media. 
6.3.4.1 Radionuclide Accumulation in Surface Soil 
In the volcanic exposure scenario, surface soil is a primary source of contamination for all 
environmental transport and receptor exposure pathways. These pathways include resuspension 
of soil particles, with the subsequent deposition on crops and inhalation by humans; external 
exposure; radionuclide uptake by crops through their roots; emission of radon and inhalation of 
radon decay products by humans; and soil ingestion by humans and animals. 
The biosphere model for the volcanic ash exposure scenario calculates radionuclide 
concentrations in the resuspendable layer of uncultivated surface soil and radionuclide 
concentrations in the surface soil down to the tilling depth for a unit activity deposited per unit 
surface area of cultivated soil. Unlike the biosphere model for the groundwater scenario, the 
biosphere model for the volcanic ash scenario does not account for any subsequent addition or 
removal of radionuclides. This function is carried out in the TSPA model. 
To calculate radionuclide concentrations in the cultivated surface soil, the available activity of a 
radionuclide is mixed within the tilling depth of the soil, thus making the radionuclide 
concentrations inversely proportional to the soil depth. This relationship results in a relatively 
strong negative correlation of the ingestion pathway of the ingestion-radon-external exposure 
BDCF component with the soil depth, as shown in Table 6.3-2. The radionuclide concentration 
in the resuspendable layer of uncultivated soil is likewise dependent on the critical thickness, 
which results in a negative correlation of the inhalation BDCF components with the critical 
thickness. 

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The dependence of the short-term inhalation BDCF for 241Am on the value of the critical 
thickness is shown in Figure 6.3-6. The relationship between these two variables for other 
radionuclides is the same. 
1.0E-07 
3.0E-07 
5.0E-07 
7.0E-07 
9.0E-07 
1.1E-06 
1.3E-06 
1.5E-06 
1.7E-06 
1.0 1.5 2.0 2.5 3.0 
Critical thickness (mm) 
BDCF (rem/yr per pCi/m 2) 
Source: Excel file Dependence of VA BDCFs on Inputs.xls (Appendix A). 
Figure 6.3-6. Dependence of Short-Term Inhalation BDCF Component for 241Am on Critical Thickness 
6.3.4.2 Radionuclide Transport to Air 
Radionuclide transport from soil to air occurs via resuspension of surface soil and exhalation of 
radon from the soil. Resuspension of soil results in particulate matter becoming airborne. 
The radionuclide concentration in air is calculated in the biosphere model for the volcanic ash 
exposure scenario using the same method as that used in the groundwater exposure scenario, as 
the product of radionuclide concentration in soil, atmospheric mass loading, and the 
enhancement factor (see Section 6.2.4.2.2). The average concentrations of 241Am in air in the 
four contaminated environments used in the calculation of the short-term and long-term 
inhalation BDCF components are shown in Figure 6.3-7. The graph shows that the level of 
radionuclide concentration in air for the active outdoor environment is much higher than that in 
any of the remaining environments. 
The radionuclide concentration in the active outdoors environment is high because both 
atmospheric mass loading and the enhancement factor are high for this environment, as shown in 
Figures 6.3-8 and 6.3-9, respectively. The mass loading for ash shown in Figure 6.3-8 is used to 
calculate the increase in mass loading following an eruption for the short-term inhalation BDCF 
component. The nominal mass loading is used in the calculation of the long-term inhalation 
BDCF component. 

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0.0E+00 
5.0E-06 
1.0E-05 
1.5E-05 
Radionuclide concentration 
in air (Bq/m3) 
Active 
Outdoor 
Inactive 
Outdoor 
Active 
Indoor 
Asleep 
Indoor 
Short-term inhalation 
Long-term inhalation 
Source: Excel file Detailed Pathway Analysis VA.xls (Appendix A). 
Figure 6.3-7. Average Radionuclide Concentration in Air by Receptor Environment Used in Calculation of 
Short-Term and Long-Term Inhalation BDCF Component. 
0.0E+00 
1.0E-06 
2.0E-06 
3.0E-06 
4.0E-06 
5.0E-06 
Mass loading (kg/m3) 
Active 
Outdoor 
Inactive 
Outdoor 
Active 
Indoor 
Asleep 
Indoor 
Mass loading for ash 
Nominal mass loading 
Source: Excel file Detailed Pathway Analysis VA.xls (Appendix A). 
Figure 6.3-8. Average Atmospheric Mass Loading by Receptor Environment Used in Calculation of 
Short-Term (Mass Loading for Ash) and Long-Term (Nominal Mass Loading) Inhalation 
BDCF Component 
0 
0.5
1 
1.5
2 
2.5
3 
3.5
4 
4.5
5 
Enhancement factor 
Active 
Outdoors 
Inactive 
Outdoors 
Active 
Indoors 
Asleep 
Indoors 
Source: Excel file Detailed Pathway Analysis VA.xls (Appendix A). 
Figure 6.3-9. Average Enhancement Factor by Receptor Environment Used in Calculation of the 
Short-Term and Long-Term Inhalation BDCF Component 

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A dependence of both inhalation BDCF components for 241Am on mass loading in the active 
outdoors environment is shown in Figures 6.3-10 and 6.3-11 for the averaged values of the 
variables. The graphs show that the inhalation BDCF components are strongly affected by mass 
loading in the active outdoors environment. This parameter accounts for 41 and 31 percent of 
the variance in the short-term and long-term inhalation BDCF component, respectively 
(Table 6.3-3). 
1.0E-07 
3.0E-07 
5.0E-07 
7.0E-07 
9.0E-07 
1.1E-06 
1.3E-06 
1.5E-06 
1.7E-06
5.E-07 2.E-06 3.E-06 4.E-06 5.E-06 
Ash Mass Loading (kg/m3) 
BDCF (rem/yr per pCi/m2) 
Source: Excel file Dependence of VA BDCFs on Inputs.xls (Appendix A). 
Figure 6.3-10. Dependence of Short-Term Inhalation BDCF Component for 241Am on Ash Mass Loading 
in the Active Outdoors Environment 
5.0E-07 
1.0E-06 
1.5E-06 
2.0E-06 
2.5E-06 
3.0E-06 
3.5E-06 
4.0E-06
2.E-06 4.E-06 6.E-06 8.E-06 1.E-05 
Nominal mass loading (kg/m3) 
BDCF (rem/yr per pCi/m 2) 
Source: Excel file Dependence of VA BDCFs on Inputs.xls (Appendix A). 
Figure 6.3-11. Dependence of Long-Term Inhalation BDCF Component for 241Am on Nominal Mass 
Loading in the Active Outdoors Environment 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 6-83 October 2004 
The influence of mass loading on the inhalation BDCF components for 241Am was investigated 
in a series of deterministic model runs. Table 6.3-4 shows the values of mass loading in the 
active outdoors environment used in the runs and the corresponding values of the short-term and 
long-term inhalation BDCF components and the percent change relative to the average value. 
Table 6.3-4. Inhalation BDCF Components for 241Am and Percent Change for Different Levels of Mass 
Loading in the Active Outdoors Environment 
Short-term Inhalation Long-term Inhalation 
Mass Loading 
Conditions 
Ash mass 
loading, mg/m3 
BDCF, rem/yr 
per pCi/m2 
% BDCF 
change 
Nominal mass 
loading, mg/m3 
BDCF, rem/yr 
per pCi/m2 
% BDCF 
change 
Average 2.5 7.14E-07 5.0 1.35E-06 
Maximum 5.0 1.35E-06 89.0 10.0 2.62E-06 94.3 
Double Maximum 10.0 2.62E-06 267.2 20.0 5.16E-06 282.8 
NOTE: BDCFs were calculated in deterministic runs of ERMYN_VA_MC8_Det_Base.gsm by changing the 
radionuclide selection and the values of mass loading. The percent change for the BDCFs was calculated in 
the Excel spreadsheet Dependence of VA BDCFs on Inputs.xls (Appendix A). 
The value of the inhalation BDCF components changes practically in proportion to the value of 
ash mass loading and nominal mass loading in the outdoor active environment. The other 
environments have a negligible influence on the inhalation BDCF component, as demonstrated 
in Table 6.3-5, which shows the results of the deterministic model runs for different values of 
mass loading in the inactive outdoors environment. 
Table 6.3-5. Inhalation BDCF Components for 241Am and Percent Change for Different Levels of Mass 
Loading in the Inactive Outdoors Environment 
Short-term Inhalation Long-term Inhalation 
Mass Loading 
Conditions 
Ash mass 
loading, mg/m3 
BDCF, rem/yr 
per pCi/m2 
% BDCF 
change 
Nominal mass 
loading, mg/m3 
BDCF, rem/yr 
per pCi/m2 
% BDCF 
change 
Average 0.06 7.14E-07 0.06 1.35E-06 
Maximum 0.20 7.27E-07 1.9 0.10 1.35E-06 0.3 
Double Maximum 0.40 7.47E-07 4.7 0.20 1.36E-06 1.0 
NOTE: BDCFs were calculated in deterministic runs of ERMYN_VA_MC8_Det_Base.gsm by changing the 
radionuclide selection and the values of mass loading. The percent change for the BDCFs was calculated 
in the Excel spreadsheet Dependence of VA BDCFs on Inputs.xls (Appendix A). 
Even when mass loading in the inactive outdoor environment is twice the maximum value used 
in the model, the BDCF change is less than 5 percent. 
6.3.4.3 Radionuclide Transport to Crops 
Environmental transport pathways considered in the biosphere model for the volcanic ash 
exposure scenario that result in radionuclide transport to crops are: 
 Deposition of resuspended contaminated soil in crop surfaces 
 Root uptakes of radionuclides present in surface soil. 

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ANL-NBS-MD-000014 REV 00 6-84 October 2004 
The fractions of radionuclide concentration in the crop types considered in the biosphere model 
for 90Sr, 99Tc, and 241Am are summarized in Table 6.3-6; see Excel file Detailed Pathway 
Analysis VA.xls in Appendix A for calculation details. Radionuclides 90Sr and 99Tc were selected 
to show pathway contributions leading to contamination of crops for radionuclides whose BDCF 
contributions arise primarily from ingestion of locally produced food, including crops. 
Americium-241 is a radionuclide that was identified as an important expected dose contributor in 
the previous assessment. However, for this radionuclide, the ingestion pathway contribution is 
negligible; inhalation of particulate matter is the only important BDCF contributor (see 
Table 6.3-1). 
Table 6.3-6. Fractions of Activity in Crops from Environmental Transport Processes for the Volcanic Ash 
Exposure Scenario 
Crop Type 
Radionuclide Transport Process 
Leafy 
Vegetables 
Other 
Vegetables Fruits Grains 
Cattle 
Forage 
Dust deposition 0.025 0.008 0.027 0.028 0.017 
Strontium-90 
Root uptake 0.975 0.992 0.973 0.972 0.983 
Dust deposition 0.001 0.002 0.005 0.008 0.002 
Technetium-99 
Root uptake 0.999 0.998 0.995 0.992 0.998 
Dust deposition 0.758 0.624 0.636 0.810 0.628 
Americium-241 
Root uptake 0.242 0.376 0.364 0.190 0.372 
Source: Excel file Detailed Pathway Analysis VA.xls (Appendix A). 
For 90Sr and 99Tc, root uptake is a dominant mechanism of radionuclide transport to crops. 
Deposition of resuspended soil contributes only up to 3 percent of the activity concentration in 
plants. Americium-241 is an element that is taken up by plant roots relatively poorly, so its 
concentration in plants is much less than that for 90Sr and 99Tc (concentrations from dust 
deposition are the same for all radionuclides because the parameters used to model these 
pathways are not element- or radionuclide-dependent). Therefore, deposition of resuspended soil 
in plant surfaces is the dominant mechanism of 241Am transport to plants. 
6.3.4.4 Radionuclide Transport to Animal Products 
Environmental transport pathways considered in the biosphere model for the volcanic ash 
exposure scenario that result in radionuclide transport to animal products are animal 
consumption of feed and animal consumption of surface soil as well as, indirectly, environmental 
transport pathways leading to radionuclide accumulation in forage plants and in the surface soil. 
The fractions of radionuclide concentration in animal products resulting from feed and soil 
consumption are summarized in Table 6.3-7. 

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ANL-NBS-MD-000014 REV 00 6-85 October 2004 
Table 6.3-7. Fractions of Activity in Animal Products from Environmental Transport Processes for the 
Volcanic Ash Exposure Scenario 
Animal Product 
Radionuclide Transport Process Meat Milk Poultry Eggs 
Feed Consumption 0.959 0.958 0.653 0.651 
Strontium-90 
Soil Consumption 0.041 0.042 0.347 0.349 
Feed Consumption 0.996 0.996 0.901 0.900 
Technetium-99 
Soil Consumption 0.004 0.004 0.099 0.100 
Feed Consumption 0.262 0.249 0.050 0.050 
Americium-241 
Soil Consumption 0.738 0.751 0.950 0.950 
Source: Excel file Detailed Pathway Analysis VA.xls (Appendix A). 
For 90Sr and 99Tc, feed consumption is the dominant mechanism of radionuclide transport to 
animal products, contributing 96 to nearly 100 percent of radionuclide concentration in meat and 
milk and 65 to 90 percent for poultry and eggs. 
The environmental pathway contributions for 241Am differ markedly from those for 90Sr. This is 
because americium is poorly taken up from the soil by cattle forage, so its overall activity 
concentration in forage is less than that for 90Sr. Thus, soil consumption becomes more 
important, in relative terms, because the activity intake for soil ingestion by an animal is the 
same for all radionuclides. 
6.3.5 Receptor Exposure Pathways 
6.3.5.1 Inhalation Pathway 
The inhalation dose for the volcanic ash exposure scenario is calculated in the biosphere model 
using a time-budget method, analogous to that used in the biosphere model for the groundwater 
exposure scenario (Section 6.2.5.2.1). Inhalation of particulate matter arising from resuspension 
of contaminated soil occurs in all receptor environments except away from contaminated area. 
Figure 6.3-12 illustrates the fractional contributions from these environments to the BDCF 
component that results from inhalation of airborne particulates. The Excel file Detailed Pathway 
Analysis VA.xls is the source of this and other figures in this section. 
The inhalation dose accrued in an active outdoors environment is a dominant contributor to both 
inhalation BDCF components. Inhalation intake for an environment depends on the time spent 
in this environment by the receptor, the activity concentration in the air, and the receptor 
breathing rate. The activity concentration in air is an environment-specific quantity that depends 
on the level of soil-disturbing and dust-generating activities that are conducted in an environment 
and on the increase in mass activity concentration of resuspended material relative to the mass 
activity concentration of the surface soil. This parameter was discussed in Section 6.3.4.2. The 
activity concentration in air is highest in the active outdoors environment for nominal conditions 
(used for calculation of the long-term inhalation BDCF component) and the post volcanic 
conditions of increased dustiness in air (used for calculation of the short-term BDCF component) 
as shown in Figure 6.3-7. 

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0.0 
0.2 
0.4 
0.6 
0.8 
1.0 
Fractional BDCF Contribution 
Active 
Outdoors 
Inactive 
Outdoors 
Active 
Indoors 
Asleep 
Indoors 
Short-term Inhalation 
Long-term Inhalation 
Source: Excel file Detailed Pathway Analysis VA.xls (Appendix A). 
Figure 6.3-12. Fractional Contributions of the Receptor Environments to the Short-Term and Long-Term 
BDCF Components 
Inhalation exposure for an environment also depends on the time spent in this environment by 
the receptor (see Section 6.2.5.2.1 for additional discussion). Figure 6.3-13 shows the weighted 
time for all receptor environments. There are small differences between this figure and 
Figure 6.2-29. The differences result from the larger aerial extent of the contaminated area for 
the volcanic ash scenario, compared with the groundwater scenario, which places some work 
locations inside the contaminated area for the volcanic ash scenario and outside for the 
groundwater scenario. Still, the conclusions drawn in Section 6.2.5.2.1 remain valid; the 
receptor spends relatively few hours per day in the active outdoors environment and most of his 
time indoors. 
0
2
4
6
8 
10 
12 
Time in environment 
(hr/day) Active 
Outdoors 
Inactive 
Outdoors 
Active 
Indoors 
Asleep 
Indoors 
Away 
Source: Excel file Detailed Pathway Analysis VA.xls (Appendix A). 
Figure 6.3-13. Weighted Time Spent in the Receptor Environments for Volcanic Ash Exposure Scenario 

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Another factor affecting radionuclide intake by inhalation is the breathing rate. The breathing 
rate in the biosphere model is environment-dependent and is the highest in the active outdoor 
environment. Breathing rates for various environments were shown in Figure 6.2-30. The same 
breathing rates were used for both exposure scenarios. 
The correlation statistics presented in Table 6.3-3 indicate that there are only a few 
receptor-related parameters used in the calculation of the inhalation BDCF components that 
affect their variance. These parameters are the proportion of outdoor workers and the times 
spent by non-workers and indoor workers (the largest population fractions) in the active outdoors 
environment. Time spent in the inactive outdoor environment by outdoor workers is another 
receptor-related parameter listed in Table 6.3-3 as having a small, but statistically significant 
correlation with the short-term inhalation BDCF component. 
Because the majority of the inhalation exposure occurs in the active outdoor environment, which 
is associated with the highest levels of airborne particulate matter, the modeling results for the 
inhalation pathway are sensitive to the proportion of outdoor workers, who spend about half of 
their time outdoors in the active outdoors environment, and on the time spent in this environment 
by the other population groups. The dependence of the short-term inhalation component on the 
fraction of outdoor workers is shown in Figure 6.3-14; there is a direct correlation between these 
two variables. 
5.0E-07 
7.0E-07 
9.0E-07 
1.1E-06 
1.3E-06 
1.5E-06
0.02 0.04 0.06 0.08 0.10 0.12 
Population proportion, outdoor workers 
BDCF (rem/yr per pCi/m2) 
Source: Excel file Dependence of VA BDCFs on Inputs.xls (Appendix A). 
Figure 6.3-14. Dependence of Short-Term Inhalation BDCF Component for 241Am on Proportion of 
Outdoor Workers 
To investigate the influence of the time spent in the active outdoors environment by the outdoor 
workers, the biosphere model was run in the deterministic mode for average conditions, that is, 
50 percent of the outdoor workers work time spent in the active outdoors environment, and for 
75 percent of their work time spent in the active outdoors environment. The parameter values 
and the model results are summarized in Table 6.3-8. 

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Table 6.3-8. Effect of a Change in the Daily Exposure Time in the Active Outdoor Environment for 
Outdoor Workers on the Long-Term Inhalation BDCF Component for 241Am 
Time in Environment, hr/day 
Conditions 
Active 
Outdoors 
Inactive 
Outdoors 
Active 
Indoors Asleep Away 
BDCF, 
rem/yr per 
pCi/m2 
% BDCF 
change 
Average (50% time in active 
outdoors environment) 3.1 4.2 6.4 8.3 2.0 1.350E-06 
75% time in active outdoors 
environment 4.5 2.8 6.4 8.3 2.0 1.565E-06 16.0 
NOTE: BDCFs were calculated in deterministic runs of ERMYN_VA_MC8_Det_Base.gsm by changing the 
radionuclide selection and the exposure time in the active outdoors environment. The percent change for the 
BDCFs was calculated in the Excel spreadsheet Dependence of VA BDCFs on Inputs.xls (Appendix A). 
If the time in the active outdoors environment is increased from 50 to 75 percent of the work 
time (an increase of about 1.4 hours in a total of 5.5 hours per day worked), the long-term BDCF 
component increases by about 16 percent. 
The members of all population groups that constitute the RMEI spend some time away from the 
contaminated area. Outdoor workers, indoor workers, and non-workers spend on average 
2 hours per day away; commuters spend, on average, 8 hours per day away, including their work 
time. To evaluate the sensitivity of the inhalation BDCF component to the time away, 2 hours of 
away time were subtracted for each of the population groups. This time was proportionally 
added to the times spent in other environments except for time asleep, which was kept fixed at 
8.3 hours per day. The resulting times are shown in Table 6.3-9. 
Table 6.3-9. Base Case and Modified Times Spent in Receptor Environments by Population Groups 
Commuters Non-workers Outdoor workers Indoor workers 
Environment Base Case Modified Base Case Modified Base Case Modified Base Case Modified 
Active outdoors 0.3 0.4 0.3 0.3 3.1 3.6 0.3 0.3 
Inactive outdoors 2.0 2.5 1.2 1.4 4.2 4.8 1.5 1.7 
Active indoors 5.1 6.5 12.2 14.0 6.4 7.3 11.9 13.7 
Asleep 8.3 8.3 8.3 8.3 8.3 8.3 8.3 8.3 
Away 8.3 6.3 2.0 0 2.0 0 2.0 0 
Source: Excel file Dependence of VA BDCFs on Inputs.xls (Appendix A). 
The long-term inhalation BDCF component for 241Am increased from 1.350  10-6 rem/yr per 
pCi/m2 to 1.473  10-6 rem/yr per pCi/m2, that is, by 9 percent. 
6.3.5.2 Ingestion 
The ingestion dose is expected to be an insignificant contributor to the receptor exposure from a 
volcanic eruption, because most of the expected dose likely will be due to inhalation of 
transuranics. There are only a few radionuclides, such as 90Sr and 99Tc, with a considerable 
fraction of the dose that is due to the consumption of contaminated food (Table 6.3-1). The dose 
from consumption of a given food type is calculated in the biosphere model as the product of 
radionuclide concentration in the food products, consumption rate, and the dose coefficient 

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converting radionuclide intake by ingestion to dose. The consumption rates of locally produced 
food were discussed in Section 6.2.5.1. 
6.3.5.3 External Exposure 
Only a few radionuclides have a large fraction of the dose attributable to the external exposure 
pathway. The most important of these radionuclides is 137Cs, with over 98 percent of the BDCF 
contribution attributable to external exposure (Table 6.3-1). External exposure depends on the 
level of contamination in the soil and the amount of time the receptor is exposed to radionuclides 
in the soil. The biosphere model assumes that, for calculating external exposure, radionuclides 
are always at the soil surface, that is, that there is no attenuation of external radiation in the soil. 
The only attenuation considered in the model is the shielding provided by dwellings. 
The exposure time in the model is population-weighted (see Section 6.2.5.2.1). Therefore, 
population proportions and time spent in the receptor environments are parameters that influence 
the variance in the BDCF contribution from external exposure (Table 6.3-2). 

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7. CONCLUSIONS 
7.1 SUMMARY OF FINDINGS 
This section provides a summary of the analysis findings. The following conclusions are 
applicable to the model files and input parameters described in Section 4.1 and may not apply for 
other model files or parameters. There is no output DTN generated in this analysis. 
7.1.1 Groundwater Exposure Scenario 
This section summarizes the findings of the importance and sensitivity analyses for the 
groundwater exposure scenario for the radionuclides used throughout Section 6.2. 
Carbon-14 
The exposure to 14C arises from ingestion of locally produced food and water. Variation in the 
BDCF for 14C is almost entirely due to uncertainty in ingestion of food. The inhalation and 
external exposure pathways are negligible. Ingestion of water contributes an average of 
18 percent. The relative importance of individual food consumption pathways reflects roughly 
the annual consumption rates of these foods. The notable exception is fish consumption. 
Although consumption rate of locally produced fish is relatively low, the fish consumption 
pathway is a dominant pathway, contributing on average up to 49 percent of the BDCF for 14C, 
because of the high calculated concentration of 14C in fish. 
Carbon has a high bioaccumulation in fish. This is because carbon is a major element that 
constitutes about 24 percent of the animal soft tissue (see Table 4.1-1 for values for meat and 
poultry). The bioaccumulation factor is a ratio of activity concentration (of 14C, in this scenario) 
in water to that in fish. The value of the bioaccumulation factor for the biosphere model was 
developed based on a literature review. Published values for the bioaccumulation factor for 
freshwater fish were measured in natural systems where the system components are in 
equilibrium. In other words, all components affecting the fish (water, aquatic plants, and aquatic 
organisms at a lower trophic level) are in equilibrium with the water with regard to the 
concentration of the contaminants. This is not the case for farm-grown fish, because they are 
raised using commercial feed, which is not contaminated. Because most of the carbon in fish 
comes from their food, the concentration of 14C in fish is overestimated. In the absence of 
bioaccumulation factors for farmed fish, it is difficult to evaluate the degree of conservatism 
associated with the estimates of 14C concentration in fish. 
Technetium-99 
The average BDCF for 99Tc is the lowest of all radionuclides considered in the biosphere model. 
About one-half of the BDCF for 99Tc is from consumption of water. The remainder is 
attributable to the consumption of locally produced food. Contributions from inhalation and 
external exposure are 2 to 3 orders of magnitude less than that for ingestion. The variation in the 
BDCF for 99Tc is almost entirely due to variation in radionuclide concentrations in foods that are 
ingested. 

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The BDCF contributions from individual food consumption pathways generally reflect the 
consumption rates for locally produced food types. Although locally produced food 
consumption rates have a direct influence on the magnitude and thus importance of the 
individual ingestion pathways, they have little influence the BDCF variance. This is because the 
consumption rates for the RMEI were developed as the means for the Amargosa Valley 
population, and their distributions reflect the uncertainty about the mean, rather than the 
population variability. Doubling the consumption rates used in the model increased the BDCF 
for 99Tc by about 22 percent. 
The model input parameters with the greatest degree of variance in common with the BDCF for 
99Tc are the overwatering rate, soil-to-plant transfer factors, transfer coefficients for animal 
products, and Kd. The overwatering rate, and to a lesser degree the technetium partition 
coefficient, control the removal of 99Tc from surface soil. The transfer factors and transfer 
coefficients for various food types and animal products influence the level of bioaccumulation of 
99Tc in these media. The values of these parameters used as biosphere model inputs typically 
span several orders of magnitude. However, orders of magnitude changes in the value of the 
partition coefficient result in the 99Tc BDCF changing by a factor of two or less. 
Regarding the environmental transport pathways leading to the contamination of crops with 99Tc, 
root uptake dominates the transport to crops, contributing about two-thirds of radionuclide 
concentration, with water deposition contributing about one-third. Feed consumption is the most 
important environmental transport pathway for animal products. 
Iodine-129 
Pathway contributions to the BDCF for 129I are similar to those for 99Tc, with consumption of 
water and ingestion of locally produced food accounting for the majority of the BDCF. 
Likewise, variation in the BDCF for 129I arises from variation in the food ingestion component. 
Contributions from the inhalation and external exposure components are 2 orders of magnitude 
less than that for ingestion and do not influence the variability in the value of the BDCF for 129I. 
The contribution from drinking water is greater than that for 99Tc, accounting, on average, for 69 
percent of the average BDCF. Consumption of animal products (meat, milk and eggs) is more 
important than consumption of crops. Contributions from consumption of meat and milk are 
more important for 129I than those for 99Tc because of the greater values of transfer coefficients 
for iodine than for technetium. 
The distribution of the BDCF for 129I is relatively narrow due to a large contribution from 
drinking water, which is a fixed BDCF component. 
The input parameters that contribute the most to the BDCF variance for 129I are those that control 
radionuclide removal from the surface soil (such as Kd and overwatering rate), and thus the level 
of radionuclide concentration in the surface soil. Also important are those parameter that 
quantify radionuclide transport to crops and animal products. The contributions of 
environmental pathways to 129I concentration in crops are different from those for 99Tc. 
Deposition of irrigation water is the most important plant pathway. Contamination of animal 
products is primarily due to feed consumption. 

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Estimates of the BDCF for 129I calculated using the biosphere model are conservative because 
the model does not account for the stable isotope of iodine, 127I, which is ubiquitous in the 
environment (NCRP 1983 [DIRS 167511], p. 2) and which will affect the dose from 129I. 
Another factor that limits the amount of 129I that can be accumulated in the human body, and 
specifically in the thyroid where iodine accumulates, is the low specific activity of 129I 
(NCRP 1983 [DIRS 167511], p. 1). Human intake of iodine involves both isotopes, and the 
thyroid content of these isotopes reflects the relative abundance of 127I and 129I taken into the 
body. 
Uranium-233 
On average, around 70 percent of the dose from 233U is due to inhalation of particulate matter, 
regardless of the climate. Consumption of drinking water and inhalation of aerosols generated 
by evaporative coolers are next, but neither one of these pathways contributes, on average, more 
than 21 percent. The importance of inhalation of aerosols from operation of evaporative coolers 
decreases for the future climate to, on average, less than 6 percent of the BDCF for 233U. The 
variance for the 233U BDCF is caused primarily by the Kd, which for uranium has an 
exceptionally large range, spanning 6 orders of magnitude from the 1st to 99th percentile. 
Although 233U has a very small ingestion component, variation in the BDCF for this radionuclide 
is influenced by parameters related to that component. This is due to a high degree of correlation 
between the Kds and the transfer factors used in the biosphere model. Similarly to other 
actinides, the BDCF for 233U also depends on the parameters that influence the level of 
equilibrium activity concentration of this radionuclide in surface soil, such as the erosion rate 
and the overwatering rate. 
Receptor exposure to 233U in resuspended particulate matter occurs primarily in the active 
outdoors environment. Thus, those model input parameters that are used to calculate doses from 
this pathway in this environment influence the BDCF value. These parameters are the mass 
loading and enhancement factor for the active outdoors environment. 
Neptunium-237 
Water consumption accounts, on average, for nearly half of the average BDCF value for 237Np 
for the present-day climate and for almost 64 percent for the future climate. Inhalation is the 
second most important exposure pathway. On average, about 60 percent of the inhalation dose 
for the present-day climate is from inhalation of resuspended soil, with the reminder due to 
inhalation of aerosols produced by evaporative coolers. The contribution of the inhalation 
pathway decreases for the future climate because of the lower level of radionuclide 
concentrations in the soil (due to a lower irrigation rate) and the decreased use of evaporative 
coolers in the future. The average contribution of the inhalation of aerosols generated in 
evaporative coolers is, on average, less than 5 percent in the future climate. Calculation of 
BDCF contribution from this pathway involves an uncertain parameter that quantifies the 
fraction of radionuclides transferred from water used in a cooler to the indoor air. The value of 
this parameter was not found in the literature; however the model results are relatively 
insensitive to its value. 

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Inhalation of particulate matter from resuspended soil depends on the level of mass loading in 
the receptor environments. Of particular importance is the active outdoors environment. 
Doubling the mass loading in this environment from an average value of 5 mg/m3 results in 
about a 14 percent increase in the present-day climate BDCF for 237Np. Mass loading in the 
other environments does not contribute substantially to the BDCF. 
Plutonium-239 
For 239Pu, inhalation of particulate matter is the most important pathway, accounting for about 
one-half of the BDCF. Consumption of water is the second most important pathway contributing 
on average from 28 percent (present-day climate) to about 44 percent (future climate) to the 
BDCF for 239Pu. Consumption of locally produced food and external exposure are not important. 
The variance in the BDCF for 239Pu arises almost exclusively from uncertainty in the inhalation 
pathway, since the water ingestion pathway contribution to the BDCF is fixed. The contributions 
to inhalation exposure from inhalation of particulate matter (resuspended contaminated soil) and 
inhalation of aerosols generated by evaporative coolers are, on average, 53 percent and 9 percent, 
respectively, for the present-day climate, and 44 and 3 percent, respectively, for the future 
climate. 
The dose accrual from inhalation of particulate matter occurs primarily in the active outdoors 
environment, where the concentration of 239Pu in air is the highest of all receptor environments. 
Increasing mass loading in this environment from an average value of 5 mg/m3 to 10 mg/m3 
increases the BDCF for 239Pu by almost 50 percent. The other environments have a negligible 
contribution to the BDCF for 239Pu. The BDCF contribution from inhalation of particulate 
matter also depends on the time spent by the receptor in the active outdoors environment. 
7.1.2 Volcanic Ash Exposure Scenario 
The pathway contributions for the volcanic ash scenario are modeled as functions of ash 
thickness and time since the eruption. Inhalation of particulate matter is the most important 
BDCF contributor for most radionuclides that were identified as important in the previous TSPA. 
These radionuclides were primarily transuranics. 
For both inhalation components, air mass loading for the active outdoors environment and the 
enhancement factor for the same environment are among the input parameters with large 
contributions to the BDCF value and variance. Critical thickness is also important as it controls 
the level of activity concentration in the resuspendable layer of surface soil that, in turn, 
influences inhalation dose. If the value of mass loading in this environment is doubled, keeping 
all other parameters at the same value, the inhalation BDCF components also double. 
External exposure is a dominant pathway for 137Cs, which may be important within a few tens to 
a few hundreds of years postclosure. The biosphere model assumes that, for calculating external 
exposure, radionuclides are always at the soil surface, that is, there is no attenuation of external 
radiation in the soil and the receptor is always exposed to contaminated soil while in 
contaminated areas. The only attenuation considered in the model is the shielding provided by 
dwellings. This approach overestimates the receptors exposure from radionuclides that are 
external to the receptors body. 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 7-5 October 2004 
7.2 HOW THE ACCEPTANCE CRITERIA WERE ADDRESSED 
The following information describes how this analysis addresses the acceptance criteria in the 
YMRP (NRC 2003 [DIRS 163274], Sections 2.2.1.3.13, 2.2.1.3.14 and 2.2.1.4.1). Only those 
acceptance criteria that are applicable to this report are discussed (see Section 4.2). In most 
cases, the applicable acceptance criteria are not addressed solely by this report; rather, the 
acceptance criteria are fully addressed when this report is considered in conjunction with other 
analysis and model reports that describe the biosphere. Where a subcriterion includes several 
components, only some of those components may be addressed. How these components are 
addressed is summarized below. 
Acceptance Criteria from Section 2.2.1.3.13, Redistribution of Radionuclides in Soil 
Acceptance Criterion 1, System Description and Model Integration Are Adequate. 
Subcriterion (1): The BDCFs are used directly by the TSPA. The analyses in Sections 6.2 and 
6.3, which identify the important soil-related pathways, processes, and parameters for the 
groundwater and volcanic exposure scenarios, respectively, show that the TSPA adequately 
incorporates important site features, physical phenomena, and couplings. 
Subcriterion (2): This analysis of the BDCFs, which constitute the biosphere model abstraction, 
provides the technical bases for determining the relative importance of the transport processes 
for the following processes related to the redistribution of radionuclides in soil that are important 
to repository performance: radionuclide accumulation in surface soil (Section 6.2.4.1); 
resuspension of surface soil (Section 6.2.4.2.2.). This analysis also provides technical bases for 
determining the relative importance of the receptor exposure pathways from groundwater that are 
important to repository development and are related to redistribution of radionuclides in soil: 
ingestion (Section 6.2.5.1), inhalation of particulate matter (Section 6.2.5.2.1), and external 
exposure (Section 6.2.5.3). 
Similarly, the following volcanic ash exposure scenario processes related to redistribution of 
radionuclides in soil that are important to repository development are addressed: radionuclide 
accumulation in surface soil (Section 6.3.4.1) and radionuclide transport to air (Section 6.3.4.2). 
This analysis also provides technical bases for determining the relative importance of the 
receptor exposure pathways related to volcanic exposure that are related to redistribution of 
radionuclides in soil and are important to repository development: inhalation (Section 6.3.5.1), 
ingestion (Section 6.3.5.2), and internal exposure (Section 6.3.5.3). 
Subcriterion (3): Section 6.1 shows that this importance and sensitivity analysis is consistent 
with modeling of redistribution of radionuclide in soil (climate, soil, sorption coefficients, 
volcanic ash properties, and radionuclide properties) used in other abstractions. For example, the 
analysis demonstrates that the uncertainty in partition coefficients does not have a proportional 
impact on BDCFs. Input parameters and assumptions for the biosphere model were developed in 
a series of five analysis reports (BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169671]; 
BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169458]; and BSC 2004 [DIRS 169459]) that are 
used consistently over all applicable abstractions. 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 7-6 October 2004 
Acceptance Criterion 2, Data Are Sufficient for Model Justification. 
Subcriterion (1): Input parameters for the biosphere model were developed and justified in a 
series of five analysis reports: BSC 2004 [DIRS 169673], BSC 2004 [DIRS 169671], BSC 2004 
[DIRS 169672], BSC 2004 [DIRS 169458], and BSC 2004 [DIRS 169459]. These parameters 
are consistent with the characteristics of the reference biosphere, including the processes of 
radionuclide redistribution in soil and with the definition of the RMEI in 10 CFR 63.312 
[DIRS 156605]. 
Subcriterion (2): Data are sufficient, as provided in Sections 4.1, 6.2, and 6.3 and in the five 
analysis reports on which this report is based, to assess the adequacy of characterization and 
incorporation of biosphere FEPs related to radionuclide redistribution in soil in the abstraction. 
The sensitivity analyses provided by this report show that adequate data were available and that 
new data would not invalidate prior modeling results or affect the extent to which the 
performance of the system is affected by a parameter value. 
Acceptance Criterion 3, Data Uncertainty Is Characterized and Propagated Through the 
Model Abstraction. 
Subcriterion (1): This sensitivity analysis shows that the values of parameters related to 
redistribution of radionuclide in soil, their assumed ranges, probability distributions, and 
bounding assumptions used in the TSPA are technically defensible, reasonably account for 
uncertainties and variabilities and do not result in an under-representation of the risk estimate. 
For example, Section 6.2.4.1 shows that the BDCFs are relatively insensitive to 
order-of-magnitude changes in Kd, thereby adding confidence to the selection of these values for 
the biosphere model. 
Subcriterion (2): The reports documenting development of the model parameter values 
(BSC 2004 [DIRS 169673], BSC 2004 [DIRS 169671], BSC 2004 [DIRS 169672], BSC 2004 
[DIRS 169458], and BSC 2004 [DIRS 169459]) and sensitivity analyses provided by this report 
show that the technical bases for the values and ranges of the BDCFs used in the abstraction, 
including soil characteristics, crop types, and irrigation rates, are appropriate. Data on the 
airborne particulate concentrations, which are based on the resuspension of appropriate material 
in a climate and level of disturbance similar to that which is expected to be found at the location 
of the reasonably maximally exposed individual during the compliance time period, are 
adequately selected and justified. 
Subcriterion (3): The uncertainty analyses show that data uncertainty in the values of 
parameters related to radionuclide redistribution in soil is adequately represented in the BDCFs 
developed for the TSPA. Statistics are developed for correlations between parameters 
comprising the BDCFs and radionuclides important to the groundwater exposure scenario 
(Section 6.2.4) and for radionuclides important to the volcanic ash exposure scenario 
(Section 6.3.4). 
Subcriterion (4): The objective of this analysis was to identify parameters or processes that 
most influence the results of biosphere model. This subcriterion is addressed throughout this 
analysis report. 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 7-7 October 2004 
Acceptance Criteria from Section 2.2.1.3.14, Biosphere Characteristics 
Acceptance Criterion 1, System Description and Model Integration Are Adequate. 
Subcriterion (1): The BDCFs are used directly by the TSPA. The analyses in Sections 6.2 and 
6.3, which identify the important pathways, processes, and parameters for the groundwater and 
volcanic exposure scenarios, respectively, show that the TSPA adequately incorporates important 
site features, physical phenomena, and couplings. 
Subcriterion (2): This analysis of the BDCFs, which constitutes the biosphere model 
abstraction, provides the technical bases for determining the relative importance of the transport 
processes for the following groundwater-related biosphere characteristics that are important to 
repository performance: radionuclide accumulation in surface soil (Section 6.2.4.1); operation of 
evaporative coolers (Section 6.2.4.2.1); resuspension of surface soil (Section 6.2.4.2.2.); 
radionuclide transport to crops (Section 6.2.4.3); radionuclide transport to animal products 
(Section 6.2.4.4); and radionuclide transport to aquatic foods (Section 6.2.4.5). This analysis 
also provides technical bases for determining the relative importance of the receptor exposure 
pathways from groundwater that are important to repository development: ingestion (Section 
6.2.5.1), inhalation of particulate matter (Section 6.2.5.2.1), inhalation of aerosols generated by 
evaporative coolers (Section 6.2.5.2.2), and external exposure (Section 6.2.5.3). 
Similarly, the following volcanic-exposure-related biosphere characteristics that are important to 
repository development are addressed: radionuclide accumulation in surface soil 
(Section 6.3.4.1), radionuclide transport to air (Section 6.4.3.2), radionuclide transport to crops 
(Section 6.3.4.3), and radionuclide transport to animal products (Section 6.3.4.4). This analysis 
also provides technical bases for determining the relative importance of the receptor exposure 
pathways related to volcanic exposure that are important to repository development: inhalation 
(Section 6.3.5.1), ingestion (Section 6.3.5.2), and internal exposure (Section 6.3.5.3). 
Subcriterion (3): Section 6.1 shows that this importance and sensitivity analysis is consistent 
with modeling of biosphere characteristics (climate, soil, sorption coefficients, volcanic ash 
properties, and radionuclide properties) used in other abstractions. Input parameters and related 
assumptions for the biosphere model were developed in a series of five analysis reports 
(BSC 2004 [DIRS 169673], BSC 2004 [DIRS 169671], BSC 2004 [DIRS 169672], BSC 2004 
[DIRS 169458], and BSC 2004 [DIRS 169459]) that are used consistently over all applicable 
abstractions. 
Acceptance Criterion 2, Data Are Sufficient for Model Justification. 
Subcriterion (1): Input parameters for the biosphere model were developed and justified in a 
series of five analysis reports: BSC 2004 [DIRS 169673], BSC 2004 [DIRS 169671], BSC 2004 
[DIRS 169672], BSC 2004 [DIRS 169458], and BSC 2004 [DIRS 169459]. These parameters 
are consistent with the characteristics of the reference biosphere and the definition of the RMEI 
in 10 CFR 63.312 [DIRS 156605]. The dietary and lifestyle characteristics of the RMEI were 
determined based on surveys of people living in the Amargosa Valley. Adequate descriptions of 
how the data were used, interpreted, and appropriately synthesized into the parameters are 
provided in the five analysis reports noted above. 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 7-8 October 2004 
Subcriterion (2): Data are sufficient, as provided in Sections 4.1, 6.2, and 6.3 and in the analysis 
reports on which this report is based, to assess the adequacy of characterization and 
incorporation of biosphere-related FEPs (such as climate changes) in the abstraction. The 
sensitivity analyses provided by this report show that adequate data were available and that new 
data would not invalidate prior modeling results or affect the extent to which the performance of 
the system is affected by a parameter value. 
Acceptance Criterion 3, Data Uncertainty Is Characterized and Propagated Through the 
Model Abstraction. 
Subcriterion (1): This sensitivity analysis shows that the parameter values, assumed ranges, 
probability distributions, and bounding assumptions used in the TSPA are technically defensible, 
reasonably account for uncertainties and variabilities and do not result in an under-representation 
of the risk estimate. For example, Section 6.2.4.1 shows that the BDCFs are relatively insensitive 
to order-of-magnitude changes in Kd, thereby adding confidence to the selection of these values 
for the biosphere model. The RMEI, per the requirements of 10 CFR 63.312(b) [DIRS 156605], 
reflects the dietary and lifestyle characteristics of people living in the Amargosa Valley 
(Section 6.1.3) and the parameters and data are consistent with that information. 
Subcriterion (2): The reports documenting development of the model parameter values 
(BSC 2004 [DIRS 169673], BSC 2004 [DIRS 169671], BSC 2004 [DIRS 169672], BSC 2004 
[DIRS 169458], and BSC 2004 [DIRS 169459]) and sensitivity analyses provided by this report 
show that the technical bases for the values and ranges of the BDCFs used in the abstraction, 
including 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 and adequate. 
Subcriterion (4): The uncertainty analyses show that uncertainty is adequately represented in 
the BDCFs developed for the biosphere characteristics modeling in the TSPA. 
Subcriterion (6): Section 6.2.2 evaluates the exposure pathway contributions to the BDCFs and 
identifies those pathways that contribute significantly to the BDCFs so as to most influence 
repository performance for the time period of compliance specified in 10 CFR Part 63. 
Section 6.2.5 discusses the important pathways, processes, and parameters for selected 
radionuclides. 
Acceptance Criteria from Section 2.2.1.4.1, Demonstration of Compliance with the 
Postclosure Public Health and Environmental Standards 
Acceptance Criterion 2, An Adequate Demonstration Is Provided That the Annual Dose to 
the Reasonably Maximally Exposed Individual in Any Year During the Compliance Period 
Does Not Exceed the Exposure Standard 
Subcriterion (1): Sections 6.1.5, 6.2.1, and 6.2.3 explain that the BDCFs for each scenario class, 
groundwater and volcanic ash exposures, are based on 1,000 model realizations. 
Subcriterion (2): Section 6.2.1 describes the calculations of the BDCFs, which are used to 
calculate the annual dose curves, and Figure 6.2-1 displays the results for BDCFs for the 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 7-9 October 2004 
present-day climate scenario in ranges which include their mean and median values, minima and 
maxima, and the 5th and 95th percentile confidence intervals to represent uncertainty in the dose 
calculations. 

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Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 8-1 October 2004 
8. INPUTS AND REFERENCES 
8.1 DOCUMENTS CITED 
BSC (Bechtel SAIC Company) 2003. Total System Performance 
Assessment-License Application Methods and Approach. TDR-WIS-PA-000006 
REV 00 ICN 01. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20031215.0001. 
166296 
BSC 2004. Agricultural and Environmental Input Parameters for the Biosphere 
Model. ANL-MGR-MD-000006, Rev. 02. Las Vegas, Nevada: Bechtel SAIC 
Company. 
169673 
BSC 2004. Biosphere Model Report. MDL-MGR-MD-000001, Rev. 01. Las Vegas, 
Nevada: Bechtel SAIC Company. 
169460 
BSC 2004. Characteristics of the Receptor for the Biosphere Model. ANL-MGRMD-
000005 REV 03. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040913.0004. 
169671 
BSC 2004. Disruptive Event Biosphere Dose Conversion Factor Analysis. 
ANL-MGR-MD-000003 REV 03. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040908.0007. 
167287 
BSC 2004. Environmental Transport Input Parameters for the Biosphere Model. 
ANL-MGR-MD-000007 REV 02. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040913.0003. 
169672 
BSC 2004. Future Climate Analysis. ANL-NBS-GS-000008 REV 01. Las Vegas, 
Nevada: Bechtel SAIC Company. ACC: DOC.20040908.0005. 
170002 
BSC 2004. Inhalation Exposure Input Parameters for the Biosphere Model. ANLMGR-
MD-000001 REV 03. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040913.0001. 
169458 
BSC 2004. Nominal Performance Biosphere Dose Conversion Factor Analysis. 
ANL-MGR-MD-000009, Rev. 03. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040909.0003. 
169674 
BSC 2004. Q-List. 000-30R-MGR0-00500-000-000 REV 00. Las Vegas, Nevada: 
Bechtel SAIC Company. ACC: ENG.20040721.0007. 
168361 
BSC 2004. Soil-Related Input Parameters for the Biosphere Model. ANL-NBS-MD- 
000009, Rev. 02. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040913.0002. 
169459 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 8-2 October 2004 
BSC 2004. Technical Work Plan for Biosphere Modeling and Expert Support. 
TWP-NBS-MD-000004 REV 03. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040527.0004. 
169573 
Canori, G.F. and Leitner, M.M. 2003. Project Requirements Document. 
TER-MGR-MD-000001 REV 02. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20031222.0006. 
166275 
CRWMS (Civilian Radioactive Waste Management System) M&O (Management 
and Operating Contractor) 2000. Total System Performance Assessment for the Site 
Recommendation. TDR-WIS-PA-000001 REV 00 ICN 01. Las Vegas, Nevada: 
CRWMS M&O. ACC: MOL.20001220.0045. 
153246 
CRWMS M&O 2001. Identification of the Critical Group (Consumption of Locally 
Produced Food and Tap Water). ANL-MGR-MD-000005 REV 01 ICN 00. 
Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20010119.0109. 
153342 
CRWMS M&O 2001. Nominal Performance Biosphere Dose Conversion Factor 
Analysis. ANL-MGR-MD-000009 REV 01. Las Vegas, Nevada: CRWMS M&O. 
ACC: MOL.20010123.0123. 
152539 
GoldSim Technology Group. 2003. User's Guide, GoldSim Probabilistic Simulation 
Environment. Version 8.01. Redmond, Washington: Golder Associates. 
TIC: 255170. 
166226 
ICRP (International Commission on Radiological Protection) 1994. Human 
Respiratory Tract Model for Radiological Protection. Volume 24, Nos. 1-3 of 
Annals of the ICRP. Smith, H., ed. ICRP Publication 66. New York, New York: 
Pergamon. TIC: 249223. 
153705 
NCRP (National Council on Radiation Protection and Measurements) 1983. 
Iodine-129: Evaluation of Releases from Nuclear Power Generation. NCRP Report 
No. 75. Bethesda, Maryland: National Council on Radiation Protection and 
Measurements. TIC: 241527. 
167511 
NRC (U.S. Nuclear Regulatory Commission) 2003. Yucca Mountain Review Plan, 
Final Report. NUREG-1804, Rev. 2. Washington, D.C.: U.S. Nuclear Regulatory 
Commission, Office of Nuclear Material Safety and Safeguards. TIC: 254568. 
163274 
Steel, R.G.D. and Torrie, J.H. 1980. Principles and Procedures of Statistics: A 
Biometrical Approach. 2nd Edition. New York, New York: McGraw Hill. TIC: 6322 
150857 
8.2 CODES, STANDARDS, REGULATIONS, AND PROCEDURES 
10 CFR 63. Energy: Disposal of High-Level Radioactive Wastes in a Geologic 
Repository at Yucca Mountain, Nevada. Readily available. 
156605 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 8-3 October 2004 
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. 
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. 
AP-SIII.9Q Rev. 1, ICN 7. Scientific Analyses. Washington, D.C.: U.S. Department 
of Energy, Office of Civilian Radioactive Waste Management. 
LP-SI.11Q-BSC, Rev. 0, ICN 1. Software Management. Washington, D.C.: U.S. 
Department of Energy, Office of Civilian Radioactive Waste Management. 
8.3 SOURCE DATA, LISTED BY DATA TRACKING NUMBER 
MO0307SEPFEPS4.000. LA FEP List. Submittal date: 07/31/2003. 164527 
MO0403SPAAEIBM.002. Agricultural and Environmental Input Parameters for the 
Biosphere Model. Submittal date: 03/22/2004. 
169392 
MO0406SPAETPBM.002. Environmental Transport Input Parameters for the 
Biosphere Model. Submittal date: 06/24/2004. 
170150 
MO0407MWDGSBMF.000. GoldSim Biosphere Model Files Used to Generate 
Biosphere Dose Conversion Factors for the Groundwater Exposure Scenario. 
Submittal date: 07/22/2004. 
170852 
MO0407MWDGSMFV.000. GoldSim Biosphere Model Files Used to Generate 
Biosphere Dose Conversion Factors for the Volcanic Ash Exposure Scenario. 
Submittal date: 07/22/2004. 
170856 
MO0407SEPFEPLA.000. LA FEP List. Submittal date: 07/20/2004. 170760 
MO0407SPACRBSM.002. Characteristics of the Receptor for the Biosphere Model. 
Submittal date: 07/19/2004. 
170677 
MO0407SPAINEXI.002. Inhalation Exposure Input Parameters for the Biosphere 
Model. Submittal date: 07/12/2004. 
170597 
MO0407SPASRPBM.002. Soil Related Parameters for the Biosphere Model. 
Submittal date: 07/20/2004. 
170755 
8.4 SOFTWARE CODES 
BSC 2004. Software Code: GoldSim. V8.01 Service Pack 4. PC, Windows 2000. 
10344-8.01SP4-00. 
169695 

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APPENDIX A 
LIST AND DESCRIPTION OF FILES GENERATED IN THIS ANALYSIS 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 October 2004 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 A-1 October 2004 
A. LIST AND DESCRIPTION OF FILES GENERATED IN THIS ANALYSIS 
This appendix contains the list and description of the files generated in this analysis and included 
in the Appendix A compact disk. 
The GoldSim files were taken from DTN: MO0407MWDGSBMF.000 [DIRS 170852] and 
DTN: MO0407MWDGSMFV.000 [DIRS 170856]. Because the DTNs include many GoldSim 
files, only those that were used in this analysis are included in Appendix A, as shown in Figure 
A-1. A designator _SA was added to the file name for tracking purposes. 
Figure A-1. GoldSim Files for Stochastic Runs of the Biosphere Model for the Groundwater and Volcanic 
Ash Exposure Scenarios 
Two GoldSim files taken from DTN: MO0407MWDGSBMF.000 [DIRS 170852] and 
DTN: MO0407MWDGSMFV.000 [DIRS 170856] were modified to perform deterministic runs 
of the biosphere model. These files, ERMYN_GW_MC8_Det_Base.gsm, and 
ERMYN_VA_MC8_Det_Base.gsm, constituted the base files that were used to run the model 
deterministically, using input parameter values listed in Tables 4.1-1 to 4.1-4. The deterministic 
results for the cases described in this analysis were manually copied from the screen. Figure A-2 
shows the details for the base files. 
Figure A-2. GoldSim Files for Deterministic Runs of the Biosphere Model for the Groundwater and 
Volcanic Ash Exposure Scenarios 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 A-2 October 2004 
Figure A-3 shows the list of the Excel files supporting this analysis. The files were used to carry 
out calculations and to produce graphs presented in this report. 
Figure A-3. List of the Excel Files Supporting this Analysis 
The description of the Excel files follows below. 
Dependence of GW BDCFs on Inputs.xlsThis Excel file contains, in individual worksheets, 
the graphs and the data used to prepare the graphs that show the dependence of the groundwater 
exposure scenario BDCFs for selected radionuclides on the values of various input parameters. 
BDCFs results for the groundwater scenario were copied from the appropriate GoldSim files 
listed in Figure A-1. The graphs were plotted using averaged values of the independent and 
dependent variables. If the raw data for individual realizations are plotted, the stochastic 
variability among BDCFs from the multiple random inputs results in plots that show little 
discernable trend. To generate a graph illustrating the trend, the results of realizations were 
averaged to minimize the impact of other variables. The results were sorted first by the value of 
the independent variable (i.e., the input parameter). Then the input parameter values and the 
corresponding BDCFs were averaged in blocks of 100 values. The triangle symbols in the graph 
represent the mean and the error bars represent the uncertainty range for the mean at 95 percent 
uncertainty interval, calculated as 1.96 times the standard error of the mean, with the standard 
error expressed as standard deviation of the BDCF values in a block of 100 values divided by a 
square root of the number of results in a block, that is, 10 100 = . 
Dependence of VA BDCFs on Inputs.xlsThis Excel file is analogous to the Dependence of GW 
BDCFs on Inputs.xls except that it applies to the volcanic ash exposure scenario. It also 
generates graphs showing dependence of the BDCF components on the model input parameters. 
Detailed Pathway Analysis GW_MC.xlsThis Excel file contains calculations of pathway 
contributions to groundwater exposure scenario BDCFs for the present-day climate. It also 
contains pathway results copied from Detailed Pathway Analysis GW_FC.xls to produce plots of 
pathway contributions for both climates. The file consists of worksheets containing the summary 
of the environmental transport pathway analysis, environmental transport pathway analysis for 
selected radionuclides, analysis of the inhalation and ingestion pathway, as well as the graphs 
showing pathway contributions for individual radionuclides. The results of model realizations 
were copied into the worksheets from the appropriate GoldSim files listed in Figure A-1. 

Biosphere Dose Conversion Factor Importance and Sensitivity Analysis 
ANL-NBS-MD-000014 REV 00 A-3 October 2004 
Detailed Pathway Analysis GW_FC.xls This Excel file is analogous to the Detailed Pathway 
Analysis GW_MC.xls except that it applies to the upper bound of the glacial transition climate. 
Detailed Pathway Analysis VA.xlsThis Excel file contains calculations of pathway 
contributions to volcanic ash exposure scenario BDCFs for the present-day climate. The file 
consists of worksheets containing the summary of the environmental transport pathway analysis 
as well as the graphs showing pathway contributions for individual radionuclides, environmental 
transport pathway analysis for selected radionuclides, and analysis of the inhalation pathway. 
The results of model realizations were copied into the worksheets from the appropriate GoldSim 
files listed in Figure A-1. 
GW BDCF Variability Plots.xlsThis Excel file contains several worksheets showing statistics 
for the groundwater exposure scenario BDCFs and their pathway BDCFs and the graphs 
illustrating the variability and uncertainty in the BDCFs and their contributing pathways. 
GW MC Correlations.xlsThis Excel file contains the correlation coefficients calculated in 
GoldSim for the groundwater exposure scenario BDCFs. Data in this spreadsheet were 
transferred from the following files: 
ERMYN_GW_MC8_C14_SA.gsm, 
ERMYN_GW_MC8_Tc99_SA.gsm, 
ERMYN_GW_MC8_I129_SA.gsm, 
ERMYN_GW_MC8_U233_SA.gsm, 
ERMYN_GW_MC8_Np237D_SA.gsm, 
ERMYN_GW_MC8_Pu239_SA.gsm. 
VA BDCF Variability Plots.xlsThis Excel file contains several worksheets showing statistics 
for the volcanic ash exposure scenario BDCFs and their component BDCFs and the graphs 
illustrating the variability and uncertainty in the BDCF components and their contributing 
pathways. 
VA Correlations.xls This Excel file contains the correlation coefficients calculated in GoldSim 
for the volcanic ash exposure scenario BDCF components. Data in this spreadsheet were 
transferred from the file ERMYN_VA_MC8_Sr90D_SA.gsm 
Water Interception Fraction.xls  This Excel file produces graphs of interception fraction 
appearing in Figure 6.2-20. Data in this spreadsheet were transferred from the file 
ERMYN_GW_MC8_Pu239_SA.gsm 

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